PhD Thesis
RESILIENT ICT NETWORKS BASED INTERACTION
RETRIEVAL ARCHITECTURE (IRA) FOR EARTHQUAKE
ZONES IN PAKISTAN
THESIS SUBMITTED TOWARDS THE PARTIAL FULFILMENT OF
THE REQUIREMENT OF THE UNIVERSITY OF SINDH, FOR THE
AWARD OF DOCTOR OF PHILOSOPHY DEGREE IN
INFORMATION TECHNOLOGY.
Muhammad Hammad u Salam
Dr. A.H.S Bukhari Institute of Information and Communication
Technology
University of Sindh, Jamshoro, Pakistan
2020
I
CERTIFICATE
This is to certify that the work presented in this thesis entitled “Resilient ICT
Networks based Interaction Retrieval Architecture (IRA) for Earthquake
Zones in Pakistan” has been carried out by Muhammad Hammad u Salam under
our supervision. The work is genuine, original and in our opinion, suitable for
submission to the University of Sindh for the award of degree of PhD.
SUPERVISOR
___________________________________________
Dr. Shahzad Ahmed Memon
Professor
Institute of Information and Communication Technology
University of Sindh, Jamshoro Pakistan
CO-SUPERVISOR
___________________________________________
Dr. Lachhman Das Dhomeja
Professor
Institute of Information and Communication Technology
University of Sindh, Jamshoro Pakistan
CO-SUPERVISOR
_______________________________________
Dr. Atta-ur-Rehman
Associate Professor
Barani Institute of Information Technology (BITT), Pir Meher Ali Shah (PMAS)
Arid Agriculture University, Rawalpindi, Pakistan
II
DEDICATION
I earnestly dedicate this endeavor to my parents, family members, friends and
Institute of Information and Communication Technology, University of Sindh,
Jamshoro, Pakistan
III
ACKNOWLEDGEMENTS
First and foremost, praises and thanks to Almighty Allah, for His showers of
blessings throughout my work to complete the research successfully.
I would like to express my deep and sincere gratitude to my research supervisor,
Professor Dr. Shahzad Ahmed Memon, for his friendly and practical support to
accomplish this research work. His dynamism, vision, sincerity, and motivation
have deeply inspired me and without his guidance and support this work could
never have been completed. I deeply thank Co-Supervisors, Professor Dr.
Lachhman Das Dhomeja and Dr. Atta-ur-Rehman, Associate Professor for their
guidance and valuable comments, which steered me to proper direction. I am
extending my heartfelt thanks for their acceptance and patience during the
discussions I had with them on research work and thesis preparation.
I am extremely grateful to my parents for their love, prayers, caring and sacrifices
for educating and preparing me for my future, especially thankful to my wife and
my daughters for their love, understanding, prayers and continuing support to
complete this research work, also I express my thanks to my sisters, brothers
especially Asad Nawaz Khan, their love, constant support and valuable prayers to
complete my PhD studies.
My Special thanks goes to my friend especially MAHIZZ (Friends Group) and
brother Zahoor Hussain Shah for the keen interest shown to complete this thesis
successfully.
IV
PUBLICATIONS
1. Hammad-u-Salam, Shahzad Memon, Lachhman Das, Atta-Ur-Rahman,
Zahoor Hussain,“drone Based Resilient Network Architecture for Survivals in
Earthquake Zones in Pakistan ”. “SURJ-SS,” vol. 50, no. 1, pp. 175–182, March
2018.
2. Hammad-u-Salam, Shahzad Memon, Lachhman Das, Atta-Ur-Rahman,
Zahoor Hussain, “Sensor Based Survival Detection System in Earthquake
Disaster Zones”. “IJCSNS, vol.18No.5, pp 46-52, May 2018.
V
ABSTRACT
Earthquake is one of the unpredictable natural disasters, which causes serious
damages including human life and infrastructures. The gaining information about
earthquake before it occurs is not possible yet. However, the efficient disaster
management services and sufficient arrangements are essential after the
earthquake to save human lives and restore communication services, which can
help locate survivals. In Pakistan, after earthquake, the army/special services
establish their own setup to restore basic communication such as voice call service
in that area for the rescue operations. But their disaster management support lacks
mechanisms and supporting infrastructure to detect underground and over-ground
survivals in disaster area and to send this information to concerned response
centers. In this research, resilient information communication technology (ICT)
networks-based Interaction Retrieval Architecture (IRA) for earthquake zones in
Pakistan has been proposed, designed, and implemented. The proposed system
detects the under-surface survivals through aliveness sensing techniques (their
movements, breathing, and respiration patterns) and sends it to be concerned cells
such as responders’ cell phones, base station unit and relevant quick disaster
management response cell. The system has been tested through different
environments such as proteus simulation, laboratory based and open-air based
environments. The prototype system has also been tested under different building
structured materials to check the survival detecting capabilities and the strength
of the aliveness sensing techniques.
VI
TABLE OF CONTENTS
CERTIFICATE .................................................................................................. I
DEDICATION ................................................................................................. II
ACKNOWLEDGEMENTS ............................................................................. III
PUBLICATIONS............................................................................................ IV
ABSTRACT .................................................................................................... V
TABLE OF CONTENTS ................................................................................. VI
LIST OF TABLES .......................................................................................... XI
LIST OF FIGURES ........................................................................................ XII
ABBREVIATIONS ....................................................................................... XV
CHAPTER 1 ..................................................................................................... 1
INTRODUCTION ............................................................................................ 1
1.1 MOTIVATION ................................................................................................ 1
1.2 RESEARCH CONTRIBUTIONS ........................................................................... 2
1.2.1 UNDER AND UPPER SURFACE SURVIVAL DETECTION ........................................ 2
1.2.2 PROVISION OF A REAL TIME COMMUNICATION SUPPORT FOR SHARING
SURVIVALS’ INFORMATION TO DISASTER MANAGEMENT .......................................... 2
1.3 THESIS ORGANIZATION .................................................................................. 3
CHAPTER 2 ..................................................................................................... 4
RESEARCH BACKGROUND LITERATURE REVIEW ................................... 4
2.1 RESEARCH BACKGROUND ............................................................................. 4
2.2 EARTHQUAKES ............................................................................................. 4
2.3 DAMAGES DONE BY EARTHQUAKE 2005 ......................................................... 6
2.4 NATIONAL RESPONSE AFTER EARTHQUAKE .................................................... 6
2.5 INTERNATIONAL RESCUE RESPONSE ............................................................... 7
2.6 LITERATURE REVIEW .................................................................................... 9
2.6.1 USAGE OF ICT BASED RESILIENT NETWORKS IN LARGE SCALE DISASTERS
10
2.6.2 GIS (GEOGRAPHIC INFORMATION SYSTEM) ........................................... 12
2.6.3 WIRELESS AD-HOC NETWORK .............................................................. 13
2.6.4 SOCIAL NETWORKS .............................................................................. 15
2.6.5 HAP (HIGH ALTITUDE PLATFORMS) ..................................................... 17
VII
2.6.6 FANET (FLYING ADHOC NETWORK) .................................................... 19
2.6.7 UAV (UNMANNED AERIAL VEHICLE) .................................................... 20
2.6.8 DRONES TECHNOLOGY ......................................................................... 22
2.6.8.1 Survivals finding Technologies used in Drones .............................. 23
2.6.8.2 Emergency Responders ................................................................. 25
2.7 RELATED WORK .......................................................................................... 26
2.8 SUMMARY OF THE EXISTING ICT NETWORKS USED IN LITERATURE ............... 28
AFTER DISCUSSING THE PROPOSED SYSTEM IN LITERATURE THEY ARE COMPARED
WITH THE PRE-DEFINED RESEARCH PARAMETER FOR THE SURVIVALS DETECTION
SYSTEM AND ALSO COMPARED THE ABILITY TO SEND THE REAL TIME INFORMATION
FLOW MECHANISM FROM DISASTER ZONE TO THE REMOTE AREA TO THE CONCERN
DEPARTMENTS FOR THE SEARCH AND RESCUE OPERATION. .................................... 31
2.9 RESEARCH GAP .......................................................................................... 34
2.10 SUMMARY OF THE CHAPTER ................................................................... 34
CHAPTER 3 ................................................................................................... 35
RESEARCH DESIGN ..................................................................................... 35
3.1 RESEARCH METHODOLOGY ......................................................................... 35
3.2 PHASE ONE: LITERATURE REVIEW............................................................... 36
3.2.1 RESEARCH ARTICLES ........................................................................... 36
3.2.2 DISASTER MANAGEMENT SERVICES ...................................................... 37
3.2.3 FIELD VISITS AND MEETINGS ................................................................ 37
3.2.4 EXTENSIVE STUDY OF DIFFERENT COMMUNICATION TECHNOLOGIES.... 37
3.3 PHASE TWO: PROBLEM IDENTIFICATION AND JUSTIFICATION ....................... 38
3.4 PHASE THREE: PROTOTYPE SYSTEM DESIGN .................................................. 39
3.5 PHASE FOUR: SYSTEM SIMULATION IN PROTEUS ENVIRONMENT WITH
DIFFERENT SCENARIO ........................................................................................... 39
3.6 PHASE FIVE: HARDWARE COMPONENTS OF SYSTEM .................................. 40
3.7 PHASE SIX: IMPLEMENTATION AND TESTING OF SYSTEM ............................ 41
3.8 PHASE SEVEN: RESULTS AND RESULT ANALYSIS OF THE SYSTEM ................ 41
3.9 SUMMARY OF THE CHAPTER ........................................................................ 42
CHAPTER 4 ................................................................................................... 44
DESIGN AND IMPLEMENTATION OF PROTOTYPE HARDWARE SYSTEM
...................................................................................................................... 44
4.1 RESILIENT ICT NETWORKS BASED INTERACTION RETRIEVAL ARCHITECTURE
(IRA). ................................................................................................................. 44
VIII
4.2 COMPONENTS OF RESILIENT IRA................................................................. 45
4.3 EARLY WARNING SYSTEM NETWORKS (EWSN) ........................................... 45
4.4 RAPID RESPONSE NETWORKS (RRN) .......................................................... 46
4.5 CENTRAL DISASTER MANAGEMENT DATABASE CELL (CDMDC) .................. 47
4.6 QUICK DISASTER MANAGEMENT RESPONSE CENTRE (QDMRC) ................... 47
4.7 PROTEUS SIMULATION OF PROPOSED SYSTEM .............................................. 48
4.8 PROTOTYPE SYSTEM AND ITS COMPONENTS ................................................. 49
4.8.1 ARDUINO 2560 MICROCONTROLLER...................................................... 50
4.8.2 DISPLAY .............................................................................................. 50
4.8.3 EXTERNAL STORAGE MODULE .............................................................. 50
4.8.4 LEVEL SHIFTER 5DCV ....................................................................... 50
4.8.5 ALIVENESS SIGNAL INDICATORS ........................................................... 51
4.8.6 GSM MODULE ..................................................................................... 51
4.8.7 ALIVENESS DETECTION SENSING RESPIRATION MODULE ....................... 51
4.8.8 RESPIRATION DETECTION MODULE ....................................................... 51
4.9 THE INFORMATION FLOW RESPIRATION MODULE ........................................ 52
4.10 PROTOTYPE SYSTEM INFORMATION FLOW MECHANISM ............................ 53
4.11 WORKING OF THE PROPOSED SYSTEM ...................................................... 54
4.12 POST-EARTHQUAKE INFORMATION FLOW OF IRA .................................. 54
4.13 SUMMARY OF THE CHAPTER ................................................................... 55
CHAPTER 5 ................................................................................................... 57
TESTING OF PROTOTYPE HARDWARE SYSTEM ..................................... 57
5.1 MULTI-LEVEL BUILDING SCENARIO ............................................................ 57
5.2 SINGLE AND DOUBLE STORY HOUSES SCENARIO .......................................... 58
5.3 MEGA MARKET SCENARIO .......................................................................... 59
5.4 PROTOTYPE HARDWARE TESTING IN CONTROLLED ENVIRONMENT .............. 59
5.5 OPERATIONAL COMPONENT OF PROTOTYPE SYSTEM ..................................... 60
5.6 DISASTER INFORMATON RESPONDANTS CELL PHONE .................................... 61
5.7 BASE-STATION COMPONENTS OF THE SYSTEM .............................................. 62
5.8 SURVIVALS ALIVENESS DETECTION UNDER BUILDING STRUCTURED
MATERIALS ......................................................................................................... 62
5.8.1 CONCRETE STRUCTURE ......................................................................... 62
5.8.2 STONE STRUCTURE ............................................................................... 63
5.8.3 BRICKS STRUCTURE ............................................................................. 63
5.8.4 BLOCKS STRUCTURE ............................................................................. 64
IX
5.8.5 WOODEN STRUCTURE ........................................................................... 65
5.8.6 PLYWOOD STRUCTURE .......................................................................... 65
5.8.7 GLASS STRUCTURE ............................................................................... 66
5.8.8 PAPER BUNDELS ................................................................................... 66
5.9 SUMMARY OF THE CHAPTER ........................................................................ 67
CHAPTER 6 ................................................................................................... 68
RESULTS AND DISCUSSSION ..................................................................... 68
6.1 TESTING OF HARDWARE PROTOTYPE THROUGH PROTEUS SIMULATION......... 69
6.2 SCENARIO 1: SIMULATION RESULTS OF MULTI-LEVEL BUILDING .................. 69
6.2.1 GRAPHICAL REPRESENTATION OF HEARTBEATS IN MULTI-LEVEL BUILDING
SCENARIO ....................................................................................................... 71
6.2.2 PROCESS OF INFORMATION FLOW FOR ALIVENESS DETECTION
TECHNIQUE (MOVEMENT, BREATHING AND RPM) OF DESIGNED HARDWARE
SYSTEM. ....................................................................................................... 72
6.2.3 CONCRETE STRUCTURE ........................................................................ 74
6.2.4 WOODEN STRUCTURE ........................................................................... 75
6.2.5 RESPONDERS CELL PHONE WORKING MECHANISM ................................. 76
6.2.6 RESULTS OF RESPONDERS CELL PHONE ............................................... 77
6.3 SCENARIO 2: SINGLE AND DOUBLE STORY BUILDING ................................... 77
6.3.1 GRAPHICAL REPRESENTATION HEARTBEATS IN SINGLE AND DOUBLE
STORIES BUILDINGS SCENARIO ......................................................................... 78
6.3.2 STONE STRUCTURE ............................................................................... 79
6.3.3 BRICK STRUCTURE ............................................................................... 80
6.3.4 PLYWOOD STRUCTURE .......................................................................... 81
6.3.5 RESULTS OF ALIVENESS DETECTION ................................................... 82
6.3.6 RESULTS OF RESPONDERS CELL PHONE ............................................... 83
6.4 SCENARIO 3: MEGA MARKET ...................................................................... 83
6.4.1 GRAPHICAL REPRESENTATION OF HEARTBEATS IN MEGA MARKET
SCENARIO ....................................................................................................... 84
6.4.2 BLOCK STRUCTURE .............................................................................. 85
6.4.3 GLASS STRUCTURE ............................................................................... 86
6.4.4 PAPER BUNDLES BOX ........................................................................... 87
6.4.5 RESULTS OF ALIVENESS DETECTION BY HARDWARE PROTOTYPE SYSTEM 88
6.4.6 VARIOUS RESULTS OF RESPONDERS CELL PHONE .............................. 89
X
6.5 COMPARISON BETWEEN PROTOTYPE SYSTEM AND EXISTING ICT NETWORKS
FOR SURVIVAL FINDING ....................................................................................... 93
6.6 CHAPTER SUMMARY .................................................................................... 94
CHAPTER 7 ................................................................................................... 95
CONCLUSION AND FUTURE DIRECTION .................................................. 95
7.1 CONCLUSION .............................................................................................. 95
7.2 SUMMARY OF CONTRIBUTIONS .................................................................... 96
7.3 LIMITATIONS AND FUTURE DIRECTIONS ...................................................... 96
REFRENCES ................................................................................................. 98
APPENDEX ................................................................................................. 110
XI
LIST OF TABLES
TABLE 2-1: DETAILS OF INTERNATIONAL AND NATIONAL RESPONSE IN OF EARTHQUAKE 2005 IN
PAKISTAN. ..................................................................................................................... 8
TABLE 2-2: DETAILS OF INTERNATIONAL AND NATIONAL RESPONSE IN EARTHQUAKE 2015 IN
