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Project Domus: Designing Effective Smart Home Systems
Project Domus: Designing Effective
Smart Home Systems
This project manual is submitted as partial fulfilment of the requirements for the BSc in
Information Systems and Information Technology (DT249) to the School of
Computing, Faculty of Science, Dublin Institute of Technology.
Author: Paolo Carner, D08117953
Supervisor: Michael Gleeson, School of Computing
Date: 18 April 2009
Project Domus: Designing Effective Smart Home Systems
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Acknowledgments
I would like to thank my supervisor Michael Gleeson for his guidance, time and support
throughout the project. My friend and colleague Massimiliano Balsamo for his
suggestions about the applications user interface. A sincere thanks also goes to my
wife Giorgia for all her patience, dedication and encouragement over the past months.
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Abstract
The subject of this work is the analysis and design of a proof-of-concept Temperature
Control System (TCS) part of a Smart Home. The TCS also implements an early-
warning Fire Alarm sub-system that uses a Bayesian Network to infer the likelihood of
a fire. The application is implemented using Visual Studio 2005, using a hardware and
software kit provided by Echelon Corp. The Bayesian Network implemented is Netica
from Norsys Corp.
Keywords: Smart Home, Home Automation, Bayesian Networks.
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TableofContents
1. Introduction ..............................................................................................................8
1.1. Project Aim and Objectives..................................................................................8
1.1.1. Aim...................................................................................................................8
1.1.2. Objectives .........................................................................................................8
1.2. Intellectual Challenge...........................................................................................8
2. Literature Review .....................................................................................................9
2.1. Definition..............................................................................................................9
2.2. History ..................................................................................................................9
2.2.1. The Mechanical Revolution .............................................................................9
2.2.2. The Electrical Revolution...............................................................................10
2.2.3. The Information Revolution ...........................................................................12
2.3. Smart Homes Today...........................................................................................13
3. Research .................................................................................................................16
3.1. Components of a Smart Home System...............................................................16
3.1.1. Control Systems .............................................................................................17
3.1.2. Actuators ........................................................................................................17
3.1.3. Home Network ...............................................................................................18
3.2. Communication Protocols ..................................................................................19
3.2.1. X10 and its Legacy.........................................................................................19
3.2.2. Other Protocols...............................................................................................21
3.3. The Market for Smart Homes.............................................................................23
3.3.1. Potential Benefits............................................................................................24
3.3.2. Reported Needs and Concerns........................................................................26
3.4. Design Challenges ..............................................................................................28
3.4.1. Gathering Valid System Requirements ..........................................................29
3.4.2. Choosing the Right Technology.....................................................................32
3.4.3. The Quest for the Effective User Interface.....................................................33
3.4.4. The Role of Artificial Intelligence .................................................................36
3.4.5. Going Beyond Home Automation..................................................................39
4. Development ..........................................................................................................41
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4.1. Analysis ..............................................................................................................41
4.1.1. Business Requirements...................................................................................41
4.1.2. Determining a User Profile.............................................................................41
4.1.3. Gathering User Requirements ........................................................................42
4.1.4. Use Case Diagrams ........................................................................................43
4.1.5. Functional Requirements................................................................................44
4.1.7. Glossary..........................................................................................................59
4.2. Design.................................................................................................................61
4.3. Implementation...................................................................................................69
4.3.1. Hardware ........................................................................................................70
4.3.2. Software..........................................................................................................75
4.4. Testing ................................................................................................................84
4.4.1. Test Plan .........................................................................................................84
4.4.2. Test Cases.......................................................................................................87
4.4.3. Functional Requirements Implemented in POC.............................................89
4.4.4. Bug Report .....................................................................................................91
4.4.5. Test Outcomes ................................................................................................92
5. Conclusion..............................................................................................................93
5.1. Summary of the Work ........................................................................................93
5.2. Project Findings..................................................................................................94
5.3. Recommendations for Future Work ...................................................................94
5.4. Learning Outcomes ............................................................................................95
5.4.1. Research .........................................................................................................95
5.4.2. Analysis ..........................................................................................................95
5.4.3. Technical ........................................................................................................95
5.4.4. Project Management.......................................................................................96
5.4.5. Lessons Learned .............................................................................................96
References ......................................................................................................................97
Appendices ...................................................................................................................100
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FiguresandTables
Figure 1 Advertisement for a Washing Machine, Daily Mail (1955) ..................................... 11
Figure 2 Adoption of new technologies over time .................................................................. 12
Figure 3 Picture of a Xanadu House........................................................................................ 14
Figure 4 Sensor and Actuator Interaction................................................................................ 17
Figure 5 X10 Zero-Crossing Signal Transmission.................................................................. 20
Figure 6 Rogers Technology Adoption Lifecycle.................................................................. 23
Figure 7 Components of Software Requirements ................................................................... 30
Figure 8 Implicit and Explicit Communication Channels....................................................... 35
Figure 9 Causal Graph............................................................................................................. 38
Figure 10 Bayesian Network ................................................................................................... 39
Figure 11 System Overview .................................................................................................... 44
Figure 12 Sub-Systems Overview........................................................................................... 54
Figure 13 Operating the System.............................................................................................. 62
Figure 14 User Authentication ................................................................................................ 63
Figure 15 User Administration................................................................................................ 64
Figure 16 Managing Devices................................................................................................... 64
Figure 17 Managing Teams..................................................................................................... 65
Figure 18 Managing Schedules ............................................................................................... 66
Figure 19 Managing Events..................................................................................................... 67
Figure 20 Dispatching Commands .......................................................................................... 67
Figure 21 Flight Control Sub-System ..................................................................................... 68
Figure 22 Inference Engine Sub-system ................................................................................. 69
Figure 23 How LonWorks Devices exchange Messages ........................................................ 70
Figure 24 Anatomy of a LonWorks Device ............................................................................ 71
Figure 25 Network Variables .................................................................................................. 72
Figure 26 A Typical LonWorks Solution................................................................................ 73
Figure 27 The Mini EVK Evaluation Kit ................................................................................ 74
Figure 28 Mini-Gizmo I/O Board............................................................................................ 76
Figure 29 Main Screen of the POC System............................................................................ 77
Figure 30 Add Device Dialog Box.......................................................................................... 78
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Figure 31 EVK Service Switch ............................................................................................... 78
Figure 32 Fire Alarm Sub-system Settings ............................................................................. 79
Figure 33 Logic Flow for the FA Sub-system......................................................................... 79
Figure 34 HVAC Sub-System Settings ................................................................................... 80
Figure 35 Logic Flow for the HVAC Sub-system................................................................... 80
Figure 36 Causal Graph for the FA Sub-system ..................................................................... 82
Figure 37 Fire Alarm Bayesian Network ................................................................................ 84
Table 1 Examples of Smart Home Applications ..................................................................... 25
Table 2 Classifying the Voice of the Customer....................................................................... 30
Table 3 Defining User Input.................................................................................................... 43
Table 4 Functional Requirements............................................................................................ 46
Table 5 Functional Requirements grouped by Sub-system..................................................... 55
Table 6 MGDEMO Attributes and Methods........................................................................... 75
Table 7 Mapping Real-world Devices to the POC.................................................................. 76
Table 8 BN Nodes and Relationships...................................................................................... 82
Table 9 Test Plan Risks and Contingencies ............................................................................ 87
Table 10 Summary of Test Results ......................................................................................... 87
Table 11 List of Functional Requirements Implemented ........................................................ 89
Table 12 Bug Report ............................................................................................................... 91
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1. IntroductionThis chapter presents the projects aim, objectives, and its intellectual challenge.
