Juan Zambada, Ricardo Quintero, Ramon Isijara, Ricardo Galeana, Luis Santillan
Computer Science Department
Technological Institute of Culiacan. Sinaloa, Mexico
{jzambada, rquintero, risijara, rgaleana, carlos santillan}@itculiacan.edu.mx
Abstract—School transport is used by millions of childrenworldwide. However, not a substantial effort is done in orderto improve the existing school transport systems. This paperpresents the development of an IoT based scholar bus monitoringsystem. The development of new telematics technologies hasenabled the development of various Intelligent Transport Systems.However, these are not presented as ITS services to end users.This paper presents the development of an IoT based scholar busmonitoring system that through localization and speed sensorswill allow many stakeholders such as parents, the goverment, theschool and many other authorities to keep realtime track of thescholar bus behavior, resulting in a better controlled scholar bus.
Keywords—School Transport, Intelligent Transport Systems(ITS), Internet of Things (IoT), propagation node, sensor, mon-itoring, MQTT, EPC, EPCGlobal, RFID, Mosquitto Broker
I. INTRODUCTION
School transport is used by millions of children in theEuropean Union (EU) [1] and so in many cities around theworld. Having said this, although children are some of themost vulnerable users, little research has been conducted withthe goal of achieving a safer school transport system for them[2]. To achieve a safer school transport, one has to considerit from the moment that children leave home, until they reachthe door of his school as most of the deaths and injuries theysuffer are presented outside the school transport (74%) [3].
In the United States from 2003 to 2012, 119 pedestriansschool age (under 19 years) have died in accidents involvingschool buses; 65% were beaten by school transportation, 5%operating as school transport vehicles and 30% by othervehicles involved in accidents [4]. The result on a pilot study[5] was that children feel safer and experience less stress level,when the school transport reduces the speed when approachingschools and bus stops. In order to have a safer school transportsystem, the Intelligent Transportation Systems (ITS) shouldtake into account all stakeholders, from government authori-ties, to parents, including those that may arise indirectly, ascan be university researchers teams, who at a certain momentcan carry out research on the behavior of school transportsomewhere in the world. Since the 80s, the development ofnew telematic technologies have enabled the development ofseveral intelligent transport systems, with the aim of providinga service to a single user or a defined number of them (Trafficmanagers, public and private Organizations, stakeholders andothers), and not as a global service where anyone interestedcould make use of it [6].
The aim of this paper is to present a new scholar busmonitoring system that implements localization and speedsensors using the Internet of Things architecture. The use ofthis system will not only allow parents to monitor the scholar
bus in order to know the location of their children or its aprox-imate arrival time to school or home. In addition to parents,new stakeholders may arise. For example, the local transportauthorities or even a research team from a university that isinterested in analyzing the behavior of school transportation ina particular region of the world using aggregate data providedby cloud services to determine when and where does the schooltransportation violates the guidelines established by their localauthorities.
The rest of this paper is organized as follows: In section II,the design of the monitoring system for the school transport isexposed. In Section III, the proposed hardware to implementa mobile propagation node, localization and speed sensors onschool transportation is presented. Section IV presents howthe properties of ubiquity, uniqueness and discoverability areimplemented in the mobile propagation node, and localizationand speed sensors, to meet the paradigm of Internet of Things.In Section V, we present a service that we developed that usesthe designed monitoring system. In section VI the results fromthe developed service are presented. Finally in section VII wepresent the conclusions and future work.
II. DESIGN OF THE MONITORING SYSTEM FORSCHOOL TRANSPORT
In this research, we propose a Monitoring System forSchool Transport, based on the paradigm of the Internet ofThings, allowing the school transportation to have intelligenceand ability to provide information and features of discov-erability and ubiquity, which allows different actors to usethe information obtained to give different uses; for instanceanalysis and visualization using new paradigms such as cloudcomputing and big data.
The system’s proposed hardware consists of a mobilepropagation node and localization and speed sensors as shownin Fig 1.