PAKISTAN ...................................................................................................................... 8
TABLE 2-3: FEATURES AND LIMITATIONS OF TECHNOLOGIES USED IN DRONE ........................... 24
TABLE 2-4: SUMMARY OF LITERATURE REVIEW: ..................................................................... 29
TABLE 2-5: COMPARISON OF EXISTING SYSTEM WITH THE PROPOSED RESEARCH PARAMETERS ... 33
TABLE 6-1: STANDARD AGE WISE HEART BEATS AND RESPIRATION RATES ................................ 69
TABLE 6-2: MULTILEVEL BUILDING ....................................................................................... 70
TABLE 6-3: ALIVENESS DETECTION BY PROTOTYPE SYSTEM .................................................... 74
TABLE 6-4: ALIVENESS DETECTION THROUGH CONCRETE STRUCTURE ...................................... 75
TABLE 6-5: ALIVENESS DETECTION THROUGH WOODEN STRUCTURE ........................................ 76
TABLE 6-6: SINGLE AND DOUBLE STORIES SCENARIO .............................................................. 78
TABLE 6-7: ALIVENESS DETECTION THROUGH STONE MATERIAL ............................................. 80
TABLE 6-8: ALIVENESS DETECTION THROUGH BRICK STRUCTURE ............................................ 80
TABLE 6-9: ALIVENESS DETECTION THROUGH PLYWOOD MATERIAL ........................................ 81
TABLE 6-10: PROTOTYPE SYSTEM HARDWARE RESULT ........................................................... 82
TABLE 6-11: MEGA MARKET ................................................................................................. 84
TABLE 6-12: BLOCK MATERIAL ............................................................................................ 86
TABLE 6-6-13: GLASS MATERIAL .......................................................................................... 87
TABLE 6-14: PAPER MATERIAL.............................................................................................. 88
TABLE 6-15: PROTOTYPE SYSTEM HARDWARE RESULT .......................................................... 89
TABLE 6-16: COMPARISON BETWEEN EXISTING ICT NETWORKS FOR SURVIVAL FINDING AND
DEVELOPED SYSTEM ..................................................................................................... 94
XII
LIST OF FIGURES
FIGURE 2-1: MAGNITUDE OF DIFFERENT EARTHQUAKES KASHMIR EARTHQUAKE ........................ 5
FIGURE 2-2: EARTHQUAKE MAGNITUDE IN 2005(PAKISTAN, KASHMIR) ...................................... 5
FIGURE 2-3: EARTHQUAKE DAMAGES IN BALAKOT ................................................................... 6
FIGURE 2-4: DISASTER OCCURRENCE IN MUZAFFARABAD .......................................................... 6
FIGURE 2-5: LOCAL AND INTERNATIONAL ORGANIZATIONS RESPONSE IN EARTHQUAKES 2005,
2013 & 2015 .................................................................................................................. 7
FIGURE 2-6: NEVER DIE NETWORK (NDN) [7]. ....................................................................... 11
FIGURE 2-7: LIFELINE LAYER (A) DRAWN BY SOFTWARE, (B) OVER A SATELLITE IMAGE [13]. ..... 12
FIGURE 2-8: CONSIDERED SYSTEM OVERVIEW (MDRU) [28] .................................................. 15
FIGURE 2-9: USAGE OF HYBRID ECNS [34]. ........................................................................... 17
FIGURE 2-11: HIGH AMPLITUDE PLATFORM SYSTEM ARCHITECTURE [43]. ............................... 18
FIGURE 2-12: FANET SYSTEMS [48]. ..................................................................................... 19
FIGURE 2-13: UAV SYSTEMS [54]. ......................................................................................... 21
FIGURE 2-14: ROTOR WING DRONE ........................................................................................ 23
FIGURE 2-15 SURVIVALS RESCUED WORLDWIDE BY THE YEARS (2013-1017) ............................ 25
FIGURE 2-16: (GEORGETOWN COUNTY EMERGENCY MANAGEMENT) [75] ................................ 26
FIGURE 3-1: RESEARCH DESIGN ............................................................................................ 35
FIGURE 3-2: COMPONENTS OF PHASE-1 OF RESEARCH DESIGN ................................................. 36
FIGURE 3-3: STUDY OF EXISTING RESILIENT NETWORKS ......................................................... 38
FIGURE 3-4: STEPS OF PROTOTYPE SYSTEM DESIGN ................................................................ 39
FIGURE 3-5: PROTEUS SIMULATION SCENARIOS ...................................................................... 40
FIGURE 3-6: COMPONENTS IDENTIFICATION AND HARDWARE DESIGN OF SYSTEM ...................... 40
FIGURE 3-7: TESTING OF SYSTEM IN SIMULATION AND IN LABORATORY .................................... 41
FIGURE 3-8: RESULTS AND ANALYSIS .................................................................................... 42
FIGURE 4-1: RESILIENT INTERACTION RETRIEVAL ARCHITECTURE (IRA) [6]. ........................... 45
FIGURE 4-2: EARLY WARNING SYSTEM NETWORKS (EWSN) [6] ............................................. 46
FIGURE 4-3: RAPID RESPONSE NETWORKS (RRN) [6] .............................................................. 46
FIGURE 4-4: CENTRAL DISASTER MANAGEMENT DATABASE CELL [6]. ..................................... 47
FIGURE 4-5: DISASTER MANAGEMENT RESPONSE CENTRE [6] ................................................. 48
FIGURE 4-6: PROTEUS SIMULATION OF RESILIENT ICT NETWORKS BASED IRA ......................... 49
FIGURE 4-7: (A) PROTOTYPE HARDWARE MODULE OPERATIONAL & BASE STATION COMPONENTS
(B) RESPONDERS CELL PHONE COMPONENT .................................................................... 50
FIGURE 4-8: ALIVENESS DETECTION MODULE ......................................................................... 51
FIGURE 4-9: OPERATIONAL FLOW OF ALIVENESS DETECTION MODULE ...................................... 52
FIGURE 4-10: INFORMATION FLOW MECHANISM BETWEEN DISASTER ZONE TO REMOTE ZONE .... 53
FIGURE 4-11: WORKING OF THE PROPOSED SYSTEM ................................................................. 54
XIII
FIGURE 4-12: POST-EARTHQUAKE INFORMATION FLOW OF IRA .............................................. 55
FIGURE 5-1: SIMULATED PROTOTYPE HARDWARE SYSTEM FOR TESTING.................................... 57
FIGURE 5-2: MULTILEVEL BUILDING DISASTER ...................................................................... 58
FIGURE 5-3: DISASTER IN SINGLE AND DOUBLE STORIES BUILDING ......................................... 58
FIGURE 5-4: EARTHQUAKE DISASTER IN MEGA MARKET ......................................................... 59
FIGURE 5-5: (A) OPERATIONAL UNIT (B) RESPONDER CELL PHONE AND (C) BASE STATION UNIT
HARDWARE PROTOTYPE AND ITS COMPONENTS .............................................................. 60
FIGURE 5-6: OPERATIONAL UNIT OF PROTOTYPE WHICH WILL BE LOCATED IN EARTHQUAKE
DISASTER ZONE ............................................................................................................ 61
FIGURE 5-7: CELL PHONE WITH RESPONDENTS ........................................................................ 61
FIGURE 5-8: REMOTE UNIT WHICH WILL BE LOCATED AT BASE-STATION TO RECEIVE INFORMATION
ABOUT ALIVENESS OF SURVIVALS AND SHARE WITH THE RELATED ................................... 62
FIGURE 5-9: ALIVENESS DETECTION THROUGH CONCRETE STRUCTURED ................................... 63
FIGURE 5-10: ALIVENESS DETECTION THROUGH STONE STRUCTURE ......................................... 63
FIGURE 5-11: ALIVENESS DETECTION THROUGH BRICK STRUCTURE ........................................ 64
FIGURE 5-12: BLOCK STRUCTURE MATERIAL SYSTEM TESTING ............................................... 64
FIGURE 5-13: WOODEN STRUCTURED MATERIAL ALIVENESS DETECTION .................................. 65
FIGURE 5-14: ALIVENESS DETECTION BY THE SYSTEM THROUGH PLYWOOD STRUCTURE ............ 65
FIGURE 5-15: ALIVENESS DETECTION BEHIND GLASS STRUCTURE ............................................. 66
FIGURE 5-16: ALIVENESS DETECTION UNDER PAPER BUNDLE ................................................... 66
FIGURE 6-1: ALIVENESS DETECTION PROCESS IN PROPOSED IRA .............................................. 68
FIGURE 6-2: HEARTBEAT DETECTION IN MULTI-LEVEL BUILDINGS ........................................... 70
FIGURE 6-3: NO OF SURVIVALS RESCUED IN DIFFERENT ATTEMPTS .......................................... 71
FIGURE 6-4: DIFFERENT HEARTBEATS OF SURVIVALS IN MULTI-LEVEL BUILDING SCENARIO ...... 71
FIGURE 6-5: ALIVENESS MECHANISM FLOW ............................................................................ 72
FIGURE 6-6: ALIVENESS DETECTION TECHNIQUES (A) MOVEMENT (B) MOVEMENT TRACKING (C)
BREATHING (D) (RPM) USED BY OPERATIONAL UNIT ...................................................... 73
FIGURE 6-7: INFORMATION FLOW OF THE RESPONDER’S CELL PHONE ........................................ 76
FIGURE 6-8: RESPONDERS CELL PHONE MESSAGING SERVICES ................................................ 77
FIGURE 6-9: SINGLE AND DOUBLE STORIES BUILDINGS ............................................................ 78
FIGURE 6-10: NO OF SURVIVALS IN VARIOUS ATTEMPTS .......................................................... 79
FIGURE 6-11: NO OF HEARTBEATS OF SURVIVALS SINGLE AND DOUBLE STORIES BUILDINGS
SCENARIO .................................................................................................................... 79
FIGURE 6-12: PROTOTYPE SYSTEM HARDWARE RESULT .......................................................... 82
FIGURE 6-13: REMOTE CELL PHONE MESSAGING RESULTS ...................................................... 83
FIGURE 6-14: MEGA MARKET RESULT .................................................................................... 84
FIGURE 6-15: NO OF SURVIVALS SAVED IN DIFFERENT ATTEMPTS ............................................. 85
FIGURE 6-16: NO OF HEARTBEAT OF THE SURVIVALS IN MEGA MARKET SCENARIO ................... 85
FIGURE 6-17: PROTOTYPE SYSTEM HARDWARE RESULT .......................................................... 88
FIGURE 6-18: REMOTE CELL PHONE MESSAGING RESULTS 3: ................................................... 90
XIV
FIGURE 6-19: REMOTE CELL PHONE MESSAGING RESULTS 4 .................................................... 91
FIGURE 6-20: REMOTE CELL PHONE MESSAGING RESULTS 5 .................................................... 92
FIGURE 6-21: REMOTE CELL PHONE CALLING RESULTS 6 ........................................................ 93
XV
ABBREVIATIONS
CDMDC Central Disaster Management Organization Database Cell
DM Disaster Management
ECN Emergency communication networks
EWSN Early Warning System Networks
EO Earth observation
FANET Flying Adhoc Networks
3G 3rd Generation
4G 4th Generation
5G 5th Generation
GSM Global System for Mobiles
GIS Global information System
GSM Global System for Mobile Communication
GPRS General Packet Radio Service
GPS Global Position System
HAP High Altitude Platforms
HBT Heartbeat
IRA Interaction Retrieval Architecture
ICT Information Communication Technologies
ITSS Intelligent Transport System
LCD Liquid Crystal Display
XVI
MANET Mobile Adhoc Networks
MAV Micro Aerial Vehicles
NDA Never Die Networks
NDMA National Disaster Management Authority
NIR near Infrared
PIR Passive Infrared
QDMRC Quick Disaster Management Response Center
RPM Respiration per Minute
RRN Rapid Response Networks
RTC Real Time Clocking
SAGA Self-protection Management Support System
SNA Social Network Analysis
SAR Search and Rescue
SN Social Networks
SUPER Social sensors for security assessments and Proactive Emergencies
management
UAV UN manned Aerial Vehicles
UAE United Arab Emirates
USA United States of America
WAN Wireless Adhoc Networks
WBSN Wireless Body Sensor Networks
WSN Wireless Sensor Networks
1
CHAPTER 1
INTRODUCTION
1.1 MOTIVATION
Natural disasters (earthquakes, Tsunami, landslides, avalanches, and floods etc.)
are most unpredictable disasters that cause severe damages, including human lives
and infrastructures. Earthquake is one of the most dangerous natural disasters and
gaining information about earthquakes before their occurrence in not possible so
far. However, the efficient disaster management (DM) services and their
preparations are important after the occurrence of earthquake to save human life
and restore communication services which can help locate victims over-ground or
underground. Dealing with earthquake disaster requires a proper planning, well
equipped response systems and resilient communication networks. Earthquakes
are well managed by many countries, various governments have plans and
facilities to provide the quick response just after occurrence of earthquake. But
they do not have proper have mechanisms to locate underground and over-ground
victims both together.
The National Disaster Management Authority (NDMA) was established by the
government of Pakistan for Natural Disaster Management. The services of NDMA
are linked with the army and they always appear in front to manage disasters with
their teams. In the disaster zone, the army establishes its own communication
services in order to reach the victims and save their lives. While their disaster
response system seems to be doing well to cope with casualties caused by natural
disasters, disaster response capacities of NDMA can be strengthened or improved
by developing mechanisms, such as detection of under-surface and over-surface
earthquake survivals and real-time communication capability to share information
of survivals to the concerned rescue teams / cells. In this research, we put forward
a resilient ICT networks-based interaction retrieval architecture for earthquake
zones in Pakistan. The synopsis of this proposed study was discussed with and
reviewed by Disaster Management Authority, Muzaffarabad and the letter issued
by them says that the proposed study will be of vital importance and helpful in
2
strengthening response capacities of disaster response institutions in Pakistan and
AJK (a copy of the letter is attached).
The proposed architecture detects survivals who are under or upper surface of
disaster area through aliveness sensing techniques, including their movements,
breathing and respiration patterns and to send this information to relevant entities,
such as responders’ cell phones, base-station units and relevant quick disaster
management response cells. The system design has been tested through different
environments, proteus simulation, laboratory, and open environments.
1.2 RESEARCH CONTRIBUTIONS
In the thesis, we present the Interaction Retrieval Architecture for efficient
earthquake disaster management which can help locate over-ground or
underground victims, restore communication between all stake holders and
transmit real time information about the survivals. The contributions of the thesis
can be described in terms of the features supported by the proposed architecture:
1.2.1 UNDER AND UPPER SURFACE SURVIVAL DETECTION
One of the main features of the system is an ability to detect underground and over
ground and upper surface survivals through their movement detection, breath
detection and respiration patterns.
1.2.2 PROVISION OF A REAL TIME COMMUNICATION SUPPORT FOR
SHARING SURVIVALS’ INFORMATION TO DISASTER MANAGEMENT
The proposed system provides real time communication capability to share the
survivals and disaster information to the concerned rescue cells. The system uses
respiration sensing techniques to collect information of survivals actions such as
motions, states and respiration and the collected information is sent to field
responded cell phone, base station placed at near disaster zone and remote quick
disaster management response center, through SMS and call ring.
3
1.3 THESIS ORGANIZATION
A remainder of the thesis has been organized as below.
Chapter 2 provides the background of the research and also discusses the role of
the local and international responses of different governments, organization and
NGOs after the happening of the earthquakes. Moreover, this chapter provides
description of diverse resilient communication networks proposed by various
researchers in literature and also related work focusing on upper and under surface
detection of the earthquake survivals.
Chapter 3 provides a design of research methodology indicating the different
research phases undertaken to complete the research, along with description of
what has been done in each of the research phases.
Chapter 4 provides a detailed description of proposed system, including
architecture of the system along with description of each of architectural
components, flow charts describing flow of information among various
architectural components.
Chapter 5 provides details of Implementation and testing of the proposed system
under various simulated and real building structures.
Chapter 6 presents and discusses results of the experiments conducted under both
simulated and real building structures in chapter 5.
Chapter 7 summarizes the research undertaken in this thesis and then outlines
future directions.
4
CHAPTER 2
RESEARCH BACKGROUND LITERATURE
REVIEW
In this chapter we present research background and literature review
2.1 RESEARCH BACKGROUND
Natural disaster such as earthquake is one of the unpredictable tragedies that cause
a massive damage to the human life and infrastructure. The scientists are not yet
successful to convey the prior information about the time and place of earthquake.
Still, well-organized disaster management services are vital part later than the
earthquake in order to reduce the destruction of human life. In this regard the
restoration of communication services is crucial that can help to find victims under
debris. The numerous organizations are engaged in the disaster managing. objects
and plans. Pakistan is one of the highly affected countries. In last two decades the
state faced the intensive earthquakes causing the massive destruction and loss of
lives. The country’s National Disaster Management Authority (NDMA) is
responsible for the handling the natural disasters. Though the NDMA is working
hard in its capacity but still there are various aspects needs to improve, especially
quick and speedy responses after the earthquakes. In this regard the pivot is the
need of a better communication networks for the restoring the communication to
link it directly to the rescue operation for the quick detection and tracking of the
survivals from debris.
2.2 EARTHQUAKES
The earthquake causes serious damages in the rocks with the strong vibrations in
the surface of earth. These vibrations cause great pressure on the coating of the
earth constantly which break the surface of earth plates and forms various faults
(https://earthquake.usgs.gov/learn/kids/eqscience.php). This is the beginning of
the earthquakes and it ends with lot of damages and causalities.
5
The earthquakes are measured in Richter scales. The strongest earthquake up till
now was of 9.5 Richter scale as shown in the figure 2.1
(https://twitter.com/IRIS_EPO). The Richter scale is the energy released by the
earthquakes.