1.1. ProjectAimandObjectives
1.1.1. Aim
The aim of this project is to develop a proof-of-concept prototype for a Smart Home
system that will address some of the challenges emerged during the research.
1.1.2. Objectives
The project has the following objectives:
Providing a brief history of the underlining technology Presenting an overview and an evaluation of existing standards Investigating potential benefits and documenting perceived issues Researching current challenges Designing and building a proof-of-concept
1.2. IntellectualChallenge
Although the project will consider proper Human-Computer Interaction (HCI)
techniques to provide users with a user-friendly interface, it will also aim at improving
the effectiveness of Smart Home systems. The Oxford Dictionary describes
effective as: producing a desired or intended result (emphasis added). According
to this definition, it is envisaged that an effective Smart Home shall not only carry out
automated actions on the users behalf, but be asked to interpret, understand and, if
possible, anticipate what users might also intend to do. Elements of Artificial
Intelligence, such as decision theories and adaptive systems, may be able to provide
these capabilities.
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2. LiteratureReviewThis chapter presents a definition of Smart Home, provides a brief history of the
technologies contained, and outlines recent developments in the field.
2.1. Definition
A common definition of Smart Home is of an electronic networking technology to
integrate devices and appliances so that the entire home can be monitored and
controlled centrally as a single machine (Pragnell et al., 2000). Another term that
describe the same technology is domotics, which derives from the Latin word domus,
meaning home, and informatics, meaning the study of the processes involved in the
collection, categorization, and distribution of data. However, since this technology is
still very much in flux, other terms are also used in the literature with equivalent
meaning, such as: home automation, smart house, digital home or electronic
home. Furthermore, note that, although the terms house and home have a
different meaning in the English language, they are often used alike in this context.
2.2. History
Although the term smart home was first used in 1980s, the concept is far from new.
The early documented attempt to envisage something very similar dates back to the
1960s, with Walt Disneys Experimental Prototype Community of Tomorrow
(EPCOT), presented in 1966i. A Smart Home will not be able to accomplish much
without appliances to control, nor will it be able to communicate to these devices in the
absence of a control network (home network). Since appliances and home network
are so interlinked with a Smart Home, the following sections provide a brief history on
how these come into being.
2.2.1. TheMechanicalRevolution
The first question that might come to mind is why we would need a Smart Home and
why we would want to find different ways of doing ordinary things, such as washing
clothes, cooking, or even turning a light on or off. A similar question could have been
asked at the beginning of the 20th Century, at the dawn of what can be called the
mechanical revolution.
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In late 1800s, the middle class was experiencing a shortage of domestic servants which
created the need to find new ways to provide help in the home (Harper, 2003). Such
necessity was the initial driving force behind the inventions of the first domestic
appliances, which had the purpose of making household chores easier and do more with
less.
In 1911, Frederick Winslow Taylor published The Principles of Scientific
Management, which advocated the use of efficiency to maximize results through
minimal effort. This theory is today known as Taylorism and, though it was originally
intended to be applied in industrial settings, this concept soon spilled over into the
domestic realm due to the need at hand.
Christine Frederick was one of the first to recognize that the challenges tackled by
Taylorism were also directly applicable to domestic issues and captured these in her
book Household engineering: Scientific Management in the Home, published in
1915. In her book, Frederick predicts that mechanical appliances would be the ones
which were to take up the work originally performed by servants where every possible
purely manual task is done by arms of steel and knuckles of copper. She also puts
forward the idea of a Smart Home where she foretells that such machinery will be far
more unified than at present with various pieces related to one another, as reported
by D. Heckman (2008).
2.2.2. TheElectricalRevolution
In spite of the first inventions, most of this new domestic technology would have still
been easily recognized by people who had lived in the pervious Century. However,
electricity, the driving force behind the electrical revolution, would soon to change this
familiar landscape beyond recognition.
Electrical energy first arrived in the homes around 1920s and, although initially used
for lightning purposes only, by 1940s mains electricity was readily available to around
65 per cent of the total of houses in the UK. (Harper, 2003). Soon after it reached a
critical mass, producers of electrical appliances inundated the market with all sorts of
items. Although some of them were nice-to-have-devices, such as electric popcorns
poppers, egg cookers and waffle irons, others were really life changing for the
household: refrigerators, washing machines, electric cookers, vacuum cleaners, just to
mention the most important.
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Regardless of their importance, all these electrical appliances were still made with the
original need in mind, which was often reminded to people as producers marketed these
products with time-saving slogans such as no longer tied down by housework or
automatically gives you time to do those things you want to do (Heckman, 2008).
Figure 1 shows example of these early campaigns: a 1950s advertisement about a
washing machine with the slogan automatically gives you the time to do the things
you want to do.
Figure 1 Advertisement for a Washing Machine, Daily Mail (1955)
It is interesting to note how some later devices could be hardly classified as time savers
and how, in spite of this, they were still quite readily adopted. By early 1980s, around
65 per cent of UK homes had a colour television set and half of them a video recorder
(Harper, 2003). More interesting still, the adoption curve was different from one to
another, sometimes regardless of the comfort that they could bring. For example,
central heating, took comparatively a while longer to become widespread that the color
television. Figure 2, taken from the research The Market Potential for Smart Homes,
shows the adoption curve of some of the most common electrical devices in the
household (Pragnell et al., 2000).
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Figure 2 Adoption of new technologies over time1
2.2.3. TheInformationRevolution
Disneys original vision for EPCOT was to create both a laboratory for new technology
and a home for its inhabitants with the promise of offering an integrated living
environment (Heckman, 2008). Due to his untimely death, just a few months after the
official presentation of the project, EPCOT was never implemented, at least not in its
original idea.
The concept behind the original vision was however to live on. In the 1960s, a number
of hardware and software innovations made possible for home owners to have access to
the first computer-like appliances in their homes. Perhaps the first attempt to create a
home automation system occurred in 1966 when Westinghouse proposed the
experimental and quite bulky Electronic Computing Home Operator (ECHO) IV.
Although the original system was supposed to automate the family finances, it was
soon extended to include recipes, shopping lists, family inventory, and, in its final
versions, added home temperature control and the ability to control appliances.
In 1975, it was the turn of the Altair 8800, followed by the Apple II in 1977 and the
IBM PC in 1981. While these computers were slowly finding their ways into the home,
they also contributed to the creation of the idea of smart machines.
1 Source: General Household Surveys 1972-98, BARB, BT, Oftel, ITC, BskyB, ONS. Note: Data refer to percentage of households for all goods except mobile phones, which refers to percentage of population.
Project Domus: Designing Effective Smart Home Systems
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In 1978, after a few years of experimentation and refinement, PICO Electronics
patented the X10 technology. This technology can be considered the first home
network as, differently to other networks available at the time, it enabled the existing
electrical wiring in anyones home to also be used as the media for the communication
network. By doing so, X10 made home automation a reality for the majority of the
household at an affordable price.