Fig. 1. Mobile Propagation Node and Sensors of Localization and Speed
Through the mobile propagation node using the MessageQueuing Telemetry Transport connectivity protocol (MQTT)[7], the internet is extended to reach the location and speed
sensors connected to it, so that they can transmit the locationand speed of school transportation in the form of small infor-mation data packets called chirps. The packages will be sentto the cloud by the mobile propagation node using the GeneralPacket Radio Service (GPRS) provided by cellular networks.Both the mobile propagation node, as those, localization andspeed sensors are installed on school transportation.
III. PROPOSED HARDWARE
School transport differs from country to country. In somecountries, school buses (properly equipped) are constructed forthe sole purpose of serving as school transport; however inother countries, the vans undergo a process of adaptation inorder to be allowed to be used as school transport. We rely onthese facts so that the hardware we propose can meet economicfeasibility and easy installation in any vehicle used as a schooltransport anywhere in the world.
A. Mobile Propagation Node
The mobile propagation node was built with aPIC18F45K20 microcontroller manufactured by Microchipwhich is embedded in a DM164130-4 demo board. Thefacilities offered by the PIC18F45K20 are: up to 16,384single-word instructions, 1536 bytes of internal RAM, 36terminals I/O, a EUSART serial port, architecture optimizedfor C compilers, among others. These facilities allow us tomeet the objectives of the intelligent identification, locating,tracking, monitoring, and managing the school transport,taking into account the vision of IoT [8]. The block diagramof the mobile propagation node is shown in Figure 2.
Peripheral and I/O ports that are not used by thePIC18F45K20 can be used to add modules to the mobile nodepropagation that enables other sensors connect to it.
The Internet of Things aims to extend the Internet to theubiquitous assets in the physical world. In this case we extendthe Internet to the localization and speed sensors to monitorschool transportation via mobile propagation node.
Fig. 2. Block Diagram of the Mobile Propagation Node and Sensors ofLocalization and Speed
The Internet of Things over IP provides fundamental sup-port for global communication and access to services andinformation [9]. To be installed on school transportation,
mobile propagation node requires mobile communication. Forthis reason, it will connect to the internet through the GPRSstandard of the physical layer, using the MQTT [7] protocol.MQTT is a lightweight machine-to-machine communicationprotocol, designed for devices with limited resources andunreliable networks.
For an economical solution, the MQTT protocol is imple-mented in the PIC18F45K20 microcontroller. For deploymentto the microcontroller, the debugger/programmer manufacturedby Microchip PICkit 3 was used. Microchips PICkit 3 In-Circuit Debugger/Programmer uses in-circuit debugging logicincorporated into each chip to provide a low-cost hardwaredebugger and programmer. The MPLAB X is an IntegratedDevelopment Environment (IDE) that we used to develop theMQTT client code embedded in the PIC18F45K20. To dothis, we used the MPLAB XC compiler, a compiler languageC/C++.
The MQTT protocol implements the publish/subscribe ar-chitecture [10] with a central broker in the cloud, so we getthe following benefits:
• Low coupling between business logic and sensors oflocalization and speed.
• Availability of communication from many to many.
The availability of communication from many to many iswhat allows us to integrate all stakeholders, from governmentauthorities, to parents, including those that may arise indirectly,as can be teams of university researchers. Figure 3 showsthe publish/subscribe architecture with a central broker in thecloud.
Fig. 3. Publish/Subscribe Architecture with a Central Broker in the Cloud
In publish/subscribe architecture, a client who needs data iscalled subscriber and can be any stakeholder, such as a parent.The subscriber registers its interest in a topic of a broker thatis in the cloud; topics of interest are the location and speedof the school transport. The client responsible for sendingfresh data towards the broker is called Publisher; the mobilepropagation node we propose in this research, is the Publisher,and is the one responsible for sending data of the location andspeed of the school transportation, which are provided by thelocalization and speed sensors.