Figure 2-1: Magnitude of different earthquakes Kashmir Earthquake
On October 8th, 2005, a powerful earthquake with 7.6-Richter scale measurement
stroke in Azad Jammu and Kashmir (AJK) and Khabar Pukhtoon Khawah province
on the Northern Pakistan-India border as shown in figure 2.2. The epicenter was
near to Muzaffarabad and it was the deadest earthquake in the history of Kashmir
and Pakistan. According to officials (http://news.bbc.co.uk/2/hi/south_asia/4322624.stm),
this disaster caused more than 87,000 lives and more than 3.3 million were made
homeless. The rehabilitation operations of the damages caused by this earthquake
are continues till today. Lot of international and nation organization are playing a
positive role in the rebuilding the state of Azad Jammu and Kashmir.
Figure 2-2: Earthquake magnitude in 2005(Pakistan, Kashmir)
6
2.3 DAMAGES DONE BY EARTHQUAKE 2005
The following figure 2.3 (https://alchetron.com/2005-Kashmir-earthquake) and in
figure 2.4 (https://alchetron.com/2005-Kashmir-earthquake) shows the damages
of the earthquake 2005 in Pakistan and Kashmir .
Figure 2-3: Earthquake damages in Balakot
Figure 2-4: Disaster occurrence in Muzaffarabad
2.4 NATIONAL RESPONSE AFTER EARTHQUAKE
During different earthquake, the national organizations plays the vital role,
specially, Pakistan army play an important role in that earthquake. Army was the
in charge to handle that disaster. They build their own communication networks
and different military helicopters were also used in rescue operations. Also, AJK
7
Government and Pakistan Government play a progressive role as shown in figure
2.5.
National
Response
Pakistan
military
forces
AJK
Government
Pakistan
Government
Earthquake
Disaster
International
Response
voluntary
organizations
International
organizations
Aid workers
World
CommunityNGOs
Figure 2-5: Local and International organizations response in Earthquakes 2005, 2013
& 2015
2.5 INTERNATIONAL RESCUE RESPOnSE
Any natural disasters, especially massive and worst, cannot be handled by a
country on its own sources. Many countries contribute to handle such disasters for
in forms of financial aid and providing help in the rescue and rehabilitation
operations. Same is seen in the AJK earthquake. Many international organizations,
NGO, s worldwide and private organizations were involved in different operations,
especially in earthquake Kashmir and KPK in 2005, 2013 and 2015.
Pakistan is geographically located in different disaster zones that are affected by
global warming, climate change, earthquake, floods, landslides, drought, and
glaciers melting etc. During past decade Pakistan is badly affected by earthquake
like, earthquake at Kashmir in October 2005 and in KPK Pakistan 2013 and 2015,
in which caused thousands of people and crippling the infrastructure of the region.
The response of different organizations after the earthquakes
2005(https://reliefweb.int/report/pakistan/kashmir-earthquake-october-8-2005-
impacts-pakistan) and 2015 (https://reliefweb.int/report/pakistan/ndma-response-
earthquake-29-oct-2015) is shown in table 2.1 and table 2.2.
8
Table 2-1: Details of International and National response in of Earthquake 2005
in Pakistan.
Provinces Number
of
Deaths
Number
of
Injured
Peoples
Houses
Damaged
International
Response
National
Response
Khyber
Pakhtunkhwa
31,928 24,695 69,632 • world
community
• voluntary
organizatio
ns
• Internation
al
organizatio
ns
• NGOs
• men and
women
• Aid
workers
• Pakistan
military
forces
(Armed
forces &
Air forces)
• Pakistan
Government
• AJK
Government
Punjab 1,789 6,763 5,624
Sindh 283 648 125
AJK & Gilgit
Baltistan
53,000 67,894 66,503
Grand Total 87,000 100,000 141,884
Table 2-2: Details of International and National response in Earthquake 2015 in
Pakistan
Province Number
of
Deaths
Number
of
Injured
people
Houses
Damaged
International
Response
National
Response
Khyber
Pakhtunkhwa
225 1,756 25,636 • International
organizations
• world
community
• NGOs
• Pakistan
military
forces
(Armed
forces &
Air forces)
• Pakistan
Government
Punjab 5 80 20
FATA 29 209 9,534
AJK & Gilgit
Baltistan
12 101 595
Grand Total 271 2,146 35,785
9
It was observed that the rescue operations after the natural disasters are hurdled
by unreliable communication and lake of cooperation between different
departments, absence of community awareness, unsatisfactory planning, lack of
technology awareness and the implementation.
2.6 LITERATURE REVIEW
In Pakistan National Disaster Management Authority deals with the natural
disasters at National and International level. NDMA has participated in many
disasters especially earthquakes but could not cope them well as it should. The
main hurdle in handling earthquakes is that there is no any permanent, speedy and
rapid response resilient ICT networks based architecture for the DM under one
umbrella [1]. Nor there is proper early warning system for any disaster accept
flood early warning system[2] neither on-time communication networks available
to by NDMA. Hence NDMA lacks the latest and appropriate mechanism of
networks for the fault-tolerant and continuous communication while there are
various types of networks used in various disastrous situations in other countries.
DM plan comprises of a number of objectives to enhance the emergency planning,
assessment and preparation, under different IT solutions with different issues
discovered, as one such example is SAGA (Self-protection Management Support
System) Spanish organization. SAGA is an emergency strategy for disaster
management [3]. There is need of significance understanding in emergency
situations, many methods are used in that such as, Delphi method is used in
dangerous areas for the flow of information between different elements involved
in disaster management[4]. Different methods are used to build local resilient
networks often involved in the association of native public groups. When
international organizations adopted such approaches, result shows that they
enhance the ability of a community to be active and acclimate when met with
diverse natural tragedies and weather change. Today in our world the global
organizations are playing a noticeable and influential role in natural disasters [5].
The National Disaster Management Authority (NDMA) was established by the
government of Pakistan for natural disaster management. The services of NDMA
are linked with the army and they always appear in front to manage disasters with
their teams. In disaster zone, the army establishes their own communication
10
services system, but no service exists which interact directly with victims over or
under ground. No concept of resilient communication network exists in the policy
of NDMA and never discussed at national level. Wireless communication
networks have an important role soon after the earthquake in restoration of
communication in the affected zones, but it fails to locate victims. The available
smart technologies are linked with high speed internet services via cellular
communication and can be used to establish wireless adhoc services. In this
research, a resilient ICT networks-based Interaction Retrieval Architecture (IRA)
is proposed for the earthquake disaster zone [6].
In literature review, many researchers have proposed various types of Resilient
Information Communication Technologies and wireless adhoc networks for
disaster recovery management globally and they have been successfully used by
different countries. These ICT networks are also used for the locating the survivals
at the upper surface. Some important ICT based networks have been discussed in
this thesis. After discussing resilient networks that have been used in Disaster
Management further the survivals finding technologies or system are discussed
that are used in upper surface detection of the survivals. In addition, the focus of
the study is to detect the under-surface survivals especially earthquake zone.
2.6.1 USAGE OF ICT BASED RESILIENT NETWORKS IN LARGE SCALE DISASTERS
The world is hit by sudden disasters such as earthquakes, Tsunami, typhoon and
hurricanes now a day rapidly. In the earthquake disaster such as, in East Japan in
2011 in which thousands of victims and large number of properties was damaged
also electric power and information system were shutdown. Lastly, the researchers
propose the systems with functions that are essential for upcoming widespread
disaster named Never Die Network. NDN is generally comprised of three networks
containing fixed, mobile and air NDNs wireless network. as shown in the figure
2.6 [7].
11
Figure 2-6: Never Die Network (NDN) [7].
Disaster recovery system network is very important for both survivals and the rescue team
members in disaster effected area. The relief operation disaster effected area also includes
in searching and finding the survivals before they are being rescued and also now a day
there are manual search and rescue operations which involves lot of time in that process.
The researchers have proposed a new Portable Disaster Recovery Network architecture.
This research allows survivors in disaster effected area or any other related search and
rescue circumstances to report their positions to a disaster management Center. This
assists responders first to rapidly rescue the survivors of these disaster effected areas [8].
In this research, the researchers have proposed a wireless sensor network have been
projected for the Disaster Management services. It is especially designed to safe guard
people in earthquake from heavy loses [9]. There is very much need of increasing the
earthquake early warning system (EEW) to meet the disaster affects. Earthquake
early warning systems can send short early warnings before the arrival of the
earthquakes. The disaster management survives must include the EEW system that
can detect the (Primary P-waves and secondary S-waves) with the seismic sensors.
This will allow enough time for people to move out of risky locations [10]. The
researcher has also Acknowledged the crucial the role ICT and Mass media in the
Japan Earthquake 2011. The researchers focused on the deep role of the ICT and
Mass Media. They have also focused their contribution in longer term post disaster
recovery. They also focus on the importance to realize and make how media can
affects the people awareness , behavior in post disaster retrieval [11]. Earth
Observation Information is often gained by the remote sensing approaches about
the Earth physical, chemical, and biological systems. Earth observation with
combined with satellites has been started in many diverse areas, such as land-
12
monitoring, change weather forecasting, natural resources management, measurement
natural disaster, and others play an important role during different disasters [12].
2.6.2 GIS (GEOGRAPHIC INFORMATION SYSTEM)
It is very important in the natural disasters, especially earthquake the networks that are
lifelines must be still working condition. For this purpose, the researchers have
proposed a GIS based software to develop for the spatial assessment of live lines by
using GEO tools. The developed GIS based software creates a map of live-lines , which
are fast in execution time, modifiable and user friendly to adopt it during the disaster
.GIS lifeline network can be seen in the figure 2.7 [13] .
Figure 2-7: Lifeline layer (a) drawn by software, (b) over a satellite image [13].
The effects of dangerous earthquakes on the road networks can be monitored multi-
criteria vulnerability assessment method and geographical, are very significant in the
disaster such as earthquakes. The researchers have proposed a data driven method
United States Geological Survey to monitor road Networks. For this purpose,
Vulnerability Surface (VS) method offers a diffident and significant technique to deal
with the impacts of dangerous earthquake. It can be useful safeguard specially in the
cities situated in disaster effect area are well organized to face earthquake disasters.
[14]. The efficiency of geographical information systems, ground observations and
remote sensing (RS), for observing variations in urban areas, the information has been
taken from past two decades. The research study has normally based on the relief
operations of disaster effected areas. The goal was to define to what techniques,
methods, and combination of the existing gears, are to be used to monitor professionally
13
the progress of retrieval in earthquake areas. These variations were recognized through
(1) the visual analysis, (2) automated detection and change (3) authentication based on
a mixture of visual and semi-automated details [15]. In the research the researchers
have presented an idea of smartphone application (earthquake averter and guidance
application) known as EAGA that direct both survivals and rescue staff during or after
earthquake. EAGA collects the information about the users frequently visiting sites and
social networks. It also delivers preliminary direction to the user during the earthquakes
[16]. Due to the natural disasters, locations such as free areas, parks and plazas may be
used after a disaster, for refuge places, which can satisfy survival necessities. The
researchers used Mapping Technique and GIS investigates to recognize the type,
functions and supply information to space system for the recovery of earthquake [17].
Contour maps and spatial distribution maps of landslide and its thickness, landslide area
is created to analysis the spatial scattering patterns of seismic landslides. Morphometric
parameters and information of size sharing of seismic landslides and it is matched by
other earthquake measures in world. There are four seismic landslide copiousness
comprising, landslide top number density (LTND), landslides centroid number density
(LCND), landslide erosion thickness (LET) and landslide area percentage (LAP), are
used to relate seismic landslides with various eco-friendly constraints [18]. The
researcher presents a Geographic Information System established framework that
enables equipment distribution in cope with disasters. The proposed outline was
composed of three subsystems to enable to collect information and to use in decision
making for equipment delivery. In addition, a GIS based system is used for decision
making and also used for rout finding in disasters [19].
2.6.3 WIRELESS AD-HOC NETWORK
In this research, researchers focus on how disaster administration can affect from recent
improvements in the wireless communication systems and the protocols, particularly
mobile systems and devices. This research provides an summary in what way the new
telecommunications technologies such as Device to Device, 5G networks , 4G/LTE,
and software based radio can recover the possible outcome of disaster management
recovery networks [20]. During various natural disasters, mostly vital system setups are
generally destroyed, the survivals requirement in this case will be diverse
communications network for their communication, deprived of a hesitation, by using
14
various wireless access technologies, i.e., Wi-Fi or Bluetooth. The network must also
be capable to easily change the access technologies, to ensure QoS for ongoing
applications and must have a mechanism to save energy. To address this issue an SDN
approach have been proposed [21]. During disaster aid and rescue operations the
wireless communication systems are vital. The wireless systems perform their best in
unfriendly conditions with limited resources can save thousands of lives which are at
risk. Past disasters like Hurricane Katrina, Sept-11 attacks, tsunami in 2011, have tinted
the severe weaknesses in the existing wireless communication systems. To address this
problem in these disasters, the researchers are upcoming up with improved approaches
in wireless networks. In this article, numerous wireless applications are considered,
such as Self-Powered Wireless Communication Platform (SPWC) to create a self-
sustaining and fast-deployable network to search and aid relief operations. The Low
Altitude Platform (LAP) Flying objects are used to communicate nonstop with the
ground units in the search and rescue operations. In disaster response, time is vital in
saving lives and significant power back up also necessary in this case, SPWC might be
the most economical solution [22]. The researchers have proposed Intelligent
Transportation Systems and Services (ITSS) that are used to play a vital role in coping
with crises and disasters. The system used micro-simulation model to adopt the
efficiency of the networks in the disaster areas. Moreover, the driver reaction is
measured and assessed. The results indicate the immense progress while applying the
ITSS in saving the human lives. The results also indication an improvement of saving
vehicles as well [23]. MAVs (Micro aerial vehicles) networks armed with numerous
sensors are progressively used for civil applications, like monitoring, surveillance, and
disaster management. In this research, researchers argue the communication
requirements upraised in MAV systems. Researchers suggest a new system that could
be used to identify diverse request on demands [24]. In this research, the researcher
proposed the idea of advance human life detection system. With the help of this system,
researchers prove the idea of auto info-provider system, and the system is applicable in
natural disaster such as earthquake and others. The system automatically checks the
position of a live person and weeps the buzzer and whenever any person finds through
PIR sensor path than receiver circuit receive this information and display all on LCD.
This robot is control by mobile from remote location and to avoid accidents, an IR
sensor is also used in the circuit with the help of 2 DC motors. [25]. In this research
article, the researchers proposed a vehicle assistance resilient network for disaster
15
management. It comprises three main modules: (1) smartphone (2) communication
between mobile stations and servers (3) geo distributed servers that gather user data,
data analysis, and also make disaster management decisions [26]. Humans are well
aware intelligent systems that are used in search and rescue operations especially used
in earthquakes to save human lives. Pervious technologies were consisting of mini
robots with Passive Infrared sensors (PIR) to detect the presence of human body under
the surface. The disadvantage of such systems is that they can be struck during
operation. Now the researchers have proposed to replace that system with robots with
IR technologies. The system is very efficient in very short duration [27]. This article
proposes a network architecture that is resilient even through devastating disasters. The
researchers have proposed a resilient network architecture which can be used in
disasters. The proposed system is MDRU i.e. moveable and deployable rescue unit
specially designed for earthquake disasters. The system has capability to share
information about the disaster area in very short time MDRU based disaster resilient
network shown in the figure 2.8 [28].
Figure 2-8: Considered system overview (MDRU) [28]
2.6.4 SOCIAL NETWORKS
The long-term investment is required in disaster resilience strategies, the ability to
restore communication, plan to respond and to recover in the upcoming disasters are
vigorous towards sustainability. The researcher have purposed framework of resilient
networks for sustainability by using unstructured Big Data, based upon 36,422 items
collected form of some of social media like news, Facebook, Instagram and YouTube
and also used structured data from 205 managers who were active in disaster relief
16
activities in Nepal earthquake in 2015 [29]. The continuing growth of Social Networks
(SNs) and the massive quantity of related users have used these systems in research
areas. The fundamental features of any Social Network delivers is to permit users
categorize their connections, establish, to groups or circles. The researcher dowries a
novel Bio motivated technique, built on Ant Colony Optimization (ACO) algorithms
which have been considered aimed at group and circles [30]. The disasters certainly
damage infrastructure causing the obstacle in the smooth system traffic flow resulted
in overcrowding and delays in rescue operations. To handle these issues Delay Tolerant
Network (DTN) routing is suggested that has ability to transport data in an alternating
network [31]. Internet has been successfully used in almost all aspects of society and
economy. This success of internet has generated a dependence on communication as
numerous of the processes behind the grounds of modern society. Though, copious to
our disappointment, the present state of security and accessibility of the internet is far
away from appropriate by its position. The internet has not been mainly premeditated
for high accessibility to face nasty actions by challengers. This article defines
(Scalability, Control, and Isolation on Next-generation networks) SCION, an system
architecture planned to deal with these issues [32]. The researchers have described the
application of SNA in the disaster effected area and show the shifting framework of
networks after the disaster. The disaster event was divided into four separate phases
namely ‘extreme event’ ‘immediate community response’ ‘relief’ and ‘rehabilitation
[33]. The Disaster management services are vital and serious research matter.
Emergency communication networks (ECNs) bring important functions for disaster
management and it plays an important role in the communication service which are
normally inaccessible due to major damage and limitations in communication services.
In this research, the researchers compare both ECNs and Big data. Further they study
the exiting data mining and analysis them. Usage of hybrid ECNs as shown in the
figure 2.9 [34].