Nowadays, an increasing number of houses have home computers, game consoles and
always-on Internet connections that extend the availability of services and resources to
the household beyond the physical boundaries of the home.
2.3. SmartHomesToday
The Oxford Dictionary defines smart as both stylish and fresh in appearance, having
a quick intelligence, and being fashionable and upmarket. Sony was among the first
companies to attach the smart buzzword to a computer when, in 1982, it marketed the
Smart Sony computer: no longer advertised simply as a home computer, but tried
to cash in on the smart concept by selling it as a device which could help you make
smarter business decisions (Heckman, 2008).
The smart concept has become since a marketing catchword, still employed today, to
sell a wide range of products, hence: smart phones, smart cameras, smart design,
smart bombs and smart homes. Usually, the word define devices that are reportedly
based on cutting-edge design that unite innovation with practical simplicity, However,
as this would soon be demonstrated, sometimes marketing buzzwords alone cannot
guarantee the sell.
Xanadu was the first example of a mass-produced Smart Home. Built throughout the
1980s in the US around the original EPCOT idea, these houses were commercially built
dwellings that made extensive use of Smart Home technologies. To look even more
futuristic, the actual house was made entirely of polyurethane foam. The Xanadu home
had a computer that monitored and controlled all its systems: the kitchen, living room,
bathrooms, and bedrooms all had their own electrical and electronic devices to control
the appliances present in the house. For example, the shower could be set to be turned
on at a specific time and a set temperature. The ad campaign eloquently described the
house as Xanadu: the Computerized House of Tomorrow and its peculiar appeal was
set by the advertisement campaign: a house with a brain a house you can talk to, a
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house were every room adjusts automatically to match your changing moods
(Heckman, 2008).
Figure 3 Picture of a Xanadu House
As the time moved on, and most of the houses were still unsold, the technology
contained soon become obsolete. One by one, these Xanadu houses started to get
demolished to make space for more commercially viable projects and, by October
2005, they were all gone.
In spite of the commercial setback provided by the Xanadu homes, the concept was
sound and a combination of elements such as computers, robotics and Artificial
Intelligence (AI) were to push the Smart Home concept further, even if sometimes only
in research laboratories. Throughout the 1980s, several innovative ideas provided a
clear indication that the technology might have been finally mature enough to deliver
commercially viable solutions. As an example, a device named Waldo, which
interfaced with an Apple computer, could use voice recognition and speech synthesis
technology to control appliances.
Today, several commercial and academic projects, funded by universities and the
industry alike, are still investigating the possibilities that Smart Homes can offer. A
possibly incomplete list of projects working with Smart Home technologies can be
found in the following paragraphs. For more information about some of them, see the
referenced endnotes.
CISCO Internet Homeii This project aims at investigating the benefits of a high-
speed, always-on Internet connection that enables an array of consumer devices and
appliances in the home. Developed in conjunction with leading consumer companies, it
Project Domus: Designing Effective Smart Home Systems
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demonstrates how Internet can enhance daily living for consumers for the homes and
communities of the future.
MIT House_niii This project is led by a multi-disciplinary team composed by
architects, computer experts, engineers and behavioural scientists who investigate key
issues and what services could be offered in the home of the future. Its focus is on the
design of the home and its related technologies, products, and services and to see how
they can evolve to meet the opportunities and challenges in the new home.
Microsoft Research EasyLivingiv Started in 1998, EasyLiving is a project funded by
Microsoft Research about creating an intelligent environment which will make
computing more accessible and more pervasive than todays desktop computer. Its goal
is to develop a prototype architecture and technologies for building intelligent
environments that facilitate people interaction with other people, computers, and other
devices.
UMASS intelligent home project This project from University of Massachusetts
uses simulations of agent-based intelligent systems that also use robotics in a domestic
context.
Adaptive Housev - This project, led by University of Colorado, aims at developing a
Smart Home system that programs itself by observing the lifestyle and desires of the
inhabitants, and by learning to anticipate and accommodate their needs.
Duke Smarthome programvi - Duke Universitys dynamic "living laboratory"
environment that contributes to the innovation and demonstration of future residential
building technology. The central concept of this project is the belief that Smart Homes
can improve that quality of life for people of all ages and incomes.
Aware Home Research Initiative (AHRI)vii An interdisciplinary research project at
Georgia Tech aimed at addressing the fundamental technical, design, and social
challenges presented by such questions by using off-the-shelf and state-of-the-art
technologies.
CENELEC SmartHouseviii - Funded by the European Committee for Electro
Technical Standardization (CENELEC), the aim of this project is to grow and sustain
convergence and interoperability of systems, services and devices that will provide
citizens with access to increased functionality, accessibility, reliability and security that
a SmartHouse, with common and open architectures, can deliver. Recently, CENELEC
has also released a European Code of Practice for SmartHouse operation.
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3. ResearchThis chapter provides details about the main elements that compose a Smart Home
system and gives an overview of the most important home network protocols. It also
attempts to define a possible market for the technology, outlining the potential benefits
and concerns emerged from recent researches. Finally, it provides some design
challenges that needs to be considered when designing a Smart Home.
3.1. ComponentsofaSmartHomeSystem
To be considered a Smart Home, the technology used must employ all the following
elements: intelligent control, home automation and internal network (Jiang et al., 2004).
The intelligent control is provided by a control system, comprised of two types of
elements: sensors, which will monitor, control and report the status of the home
environment, and a control agent (human or software based) which acts on the
information provided by the sensors.
The home automation function is fulfilled by electrical or electronic devices, called
actuators, that will interact and modify the environment by accomplishing specialized
tasks. These tasks often work towards a more complex goal defined by the user of the
system.
The purpose of the home network is simply to ensure that all the components can
receive and send instructions to each other.
Figure 4 provide a simple example on how all three elements interact. A thermometer,
an example of a sensor, reports the current temperature. In response to this input, the
control agent, which can be a piece of software or an actual person, acts on the heater,
via the actuator, and instructs the device to switch on. This action accomplishes the
users initial goal: to increase the temperature to a comfortable level (Helai et al.,
2005). The result of a task might modify the environment monitored by the sensors,
whose input might cause the control agent to perform other tasks, such as turning the
heater off when the temperature has reached the desired level, and the cycle starts
again. Although not explicitly represented, all the actions depicted in the example
above can only be made possible by the existence of a home network that can carry the
information provided by the sensors and send commands to the actuators.
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Figure 4 Sensor and Actuator Interaction
3.1.1. ControlSystems
The control system is a critical part of a Smart Home as it determines usability,
reliability and overall effectiveness of the solution provided. These systems are written
as a piece of software that is run on a home computer or embedded in an electronic
device. These software systems offer the ability to control a subset of the home
appliances from a centralized location. Most of them also provide users with the option
to store macro commands; that is, to combine a list of tasks together. These macros can
be then invoked by the user when required or be automatically executed by the system
at a pre-set scheduled date and time.
3.1.2. Actuators
Actuators are electrical or electronic devices that can control a household appliance.
When they come as a separate device, they need to be electrically coupled with the
appliance and can control it by executing some simple commands, such as switching it
on or off. When they are embedded within the appliance itself, they can be more
sophisticated and provide more value added to the user.