B. Localization and Speed Sensors
For information on the location and speed of schooltransportation, the SIM908 module manufactured by SIMComWireless Solutions Co. Ltd. was used. The SIM908 has lo-calization and speed sensors embedded, and is a GSM/GPRSmodule ideal for M2M applications, which combines GPStechnology for satellite navigation.
The compact design that integrates GPRS and GPS ina SMT package saves time and money significantly in thedevelopment of applications that require GPS technology. TheSIM908 module is controlled using AT commands (GSM07.07, 07.05 and SIMCOM enhanced AT Commands) by usingthe USART serial communication protocol. The main featuresof the GPS module embedded into the SIM908 are:
• TTFF Time To First Fix - The time required by theGPS receiver to acquire satellite signals and navigationdata, and calculate a position (called Fix).
◦ Cold Start: 30s (typical).◦ Hot Start: 1s (typical).
To reduce design time, the GPS/GPRS/GSM V3.0 modulemanufactured by DFRobot (which has embedded the moduleSIM908) was used. Figure 4 shows the GPS/GPRS/GSM V3.0module.
Fig. 4. GPS/GPRS/GSM V3.0 Module manufactured by DFRobot
The block diagram of the mobile propagation node im-planted in the DM164130-4 demo board and the localizationand speed sensors that are embedded into the GPS/GPRS/GSMV3.0 module, which allow for control and communicationbetween them, is shown Figure 5.
Fig. 5. Block diagram of the Demo Card DM164130-4, and theGPS/GPRS/GSM V3.0 Module
IV. UBIQUITY, UNIQUENESS ANDDISCOVERABILITY
We believe that you have to take into account the Radio-Frequency Identification (RFID) tags due to the millions ofthem existing in the world and transducers. The RFID tags areused to identify things and transducers are devices that convertenergy from one domain to another and allow us to observethe status of a physical entity.
The British employed RFID principles in World War IIto identify their aircrafts. In the 1960s, Los Alamos NationalLaboratory incorporated RFID tags into employee badges toautomatically identify people, limit access to secure areas, andmake it harder to forge the badges. Niche domains have alsoused RFID in various applications, such as to identify animals,label airline luggage, time marathon runners, make toys inter-active, prevent theft, and locate lost items. Nowadays, threemajor organizations are pioneering its large-scale adoption:Wal-Mart, Tesco, and the US Department of Defense. Eachaims to offer more competitive pricing by using RFID to loweroperational costs by streamlining the tracking of stock, sales,and orders [11].
The transducers may be sensors or actuators. A sensorconverts a physical, biological or chemical parameter to anelectrical signal and an actuator accepts a data sample orsamples and converts them into an action [12].
For our work we select the EPCglobal framework as thebasis for implementing the IoT paradigm that allows us tomonitor school transportation through the localization andspeed sensors. The EPCglobal framework includes RFID tagsbut will extend to include the location and speed sensors. TheEPCglobal framework, also serve as the basis for meeting theobjectives of ubiquity, uniqueness and discoverability neededin the paradigm of IoT [8]. The framework of the EPCglobalarchitecture is divided in layers of identification, capture andexchange [13], [14] as shown in Figure 6.
The following subsections describe how the framework ofEPCglobal extends to integrate location and speed sensors toachieve ubiquity, uniqueness and discoverability of them toreach compliance with the paradigm of IoT.
The ubiquity of the localization and speed data is accom-plished by extending to them the Internet through the mobile
propagation node using the communication protocol MQTT,via a mosquitto broker [15] located in a publicly accessiblesandbox server available at iot.eclipse.org, port 1883.
Fig. 7. The ubiquity of the localization and speed sensors
Figure 7 illustrates how the ubiquity is achieved by usingthe publish/subscribe architecture which is described in section3.
B. Uniqueness
The mobile propagation node and the location and speedsensors can be in two stages, and in any of the two stagesshould be uniquely identified in the world. These two stagesare:
• The supply chain.
• The operation of them on school transportation.
