Smarthome Presentation

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Smarthome Thesis Presentation

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Development of Development of Smarthome application Smarthome application for remote access to a for remote access to a

ZigBee NetworkZigBee Network

By: Neil Higginbotham By: Neil Higginbotham

Supervisor: Dr. Fred Japhet MtenziSupervisor: Dr. Fred Japhet Mtenzi

Project GoalsProject Goals

►Smarthome application communicates with smart objects in the home

►The Smarthome application will exist on a Linux box or Windows Pc and can access the ZigBee network

►Devices can be switched on and off if needed, and configured

►Smarthome application should be used for making a home more efficient

►Services to monitor the use of resources

ResearchResearch

►ACHE (Adaptive Control of Home Environment) One is anticipation of inhabitants’ needs. Lighting, air

temperature, and ventilation The second objective of ACHE is energy conservation

► The MIT (Massachusetts Institution of Technology) House n Consortium and TIAX, LLC have developed the PlaceLab PlaceLab - This initiative is being used to research human

interaction within the home The Smart Home vs. Smart people by Stephen S Intille Just-in-Time information by Stephen S Intille

ResearchResearch

►Georgia Institute of Technology - The Aware Home

“The research interests assembled to work on this project cover a wide spectrum.

These interests include HCI, ubiquitous computing, ethnography, machine learning, computational perception, augmented reality, wearable computing, wireless networking, security, distributed systems, software engineering and sensor technology [1].”

TechnologyTechnology

► ZigBee in a set of high level protocol based on the IEEE 802.15.4-2006 specifications.

► The JavaSE APIs resemble building block and allow the user to customise an application. This application runs in a Virtual Environment allowing portability.

MethodologyMethodology

► Incremental MethodologyMethodology Generates working software quickly More flexible Easier to manage risk

► Incremental Stages Smarthome prototype – using streams ZigBee coordinator to terminal – communication of sensor

values ZigBee to Java Class – communication of sensor values Smarthome prototype two – Java RMI Smarthome Client Interface ZigBee to Java Class – changing states.

Design – Three Tire & Design – Three Tire & DistributedDistributed

ImplementationImplementation

► Familiarise with ZigBee node firmwareFamiliarise with ZigBee node firmware►Modify functions for applicationsModify functions for applications► Test communication with HyperTerminal and Test communication with HyperTerminal and

Mincom with coordinatorMincom with coordinator► Create classes to communicate with Create classes to communicate with

coordinatorcoordinator► Java RMI for Smart serverJava RMI for Smart server► Java Interfaces – JFrameBuilderJava Interfaces – JFrameBuilder

Is the Smarthome smart?Is the Smarthome smart?

►Any type of software which has the ability to change the state of a device can be discredited as being smart.

► Is the setting of temperature threshold smart?►An IF statement that invokes some function

when the conditions are met, is that smart?►The user can change these thresholds, so they

are effectively in full control of the application.►This is not Smart!

Machine LearningMachine Learning► ”Discipline concerned with the development of software algorithms that as

a result of exposure to experiential data, improves their performance at a given task[2].”

► Classifier: Decision Tree► Classifier: Naïve Bayes

Machine Learning – Decision Machine Learning – Decision TreeTree

► Generates a set of rule for the systemGenerates a set of rule for the system

If day =Friday and time = 4am and temperature = t<26 and window = closed then = on

If day = Friday and time = 4am and temperature = t>26 and window = closed then = off

Machine Learning – Naïve Machine Learning – Naïve BayesBayes

►Nave Bayes works on the probability of an event happening based on some other value occurring. P(h|X) = probability of h being true after we have been the

observed data x P (on) = (Day x Hour x Temp x Window) x On = .062 P (off) = (Day x Hour x Temp x Window) x Off = .056 The probability of On is higher

►The two classifiers can produce models that can be imported into application as a serialised object.

ConclusionConclusion

► ConclusionConclusion Successful implementationSuccessful implementation ZigBee node very flexible and recommended for further ZigBee node very flexible and recommended for further

researchresearch Serial connection challenge must be addressedSerial connection challenge must be addressed A different approach to address challenges with smartness A different approach to address challenges with smartness

of applicationof application► Future WorkFuture Work

ZigBee Node – Firmware for longer useZigBee Node – Firmware for longer use Serial ConnectionSerial Connection J2ME – Java RMI packageJ2ME – Java RMI package Machine Learning – Other classifiers and integrationMachine Learning – Other classifiers and integration Look at intelligent agentsLook at intelligent agents

References References

[1][1] Gregory D. Abowd Christopher G. tkeson Irfan A. Essa Blair MacIntyre Elizabeth Mynatt Thad E. Starner Cory D. Kidd, Robert Orr and Wendy Newstetter. The aware home: A living laboratory for ubiquitous computing research. pages 2,3, October 1999.

[2]http://www.gisdevelopment.net/proceedings/mapmiddleeast/2006/land%20administration/images/mme06044_2.jpg