Smart Home-enabled appliances can be subdivided into two categories. The first
category is composed by familiar items, such as refrigerators or washing machines,
which would also provide an intelligent interface to control them. The second category
is comprised of entirely new devices. To a greater extent, most of these devices are still
at a prototype stage, with their viability and effectiveness being studied in some of the
home lab projects outlined in the previous section. Some interesting examples are:
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smart picture frames, which display users images in rotation updated in real-time;
smart mirrors2 that can display the news and remind the user of todays appointments
while brushing the teeth; smart tables, which incorporate a touch screen that allow users
to display and edit documents stored in file servers accessed via the home network;
smart pillow, which can read a book, or play the users favourite music when they
detect that their user is drifting into sleep.
3.1.3. HomeNetwork
Smart Home network technology can be subdivided into three main areas, depending
on the communication media used: Powerline, Busline, and Wireless.
Powerline systems plug in directly to the house electrical network (electrical mains)
and do not require additional cabling. This technology is the oldest of the three and,
though simple to configure and cheaper than other solutions, it may lack scalability and
considered the least reliable due to its susceptibility to electrical interferences. Some of
the earlier protocols support one-way communication, which allows devices to receive
information but not to communicate.
Busline systems use a separate media to send/receive signals, usually twisted-pair
cabling, which is similar to the cables adopted for phone or network services. Albeit
being more expensive to install, especially when retro-fitting existing houses, the use of
a separate cable provides a positive note as it makes this technology the most reliable of
the three and can provide higher bandwidth. Components based on this technology are
usually more complex to configure and require some knowledge of networking.
Finally, thanks to the dedicated media, this technology usually provides a completed
two-way communication protocol so that connected devices can communicate with
each other.
Wireless systems do not require any wires to operate. This technology can be further
subdivided into Radio Frequency (RF), and Infrared (IR). It is the most recent of the
three and is increasingly becoming more popular as costs per unit decrease. Solutions
based on this technology are usually very easy to install and configure and can combine
most of the benefits offered by Busline technology, such as two-way communication
and scalability, though with a relatively lower bandwidth. However, similarly to 2 See: http://gizmodo.com/gadgets/gadgets/touchscreen-smart-mirror-widgets-in-the-mirror-246384.php
Project Domus: Designing Effective Smart Home Systems
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Powerline, this technology can be prone to interferences, though the existence of two-
way communication can address it by implementing acknowledgment of commands
received and error checking/recovery mechanisms. Finally, due to its wireless nature,
this technology introduces some privacy concerns as unauthorized access can be gained
without even the need to be in the house. Some of the most recent protocols have tried
to address this issue by introduced data encryption and authentication mechanisms.
However, this also adds to the communication overhead, thus decreasing the bandwidth
available, and make systems based on this technology more complex to configure and
manage.
3.2. CommunicationProtocols
This section provides an overview of some the most important communication
protocols for home networks available today. Some of the protocols listed are
proprietary, that is, details are not disclosed to the public. Others are owned and
maintained by a company or consortium but openly made available. Finally, some of
these are also recognized standards, that is, acknowledged by nationally or
internationally accredited bodies.
3.2.1. X10anditsLegacy
X10 was the first general-purpose home network solution. PICO Electronic, a UK-
based engineering firm, patented it in 1978. After a first unsuccessful attempt to
market it in Europe, the company established itself in the US, where it was more
successful. The RadioShack, the US-based chain of electronics retail store, was the first
to offer consumer solutions based on this technology.
X10 is a Powerline system, so uses the existing electrical network in the house and can
allow users to remotely control, at least in principle, any appliance connected to the
house mains. A controlling device would just be plugged in between the mains and the
electrical appliance to be controlled. Properly instructed, this controlling device will
then turn the appliance on or off at specific times or as a response to specific events
coming from the home network.
The original implementation allows one-way communication and can address up to 256
devices subdivided into eight different homes (channels) to lessen the chances of
interferences with other systems nearby. Figure 5 provides a graphical representation
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on how X10 communicates. The X10 signal is sent when the voltage value crosses
zero, which happens twice at every current cycle. Virtually all other Powerline home
communication protocols use a variation of this method.
Figure 5 X10 Zero-Crossing Signal Transmission
In spite of its limitations, and thanks to the low installation costs and its ease of use,
X10 is still widely used today by DYI enthusiasts, especially in the US, where a
multitude of off-the-shelf components are readily available. However, due to the
differences between the US (120V/60HZ) and European (220V/50HZ) power lines,
devices built for the US market will not work in Europe.
In more recent years, this technology made a comeback due to the fact that the patent
for the protocol expired in late 1990s, and several forums on the Internet now can
provide resources for anyone interested in investigating this technology. A wireless
version of this protocol which offers limited two-way communication seem to exist but,
besides being called X10, it might have little to do with the original Powerline
technology.
After the original idea first implemented by X10, several other protocols have emerged
using the same concepts, sometimes enhancing the original specifications, such as
implementing two-way communication, providing support for more devices and
different types of media. The communication protocols listed below are an example of
the most known.
INSTEON derives directly from X10, for which is backward compatible. It is a
proprietary protocol developed by SmartLabs, Inc.ix and can use electrical power lines
or wireless. It offers two-way communication where the controlled devices also
function as repeaters for the messages to increase reliability.
Powerline Control Bus (PLCBUS) is a proprietary, two-way communications
technology developed by ShangHai Super Smart Electronics Co. Ltd.x. Differently from
X10, it can support up to 64,000 devices.
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CEBus, the Consumer Electronic bus (CEBus) protocol, also known as EIA-600, is by
some considered the US standard for home networking. It was first released in 1992
with the intent of expanding the capability of X10. It is an open architecture and is
outlined by a set of specification documents which define details for communicating
through power lines, twisted-pair cables, wireless, and others media.
Universal Powerline Bus (UPB) was released in 1999 by PCS Powerline Systemsxi of
Northridge, California (USA). Reportedly, it features an improved transmission rate
and higher reliability than X10, due to the different method used in transmitting the
electrical pulses.
3.2.2. OtherProtocols
Konnex (KNX) is a standard (EN 50090, ISO/IEC 14543), OSI-based network
communications protocol for home automation. It is the result of a convergence of three
existing European standards: the European Home Systems Protocol (EHS), BatiBUS,
and the European Installation Bus (EIB). In contrast with other similar technologies,
KNX defines several possible physical communication media and it is designed to be
independent of any particular hardware platform. The KNX standard is administered by
the Konnex Associationxii.
LonWorks, similarly to KNX, is a networking platform which specifies both the
communication protocol and the hardware required by it. Developed by Echelon
Corporationxiii in conjunction with Motorola in the early 1990s it supports a variety of
communication media, such as twisted pair, power lines, fiber optics, and RF. It has
established itself as a de-facto standard for building control and automation. In 1999,
the communications protocol was submitted to ANSI and accepted as a standard for
control networking (ANSI/CEA-709.1-B).
C-Bus is a proprietary protocol created by Clipsalxiv for use with its brand of home
automation and building lighting control system. C-Bus requires Ethernet-network like
Cat 5 Unshielded Twisted Pair (UTP) cables, though a two-way wireless version also
exists. This system is primarily used in Australia (e.g. Sydney Opera House) and in
Asia, but it is becoming more known in Europe as well.