For identification of sensors we used the Electronic ProductCode (EPC) universal identifier of the EPCglobal frameworkwhich provides a unique identifier to each object in thephysical world. The representation of an EPC identifier isa Uniform resource identifier (URI) called ‘Pure IdentityURI”, and is used when referring to a physical object in theinformation systems and business applications. The EPCglobalTag Data Standard [16] defines the format of EPC Pure IdentityURI, the Tag URI format and the compact binary format.The latter two allow efficiently represent an EPC identifierwithin the RFID tags. An EPC identifier can also be usedby barcode technology. To do this, we must convert the EPCPure Identity URI to a GS1 (General Specifications 1) ElementString from the GS1 system identifiers [17]. Figure 8 illustratesthe different ways it can represent a physical object accordingto the context in which it is identified.
Once manufactured the mobile propagation node and thelocation and speed sensors, will go through the entire supplychain until they are purchased at a point of sale by the end user.In the supply chain, enterprise applications can identify themvia RFID tags adhered to them or through bar codes printedon them as show in Figure 9. Each RFID tag contains the EPCof the sensor in question. Similarly, each barcode contains theGS1 key of the sensor in question.
Fig. 8. Different representations of a physical object
Fig. 9. The sensors in the supply chain stage
Once installed on school transportation, the sensors beginto send information in the domain of IoT, and in order tobe identified printed bar codes may be used with GS1 keyson school transportation or web services using their “EPCPure Identity URI” as shown in Figure 10. The followingdescribes the implementation of the different representationsfor the location and speed sensors.
Fig. 10. Web service to identify sensors
1) EPC Pure Identity URI: Is the format that applicationsuse to uniquely identify each thing or concept in the world.
To ensure that the location and speed sensors can beidentified uniformly in the IoT applications, we have extendedthe EPC schemes to new Serialized Global Transducer ItemNumber (SGXIN) scheme that inherits from General Identifier(GID) as proposed in [18]. For a unique identification on theplanet for sensors we have extended the identification layer ofthe framework of the EPCglobal architecture to integrate thestandard IEEE 1451 of the transducers. Based on the IEEE
1451 standard, the uniqueness of the sensors is obtained byusing the field Universal Unique Identification (UUID) plus theserial number of each sensor [18]. The UUID field consists offour subfields: location, manufacturer, year and time [12]. Tosubfield time, is considered the day of the year it was built x1000 + the number produced on that day [18]. To fill the UUIDfield shown in Table 1, we use the following data: the mobilepropagation node was built in the graduate department of theTechnological Institute of Culiacan located at the geospatialcoordinates 24°47’18” N 107°23’48” W on November 1, 2014and the first produced that day.
TABLE I. UUID FIELD
Field Value Field Bits Binary Value
N/S N 1 1
Latitude 24°47’18” 8+6+6 00011000101111010010
E/W W 1 0
Longitue 107°23’48” 8+6+6 01101011010111110000
Manufacturer 0 4 0000
Year 2014 12 011111011110
Time 304001 22 0001001010001110000001
The maximum number of transducers that can handle themobile propagation node is 255 to meet the standard IEEE1451, which dictates that a Smart Transducer Interface Module(STIM) (in the form of the mobile propagation node) canhandle up to 255 transducers, which can be serialized from1 to 255, since 0 has a special meaning [19]. Transducernumber is represented by 8 bits. As the mobile propagationnode extends the Internet to a location sensor and one of speed,we can assign serial numbers 1 and 2 respectively. Because ofthis, there are two SGXIN-URI; one representing the locationsensor and other representing the speed sensor. The semanticSGXIN-URI format is:
According to the EPC scheme designed for SGXIN, thelocation and speed sensors are expressed with the followingSGXIN-URIs (Note that the numbers are represented in theirdecimal value):
Using the paradigm of IoT, the proposed sensors senddata about the location and speed of the school transport toInternet through a broker, as well as billions of objects inthe world are sending their own data to the Internet. Usersrequiring school transport information will have to make useof Discovery Service (DS) to know where and how to obtainsuch information. The EPCglobal organization defines thecomponent EPC Discovery Services (EPCDS) for this purpose,but its design is still under investigation [13]. Because of this,we implemented the Secure Discovery Service Model (SecDS)[20] . To do this, we use the components Object NamingService (ONS) [21], and EPC Information Services (EPCIS)[22] of the EPCglobal Architecture Framework.