17
Figure 2-9: Usage of Hybrid ECNs [34].
The researchers have focused on the need of social media information into the resilience
process. The researchers argue that despite of widespread use of the social media in
numerous domains e.g. (finance/marketing/building), there is also needed to focus on
social sensor for security and emergency management applications. The researchers
describe EUFP7 project SUPER( social sensors for security assessment and emergency
management [35]. The researchers have examined the real-time interaction of various
events such Twitter in earthquake and proposed an algorithm which monitor tweets and
also detect an objective. The researchers develop a system to use it in Japan. This
system detects earthquakes with high probability and notifications are delivered much
faster than Japan Meteorological Agency (JMA) [36]. The governments’ policies to
diminish the damages caused by natural catastrophe deemed to focus on the impacts on
(DEWS) disaster early warning system. In this research the researcher’s goal was to
improve natural hazards impact on disaster early warning system. The researchers have
proposed that the government should have different types of mechanisms to inform
their citizens such as by tweeter to inform them well in time so that they can be safe as
early as possible. The researchers focused on speed and massive spread of the
government’s tweets; tsunami early warning system would be less sustainable without
citizen’s straight involvement in re-tweeting. The government should have to the
support of re-tweet mechanism of an event so that it could affect significantly for the
society and safe their lives with in time [37].
2.6.5 HAP (HIGH ALTITUDE PLATFORMS)
Keeping in view the unfeasible situation for helicopters to fly at very low height (fewer
than 300 meters) due to certain reasons, genesis the dire need to activate high altitude
18
platform (HAP) unmanned systems, such as based on helium gas balloons systems
which is a faster, accurate, lower cost and safer. These systems devise many benefits,
for example in typhoon, earthquake, disaster areas to investigate, and the actual time
information direct to the base station. [38]. High altitude balloon (HAB) is a stable and
ultra-long duration podium that can continue motionless condition would be new
pattern for high-altitude surveillance and broadcast services for telecommunications.
Electro hydrodynamic offered to keep position by overwhelming stratospheric storms
[39]. The motivation of this research is to develop such system which remains active
all time and fault tolerant with respect to natural disasters. The researcher main focus
was to involve transmission of warning signals of disaster, signals information related
to disaster relief by using an all-terrain Unmanned Ground Vehicle [40]. In this
exploration, scholars present an observing system of wireless ballooned combination
of Omni-directional high-resolution camera and wireless LAN to take images and
videos from sky, also sends them to base station on the ground. These wide area images
are then send quickly for rescue to disaster headquarter [41]. The researchers suggest
a Medium Access Control protocol i.e. Location Oriented Directional MAC
(LODMAC) protocol. The LODMAC effectively grips data transmission and the
detection in parallel through directional antennas [42]. The researcher dowries a
summary of (HAP) networks, and examines application on dissimilar network, like,
intelligent environmental monitoring, transportation systems, two-way (hybrid)
communication networks etc. Momentarily HAPs have precise characteristic that can
be extensive in future networks. The research also emphases on the technical matters
which are connected to HAP networks and it can be connected to other networks like
(terrestrial or satellite) as shown in the figure 2.10 [43].
Figure 2-10: High Amplitude Platform System Architecture [43].
19
2.6.6 FANET (FLYING ADHOC NETWORK)
Flying ad-hoc networks are attractive an encouraging solution for diverse application
situations connecting unmanned aerial vehicles, like urban surveillance or search and
rescue missions. Though, such systems present numerous and very precise
communication matters. In this article, researcher list the present mobility prototypes
and provide direction to comprehend whether they could be really accepted dependent
on the exact flying ad-hoc network application circumstances, whereas debating their
advantages and disadvantages [44]. In this research, the researcher associates two
dissimilar algorithms used in ad hoc networks that are improved link-state routing
(OLSR) and predictive OLSR (P-OLSR). The last OLSR is designed especially for
FANETs. It has the benefit of Global Positioning System is available on panel. P-
OLSR is now the individual FANET routing method available for Linux
implementation [45] . In this research the researchers focus on the abilities and roles of
UAV quickly changed recent years. The usage of UAV in military and as well as
civilian areas are tremendously dominant in the developments the technology of
robotics like sensors, communication systems, processors, and also networking systems
[46] . In the research article, researchers have investigated Flying Ad-Hoc Networks
with challenges linked to outdated ad hoc networks. The current routing protocols of
FANETs are categorized into six major categories [47]. In this research, they survey
FANET system and are connected the UAVs. The modifications among VANETs
(Vehicle Ad-Hoc Networks) MANETs and FANETs, are explained and then FANET
design experiments were presented. Laterally they presents the current FANET routing
protocols, outdoor research matters are discussed [48]. The figure 2.11 shows the
overview of the system.
Figure 2-11: FANET Systems [48].
20
2.6.7 UAV (UNMANNED AERIAL VEHICLE)
UAV are ahead of popularity growing communication systems of different service
suppliers. Developing system, like mobile edge computing and LTE 4G/5G systems
will expand the use of UAVs. In the research, researchers argue the prospective of
UAVs, armed with devices, for providing Internet of things services from great heights
[49]. During the public-safety operations communications play a significant role.
Since the present communication systems deeply depend on the mainstay network, in
the failure of base stations (BSs) due to natural disasters or spiteful attacks causes
communication problems for emergency communications and public safety. In recent
times, the use of UAVs, such as gliders and quad copters, has grown consideration in
public safety communications (PSCs). They can be operated as unmanned aerial BSs
(UABSs), which can be positioned quickly as a part of the heterogeneous-network
(HetNet) architecture [50]. Emergency relief squads and disaster managers have to
work continuously quicker with a cumulative requirement of extraordinary quality,
high-resolution geospatial data to achieve reach level such of competency that is needed
with the usage of UAV (Unmanned Autonomous Vehicles), both on the ground and
airborne [51]. In this research, researchers proposed UAV-based design and IoT
services being presented, also the significant key challenges and necessities are
discussed [52]. In this research the researcher focus on the RIFD technologies are
applied in a various environmental observing application. The proposed system
composed of the RFID technologies and an UAV. The notion is to use the UAV to
gather data from the RFID sensors spread to wide area by only flying above,
approaching, and downloading collected data. The justification could be acknowledged
to implement a RFID sensors which cover a large area, which is unsafe situations for
humans [53]. In this research, the researchers proposed a new multi UAV for FANETs
to achieve the target in minimum time, while conserving all time network connectivity.
This is the effectiveness in the mission completion and all cost efficient in the task
distribution. Multi UAV for FANET are shown in the figure 2.12 [54].
21
Figure 2-12: UAV systems [54].
In this research focus on live aerial observations operations center to control center, in
form of video, photos information for decision making. They are valued in several
important mission operations, like security, safety, police operations, and disaster
management. To acquire these annotations, the use of small UAVs is good-looking but
then frequently defied the absence of appropriate explanations to improve a real-time
image capturing mechanism for decision makers. In critical mission and operations, the
in-depth observations, should be in real time and information should be shared. It is
necessary for UAV to fly anywhere /anytime, established on radio line-of-sight.
Satellite communications is compulsory in the UAV to secure the observations that can
be shared. In this research scholars proposed an innovative idea for collecting live
critical mission photographic and video streaming information through UAVs that
compete these outdated system operations [55]. Admitting the necessity for boosting
disaster resilience networks, the researcher in this research have presented an idea for
improving the up to date improvements in unmanned aerial vehicles (UAVs) and
wireless sensor network technology to increase the capability of network-assisted
disaster response, prediction, and assessment whenever a disaster occurs, the supreme
significant matter is protecting human lives. In this situation, the first 72 hours after the
disaster are crucial for search and rescue operations to accomplished quickly and
efficiently. Particular , researchers present an methodology for categorizing disasters,
and they also suggest a suitable network architectures for the disaster management
services on these observations [56].
22
2.6.8 DRONES TECHNOLOGY
The Drone technology has been used in rescue and search operation in different
scenarios such as earthquake disaster zones, floods, and upper surface detections.
However, drone technology has only capability to identify the upper surface survivals
in any disaster zones. The existing drone technologies search and rescue operation were
referred and evidenced to be insufficient. However, some researchers start working on
drone to increase the capabilities by some modification such as embedded some sensor,
high resolution camera and modify and improve the limitations of the pervious drone
technologies. In literature a researcher suggests to integrated sensor technology along
with drone technology to provide accurate, quick, and safely identify the misplaced
survivals in the wilderness and disaster by using multimodal sensing methods. In this
method, drone technology was used to send the feedback to operators on field, victims
and deliver the necessarily supplies to the survivals [57]. After embedded the
multimode sensing technology with drone, the researcher claimed that the modified
drone is better, effective and in the rescue and search operation to survivals in any
disaster [58]. Indonesia and Japan are the most affected countries by different disasters.
the communication networks were badly affected and damaged just after occurrence of
disasters while the government used different reliable communication links to restore
and overcome the difficulties in rescues and search operations but unable to find the
survivals from disaster timely [59]. However, to overcome the searching problems, the
government design and implemented autonomous based operation where they used the
autonomous navigation based three-dimensional drone technologies to detect the
obstacles and survivals detections and tracking systems [60]. Some other researchers
developed a swarm quad rotor robot who have capability to self-deployments on
disaster area and extended the Wi-Fi services coverage. The proposed quad rotors create
a Wi-Fi network where the other nearest devices join that network and restore the
communication links on the disaster zones. The quad rotor robots are based on parrot
AR drone with Wi-Fi adapters and GPS module [61]. Another research suggests using
multiple small drones or Unmanned Aerial Vehicles to locate the areas by the help of
webcams to send the information to rescue teams and observe the activities in disasters
zones. Furthermore, the small multiple drones helped to locate the hotspots where
identify the buried and broken persons and also maintain the internet connectivity to
disseminate the necessary information [62]. One researcher developed a multimode
23
frame works which allows the operators to interact with drone technology to perform
the search and rescue operations in contrast of normal rescue operations. The proposed
framework supports the multimodal communication along with human and robots to
develop an effective and natural interaction among them [63]. Similarly, the Italian Fire
Crops developed a team of operators and robots (UGV, UAV) in the red zone of
Mirandola to provide quick response and recovery of population and building in case
of any disaster [64]. The multi drone interaction prototype system was developed by a
researcher to allow an operator to supervised and control the rescue operations and set
of UAVs by means of multimode communication. The main task of that multimode
drone technology was to locate the misplaced person in disaster affected areas [65].
2.6.8.1 SURVIVALS FINDING TECHNOLOGIES USED IN DRONES
The most important role of drone till now is to involve in saving human life in many
search and rescue operations. Drones offer a surprising way to rapidly find missing
people with normal cameras or thermal imaging sensors, and also have capability for
emergency supplies like medicine, water, rescue ropes, life jackets etc.
The drones are also used in the sky to monitor and protect rescue workers during fires
and SAR operations without putting them to danger. Constrained area for searchers put
the workers at risk, rapid up the rescue work and increasing the rescue capability of
survival. Mostly rotor wing drones are used in search and rescue operations it is shown
in the figure 2.13 (https://www.dji.com/phantom).
Figure 2-13: Rotor Wing drone
According to the first published DJI list 2017 59 lives have been saved by drones in 18
different occasions. Out of 59 people 38 of those were saved in just the last 10 months.
24
Another 19-missing people were found on mountains, snowbanks and on land. Nine
more people were rescued from non-flooded water environments, including off beaches
or in boats. now it is reported that drones are saving one person per week [66].
Table 2-3: Features and Limitations of Technologies used in Drone
The figure 2.14 shows the graphical representation no of disasters and the people saved
by the drones by year from (2013-2017).
4
2
6
21 1
4
1413
10
2
2013 2014 2015 2016 2017
NO
OF S
UR
VIV
ALS
YEAR OF DISASTERS
USA Canda China Turkey UAE
Country Features Technology limitations
Canada
1: Infrared Camera
and Camera technology
In Canada in three disasters the simple drones were
used with Infrared camera and with normal camera
embedded to save six lives.
USA
1: Camera/GPRS
2: Heat Sensing Camera
and Hook embedded with
camera
In USA four types of the technology embedded drones
were such as camera/GPRS, Heat Sensing camera,
simple camera and hock. Attached used in eight
disasters to save fourteen peoples.
China
Hook embedded with
camera
In china, drones were used with very simple
technology just camera with hock embedded to save
twenty-seven survivals in five different disasters.
UAE High Resolution Camera
technology
In UAE two persons were saved with simple camera
embedded drone technology
Turkey Camera Technology In Turkey ten lives were saved by the single
technology-based drone
25
Figure 2-14 Survivals rescued worldwide by the years (2013-1017)
2.6.8.2 EMERGENCY RESPONDERS
The drones can contribute the valuable role to keep rescue workers safe during
emergency operations by providing them aerial views, also shows better way to access
or entering unsafe circumstances. Drones have an eye view in the sky and have all the
viewpoint that could be helpful to the responders to well plan for the best to action
without put themselves in danger. The drones are used in different countries in
emergency situations and they have not only help in searching the people but also
managed to save lot of peoples in very short time. Some countries are being discussed
in which the drones play a vital role in emergency situations. The Royal Canadian
Mounted Police in have successfully used the small helicopter drone to locate and treat
an injured man [67]. A man with dementia who had disappeared was found within
hours, by using some new drone technology[68]. An drone was used to rescue four
people in darkness, and snow infrared-equipped mechanism in British Columbia [69].
The drone had a haul line attached to it and flew to the middle of the river to rescue the
18-year-old person. The drone took video footage of the rescue operation. [70]. One
volunteer Garret Bryl, drone pilot, used his drone on two separate occasions to help
save four people floodwaters[71]. The Tippecanoe County Sheriff’s office with a drone
helped find missing teacher Krista Perdue alive [72]. A 20-person team was searching
uses a drone and within three minutes of takeoff, they found the missing person and a
young girl [73]. A drone helped save a lost hunter and his dog in Anoka County. A 65-
year-old hunter and his dog were hunting in the Carlos Avery State Wildlife
Management area in the northeastern corner of Anoka County[74]. Guangxi Province
suffered from heavy rains and due to heavy rains too many people were trapped in the
floods. Six people were saved by using drones to rescue them by ropes, and supply
them food into the storm. Fire Rescue after searching for about 20 minutes, they found
two kayakers near the causeway at the state park by use of a drone with thermal imaging
technology as shown in the figure 2.15 [75] .
26
Figure 2-15: (Georgetown County Emergency Management) [75]
The drone was used to locate 36 people who were trapped due to flooding of the Weihe
River [76]. Total 14 construction workers in Wutong Town, Lingui District, was
trapped and was trapped for more than 3 hours. The drones were used to deliver the
rescue supplies to be trapped people. The rescue started in full swing and 14 trapped
staff escorted to a safe position, all out of danger[77]. A woman climbing
mountaineering scenery, trapped because of fire after receiving the alarm, the rescuers
enable drone detection to find trapped woman, and then use the rope to save her from
the mountain[78]. From the coast of Ajman in the UAE drones were used maritime
search and rescue operations in which two people who were rescued [79]. In Turkey
film crew who went missing in a remote region were saved by a drone. Crew was
consists of Ten men were saved after being identified by drone in the Adana region[80].
December, 2015 in India, up to 200 individuals, were spotted and rescued by drones
[81].
2.7 RELATED WORK
In literature, some researchers suggest and proposed various technologies to
identify the survivals from the earthquake disaster zones such as PIR,
Microcontroller based GSM technology, power line communication which helped
to provide the information about vibration, temperature, ultra-sonic detector as
well as IR. These technologies are used to indicate the presence of aliveness of
human bodies and communicate that information to remote control rooms [82].
The different kinds of radar system have been using by various researcher for
evaluating the human bodies’ movement during disasters. The frequency-based
27
radar was used to detect the human presences and indicates the human activities.
Moreover, the latest radar technology allowed the measurement of regular velocity
of person movements [83]. Some Ultra-Wide Band radar sensor has a capability to
sense the person behind the wall such as during earthquake, survivals can be trapped in
collapsed buildings, the sensor were used to locate the survivals locations. The
proposed sensor used standard deviation approach to sense through different building
materials such as wall, wooden door[84]. Another research approached was based on
robot system along with lightweight sensors for the survival detection [85]. It comprises
the integrated various biological sensors with radio interface to sense biological data
from a survivals body and then sent that information to remote healthcare cloud center
via smartphone as an interface. The PIR based robot technology was used to detect the
aliveness of humans in debris so the timely help can be possible as soon as possible to
the survivals. The robot technology is equipped with passive infrared sensors and
robotic arms was used to remove the obstacle in its ways and camera was used to send
the image to control station while microcontroller is used to control the activities of
robots [86].
A researcher proposed a system with novel concept as arrayed laser image contrast
evaluation (Alice) to identify survivals bodies which is based on unique characteristic
of human skins. In that system an NIR dot array laser was used to illuminate, and
irradiated area detected from the human skins using a near infrared camera [87].