Universal Plug and Play (UpnP) protocol is actually a set of protocols promulgated by
the UPnP Forumxv. The goals of UPnP are to allow devices to connect seamlessly in
order to simplify the implementation of networks in the home. Its control protocol is
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based upon an open architecture based on established standards such as TCP/IP, UDP,
HTTP and XML. However, this protocol is not an officially recognized IETF or IEEE
standard and may not be supported by many networking devices.
Zigbee is the name of a specification for a suite of communication protocols that use
RF as their transmission media. Based on the IEEE 802.15.4-2006 standard for wireless
personal area networks (WPANs), the standard is maintained by the ZigBee Alliance
Groupxvi. For non-commercial purposes, protocol specifications are available free to
the general public.
Z-Wave, smilarly to ZigBee, Z-Wave is a communications standard based on wireless
communication. The technology is developed and maintained by Zensysxvii, a Denmark-
based company. The Z-Wave Alliance is an international consortium of manufacturers
that oversees interoperability between Z-Wave products and enabled devices. This
protocol is a mesh networking technology where each node or device on the network
capable of sending and receiving control commands. Devices can work as stand alone
or in groups, and can be programmed into sequences (called scenes or events) that
trigger multiple devices, either automatically or via remote control.
BACNetxviii is an acronym for Building Automation and Control Network. This
communication protocol was developed by the American Society of Heating,
Refrigerating and Air-Conditioning Engineers (ASHRAE) in conjunction with building
management organizations, system users, and building system manufacturers. BACNet
standard was officially ratified in 1995 as ANSI/ASHRAE 135-1995 and it is
advertised as an open protocol which could be applied to any type of systems, such as
Heating, Ventilating and Air Conditioning (HVAC) systems, lighting, life safety,
access control, transportation, and maintenance systems. It can use a wide range of
network technologies for communication.
Modbus is a communication protocol that was developed in the 1970s by Modicon,
Inc. for use in industrial automation systems with programmable logic controller (PLC)
devices. Reportedly, it is one of the most widely used communication protocol for
connecting electronic equipment in industrial settings. In 2004, the standard was
transferred to Modbus-IDAxix, a non-profit organization made up of users and suppliers
of automation devices primarily in manufacturing.
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3.3. TheMarketforSmartHomes
As outlined in Chapter 2, the 20th Century introduced a dramatic revolution in domestic
technology which culminated with the emergency of the Smart Home concept.
However, in many cases, the research carried out for Smart Home systems has been
focusing more on the technical possibilities without little or no consideration of the
social aspects or the actual needs of the potential user (Harper, 2003). As a
consequence, Smart Home solutions are mostly appealing only to DIY enthusiast and
hobbyists and seem to be stuck in the Early Adopter phase of Rogers Technology
Adoption Lifecycle.
Figure 6 Rogers Technology Adoption Lifecycle3
A survey carried out for the UK-based Joseph Rowntree Foundation in 2000 reported
that we may be very close to a change of attitude whereby Smart Home technologies
may soon become more popular and widespread. According to the research, 59 per
cent of the people interviewed stated their interest for a technology that would save
time and effort in their home, though it also outlined concerns about how complicate
this technology might still be to operate (46%). As perhaps expected, the demographics
outlined that young people would be more in favour of such technology than elderly
people, due their degree of familiarity with game console and computers (Pragnell et
al., 2000). However, this generation will soon become the decision-maker for these
systems in the near future.
A similar study identifies other types of users who could benefit from this technology.
The relatively recent concept of teleworking opens new opportunities for executives
3 Courtesy of Wikipedia: http://en.wikipedia.org/wiki/File:DiffusionOfInnovation.png
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and professionals to work from home. These individuals will spend more time at home
and may be more interested in taking advantage of the potential benefits that this
technology can offer. Moreover, as population in the western world becomes older,
households with members over 65 will substantially rise in the next years. Another
research reported how the installation of digital control and communication systems, as
part of a fully integrated Smart Home system, can enhance important health and
support services, improve independence, and overcome isolation for this category of
people (Gann et al., 1999).
Finally, another research points out that busy households, that is a family with children
and both parents working, could themselves become adopter of Smart Home services.
Dual-income families represent already almost half of the total in the US and these
families often live a very structured life with almost no un-scheduled time. The
potential time-saving features that a Smart Home can provide will help to maintain a
sense of control and relieve some of the stress associated with running the household
(Kyung Lee et al., 2008).
3.3.1. PotentialBenefits
Although features offered by a Smart Home may vary, an effective implementation can
bring several potential benefits. Childrens needs and busy days prevent families from
having enough spare time and a Smart Home may make everyday life at home easier
for its inhabitants (Harper, 2003). The ability to monitor and control all the devices in
the house from a central location can introduce time-saving benefits. Furthermore, over
half (59%) of the participant of a recent survey reported that they would welcome a
new technology that would save time and effort in their homes (Pragnell et al., 2000).
Furthermore, such gain can be sensibly expanded with applications that offer
opportunities to group stand-alone operations into logical macro tasks. For example,
the turning on of a DVD player could automatically operate the TV and either dim the
lights in the room or lower the window blinds to obtain the optimal light level.
Going further, an effective Smart Home system may be able to make complex decisions
that are likely beyond the technical expertise of the inhabitants of the house: for
example, an expert system built into a Smart Home system could contain a detailed
knowledge of thermal systems, of human physiology, and of the HVAC system
installed in the house and being able determine the optimal choice of temperature and
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humidity based on the information received by thermometers and humidity sensors
located inside and outside the house (Greyson, 1991).
Modern technology is already changing the home as an increasingly larger number of
appliances come with embedded computing capabilities. Smart Homes of the future
will be able to integrate all heating, air conditioning, lighting, home entertainment, and
security systems together. Although safety, security, and centralized control are
currently what potential users expressed as the most interesting (Pragnell et al., 2000),
the result of this integration, combined with modern networking technology, will open
new possibilities and the creation of additional services that might not exist today.
Table 1 represents possible areas where Smart Home technology can already help today
(Green et al., 2004).
Table 1 Examples of Smart Home Applications
AREA EXAMPLES
Welfare Health and monitoring; remote diagnosis; remote personal trainer.
Entertainment Music television and video downloading.
Environment Remote control of lighting, heating/air-conditioning; energy usage and
costs.
Safety Alerting of problems e.g. gas leaks, CO.
Communication Video phone; calendar reminders; communication inside and outside
home.
Appliances Self-diagnosis or problems and assistance in their operations; automated
food ordering.
Linking the home network to the outside world via the Internet connection opens up the
possibility for the a Smart Home to also be managed remotely, e.g. when at work or
away on holiday. This option could also be extended to authorized third parties, such
as electricity or gas utilities, who can run routine maintenance or troubleshooting tasks
remotely or on behalf of the house owner.