V. SCHOOL TRANSPORT TRACKING
With the aim that any interested user could be able tomonitor in real time a vehicle being used as a school trans-port in relation to its location and speed, we designed theweb application “School Transport Tracking” based on theparadigm of IoT. The application was installed on Heroku, acloud Platform as a Service (PaaS) that enables the applicationto run completely in the cloud and interact with it through abrowser. Figure 11 describes the steps that are necessary totrace school transport.
Fig. 11. Scholar bus monitoring system
• 1) When the location and speed sensors installedon the school transport are energized, the propa-gation node connects to Mosquitto broker availableat m2m.eclipse.org on port 1883 using the MQTTprotocol. Once connected to the broker, the sensorsbegin to publish their data to it.
• 2) When a client has the need to track the schooltransport uses an android application or a web appli-cation that resides on Heroku accessed by the URLhttp://www.transportes-inteligentes-itc.com.mx/ usingany web browser on any device.
• 3) Once the client is authenticated, the applicationsubscribes to the same Mosquitto broker in order tobe notified whenever the sensors publish data aboutthe location and speed of the school transport.
• 4) Whenever the sensors publish their data to thebroker, the broker notifies the subscribed web app withsuch data and stores them in MongoDB, a document-oriented database.
• 5) In addition to storing the data, the application sendsthem as parameters to the “Google Maps JavaScriptAPI v3” in order to map the location of the schooltransport.
• 6) The web application builds a response with theinformation received from the Google Maps API andsends it through the chain to the browser where youcan view the map with the location and speed of theschool transport as shown in Figure 12.
VI. RESULTS
The system was tested during two months from 6:00 amto 7:30 am from Monday to Friday in a vehicle used as schooltransport in order to validate if the system offers better security
Fig. 12. Mapping the Location and Speed of the School Transport
to users. The information that the monitoring system receivedwas stored in a non relational database. During the first montha trained driver used the system and an untrained driver usedit during the second month.
The following results were obtained from the data analysis:
• First month, trained driver: The 100% of the timethe vehicle’s speed did not exceed the 60kph speedlimit.
• Second month, untrained driver: The 15% of thetime the vehicle’s speed exceeded the 60kph speedlimit.
On 02/23/2015 the system was used for 25 minutes. Fromthis 25 minutes the 1.4% of the time, the system reportedthat the vechicle exceeded the speed limit. Here we can noticethat although the percentage of time that the vehicle exceededthe speed limit is short, during 21 seconds the law wasviolated. From this analysis we can notice that the safety ofthe passengers can be increased thanks to the effective realtimemonitoring the system provides.
VII. CONCLUSIONS AND FUTURE WORK
In recent years, the Internet of Things has developed veryrapidly and has become a development trend to improve livingconditions in the world as a whole. One of the feasible areasto cover with this new paradigm in the field of smart cities isthe monitoring of school transport. Considering the above, wepropose a scholar bus monitoring system easy to implementin any vehicle and usable by anyone or any “thing” using theparadigm of the Internet of Things in order to provide greatersecurity to the users of this medium of transport.
The Internet of Things applied to the monitoring of theschool transport will play an important role in the managementof urban transport in the cities of the future. So, as future work,we consider integrating wireless communication protocols tothe mobile propagation node, to add other sensors to it suchas proximity sensors at the school transportation stops, in the
passenger seat and integrate them to the Internet of things. Itwill also be necessary to create models to analyze data thatprovides the monitoring system using the Big Data approach.
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