Another experiment done by the PANDORA robotic team aims to develop a robotic
platform which was used to identify the survivals from any disaster zones [88, 89]. The
hybrid radar with wideband Boolean Chaos Code and single phase based Doppler Mode
has been developed by the experts to human localization and heartbeat and respiration
detection. The signal-based processing technology of the radar system allows working
simultaneously on two modes for different aims [90]. The 24GHZ Doppler radar
network was design for non-contact human respiration detection signal and it also
support self-correlation that can be used to increase the quality of the respiration
signals. This method minimizes the interference of any moving object around the
human body [91]. Another ultra-wide and radar was used to collect eco signal from the
stationary and moving statuses of survival bodies [92]. The surveillance robots were
also used to collect the aliveness signs of human bodies such as live videos, surrounding
area conditions, temperature measurements, humidity, gases volume and vibrations
28
[93]. The ultra-wideband radar performed key role to locate the victims by detecting
respiration and heartbeats signals and rescue the survivals from the disaster’s areas [94].
Many other technologies have been proposed by different researcher to rescue the
human lives from the disaster’s areas such as thermal camera, CO2 sensors, and
microphones. These technologies detect the human bodies from the rubbles and high
risky areas of disaster zones. The CO2 sensor is used effectively to reduce the disturbed
zone, while the thermal camera endorses the accurate location of the object [95].
Nowadays the smartphone technology with embedded sensors is used to locate the
motions of earthquake as well as human being motions. A researcher developed a
seismic network using smartphones which increases traditional networks capabilities to
detect the devices, distinguishes earthquakes and human activates. An algorithm was
embedded with smartphone technology that effectively differentiates the human
activities from the earthquake disaster [96]. In [97], the researchers have used drone
technology to detect the survivals through images and videos, and a PC controlled robot
was used to detect the under- surface survivals through PIR and ultrasonic technology
[98]. In [99], a proposed system of drone captures image sequences through camera to
detect the motion of the chest movement of survivors. In [100], UAV has been used for
the detection of the survivals and in [101], three types of sensor system have been used
to detect the survivals
2.8 SUMMARY OF THE EXISTING ICT NETWORKS USED IN
LITERATURE
Several types of Information Communication networks have been debated in the
literature are summarized in the table 2.4..
29
Table 2-4: Summary of literature review
Year
Title of Publication
Technologies
Working/Limitations
2020 “Detection and Localization
of Life Signs from the Air
Using Image Registration and
Spatio-Temporal
Filtering. Remote Sensing”
[97]
Drones • Researchers present a new technique
to guess the positions of people from
aerial video using image and signal
processing designed to detect
breathing movements.
2019 “PC Controlled Wireless
Robot for Detecting Human
Presence.” [98]
Robot • A PC controlled wireless robot has
been proposed for detecting human
presence with the PIR and ultrasonic
waves.
2019 “Life signs detector using a
drone in disaster
zones. Remote Sensing” [99]
Drone • The proposed system uses image
sequences captured by a drone
camera to remotely detect the
cardiorespiratory sign caused by
discontinuous chest movement of
survivors
2018 “Evaluation of a sensor
system for detecting humans
trapped under rubble: A pilot
study. Sensors” [100]
Sensor • A system based on thermal camera,
microphone and CO2 sensor has
been developed to detect the
survivals trapped under rubbles.
•
2018 “Rapid Human Body
Detection in Disaster Sites
Using Image Processing from
Unmanned Aerial Vehicle
(UAV) Cameras” [101]
UAV • The research proposes to detect the
human body skin, by image
processing system built-in UAV and
the camera can clearly detect
survivals body or a part of body.
2017 “Help from the Sky:
Leveraging UAVs for
Disaster Management” [57]
Drones
• The proposed system can only detect
the over -surface disaster survivals
but does not detect the survivals
locations.
30
Year
Title of Publication
Technologies
Working/Limitations
2017 “UAV-Based IoT
Platform:
A Crowd Surveillance
Use Case” [50]
UAV
Networks
• Proposed system can be used for
surveillance only and detect upper
surface survivals.
2017 “The role of Big Data in
explaining disaster
resilience in supply
chains for
sustainability” [29]
Social
Networks
• Community and social systems are
being used as early warning system to
communicate the information about
disasters through SMS messages
service to the people.
2017 “Characteristic ground
motions of the 25th
April 2015 Nepal
earthquake (Mw 7.9)
and its implications for
the structural design
codes for the border
areas of India to Nepal”
[33]
Wireless
Sensors
• The wireless network has been used in
Nepal and India with structural design
code for border areas for the purpose of
monitoring of the characteristics of the
ground motion in 2015 earthquake.
2016 “Software Defined
Mobile Sensor Network
for Micro UAV
Swarm” [59]
MAV
Networks • The proposed system has providing
SMS services for information from
the inaccessible locations by using
mobile adhoc networks.
2016 “UAV-based
Photogrammetry and
Geocomputing for
Hazards and Disaster
Risk Monitoring” [52]
Ad Hoc
Networks
UAV
• Suggested systems allow a small-
term transmission between a
disaster zone and a base station..
31
Year
Title of Publication
Technologies
Working/Limitations
2016 “Social Networks in
Crisis Response:
Trust is Vital” [102]
Social
networks
• Social networks are used for the
information on social and electronic
medium for the news about the
disaster incidents.
• Cannot track aliveness of survivals
2016
“Using tweets to
support disaster
planning, warning,
and response” [103]
Social
Networks
• Tweets are used to flow the
information about the disaster area as
an early warning to the community
for better planning and quick
response.
• Through SMS services the disaster
locations are indicated
2016 “A dynamic decision
support system
based on
geographical
information and
mobile social
networks: A model
for tsunami risk
mitigation in
Padang, Indonesia”
[104]
Mobile
Social
Networks
and GIS
• This system is designed as a field
experiment in Padang, Indonesia, to
help public officials design tsunami
risk maps with timely evacuation
routes and transmit these maps to
influential leaders in local
neighborhoods that are exposed to
tsunami risk
2016 “A Resilient
Network and
Information
Management System
for Large Scale
Disaster” [7]
LAN,
WAN,
Internet,
and Radio
systems
• In this paper, the information network
recovery activity on the East Japan
Great Earthquake is described.
• Then the problems of current
information network systems are
analyzed to improve disaster
information network and System
through the network recovery
activity.
2016 “A geographical and
multi-criteria
vulnerability
assessment of
transportation
networks against
extreme
earthquakes” [14]
GIS • The researchers have developed a
geographical and multi-criteria
vulnerability assessment method.
• Also, Measure the impacts of extreme
earthquakes on transportation
networks.
32
After discussing the proposed system in literature they are compared with the pre-
defined research parameter for the survivals detection system and also compared
the ability to send the real time information flow mechanism from disaster zone to
the remote area to the concern departments for the search and rescue operation.
Year Title of Publication Technologies Working/Limitations
2015 “A Cooperative
Network Framework
for Multi-UAV
Guided
Ground Ad Hoc
Networks” [105]
Ad Hoc
Networks
• The proposed framework can form a
search maps that are able to define
multiple way points for each UAV in
the network to follow a non-
redundant path for searching and
identifying various user nodes and
geographical territories.
2015 “Autonomous
Drones for Disasters
Management: Safety
and Security
Verifications” [106]
Drones • A parrot platform is used to capture
videos of its surroundings.
• Those videos are transmitted by the
UAV to a remote computer, which
autonomously controls the drone
according to its mission.
2014 “SAR.Drones:
Drones for
Advanced Search
and Rescue
Missions”[61]
Flying
Technolog
y
• The researchers present the
framework based on visual
assessment of disaster areas
2013 “On the performance
of Flying Ad Hoc
Networks (FANETs)
Utilizing Near Space
High Altitude
Platforms (HAPs)”
[43]
FANET
Networks
• A Medium Access Control (MAC)
Location Oriented Directional MAC
(LODMAC) protocol is used for
discovery and data transmission in
parallel with the help of directional
antennas.
33
Table 2-5: Comparison of existing system with the proposed research parameters
Systems Integration
with Multiple
Networks
Over surface
Detection
Under surface
Detection
Location
Tracking of
survivals
Respiration
Detection of
survivals
Under
surface
Movement
Detection
of survivals
Under
surface
GSM
based
Alerts
GIS √ √ × √ × × ×
WAN √ × × × × × ×
Social
Networks √ × × × × × ×
Multi-WSN √ √ √ × × √ ×
HAP √ √ × √ × × ×
FANET √ √ × √ × × ×
UAV √ √ × √ × × ×
Drones √ √ × √ × × ×
In the above table there were some research parameters the system should have to
match for the better performance to locate and find the survivals. From the existing
system mostly the multi WSN can be used to meet the maximum research
parameters as given in the table 2.5. Other than that, are just meeting the few
research parameters.
After this comparison we have to develop a system that can meet the maximum
research parameters to complete our task for the detection of the survivals and to
transmit the real time information of the survivals to the concern departments for
the search and rescue operations.
34
2.9 RESEARCH GAP
The National Disaster Management Authority (NDMA), in charge of rescue
operations in Pakistan, does not have an efficient, resilient ICT communication
network for disaster management. The ICT network used by NDMA has the
following limitations because of which they are unable to locate the survivals of
disaster.
• Inability for restoration of communication after occurrence of earthquakes.
• Lack of mechanisms for transmitting real time information about the
affected areas.
• Lack of mechanisms for detecting the survivals and their positions in
disaster affected areas and sending this information to concerned disaster
management department(s).
• This research proposes a resilient ICT networks-based Interaction Retrieval
Architecture (IRA), which addresses above limitations.
2.10 SUMMARY OF THE CHAPTER
In this chapter the background of the research and the role of the local and
international responses of different governments, organization and NGOs after the
happening of the earthquakes is discussed. Moreover, different resilient
communication networks globally proposed by different researchers are analyzed
in order to indicate the development and the existing gaps in this research field. In
this regard various networks have been discussed in detail. The main focus was on
detecting the survivals in earthquakes through the above proposed resilient
networks used in natural disaster especially earthquakes. The limitations of the
existing wireless technologies are compared with the designed resilient ICT
networks-based Interaction Retrieval Architecture (IRA). The research Gap is also
identified.
35
CHAPTER 3
RESEARCH DESIGN
3.1 RESEARCH METHODOLOGY
The research design chapter elaborates the various steps towards the culmination of the
current research work. It is divided into seven phases and every phase demonstrates
different stages of the research work as shown in figure 3.1.
Research Design
• Research
articles
• Journals
• Conferences
• Newspapers
• News
• Web sites
• Workshops
• Surveys
• Meetings with
• NDMA
• SDMA
• GBDMA
• Disaster
Management
• Services
• NDMA
• SDMA
• GBDMA
Literature Review
• Wireless
Communication
Networks
• MANET
• VANET
• FANET
• GIS
• HAP
• UAV
• Drones
Testing of simulation in earthquake zone
scenario
Hardware design of the proposed systemInteraction Retrieval architecture design
and simulaion
• Problem Identification and
justification
Results and Analysis
Implementation of proposed system
Phase 1
Phase 2
Phase 5
Phase 4 Phase 6
Phase 7
Phase 3
Figure 3-1: Research Design
36
3.2 PHASE ONE: LITERATURE REVIEW
The phase consists of extensive literature review such as study of different articles,
review of different disaster management services, filed visits and extensive of
different communication technologies as illustrated in figure 3.2.
• Research
articles
• Journals
• Conferences
• Newspapers
• News
• Web sites
• Workshops
• Field Visits
• Meetings with
officials of
• National Disaster
Management
Authority
• State Disaster
Management
Authority
• Gilgit Baltistan
Disaster
Management
Authority
• Disaster
Management
• Services
• National Disaster
Management
Authority
• State Disaster
Management
Authority
• Gilgit Baltistan
Disaster
Management
Authority
Literature Review
• Wireless
Communication
Networks
• Mobile Adhoc Network
• Vehicle Adhoc Network
• Flying Adhoc Network
• Global Information
System
• High Amplitude
Platform
• Unman Aerial Vehicles
• Drones
Phase 1
Figure 3-2: Components of Phase-1 of Research Design
3.2.1 RESEARCH ARTICLES
Literature review is categorized in four major parts:
• Journal articles, conference papers, poster papers, books newspapers websites,
and related seminar.
• Media news, such as the television programs, print and social media news
related to the resilient ICT networks that are been used in different countries for
disasters handling.
• Reports and official documents available for the disaster management and
different services related to it.
37
3.2.2 DISASTER MANAGEMENT SERVICES
The disaster management services review includes the various services render by
different disaster management organizations to handle the natural disaster at various
levels such as National Disaster Management Authority (NDMA). The NDMA is
responsible to establish a communication mechanism among the various provisional
disaster management cells to handle the damages caused by various natural disasters.
The NDMA also provides different services such as technical, financial, transportation
and rescue assistances to provisional disaster management authorities. State Disaster
Management Authority Azad Jammu & Kashmir (STDMA, AJK). The STDMA-AJK
was established in 2006. It is responsible to handle the earthquake disaster in Azad
Jammu & Kashmir State. Moreover, The STDMA provides quick response when any
natural disaster is occurred and also performed the weather forecasting. Gilgit Baltistan
Disaster Management Authority (GBDMA). The GBDMA was established in 2010 in
Gilgit-Baltistan province to manage monitor natural disaster occurs due to earthquake,
floods, avalanches and landslides.
3.2.3 FIELD VISITS AND MEETINGS
Visits of National Disaster Management Authority, State Disaster Management
Authority Azad Jammu and Kashmir and Gilgit Baltistan Disaster Management
Authority Gilgit offices in person meetings and Interviews such as, Director State
Disaster Management Authority Azad Jammu and Kashmir, Assistant Director Gilgit
Baltistan Disaster Management Authority Gilgit
3.2.4 EXTENSIVE STUDY OF DIFFERENT COMMUNICATION TECHNOLOGIES
The section of literature review consists of profound study of the various wireless
technologies such as, Wireless Communication Networks, Mobile Adhoc Network,
Vehicle Adhoc Network, Flying Adhoc Network, Global Information System, High
Amplitude Platform, Unman Aerial Vehicles and Drones technologies are used in
disaster zones to rescue the disaster survivals.
38
3.3 PHASE TWO: PROBLEM IDENTIFICATION AND JUSTIFICATION
The figure 3.3 shows the diverse existing wireless resilient information and
communication networks used to obtain the information from the disaster affected
zones:
Process
critical review of research articles,
media reports, news for communication
networks used in detection of
earthquakes survivals
Review of ICT based Resilient
Networks used in earthquakes
Identification of features and
limitations of available ICT Resilient
Networks
Justification of Interaction Retrieval
Architecture (IRA)
Phase 2
Figure 3-3: Study of Existing Resilient Networks
After critical review of literature and various ICT based resilient wireless networks
being proposed by different researchers (e. g HAP, UAV, Drones etc.) for the disasters
especially earthquakes. The next step is the identification of the features and limitations
of existing available networks which are being used to detect the earthquake survivals.
The existing resilient networks can transmit information between disaster zone and base
station offices. However, existing ICT networks do not have mechanism to detect
survivals location and their aliveness signs. Moreover, these systems have not
bidirectional communication links among survivals, rescue teams, base stations offices
and NDMA. To cops the limitations of existing ICT based resilient networks, the
Interaction Retrieval Architecture (IRA) has been designed and develop.
39
3.4 PHASE THREE: PROTOTYPE SYSTEM DESIGN
Phase three comprises the system simulation in proteus environment, identification of
system components and design of hardware system. The figure 3.4 shows various steps
toward the culmination of system designing.
Process
Identification of hardware components
to design a prototype system
Development of Hardware module
System Simulation in Proteus
Phase 3
Figure 3-4: Steps of prototype System Design
3.5 PHASE FOUR: SYSTEM SIMULATION IN PROTEUS ENVIRONMENT
WITH DIFFERENT SCENARIO
The design system has been simulated in proteus simulation environment. Where the
prototype system has been tested through different scenarios while different parameters
has been set for the system simulation such as parameter for single heartbeat, two
heartbeats and three heartbeats detection. The phase four explains various steps of
system simulation scenarios to detect the heartbeats of survivals as shown in figure 3.5.
40
Testing of developed system in three
simulated scenarios
Scenario 1:
Multi-level building
Scenario 2:
Single and double story
Scenario 3:
Mega Market
Phase 4
Figure 3-5: Proteus simulation Scenarios
3.6 PHASE FIVE: HARDWARE COMPONENTS OF SYSTEM
The figure 3.6 depicts the hardware components of hardware prototype system such as
(i.e. Arduino Mega 2560 microcontroller, respiration module GSM SIM 900, cell
phones, LCD, aliveness indicators, resisters, 5vDC level shifter, storage module and
respiration module.
Hardware Design and Component Identification
for development of prototype
Under Surface
Liveness Detection
of survival
GSM Module Arduino Board
Mega 2560
Respiration
detection,
body movement
and measurement
of breathing
patterns
Phase 5
Communication and
Tracking Controller
Figure 3-6: Components identification and hardware design of system
The aliveness indicators are used to locate the under-surface aliveness such as
respiration, body movement, and breathing measurements detection of the earthquake
41
survivals. Moreover, communication and tracking links disseminate the information via
GSM communication module between affected zones to base-station office. The
controller (Arduino 2560 MC) is the brain of system which controlled the overall
activities and functioning of the whole prototype system.