Studies demonstrated how mobile phones and Short Message Service (SMS) messages
have become a popular way to keep in touch and how this can increase the sense of
safety and connectedness among family members (Harper, 2003). These benefits may
be further expanded by integrating this mobile communication network, now composed
also by other devices such as Personal Digital Assistance (PDA) and hand-held
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computers, with components of Smart Home systems and with the Internet itself. For
example, family members may be able to leave notes to each other and making or
changing appointments with ease. According to the same study, this network society
will enable always-on, real-time communication, bring people closer, and could
concretely add to family communication as a means of organizing daily living as Smart
Home might become: the gate to a new kind of collectivity (Harper, 2003).
Finally, Smart Home technology can increase the quality and facilitate the life of
elderly people or people with disabilities. Todays digital controls and communication
systems can already allow enable health and support services personnel (telecarer) to
carry out routine diagnostics, monitoring and basic services whilst allowing the person
to remain comfortably at home.
3.3.2. ReportedNeedsandConcerns
The same researches carried out on Smart Home technologies also raised some
concerns. Regardless of the technical edge provided by one particular technology over
another, addressing such concerns will play a pivotal role to ensure the buy-in to the
Smart Home concept by the majority of consumer market.
The survey carried out in 2000 for the Joseph Rowntree Foundation (UK) unveiled
some interesting findings, where the most significant concerns were the fear of
technical issues that would cause the system to stop functioning or perform unintended
(unwanted?) operations, and users who may be intimidated by a system too complex to
be used effectively or who would be unable to take back control of the system (Pragnell
et al., 2000).
Similar findings were outlined by a 2002s survey carried out by the Digital Media
Institute of Tampere University of Technology (Finland). In addition, the research
showed that people are traditional when it comes to their daily routines and working on
household chores and might at times decide to carry out these tasks themselves.
Furthermore, people will have different opinions on what is enjoyable and what is not:
for example, a person might like to cook but hates dusting, another might hate ironing
but likes hovering so the system should be able to cope with these preferences too.
Finally, although basic daily routines may be the same across households, the way to
perform them may vary from household to household and from individual to individual
(Koshela et al., 2004).
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Often, peoples vision of technology is tainted by reservations and fears, not only in
science fiction movies terms, such as that the house might start living a life of its
own, but also a concern connected to very real situations, such as not being able to
turn a device off. Smart Home systems encompass complex socio-cultural aspects that
strongly relate with the concept of home and, as such, can evoke strong feelings and
emotions. It is also interesting to note how some participants feared that technology
would actually reduce the amount of communication, though it was acknowledged at
the same time that communication between family members has improved with the
usage of mobile phones.
Other concerns identified were the worry of being constantly on line and general
security issues, with one of the participants being worried about the possibility of their
microwave being operated by an outsider without them knowing about it (Harper,
2003).
The use of this technology also raises many ethical questions, such as how to protect
the privacy for such items as remote access and allowed level of surveillance for
telecarer. (Gann et al., 1999).
Another research conducted in 2003 in US and Korea outlined the importance for a new
technology to be compatible with existing devices, to be customizable, and provide
improvements on communication methods (e.g. support for wireless technology).
Accessibility features and centralized entertainment resources were also being of high
interest, though dedicated devices for stand-alone appliances were preferred to multi-
function devices controlling several of them (Chung et al., 2003).
A research conducted in 2004 outlined the following themes as being the major
concerns for the participants: costs, system reliability, security and privacy concerns,
ease of use, flexibility, convenience, maintaining independence, expandability with
future technologies, and ability for the users to take control when required (Green et al.,
2004).
Finally, the research conducted by Tampere University of Technology in 2004, which
also prototyped different user interfaces, reported the appreciation of having a mobile
device when interacting with the system rather than a fixed one, such as the TV set.
From this study, further requirements emerged, such as having a way to record pre-
defined actions at a certain time and day in advance (pattern control), whilst at the
same time provide users with the ability to act on a device immediately (instant
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control). The study also highlighted the confusion that might occur when multiple
users operate the same device, e.g. a light, or that a user might not be aware of a pattern
control set by another user (Koskela et al., 2004)
Finally, the nature of the home is quite dynamic and the type, level of information and
interaction required by its inhabitants change throughout the day (Chung et al., 2003).
Smart Home systems will need to maintain a profile of its users in order to keep track
of their needs, preferences, and how these can change throughout time.
3.4. DesignChallenges
In addition to the needs and concerns expressed above, Smart Home systems provide
several design challenges.
30 years in the making, Smart Home technologies do not yet seem to have reached
most of potential users. D. Gann (1999) in his research, reported five reasons for this
slow growth and, though few years have gone by since these findings, todays situation
does not seem to have improved significantly in any of these areas:
Poor understanding of user needs Users lack of understanding about potential benefits Difficulties in installing and integrating solutions into existing households Immature technology, causing defects, rapid obsolescence and upgradeability
issues
Costs.
Whilst some of these design challenges are beyond the scope of this project, others can
be investigated and expanded further in this paper. For example, it is certainly possible
to gain a better understanding of the users needs and, by doing so, have a better chance
to develop solutions that are useful, usable, and used (Dix et al., 2004). Furthermore,
it may be possible to choose technologies that are more reliable, less disruptive, more
supported and upgradeable than others and that should provide a better chance to be a
sound investment from the users point of view.
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3.4.1. GatheringValidSystemRequirements
The true potential of Smart Homes can only be unleashed with a user-centric approach.
One of the challenges often reported by the current literature on the subject is that
designers of Smart Home solutions seem to be more focused on the technical part of the
solution and often ignore what customers might actually want the product to do. In
some cases, this resulted in making available technically valid products for which very
few customers were interested in. The techniques described in this section can help
bridge this gap and will be used later on when documenting the system requirements
for this project as gathering unambiguous and detailed software requirements is a vital
part of any software development endeavour. K. Wiegers (2003) states that not
dedicating enough time to properly document requirements for a system usually leads
to at least one of the following:
Unusable product Poor product quality Dissatisfied customers Wasted time and rework Project overruns (time, costs) Gold-plating (adding of unnecessary features)
Wiegers suggests that software requirements can be subdivided into three main
sections: user requirements, business requirements, and functional requirements. Figure
7 provides a visual representation of the major components of all system requirements
and their relations (Wiegers, 2003).
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Figure 7 Components of Software Requirements
Business requirements are documented in the vision and scope document of the project,
whilst functional requirements are usually formally recorded in software requirements
specification (SRS) documents. These formal documents describe, in as much detail as
possible, the expected behavior of the system and often also outline non-functional
requirements such expected quality standards, regulations and other constraints.
User requirements, sometimes also called Voice of the Customer, describe the system
as a set of tasks that the user must be able to accomplish with the product.
Unfortunately, gathering these requirements is seldom an activity that will result in a
well-ordered list of detailed needs and it will often require refining steps and
subdividing the input provided into different categories as a better understanding is
gained. Table 2 outlines how the Voice of the Customer can be further subdivided into
nine requirement categories and provides a brief description of each one (Wiegers,
2003). These requirements are documented, expanded, and confirmed using Use Case
diagrams, which describe a single instance of usage of the system and outline the
relationship between users (actors) and tasks (use cases) to be performed.
Table 2 Classifying the Voice of the Customer
Business Requirements Any business benefit that either customers or the developing organization wish to gain from the product.
Use Cases General statements of user goals or business tasks that users
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need to perform.
Business Rules Rules that states which users can perform a specific activity and under which specific conditions. These rules will need to be captured in the software functional requirements and enforced by the system.
Access control is a typical business rule in most of computer systems.
Functional Requirements
Description of observable behaviors that the system will exhibit under certain conditions and descriptions of actions the system will let users take.
They are derived from system requirements, user requirements, business rules, and other sources.
Quality Attributes Qualitative statements are modifiers that will indicate how a task needs to be performed.
Some examples of these statements are: fast, easy, intuitive, user-friendly, robust, reliable, secure, and efficient.
External Interface Requirements
How the system needs to connect to other systems or, generally, to the outside world.
Constraints Constraints restrict the options available to the developer. For example, constraints such as size, weight, and interface connections.
Data Definitions The format, data type, allowed values, or default value for a data
These requirements are usually collected in a data dictionary that will serve as reference for the project team.
Solution Ideas A description of a desired way to interact with the system to perform a particular task.
Most of user requirements usually fit in this category.
The list below, again adapted from K. Wiegers (2003), defines the major steps that
should be carried when documenting requirements for a software project:
1. Identify Business Requirements
2. Identify users of the software
3. Gather User Requirements
4. Define Use Case scenarios
5. Gather Functional Requirements
6. Subdivide system-level requirements into major subsystems and match
requirements to software components
7. Define implementation priorities
8. Review use cases against original requirements to ensure correctness.
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In addition to this, contrarily to the typical software design where the user base can be
quite homogenous, users of a Smart Home are far less so, ranging from children, to
adults, to elderly people. This poses the challenge to define a user interface that can be
versatile enough to be effective with every user of the system. (Ringbauer et al., 2003).
In order to better address this, one of the techniques that can be used is the creation of
different personas, i.e. virtual users, to try and represent these differences. Most of the
times, personas take the form of fictional characters, who are though provided with
enough real-life details so that developers will be able to relate to them when discussing
a particular requirement or feature of the product e.g. John would never use that
feature this way. Using personas will also increase the developers connection with a
real user, instead of abstractions, while designing the system (Courage & Baxter, 2005).
3.4.2. ChoosingtheRightTechnology
Advancements in networking in 1980s and 1990s allowed home computer networks to
become a reality. However, though several alternatives emerged, none of these have yet
managed to establish themselves as de-facto standards in the industry. This has affected
the consumer industry, which had been delaying the adoption of Smart Home-enabling
technology in their products, worrying that they may invest in the wrong technology.
Already, some of these network protocols have since been abandoned due to lack of
profitability. From the end-users point of view too, as the home network is a vital part
of any Smart Home solutions, the risk is that by siding with the wrong technology you
would soon end up with a system that might no longer be expandable or even supported
tomorrow.
The good news is that these concerns are starting to be addressed as consolidation
seems to be occurring, at least in Europe and some major players are emerging. Konnex
(KNX), for example, represents the convergence of three previous European standards:
the European Home Systems Protocol (EHS), BatiBUS, and the European Installation
Bus (EIB). These consolidation efforts will create viable platforms that can then be
picked by producers of electronic and electrical home appliances to introduce smart
features in their devices (Wacks, 2002). With a proper economy of scale, development
and implementation costs should also be driven down, making these solutions more
appealing to consumers.
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The building industry is part of this challenge too. As very few new residential
dwellings are built to natively support the Smart Home, e.g. by installing twister-pair
cabling, most of todays Smart Home systems will be installed in existing houses. In
order to ensure ease of installation and minimize costs, it will not be feasible for the
average user to run new cabling that would support a twisted-pair home network. By
excluding Busline technology, Smart Homes will need to be implemented with either
Wireless or Powerline communication. As Wireless is still expensive, Powerline, that
is technology that use of the existing electrical network to operate, seems the only truly
viable alternative. The issue here is that most of the protocols that use this type of
communication are quite old, can be unreliable, and are quite limited in terms of
bandwidth. Some of the drawbacks of X10, the most common Powerline
communication protocol, have been outlined by a recent research: sluggish response
times especially over longer distances, bandwidth limitations, the increase in costs
due to need of amplifiers and filters required to boost reliability, lack of connection to
external network resources, and performance impact in electrically noisy environments
(Chunduru & Subramanian, 2006).
Concluding, although it seems that when choosing the communication protocol for a
Smart Home solution, there are several alternatives, when these are evaluated against
parameters such as ease of integration, reliability, support, compatibility, long-term
investment, and, ultimately, costs, these options may become fewer.
3.4.3. TheQuestfortheEffectiveUserInterface
Human-Computer Interaction (HCI) is a technical field that studies the interactions and
the relationships between humans and computers (Fischer, 2001). Most of the HCI
research can employ several years before it materializes into an available off-the-shelf
product. The idea behind todays point-and-click graphical interfaces was first
demonstrated in 1963, while, at around the same time, Douglas C. Engelbart was
developing the first mouse at Stanford Research Laboratory, carved in wood and
initially intended to be a cheaper replacement for light pens. Commercial systems that
used direct manipulation of objects using the concept of a desktop were not available
since the 1980s, with the Xerox Star (1981) and the Apple Lisa the following year
(Myers et al. 1998, Dix et al., 2004).
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Recently, the HCI focus has shifted from studying computer interfaces into the way
people use computers in a more general sense; that is, how people and computers can
collaborate together to achieve the users goal. One of main areas of HCI research is
about the concept of usability of systems, which can be approached from two
perspectives. The early area of focus was the emulation approach, where the computer
is programmed to exhibit human-like abilities, e.g. computers greeting their user with
How can I help you today?. More recently, the research shifted towards exploring a
complementing approach, which can better leverage on the difference between humans
and computers and can open up to new interaction and collaboration possibilities
(Fischer, 2001).
Usability requirements are influenced by the complexity of the system being designed.
An Automated Teller Machine (ATM) is an example of a simple system with a few
basic functions and which needs to be understood by users with little or no prior
knowledge of the system. At the other end of the spectrum, a high-functionality
application (HFA) is a complex system that requires users to learn the intricacies of its
interface and functionalities before they can become proficient with it. However, HFAs
can perform a richer variety of functions than simple applications, hence they can assist
users with resolving more complex problems. An example of a HFA is Adobe
PhotoShop, the leading application for editing digital images, which literally contains
hundreds of functions, each one with several settings and subtle nuances.
In todays applications, there seem to be an inversed proportion between the usefulness
of a system (i.e. its complexity), and its usability (i.e. how user-friendly the user
interface is). However, as costs of hardware keep falling, cognitive costs, that is the
costs involved in learning a system, will represent an increasingly higher part of the
total cost of ownership (TCO). This calls for proper HCI techniques that will help
maintaining an appropriate level of usability whilst providing the ability of adding more
features. When dealing with usability of a system, developers of user interfaces will
need to make generic assumptions about the users knowledge in order to find the right
balance between beginner and expert users and reach a compromise that can work with
both these extremes. The challenge is that, when making this choice, there is always a
risk to either leave novice users without the required help or to create a system that gets
in the way more than the necessary with more experienced user.
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Todays Windows, Icons, Menus and Pointers (WIMP) interfaces have exacerbated this
challenge even further (Dix et al., 2004). Older, text-based interfaces provided a clear,
explicit communication channel between user and the machine. Where the user was
presented with a prompt they could enter only one command at any time and this
command was to be picked from a well-defined list constrained by the current context.