3.7 PHASE SIX: IMPLEMENTATION AND TESTING OF SYSTEM
The phase six includes the designing, implementation and testing where the system has
been design, implemented and tested in controlled environment to check the
performance of system figure 3.7. The system evaluation is based on proteus simulation
and hardware-based environments. The proteus based simulation is further divided into
three different scenarios: Multi-level, Single/double story and Mega Market Buildings.
The system simulation is based on heartbeats detection of the survivals. The hardware
testing environment was also further divided in controlled and open-air environments.
The prototype results are based on movement detection, movement tracking, breathing,
breathing tracking and respiration per minutes (RPM) respectively in different building
structural materials. Derbies of
System Testing in controlled
environment
Testing in Proteus Simulation Testing of Hardware
Prototype
Phase 6
Scenario 1:
Multi-level Building
Scenario 2:
Single/double story
Building
Scenario 3:
Mega MarketOpen Air Test Under various Building
Materials
Survivals Heart
Beat Detections
Movement
Tracking
Breathing
Tracking
Respiration
Per Minutes
Figure 3-7: Testing of system in simulation and in laboratory
3.8 PHASE SEVEN: RESULTS AND RESULT ANALYSIS OF THE SYSTEM
Phase seven comprises of the simulation and hardware-based results of the prototype
system. Simulation results based on single and multiple heartbeats detection and
42
hardware component is further comprises in two parts as operational and base-station.
The operational component is used to detect the survival movement, breathing and
respiration information and broadcast that information to the base-station component
while the base-station components share the same information among the various
organizations through cell-phone-components of the system as shown by figure 3.8.
Results and Analysis
Simulation Hardware
Phase 7
Single Heartbeat
Detection
Multiple Heartbeat
Detection
Operational
Component
Remote Area
Component
Detection of
Survivals
Real Time
Information
Brodcasting
Cell Phones Base Station
Real Time Information Broadcasting
from Disaster Zones
• Analysis of Incoming Results
• Develop Communication between
different components of the system
Figure 3-8: Results and Analysis
3.9 SUMMARY OF THE CHAPTER
The above discussion displays and explains the research design of the recurrent study.
It illustrates that the current research design comprises in seven phases and every phase
indicates the different steps to the culmination of prototype system design. The phase
one elaborates the extensive literature review (journal articles, conference proceedings,
books and different print, electronic and social media news). Moreover, literature
review phase includes, in persons meeting and interviews with the responsible of
STDMA and GDBMA. After the completion of literature review, the problems with
existing system has been identified. When the research problem has been identified, the
next step is designing the logical architecture of prototype system in proteus
environments and the system has been simulated in proteus simulation software. In
43
addition, the system hardware components have been identified through proteus
simulation environments. Once the prototype system is simulated the next step was the
designing of hardware module to detect the location, movements, heartbeats, breathing
and respiration per minutes (rpm) of the survivals. Moreover, the system performance
has been tested and evaluated through different substances.
44
CHAPTER 4
DESIGN AND IMPLEMENTATION OF
PROTOTYPE HARDWARE SYSTEM
In this chapter we propose architecture for earthquake disaster management system
called Resilient ICT Networks Based Interaction Retrieval Architecture (IRA),
which can be adopted by NDMA Pakistan. While the proposed architecture
provides a comprehensive earthquake disaster management system, in order to test
its basic and core functionality we have implemented prototype hardware system
that comprises some core components of this architecture. In this chapter , we also
provide a description of proposed architecture along with its various components
and discuss our prototype hardware system and its working. The prototype
hardware-based system is used to locate the survivals from the disaster affected
area. The system helps rescue teams to identify the survivals location, movement
detection, breathing tracking and respiration per minutes (RPM). In addition, it
develops bidirectional communication links among the disaster affected zone,
remote base-stations and quick disaster management response center for the rescue
purpose. The system design comprises operational hardware and base-station
hardware components. The operational hardware component is responsible to
track the survivals under surface of the disaster zones by using sensing technique
and transmit information to base-station hardware component through GSM SIM
900 communication protocol, while the base-station hardware component
disseminates the acquired disaster information among the operator cell phone,
central disaster management database cell, quick disaster management response
center and national disaster management authority.
4.1 RESILIENT ICT NETWORKS BASED INTERACTION RETRIEVAL
ARCHITECTURE (IRA).
The proposed resilient IRA comprises various components such as Early Warning
System Networks (EWSN), Rapid Response Networks (RRN), Central Disaster
Management Organization Database Cell (CDMDC), Quick Disaster Management
Response Centre (QDMRC) and NDMA as shown in figure 4.1. Moreover, the
45
early warning and repaid response networks consist with different communication
networks such as drone based, social, GIS/GSM and underwater networks. The
CDMDC is another component of IRA which contain various information data for
instance, geographical data, registered cell phone information as well as ICT
networks. Furthermore, the architecture has QDMRC component which is
responsible to share the disaster information with NDMA office.
Quick Disaster Management Response Center
Early Warning System
Central Disaster Database Management cell
Rapid Response Networks
Private Organizations/
NGO S
National Organizations
International Organizations
Geographic Data
Registered Cell Phones
ICT Networks
Sensor Networks
GIS/GSMSocial
networksDrones
Networks
National Disaster Management Authority
Under water
Networks
Figure 4-1: Resilient Interaction Retrieval Architecture (IRA) [6].
4.2 COMPONENTS OF RESILIENT IRA
The proposed architecture has four components which are being used to retrieve
the information of live survivals, data about survivals and transmit that collected
within disaster zone to base-station. These four components of prototype are
discussed in the following section.
4.3 EARLY WARNING SYSTEM NETWORKS (EWSN)
The EWSN is the important component of the IRA which is used to generate the
early warnings alerts and communicate them quickly with the disaster management
response centre as illustrated in fig 4.2.and has following features:
• Consist of multiple resilient ICT networks to transmit the early warning alerts.
46
• EWSN component has network redundancy in case of failure of GSM network it
will sends the information via another available network.
EWSN
GSM
Drones
Social
SensorGIS
Disasters
Earthquakes Floods Tsunami
TV/Radio
Figure 4-2: Early Warning System Networks (EWSN) [6]
4.4 RAPID RESPONSE NETWORKS (RRN)
The rapid response component is used to detect the survival from the earthquake
disaster zones. The RRN has various kinds of communication networks to detect
the survivals and communicate that information about the survivals to the base-
station component of IRA. The figure 4.3 depicted rapid response networks
component. It has following features:
• The RRN is the core component of the prototype system effectively work
during the occurrences of any natural disasters especially earthquakes.
• Perform quick and speedy response to collect survival detection
information
• Establish communication between all components of the IRA prototype
system.
Rapid Response Networks
Drones Networks Sensor NetworksGSM / GIS Under water
Networks
Figure 4-3: Rapid Response Networks (RRN) [6]
47
4.5 CENTRAL DISASTER MANAGEMENT DATABASE CELL (CDMDC)
The central disaster management database contains different data cells such as
geographical data, registered mobile phone information and ICT networks cells.
The geographical data cell contains the geographical information of various
disaster zones and the registered cell phone maintains the occupant cell phone
information living in disaster affected areas. In the same line the ICT networks
cell contain the information of available resilient ICT networks mainly working in
disaster areas. The figure 4.4 shows the various cells of CDMDC. It has following
features:
• Maintain the entire record of the design system network and other
important information necessary for the rescue operations.
• Population records has been maintaining by this component.
• Continuously update the information about registered cell phones,
disaster zones and available networks.
Central Disaster Database Management cell
Geographic Data
Registered Cell Phones
ICT Networks
Figure 4-4: Central disaster Management Database Cell [6].
4.6 QUICK DISASTER MANAGEMENT RESPONSE CENTRE (QDMRC)
The quick disaster management cell is responsible to developed coordination
among the national disaster management authorities, national, international and
private non-profit (NGO) organisation to perfume the rescues operation timely.
Figure 4.5 illustrate the QDMRC relationship among the components. It has
following features:
• Create communication links among related organisations which offers
emergency rescue services just after disaster
48
• Broadcast real time information about of the occurrence of earthquake
among disaster management authorities
• Provides quick assistance in emergency situation while activating the RRN
in effected zone.
Quick Disaster Management Response Center
Private Organizations/NGO SNational Organizations International Organizations
National Disaster Management Authority
Figure 4-5: Disaster Management Response Centre [6]
4.7 PROTEUS SIMULATION OF PROPOSED SYSTEM
Before designing the hardware prototype system, the proposed system has been
simulated in proteus environment. The proteus simulation environment offers various
features to design the layouts of different electrical, electronic and electromechanical
architectures. Moreover, the through the proteus simulation, the hardware components
have been identified for prototype system designing. The figure 4.6 illustrate the
simulation diagram of IRA.
49
Display Aliveness Indicators
GSM Module Level Shifter5DCV
Storage Modules
Arduino Mega 2560 MC Board Aliveness Detection Module
Figure 4-6: Proteus Simulation of resilient ICT Networks based IRA
4.8 PROTOTYPE SYSTEM AND ITS COMPONENTS
The prototype system is combination of various hardware components such as
display, aliveness indicators, voltage level shifter, Arduino mega 2560
microcontroller, external storage module, GSM communication module and
aliveness detection sensing module. The figure 4.7 shows the complete hardware
prototype module.
50
(a) (b)
Figure 4-7: (a) Prototype Hardware Module Operational & Base station Components
(b) Responders cell phone component
4.8.1 ARDUINO 2560 MICROCONTROLLER
Arduino microcontroller is the main component of system which provides several
interfaces through which all other components of hardware module are connected.
Moreover, Arduino microcontroller transmits sensor data via different inputs and
outputs embedded ports.
4.8.2 DISPLAY
The system uses LCD to show the output of the respiration module data. It is consisting
light emitting diode and gas plasma technologies to display the incoming results
4.8.3 EXTERNAL STORAGE MODULE
External storage module is a backup memory for a system. It is installed inside the
circuit and used to store information. When GSM communication link is down, the
storage module stores the respiration sensor reading information and later transmits that
information to software module at once after the GSM link is up.
4.8.4 LEVEL SHIFTER 5DCV
The level shifter 5DCV is used to configure it to the requirement of the Respiration
module which works on 3.3v.
51
4.8.5 ALIVENESS SIGNAL INDICATORS
The Green, red or/ yellow LEDs are used to detect the aliveness of different survivals
in various scenario. When single survival aliveness is detected, any one LED is
activated, and maximum survival aliveness detection is three and to represent there
aliveness three LEDs will be active otherwise they will remain deactivate.
4.8.6 GSM MODULE
GSM SIM 900 communication module is being used to develop wireless
communication links among the operational components, base station and operator cell
phones.
4.8.7 ALIVENESS DETECTION SENSING RESPIRATION MODULE
The respiration module is a non-contact sleep and respiration monitoring module built
on a single sensor. It is the product of Novelda’s proprietary, and its composition is
based on highly integrated X2 system-on-chip (SoC). It is the sensor, capable to provide
the exact dimension of a person that is the respiration pattern, with the in the distance
range of the sensor, person movement and the signal quality data respectively as shown
by figure 4.8.
Figure 4-8: Aliveness detection module
4.8.8 RESPIRATION DETECTION MODULE
The respiration module sensor detects the presence of a person within detection zone
by detecting the different states of survivals like movement, breathing pattern and then
52
it starts processing the data. When the module senses the movement, it will try to detect
a breathing pattern or movement tracking.
The respiration profile has the following six states shown in figure 4.9:
1. No Movement: It mean there that No presence of survivals is detected.
2. Movement: This shows that there the presence of survivals but breathing
movement is not distinguishable.
3. Movement Tracking: This shows the presence of survivals and possible
breathing movement is detected.
4. Breathing: This state is showing the valid breathing movement detection of
survivals.
5. Initializing: The sensor initializes after the Respiration Profile is chosen
6. Unknown: This is the unknown state, and the sensors have to set the profile.
Figure 4-9: Operational flow of Aliveness detection module
4.9 THE INFORMATION FLOW RESPIRATION MODULE
The figure 4.10 illustrates that the information of different sources is taken as an
input that is processed by the sensor module. The input is stored in frame storage
buffer before any further process. Respiration module processing is known as 2d
processing, that indicates the movement detection process and respiration
OUTPUT
State
Combiner
(High, Low)
Movement
Detector
Respiration
Detector
Breathing
Pattern
Estimator
Frame
Storage
Buffer
2-D
Processing Input
Breathing
pattern
Distance,
RPM
53
detection process. This process first, it detects the movement of the object. Its take
its impulse from the object and it starts processing. Impales received pattern in
which high and low pulse is combined and it processes in the state’s combiner.
The sensor in the respiration detector detects the respiration of the objects and it
also detects the distances and the different RPM of the objects. Breathing Pattern
Estimator is responsible for detecting various breathing patterns of the objects and
processes them and further transmitted to the next step. The last step of the
processing is the output which is in the form of movement, movement tracking,
breathing detection, and different breathing Patterns (RPM).
4.10 PROTOTYPE SYSTEM INFORMATION FLOW MECHANISM
The prototype decisions are based on the information flow mechanism of resilient
based ICT networks interaction retrieval architecture where different resilient
networks send the information from the disaster zones. Figure 4.10 shows the
information flow mechanism of IRA prototype system from disaster zone to base-
station.
Figure 4-10: Information flow Mechanism between Disaster zone to Remote
zone
The system will first initialize. Next it will search for the networks. In third step
all the available networks will be available and searched by the system. As the
system is GSM based it will connect to it. Once the system is connected to the
required network the decision is made for the flow of information to the concern
parts, the real time information is sent to cell phone, base stations and quick
54
disaster management response centers. If the required network is not available then
the back-up networks will be used to flow the information to the connected centers.
4.11 WORKING OF THE PROPOSED SYSTEM
When the earthquake occurs, the system will be placed in earthquake zone and the
system will start its working. Whenever the system detects the survivals
movement, breathing or RPM then the system will transmit the information in the
form of GSM alerts to the respondent’s cell phone, base station unit and also to
the Quick disaster management response center. The working of the proposed
model is shown the figure 4.11.
Figure 4-11: working of the proposed system
4.12 POST-EARTHQUAKE INFORMATION FLOW OF IRA
The figure 4.12 depicts the post information flow relationship diagram of IRA.
When the natural or human-made disaster is occurred, then the survivals
information is float from base-station to central network station, provincial as well
to the district level network stations. Furthermore, the disaster information is
shared quickly with the disaster management response center for speedy
assistance. The quick disaster response management center activates available
55
repaid response networks on disaster affected zone to collect the information about
survivals, damages and populations.
Base-Station
District Network
Station
Provincial Network
Station
Central Network
Station
• Activation of Rapid Response Networks
• Different International and National organization
to involve in Disaster Management services
Quick Disaster
Management
Response Center
Decision
Red Zone Red Zone Red Zone
Figure 4-12: Post-Earthquake Information Flow of IRA
4.13 SUMMARY OF THE CHAPTER
This chapter comprises the logical architecture, information flow mechanism and
simulation and hardware prototype results of designed system. Moreover, the
simulation results show the single heartbeat detection and multiple heartbeats detection
of undersurface earthquake disaster survivals while the hardware prototype system
detect the movement, breathing, location and respiration per minutes and tracking.
56
Furthermore, the system has two hardware components such as operational component
and base-station components. The operational components is used to detect earthquake
survivals from the disaster, collect their aliveness information and send to the base-
station, mobile phone through aliveness detection sensing technique and GSM
communication links respectively on real time biases. On the other hand, the base-
station hardware component receives the relevant information and disseminating that
information to relevant office of IRA components for rapid and necessarily rescues
operations.
57
CHAPTER 5
TESTING OF PROTOTYPE HARDWARE
SYSTEM
We have tested the prototype system through simulated scenarios and real environment
under various building structures. The simulated scenarios are as follows: multi-level
building, single and double stories, and mega market buildings. The figure 5.1
shows simulation environments for different scenarios to detect the survivals
under-surface of disaster zones. The survivals may be a child, male and female.
The system has predetermined parameters to locate the survivals such as when the
system detects detect the 30-44, 45-60, 61-75 heartbeats of survivals. The system
indicates aliveness of survivals as by the aliveness indicators respectively.
Figure 5-1: Simulated prototype hardware system for testing
5.1 MULTI-LEVEL BUILDING SCENARIO
The damage cause in a multiple level building scenario is illustrated in the figure 5.2.
just after earthquake happens. When any natural disaster is occurred, the different
organization used various assistance techniques to rescue the survivals from the upper
surface of disaster. However, the existing system do not propose any mechanism to
detect the survivals from under-surface of disaster area. Hence, our design system has
58
capabilities to detect the survivals in both disaster scenarios such as Upper-Surface and
Under-Surface.
Figure 5-2: Multilevel Building Disaster
5.2 SINGLE AND DOUBLE STORY HOUSES SCENARIO
The figure 5.3 shows the damages of single and double stories buildings just after
occurrence of natural or human made disaster. The disaster environment is simulated
in proteus environment to detect the heartbeats of survivals. The different circle shows
the presences of different survivals in earthquake zones. The system has multiple
attempts to detect the survivals.
Figure 5-3: Disaster in Single and Double Stories Building
Survivals
Survivals
59
5.3 MEGA MARKET SCENARIO
The another system testing scenarios was maga market disaster zones as shown in
figure 5.4. In mega market disaster zone , the design system has more then 9 attempt to
discover the aliveness of surivals from disaster zones.