Modern multi-modal graphical interfaces allow users to impart instructions via multiple
input devices (e.g. a keyboard and a mouse) in a less constrained sequence and within a
wider context. This new level of interaction has created the possibility for multiple
implicit communication channels. This extra level of complexity often requires the
system (and developers) to gain a wider understanding of multiple areas:
Users knowledge of the system Users goals and how they can be mapped against the systems primitive
operations
Understanding of the communication processes and which communication channel is more appropriate to use in relation to the above
Instructional strategies, based on pedagogical theories that can exploit the knowledge contained in the system to the benefit of the user.
Figure 8 provides a graphical representation of implicit and explicit channels (Fischer,
2001).
Figure 8 Implicit and Explicit Communication Channels
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In truth, recent progresses in this area have made systems easier to learn and to interact
with: context-sensitive help systems, today present in almost the totality of systems, is a
direct product of this research. The challenge here is to be able to infer correctly what
tasks will actualize the users goal without being intrusive. For example, potential users
of a Smart Home system tend to assume that such system should have voice recognition
capabilities but natural speech interfaces are still far from perfect and still cause
unintended operations (Koskela et al., 2004).
Future success of new computer systems will be less judged on factors such as
processing speed or the amount of memory available and more on the ability to interact
effectively with users, regardless of their current knowledge of the system.
3.4.4. TheRoleofArtificialIntelligence
As per other computer systems, the factors that will influence the success of a Smart
Home product are not purely technical. The challenge lies in how to make an intuitive
system powerful yet still intuitive to use in order to provide real value for its users.
Artificial Intelligence (AI) techniques can provide a positive contribution towards
resolving such challenges. To successfully resolve the speech recognition problem
presented in the previous section, for example, will require systems with the ability to
provide syntactic analysis, semantic recognition, along with some pragmatic analysis
(Greyson, 1991).
Moreover, Smart Home system will need to be able to adapt to a changing environment
and to multiple users. In this context, the best user interface is the one that requires the
least amount of user interaction; that is, the system should be able to correctly
understand the users need using a probabilistic approach coupled with other factors
such as knowledge of past events and users preferences. With this knowledge, a Smart
Home system will then be able to perform some of the required tasks autonomously. An
AI field of research that can work towards this goal is the studies done on Bayesian
Networks. Bayesian Networks (BN), also known as belief networks, knowledge maps
or probabilistic causal networks, provide a method of reasoning using probabilities and
have already been applied successfully to problems in medical diagnosis, whose results
are often more accurate than an expert diagnosis (Charniak, 1991). A BN tree is a
graphical representations of probabilistic relationships among variables of a system that
may influence the probability for a given event to occur. It represents a graph which
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includes a set of nodes, representing the variables, connecting lines (edges or arcs),
which display their inter-relations between hypothesis and variables, and associated
probability values for all the edges. By using this method, one can reason and calculate
the likelihood for an event to occur. E. Charniak (1991) illustrates a BN with a simple
example: we want to know whether our family is home when deciding what door to use
when enter the house. For arguments sake, let us say that the most convenient door
would be doubly locked if nobody is home. Since this door will require more fumbling
with its keys in order to be opened, we may decide to go for the other one instead, once
we have sufficient reason to believe that this would indeed be the case. The BN tree
will use the expert knowledge embedded in the relationships among the nodes to
calculate the likelihood of the family being out. So, if nobody is home, the dog is
usually put out in the backyard and the porch light is usually turned on. If the dog is
out, we would know it because we could hear its barking. However, when the dog has
bowel problems, it will also be put out. The BN provides a way to weigh these
variables and determine the likelihood of the family being out. Figure 9 provides a
graphical representation of the sentences given above in the form of a causal graph
(Charniak, 1991). From this graph, we can draw the following general hypothesis: if
dog-out and light-on then family-out is likely to be true. However, if dog-out the bowel-problem hypothesis could also be true. The arcs in the BN tree will tell what nodes (also called variables) influence others. In this case, the dog-out node is said to have a direct causal connection on hear-bark so that, if hear-bark is true, then dog-out is more likely to be true. However, if light-on is true, it will tell us nothing more about dog-out as these variables do not have a direct causal connection between each other. Furthermore, light-on will not influence the likelihood of the bowel-problem event in any way.
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Figure 9 Causal Graph
It is important to understand that BN cannot provide absolutes but always return a
degree of confidence (probability) for the given hypothesis. To refer back to the
example, the family might sometimes forget to turn on the porch light or to leave the
dog out when leaving the house. Figure 10 expands the causal graph by adding the
probability values given for all the BN nodes. These values are usually gathered by
direct observation, from historical data (also known as cases) or from information
gathered via expert knowledge. So, let us say that when the family leaves the house,
someone remembers to turn the porch light most of the times (60%), but that there is a
smaller (5%) chance that the light is on even when people are in the house, say when a
guest is expected. The first is represented as P(lo|fo)=0.6, which reads: the likelihood (P) that light-on (lo) and family-out (fo) equals to 60% (0.6). Conversely, the second case is represented by P(lo|fo)=0.05; that is, the likelihood (P) that light-on (lo) but not family-out (fo) equals to 5% (0.05). Once all the probabilities are provided, the BN tree is used to validate the hypothesis for which is was created
(e.g. to resolve the family-out scenario).
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Figure 10 Bayesian Network
A practical example of how BN can be used to infer the users goal is Project Lumire.
Started in 1993 by Microsoft Research Labs, the project investigated how BN trees
could be used to help users of a computer system. The model built tried to infer a
users goals based on their past and current actions and on their supposed knowledge of
the system. The system would then propose tasks that should have helped the user to
reach his/her goal. A short videoxx, available from Microsoft, shows a live
demonstration of the prototype. The findings of this project were eventually used to
develop the Office Assistant in the Microsoft Office 97 suite (Horvitz et al., 1998).
Smart Home systems can benefit from BN models. For example, a reasoning
framework will greatly facilitate any event-condition-action scenario that contains
uncertain or incomplete knowledge (Dimitrov et al., 2007). A problem domain where
BN models can be employed is the detection of a dangerous situations. Such a
probabilistic model would be able to identify anomalous or dangerous situations, e.g. a
person falling, by continuously gathering evidence considering whether the information
increases the likelihood of the event beyond a threshold that would trigger the alarm
(Cucchiara et al., 2003).
3.4.5. GoingBeyondHomeAutomation
Very few of todays off-the-shelf products go much farther than providing basic home
automation functionalities. Despite the abundance of electrical and electronic devices,
little effort has been placed to try and connect these devices in a meaningful way that
will add value to the users. The number of remote controls that are still required today
in an average home media center would serve a good example for such lack of
integration. However, an effective Smart Home should also be able to infer the goal
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intended by the user and to carry out (or propose to the user) tasks that will help
reaching the goal, thus adding value from a users point of view.
Smart Homes can successfully implement the idea of ubiquitous computing. Earlier
definitions of ubiquitous computing simply focused on making devices so small to be
hidden from the users view, what is called perceptual visibility. Rather than merely
focusing on size alone, a more recent definition of ubiquitous computing outlines the
computers ability to become integrated with the users goal