Figure 5-4: Earthquake Disaster in Mega Market
5.4 PROTOTYPE HARDWARE TESTING IN CONTROLLED
ENVIRONMENT
After simualtion of IRA system. the system has been tested in controlled environemnts
such as system has been installed in vrious places and vaildate the aliveness sensing
approch of design system. Moreover, the IRA system has three main components
(operational, cell phones and base-station) to detect the survivals from the disaster
zones, collect the information from the affcted aera and send the informtion to opertors
mobile as well base-station. The figure shows 5.5 the main components of hardware
prototype.
60
(a) Operational unit (b) Responder cell phone
( c ) Base station unit
Figure 5-5: (a) Operational unit (b) Responder cell phone and (c) Base station unit
Hardware prototype and its components
5.5 OPERATIONAL COMPONENT OF PROTOTYPE SYSTEM
The figure 5.6 shows the operational component of the desgin system. It is the main
components which is used to detect the survivals from the earthquake afftected areas.
The operational components has aliveness sensing module which is used to detect the
movement, breathing and RPM of survivals and store that information on external
storage module. Moreover, when the components collect the information from the
disaster zone is simultaneously transfering that information on operator mobile phone
as well as base-station components through GSM communication SIM 900 protocol.
61
Aliveness Detection module
GSM Module
Display
Figure 5-6: Operational unit of prototype which will be located in earthquake disaster
zone
5.6 DISASTER INFORMATON RESPONDANTS CELL PHONE
This is the remote component of system where the operational components transfer the
disaster information for qucik rescue operations. The mobile phone component of the
system mainly hold by the field operators as well as centeral response management cell
persunnels. Figure 5.7 depicts the operator mobile phone component of the system.
Movement tracking
Breathing tracking
Movement
Figure 5-7: Cell phone with respondents
62
5.7 BASE-STATION COMPONENTS OF THE SYSTEM
The third component of prototype system is called as base-station component. The base-
station components receive the information from the operational components and
commuincate that information to the field operators to lunch speedy rescue activities in
disaster affetecd zones. Moreover, the base-station also has information of available
repaid response netwroks for quick activiation. The figure 5.8 shows the base-station
component of the IRA.
base station unit
GSM Module
Figure 5-8: Remote unit which will be located at Base-Station to receive information
about aliveness of survivals and share with the related
5.8 SURVIVALS ALIVENESS DETECTION UNDER BUILDING
STRUCTURED MATERIALS
The section explain and shows various practical scenarios of the hardware prototype
system. the system has been installed on different material and checked the signal
penitration abilities of system. The tested sceanrios are following :
5.8.1 CONCRETE STRUCTURE
The system was install on concrete material and tested the signal penitarion rate as well
detection rate . Figure 5.9 shows the concrete material with prototype system. the
system results has been discuss in chapter 6.
63
Figure 5-9: Aliveness detection through Concrete structured
5.8.2 STONE STRUCTURE
The design system has been install behind the stone walls and check the detection
ability of system as shown by figure 5.10. the detection result table has been discuss in
chpater 6.
Figure 5-10: Aliveness detection through Stone structure
5.8.3 BRICKS STRUCTURE
Another practical sceanrios of the system was the bricks material as shown in figure
5.11. The system succeccfully detect the survival movement, breathing and RPM
under-surface of bricks material. The results will be discused in chapter 6.
64
Figure 5-11: Aliveness detection through Brick structure
5.8.4 BLOCKS STRUCTURE
The blocks wall testing is the another testing scenario of design system.where the
hardware system was placed behind the blocks wall and checked the detection ability
of system. The acquire results vaildated the system detection results. Figure 5.12 depicts
the blocks sceanrio.
Figure 5-12: Block structure Material System Testing
65
5.8.5 WOODEN STRUCTURE
The system detection abilities has been tested throgh wood materials against the
movement tracking , RPM and breathing detection. Figure 5.13 shows system testing
scenario on wood door material.
Figure 5-13: Wooden structured Material Aliveness detection
5.8.6 PLYWOOD STRUCTURE
Plywood door material testing is the another practical experiment of design system to
vaildate the system performances. Figure 5.14 shows testing plywood testing sceanrio.
Figure 5-14: Aliveness detection by the System through Plywood structure
66
5.8.7 GLASS STRUCTURE
Glass material testing was another scenario for hardware prototype system. The system
successfully detects the movement, breathing and RPM of survival undersurface of
glass material. Figur 5.15 refer the testing scenario of glass material.
Figure 5-15: Aliveness detection behind glass structure
5.8.8 PAPER BUNDELS
Paper bundles testing sceanrio was carried out as shown by figure 5.16. The system is
able to detect the survivals behind the paper materials. The results will be discused in
next chapter 6.
Figure 5-16: Aliveness detection under paper bundle
67
5.9 SUMMARY OF THE CHAPTER
This chapter includes the proteus simulation and prototype hardware-based scenarios.
The simulation scenarios results are based on predetermined values of heartbeats
detection of the earthquake survivals while the hardware prototype system results are
based on practical experiments of the design system. Furthermore, system has been
tested and evaluated through system installation on different building structured
materials such as concrete, stone, bricks, blocks, ply wood door, glass material, wood
door and paper rims. The acquire results has been validated the system performance by
its sensing abilities.
68
CHAPTER 6
RESULTS AND DISCUSSSION
This chapter presents the results of proteus simulation and prototype hardware module
based on different scenarios as discussed in Chapter Six. The simulation results of
system are based on single heartbeat and multiple heartbeats detection in multilevel,
single and double stories and mega market buildings disaster scenarios. In addition, the
prototype system has been placed in various building structured material to detect the
location, movement, breathing and respiration patterns of survivals. Aliveness detection
process is shown in the figure 6.1.
Aliveness detection
Prototype system
Proteus simulation scenarios
Structured materials
Multilevel
Single & double story
building
Mega market
Base station
Cell phones
Concrete structure
Stone structures
Bricks structures
Blocks structures
Wooden structures
Plywood structures
Glass structures
Paper bundle
Figure 6-1: Aliveness detection process in proposed IRA
69
6.1 TESTING OF HARDWARE PROTOTYPE THROUGH PROTEUS
SIMULATION
Before designing the actual hardware module of the system, we simulated the system
by using proteus simulation environment and evaluated system capabilities through
survivals movements, breathing and RPM. Moreover, the design system successfully
penetrates the different building materials and detect the survivals accordingly. The
table 6.1 depicts results of different survivals with different heartbeats and RPMS
detected by prototype system.
(https://www.rch.org.au/clinicalguide/guideline_index/Normal_Ranges_for_Physiolo
gical_Variables).
Table 6-1: Standard age wise heart beats and respiration rates
Age
(Months)
Heartbeat
(Per minute)
Respiratory Rate
(Respiration per minute)
Premature 110-170 40-70
0-3 110-160 35-55
3-6 110-160 30-45
6-12 90-160 22-38
12-36 80-150 22-30
36-72 70-120 20-24
72-144 60-110 16-22
>144 60-100 12-20
6.2 SCENARIO 1: SIMULATION RESULTS OF MULTI-LEVEL BUILDING
The system has been simulated through different scenarios such as multi -level
single, double stories, and mega market buildings. The system performed various
attempts to detect the heartbeats of survival in different scenarios as multilevel
building destruction situations, single and double stories building damages and
mega markets disaster debris. The figure 6.2 shows heartbeats detection of more
than one survival in single attempts. The heartbeats are represented as hbt1, hbt2
and hbt3. Three aliveness indicators (Red, Green and Yellow) indicate the
70
heartbeat detection of survivals. Whenever the heartbeats are detected by system,
the aliveness indicators being active otherwise indicators remain deactivated. In
figure 6.2, system detects three different heartbeats in single attempt such as 30,
55,70 hbts respectively.
Figure 6-2: Heartbeat Detection in Multi-level buildings
The below Table 6.2 shows simulation results of system where the system performed
multiple attempts to detect the heartbeats. The table comprises the number of attempts
of system, detected survivals numbers and multiple heartbeats detection. In the first
attempt the system detected three survivals with different heartbeats such as 30, 55 and
70 hbts respectively. In the second attempt, it has detected two survivals with different
heartbeats 30 and 70 hbts simultaneously. While in third attempt, again three survivals
have been detected with different heartbeat rates. Similarly, the system performed five
attempts and detected thirteen survivals with different heartbeat rates as shown in table
6.2.
Table 6-2: Multilevel building
No. of detection
attempts
No of survivals
detected
Detected Heartbeats rates
hb1 hb2 hb3
1 3 30 55 70
2 2 0 30 70
3 3 50 60 45
4 2 60 00 30
5 3 43 68 57
71
6.2.1 GRAPHICAL REPRESENTATION OF HEARTBEATS IN MULTI-LEVEL
BUILDING SCENARIO
Figure 6.3 and figure 6.4 represents the no of the survivals with different
heartbeats in five different attempts of the system.
Figure 6-3: No of survivals rescued in different attempts
Figure 6-4: Different heartbeats of survivals in Multi-level building scenario
3
2
3
2
3
1 2 3 4 5
No
of
surv
ival
s d
ete
cte
d
No of detection attempts
30
0
50
60
43
55
30
60
0
6870 70
45
30
57
No
of
he
art
be
ats
rate
s
No of Survivals detected
72
6.2.2 PROCESS OF INFORMATION FLOW FOR ALIVENESS DETECTION
TECHNIQUE (MOVEMENT, BREATHING AND RPM) OF DESIGNED
HARDWARE SYSTEM.
The process of aliveness detection technique is illustrated in the following figure
6.5. The designed system will initialize first and then starts searching different
aliveness detection techniques (movement, breathing and respiration per minutes
(RPM)).
Single detection technique is used at one time. The system will detect any of the
above-mentioned techniques continuously. Whatever is happening it will display
that technique on the designed component display screen. The system will
constantly be working and searching for the detection of the survivals location,
moment, breathing and RPM, respectively.
Initializing
Aliveness teachnique
Movement Breathing RPM
Display movement detection
Display Breathing detection
Display RPM detection
Yes Yes Yes
NO NO NO
Figure 6-5: Aliveness mechanism flow
73
(a) (b)
(c) (d)
Figure 6-6: Aliveness detection techniques (a) Movement (b) Movement tracking (c)
Breathing (d) (RPM) used by Operational unit
In the Table 6.3 shows the prototype system started to detect the movement at 12:37:37
pm at 12:38:15 pm it starts movement tracking. At 12:38:28 pm the system detects the
Breathing and at 12:38:41 pm the system manages to detect its 1st respiration per minute
74
RPM that was 12.34 as shown in the figure 5.10 chapter 5. The way system processing
and again at 12:38:54 the movement was detected by the system at 12:39:6 pm. The 2nd
RPM 26.15 was detected at 12:39:19 pm. Then the system again at 12:39:32 pm start
detecting the movement tracking of the person. The breathing was detected at 12:39:45
pm. The 3rd RPM 17.35 was detected by the system at 12:39:58. The system again starts
movement tracking at 12:40:10 pm. At 12:41:32 pm the breathing was detected and at
12:41:45 pm 4th RPM 21.5 was detected by the system respectively.
Table 6-3: Aliveness detection by Prototype system
Time Aliveness feature Detection
12:37:37 Movement
12:37:50 Movement tracking
12:38:02 Movement
12:38:15 Movement tracking
12:38:28 Breathing
12:38:41 12.34 RPM
12:38:54 Movement
12:39:06 Breathing tracking
12:39:19 26.15 RPM
12:39:32 Movement tracking
12:39:45 Breathing
12:39:58 17.35 RPM
12:40:10 Movement tracking
12:41:32 Breathing detected
12:41:45 21.5 RPM
6.2.3 CONCRETE STRUCTURE
In the table 6.4 shows that concrete structure was used for hardware result as discussed
in Chapter five figure 5.9, that the breathing was detected at 13:2:44 pm, 13:2:45 pm,
and 13:2:45 pm. The first RMP was detected at 13:2:46 pm which was 14.7 RPM. Then
the system starts movement detecting at 13:3:1 pm, breathing detection at 13:3:7 pm,
movement at 13:3:1 pm, breathing detection at 13:3:20 pm and breathing detection at
13:3:27 pm respectively. 2nd RPM 10.25 was detected at 13:3:27 pm. The system again
starts breathing detection at 13:3:28 pm, and movement detection at 13:3:29 pm.
Breathing detections at 13:3:38 pm, 13:3:44 pm and 13:3:45 pm.
75
Table 6-4: Aliveness detection through Concrete structure
Time Aliveness feature Detection
13:02:44 Breathing
13:02:45 Breathing
13:02:45 Breathing
13:02:46 14.7 RPM
13:03:01 Movement tracking
13:03:07 Breathing
13:03:14 Movement
13:03:20 Breathing
13:03:27 Breathing
13:03:27 10.25 RPM
13:03:28 Breathing
13:03:28 Breathing
13:03:29 Movement
13:03:38 Breathing
13:03:44 Breathing
6.2.4 WOODEN STRUCTURE
Wooden Structure as discussed in Chapter 5 figure 5.13 used for the Table 6.5. The
table shows result of the movement was detected at 13:26:39 pm, breathing detection
at 13:26:40 pm, and the first rpm was detected at 13:26:41 pm which was 12.8 RPM.
Then the system starts movement tracking at 13:26:50 pm, breathing detection at
13:26:57 pm, movement tracking at 13:27:3 pm, movement at 13:27:12 breathing
detection at 13:27:31, movement at 13:27:50 pm and breathing detection at 13:27:57
pm respectively. The second 12.51 RPM was detected at 13:28:1 pm. Then the system
again starts breathing detection at 13:28:3 pm, and at 13:28:4 pm.
76
Table 6-5: Aliveness detection through Wooden Structure
Time Aliveness feature Detection
13:26:39 Movement
13:26:40 Breathing detected
13:26:41 12.8 RPM
13:26:50 Movement tracking
13:26:57 Breathing detected
13:27:03 Movement tracking
13:27:12 Movement
13:27:24 Movement tracking
13:27:31 Breathing detected
13:27:37 Movement tracking
13:27:44 Breathing detected
13:27:50 Movement
13:27:57 Breathing detected
13:28:01 21.51 RPM
13:28:03 Breathing detected
13:28:04 Breathing detected
6.2.5 RESPONDERS CELL PHONE WORKING MECHANISM
The responders cell phone gets the information of the aliveness of the survivals by
different aliveness detection techniques send by the operational unit by SMS and
ring call services. The aliveness detection techniques are shown in the figure 6.7.
Cell Phone
SMS services Ring call services
Movement BreathingRespiration per
minute
Flow of information in Respondent Cell phones
Figure 6-7: Information flow of the responder’s cell phone
77
6.2.6 RESULTS OF RESPONDERS CELL PHONE
The prototype system sends the real time results to the remote mobile cell phones which
were located at different places after detection of movement. The breathing detection
are shown in figure 6.8. The system detects the movement at 19:11:54 pm and then
Breathing detection at 19:13:6 pm.
Figure 6-8: Responders Cell Phone Messaging services
6.3 SCENARIO 2: SINGLE AND DOUBLE STORY BUILDING
In this single and double stories scenario, the system was used in Proteus
environment to detect the survivals heartbeat in multiple attempts. In this scenario
in Table 6.6 the system has made five maximum attempts and different survivals
were detected with different heartbeat rates. These results have been taken from
figure 6.9. Three different fields that is no of detection attempts, no of survivals
detected and detected heartbeats rates were used in Table 6.4.
78
Figure 6-9: Single and double stories buildings
The Table 6.6 indicates that in first detection attempt three survivals were found with
the hbt1 56, hbt2 61 and hbt3 42 in the figure 6.11. In the 2nd detection attempt, the 3
survivals with the heartbeats hbt1 60, hbt2 59 and hbt3 35 were detected respectively.
The system performed total five attempts and detect eleven number of survivals
illustrates by Table 6.6.
Table 6-6: Single and double stories Scenario
No. of detection
attempts
No of survivals
detected
Detected Heartbeats rates
hb1 hb2 hb3
1 3 56 61 42
2 3 60 59 35
3 2 65 00 46
4 1 70 00 00
5 2 67 35 00
6.3.1 GRAPHICAL REPRESENTATION HEARTBEATS IN SINGLE AND DOUBLE
STORIES BUILDINGS SCENARIO
Figure 6.10 and Figure 6.11 is the graphical representation of different hearts beats
that were detected by the system and for that purpose the system makes multiple
attempts to detect the heartbeats of the survivals.
79
Figure 6-10: No of survivals in various attempts
Figure 6-11: No of heartbeats of survivals Single and double stories buildings scenario
6.3.2 STONE STRUCTURE
By using Stone, wall as discussed in the chapter 5 figure 5.10, various results are
collected in Table 6.7. The Hardware Result shows that the breathing was detected at
13:10:50 pm, 13:10:51 pm, and 13:10:52 pm. The first rpm was detected at 13:10:53
pm which was 11.6 rpm. Then the system starts movement detecting at 13:11:2 pm,
breathing detection at 13:11:8 pm, and at 13:11:15 pm. 2nd rpm 21.5 was detected at
13:11:16 pm. Then the system again starts movement detection at 13:11:17 pm, and
movement tracking at 13:11:26 pm. Breathing detections at 13:11:34 pm, and 13:11:41
pm.
3 3
2
1
2
1 2 3 4 5
No
of
surv
ival
s
No of detection attempts
5660
6570
67
61 59
0 0
35
42
35
46
0 0
No
of
he
artb
eat
rat
es
No of survivals detected
80
Table 6-7: Aliveness detection through Stone Material
Time Aliveness feature Detection
13:10:50 Breathing
13:10:50 Breathing
13:10:51 Breathing
13:10:52 Breathing
13:10:53 11.6 RPM
13:11:02 Movement
13:11:08 Breathing
13:11:15 Breathing
13:11:16 21.5 RPM
13:11:17 Movement
13:11:26 Movement tracking
13:11:34 Breathing
13:11:41 Breathing
6.3.3 BRICK STRUCTURE
Table 6.8 by using brick wall shown in the chapter 5 figure 5.11. The breathing was
detected at 13:7:55 pm, 13:7:56 pm, and 13:7:57 pm. The first rpm was detected at
13:7:57 pm which was 11.8 rpm. Then the system starts movement detecting at 13:8:7
pm and breathing detection at 13:8:13 pm, movement at 13:3:1 pm, at 13:3:20 pm,
movement tracking detection at 13:3:28 and breathing detection at 13:8:34 pm
respectively. Then the system once again starts movement at 13:8:40 pm and breathing
detection at 13:8:48 pm. The second rpm 12.37 at 13:8:50 pm.
Table 6-8: Aliveness detection through Brick structure
Time Aliveness feature Detection
13:07:55 Breathing
13:07:56 Breathing
13:07:56 Breathing
13:07:57 11.8 RPM
13:08:07 Movement
13:08:13 Breathing
13:08:20 Movement
13:08:27 Movement
13:08:28 Movement tracking
13:08:34 Breathing
13:08:40 Movement
13:08:48 Breathing
13:08:50 12.37 RPM
81
6.3.4 PLYWOOD STRUCTURE
Table 6.9 Hardware Result is taken from the Plywood material as shown in chapter no
5 figure 5.14 that the movement was detected at 13:30:8 pm, and breathing at 13:30:9
pm. The first RPM was detected at 13:30:12 pm which was 12.5 RPM. Then the system
starts breathing detections at 13:30:15, 13:30:17 pm, 13:30:20 pm, 13:30:23 pm,
13:30:25pm, 13:30:26 pm, and at 13:30:29 pm respectively. Second RPM 11.6 was
detected at 13:30:32 pm. Then the system again starts movement tracking detection at
13:30:34 pm, and movement detection at 13:30:40 pm, 13:30:53 and at 13:31:6 pm
separately and Breathing detections at 13:31:19 pm.
Table 6-9: Aliveness detection through Plywood Material
Time Aliveness feature Detection
13:30:08 Movement detected
13:30:09 Breathing detected
13:30:12 12.5 RPM
13:30:15 Breathing detected
13:30:17 Breathing detected
13:30:20 Breathing detected
13:30:23 Breathing detected
13:30:25 Breathing detected
13:30:26 Breathing detected
13:30:29 Breathing detected
13:30:32 11.6 RPM
13:30:34 Movement tracking
13:30:40 Movement
13:30:53 Movement
13:31:06 Movement
13:31:19 Breathing detected
82
6.3.5 RESULTS OF ALIVENESS DETECTION
Figure 6-12: Prototype System Hardware Result
In the Table 6.10, the system started to detect the movement at 13:30:7 pm at 13:30:8
pm it starts movement tracking. At 13:30:16 pm the system detects the breathing and
at 13:30:18 pm the system manages to detect its 1st respiration per minute (RPM) that
was 16.79 as shown in the figure 6.12. Then again, the system process and at 13:30:19
the movement was detected. The breathing was detected by the system at 13:30:20 pm.
The 2nd RPM 11.6 was detected at 13:30:22 pm. Then the system again at 13:30:32 pm
start detecting the movement tracking of the person.
Table 6-10: Prototype System Hardware Result
Time Aliveness feature Detection
13:30:07 Movement
13:30:07 Movement
13:30:08 Movement tracking
13:30:16 Breathing detected
13:30:18 16.79 RPM
13:30:19 Breathing detected
13:30:19 Breathing detected
13:30:20 Breathing detected
13:30:20 Movement
13:30:20 Movement
13:30:21 Movement tracking
13:30:21 Breathing detected
13:30:22 11.6 RPM
13:30:32 Movement tracking
83
6.3.6 RESULTS OF RESPONDERS CELL PHONE
The operational component system again sends the information to the remote cells as
shown in figure 6.13. The movement tracking was at 17:16:41pm, breathing detection
was at 17:17:11 pm and the respiration was detected at 17:19:18 pm.
Figure 6-13: Remote Cell Phone Messaging results
6.4 SCENARIO 3: MEGA MARKET
In the Mega Market Scenario was used in proteus environment to detect the
survivals heartbeats in multiple attempts. In Mega Market scenario, five numbers
of attempts were made, and different heartbeats were detected as indicated in
Figure 6.14.
84
Figure 6-14: Mega Market result
The first detection attempts in Table 6.11, 2 number of survivals were found as shown
in Figure 6.14 with hbt1 68 and hbt2 53. In second detection attempt, 3 numbers of
survivals with the heartbeats hbt1 52, hbt2 43 and hbt3 61 were detected respectively.
The system performed five attempts and detected ten survivals with different heartbeats
rates.
Table 6-11: Mega Market
No of detection
attempts
No of survivals
detected
Detected Heartbeats rates
hb1 hb2 hb3
1 2 68 53 00
2 3 52 43 61
3 1 33 00 00
4 3 71 51 48
5 1 36 00 00
6.4.1 GRAPHICAL REPRESENTATION OF HEARTBEATS IN MEGA MARKET
SCENARIO
Figure 6.15 and figure 6.16 is the graphical representation of different heartbeats with
respect to number of attempts as shown in the Table 6.11.
85
Figure 6-15: No of survivals saved in different attempts
Figure 6-16: No of heartbeat of the survivals in Mega Market Scenario
6.4.2 BLOCK STRUCTURE
The block wall used to combine results in Table 6.12. Hardware Result shown Chapter
Five in the figure 5.12, that the breathing was detected at 13:5:25 pm, 13:5:26 pm, and
13:2:45 pm. The first RMP was detected at 13:5:26 pm which was 15.1 rpm. Then the
system starts breathing detecting at 13:5:37 pm, at 13:5:36 pm, and at 13:5:39 pm
respectively. 2nd rpm 15.7 was detected at 13:3:39 pm. Then the system again starts
2
3
1
3
1
1 2 3 4 5
No
of
the
su
rviv
als
save
d
No of detection attemts
68
52
33
71
36
53
43
0
51
00
61
0
48
0
No
of
he
artb
eat
rat
es
No of Survivals detected
86
movement detection at 13:6:57 pm and breathing detection at 13:7:4 pm. The last
movement was detected at 13:7:10 pm by the system.
Table 6-12: Block Material
Time Aliveness feature Detection
13:05:25 Breathing
13:05:26 Breathing
13:05:26 Breathing
13:05:26 RPM 15.1
13:05:37 Breathing
13:05:37 Breathing
13:05:38 Breathing
13:05:38 Breathing
13:05:39 Breathing
13:05:39 RPM 15.7
13:06:57 Movement
13:07:04 Breathing
13:07:10 Movement
6.4.3 GLASS STRUCTURE
In the Table 6.13 result is taken from glass material, shown in the Chapter Five, figure
5.15 that the breathing was detected at 15:35:0 pm and 15:35:5 pm. The first rpm was
detected at 15:2:46 pm which was 8.8 rpm. Then the system starts breathing detection
at 15:35:11 pm, movement detection at 15:35:12 pm, and breathing detection at
15:35:19 pm respectively. The 2nd rpm 28.0 was detected at 13:3:27 pm. Then the
system again starts movement detection at 15:35:25 pm, and breathing detections at
15:35:26 pm, 15:35:27 pm and 15:35:28 pm respectively. The 3rd rpm 11.58 was
detected at 15:35:29 pm. Then the system again processes and Breathing tracking
detections at 15:35:30 pm, 15:35:31 pm and 15:35:32 pm were noted.
87
Table 6-13: Glass Material
6.4.4 PAPER BUNDLES BOX
The Paper bundle box as shown in the Chapter Five displayed in figure 5.16 were used
to extract results in the Table 6.14. Hardware Result shows that the breathing was
detected at 19:4:54 pm and the first rpm was detected at 19:4:57 pm which was 9.3
RPM. Then the system starts breathing detection at 19:5:3 pm, 19:5:4 pm and at 19:5:5
pm respectively. 2nd RPM 13.2 was detected at 19:5:9 pm. The system again starts
breathing detection at 19:5:12 pm, 19:5:16 pm, and at 19:5:17 pm. Then the system
again detects the movement detection at 19:5:18 pm, 19:5:30 pm, 19:5:38 and at
19:5:38 pm. The movement tracking was detected at 19:5:41 pm and the breathing
detections at 19:5:45 pm.
Time Aliveness feature Detection
15:35:00 Breathing
15:35:05 Breathing
15:35:08 RPM 8.8
15:35:11 Breathing
15:35:12 Movement
15:35:19 Breathing
15:35:23 RPM 28.0
15:35:25 Movement
15:35:26 Breathing
15:35:27 Breathing
15:35:28 Breathing
15:35:29 RPM 11.58
15:35:30 Breathing tracking
15:35:31 Breathing tracking
15:35:32 Breathing tracking
88
Table 6-14: Paper Material
Time Aliveness feature Detection
19:04:54 Breathing detected
19:04:57 RPM 9.3
19:05:03 Breathing detected
19:05:04 Breathing detected
19:05:05 Breathing detected
19:05:06 Breathing detected
19:05:09 RPM 13.2
19:05:12 Breathing detected
19:05:16 Breathing detected
19:05:17 Breathing detected
19:05:18 Movement
19:05:30 Movement
19:05:38 Movement
19:05:39 Movement
19:05:41 Movement tracking
19:05:45 Breathing detected
6.4.5 RESULTS OF ALIVENESS DETECTION BY HARDWARE PROTOTYPE SYSTEM
Figure 6-17: Prototype System Hardware Result
In the Table 6.15 Prototype system shows that the system started to detect the
movement at 19:4:50 pm at 19:4:51 pm. At 19:4:52 pm the system detects the breathing
and at 19:4:52 pm the system manages to detect its 1st respiration per minute RPM that
was 10.2 as shown in the figure 6.17. Then again, the system process and again at
89
19:5:16 the breathing was detected. The breathing was also detected by the system at
19:5:24 pm. The 2nd RPM 15.11 was detected at 19:5:30 pm. Then the system again at
19:5:38 pm start detecting the movement of the person.
Table 6-15: Prototype System Hardware Result
Time Aliveness feature Detection
19:04:50 Breathing
19:04:50 Movement
19:04:51 Movement
19:04:51 Movement
19:04:51 Movement tracking
19:04:52 Breathing
19:04:52 RPM 10.2
19:05:03 Movement
19:05:03 Movement
19:05:03 Movement
19:05:04 Movement tracking
19:05:04 Breathing
19:05:04 Movement
19:05:05 Movement tracking
19:05:05 Breathing
19:05:16 Breathing
6.4.6 VARIOUS RESULTS OF RESPONDERS CELL PHONE
The prototype system sends the remote flow of information to the remotely placed cell
phone as shown in figure 6.18. The system detects the movement at 10:37:46 pm. at
10:38:0 pm. It detected the breathing and the system again detects movement tracking
at 10:40:12 pm
90
Figure 6-18: Remote Cell Phone Messaging results 3:
The proposed system sends some results to the cell phone as shown in figure 6.19. The
movement tracking was started at 16:10:13 pm and breathing was detected at 16:29:3
pm. The remaining results can be seen in the figure mentioned below.
91
Figure 6-19: Remote Cell Phone Messaging results 4
The prototype system sends the real time information to the remote cell phone as shown
in figure 6.20. The system fi detects the of movement at 19:37:11 pm, breathing
detection at 19:37:18 pm, movement tracking detection at 19:37:24 pm, breathing
detection at 19:37:31 pm and movement tracking detection at 19:37:37 pm
simultaneously.
92
Figure 6-20: Remote Cell Phone Messaging results 5
The prototype system has another feature to active the ring calls on the remote cell
phone when the prototype system detects any movement, movement tracking, breathe
detection, breathing tracking. The detection of respiration per minutes’ detection RPM
then the system made different ring calls on registered cell phones at disaster zones
especially and partially in remote places. Different calls have been activated on
different times as shown in the figure 6.21.
93
Figure 6-21: Remote Cell Phone Calling results 6
6.5 COMPARISON BETWEEN PROTOTYPE SYSTEM AND EXISTING ICT
NETWORKS FOR SURVIVAL FINDING
After all results and their analysis, the proposed research, comparison between
existing ICT Networks for Survival Finding and developed System is presented in
the table 6.16. The table illustrates the different features of the proposed IRA such as
integration of multiple technologies, over surface detection, under surface / behind the
wall detection, location tracking of survivals, the respiration detection of survivals,
movement detection of survivals and call and SMS services with other proposed
systems.
94
Table 6-16: Comparison between Existing ICT Networks for Survival Finding
and developed System
Systems Integration
with Multiple
Networks
Over surface
Detection
Under surface
Detection
Location
Tracking of
survivals
Respiration
Detection of
survivals
Under
surface
Movement
Detection
of survivals
Under
surface
GSM
based
Alerts
Proposed
System √ √ √ × √ √ √
GIS √ √ × √ × × ×
WAN √ × × × × × ×
Social
Networks √ × × × × × ×
Multi-WSN √ √ √ √ × √ ×
HAP √ √ × √ × × ×
FANET √ √ × √ × × ×
UAV √ √ × √ × × ×
Drones √ √ × √ × × ×
6.6 CHAPTER SUMMARY
The current chapter contains all of the results of the prototype system. The
prototype system results were divided in to multiple scenarios and each scenario
results were collected in this chapter. Three different scenarios were taken and in
that scenarios some parameter before making the prototype system hardware
components. The results of the simulation are presented in this chapter after that
the hardware results of the system were presented as well. The experiments were
made by using different materials and the detection of the respiration rates were
detected and presented in this chapter.
95
CHAPTER 7
CONCLUSION AND FUTURE DIRECTION
7.1 CONCLUSION
In Pakistan, the National Disaster Management Authority (NDMA) was
established by the government for natural disaster management including
earthquake and its services are linked with the army, which establishes their own
communication services in the disaster zone. However, they lack mechanisms,
such as detection of under-surface and over-surface earthquake survivals and real-
time communication capability to share information of survivals to the concerned
rescue teams / cells. Because of no proper earthquake disaster management
systems in Pakistan, this natural calamity causes a huge number of human
casualties which could otherwise be saved, if there was an adequate earthquake
survival detection system. Our research therefore focuses on detection of under -
surface and over-surface earthquake survivals in the disaster zone and
establishment of real-time communication support for sharing information of
survivals to concerned rescue teams / departments.
As a resulting effort, a prototype interaction retrieval system has been
designed and implemented to detect the disaster survivals in different
circumstances. The prototype system has capability to detect the survivals ’
movement, movement tracking, breath, and identification of the respiration
patterns of survivals, and to send this information to concerned teams through
SMS and call ring alerts. While the proposed prototype system can be used with
various types of networks (such as UAV (Un-armed vehicle), MAV (Move-able
Vehicle), MANET (Mobile ad hoc Networks), FANET (Flying ad hoc Networks)
and HAP (High amplitude Platform), its use with Drone is more befitting since the
Drones can fly above the earthquake-affected zone and also can go close to
survivals’ locations. The prototype system has been tested under various simulated
and real building structures.
96
7.2 SUMMARY OF CONTRIBUTIONS
The outcome of our research is the design and implementation of the system called
Interaction Retrieval Architecture, which supports underground and over ground
detection of earthquake survivals and transmits real-time information of survivals
to concerned cells (e.g. respondent’s cell phones, base station and quick disaster
management response centre). This acts a proof of concept for various features
below supported by the system
1- Under and Upper Surface Survival Detection: The system detects aliveness
of the survival through their movement, movement tracking, breathing and
respiration pattern.
2- Real-time transmission of Aliveness Detection Alerts by SMS and Loop
Based: The system has capability to send aliveness alerts to field responds’ cell
phone, base station placed at near disaster zone and remote quick disaster
management response centre.
7.3 LIMITATIONS AND FUTURE DIRECTIONS
While the system various features that are required for earthquake disaster
management, some limitations have been identified that need to be investigated
further and resolved for future work.
The current detection ranges of survivals supported by the system is up to 2.5
meters, which may be worked around to extend detection range of survivals.
At the moment, the system takes into account two biomedical parameters,
heartbeat and respiration. More biological parameters may be considered (e.g.
pulse and skin detection) for improved aliveness detection capability.
The system provides network connectivity through GSM technology for sharing
information of survivals with concerned rescue units. The multiple wireless
technologies such as WIFI, 3G/4G and WIMAX can be integrated in the system to
provide fault-tolerance in that if one network connectivity fails whatsoever the
97
reason is, the system is able to continue working using an alternative available
wireless technology.
98
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