Development of Smarthome application for remote access to a ZigBee Network By: Neil Higginbotham  Supervisor: Dr. Fred Jap...
Project Goals <ul><li>Smarthome application communicates with smart objects in the home </li></ul><ul><li>The Smarthome ap...
Research <ul><li>ACHE (Adaptive Control of Home Environment) </li></ul><ul><ul><li>One is anticipation of inhabitants’ nee...
Research <ul><li>Georgia Institute of Technology - The Aware Home </li></ul><ul><ul><li>“ The research interests assembled...
Technology <ul><li>ZigBee in a set of high level protocol based on the IEEE 802.15.4-2006 specifications. </li></ul><ul><l...
Methodology <ul><li>Incremental  Methodology   </li></ul><ul><ul><li>Generates working software quickly </li></ul></ul><ul...
Design – Three Tire & Distributed
Implementation <ul><li>Familiarise with ZigBee node firmware </li></ul><ul><li>Modify functions for applications </li></ul...
Is the  Smarthome smart? <ul><li>Any type of software which has the ability to change the state of a device can be discred...
Machine Learning <ul><li>” Discipline concerned with the development of software algorithms that as a result of exposure t...
Machine Learning – Decision Tree <ul><li>Generates a set of rule for the system </li></ul><ul><ul><li>If day =Friday and t...
Machine Learning – Naïve Bayes <ul><li>Nave Bayes works on the probability of an event happening based on some other value...
Conclusion <ul><li>Conclusion </li></ul><ul><ul><li>Successful implementation </li></ul></ul><ul><ul><li>ZigBee node very ...
References  <ul><li>[1]   Gregory D. Abowd Christopher G. tkeson Irfan A. Essa Blair MacIntyre Elizabeth Mynatt Thad E. St...
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  • Smarthome Presentation

    1. 1. Development of Smarthome application for remote access to a ZigBee Network By: Neil Higginbotham Supervisor: Dr. Fred Japhet Mtenzi
    2. 2. Project Goals <ul><li>Smarthome application communicates with smart objects in the home </li></ul><ul><li>The Smarthome application will exist on a Linux box or Windows Pc and can access the ZigBee network </li></ul><ul><li>Devices can be switched on and off if needed, and configured </li></ul><ul><li>Smarthome application should be used for making a home more efficient </li></ul><ul><li>Services to monitor the use of resources </li></ul>
    3. 3. Research <ul><li>ACHE (Adaptive Control of Home Environment) </li></ul><ul><ul><li>One is anticipation of inhabitants’ needs. Lighting, air temperature, and ventilation </li></ul></ul><ul><ul><li>The second objective of ACHE is energy conservation </li></ul></ul><ul><li>The MIT (Massachusetts Institution of Technology) House n Consortium and TIAX, LLC have developed the PlaceLab </li></ul><ul><ul><li>PlaceLab - This initiative is being used to research human interaction within the home </li></ul></ul><ul><ul><li>The Smart Home vs. Smart people by Stephen S Intille </li></ul></ul><ul><ul><li>Just-in-Time information by Stephen S Intille </li></ul></ul>
    4. 4. Research <ul><li>Georgia Institute of Technology - The Aware Home </li></ul><ul><ul><li>“ The research interests assembled to work on this project cover a wide spectrum. </li></ul></ul><ul><ul><li>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].” </li></ul></ul>
    5. 5. Technology <ul><li>ZigBee in a set of high level protocol based on the IEEE 802.15.4-2006 specifications. </li></ul><ul><li>The JavaSE APIs resemble building block and allow the user to customise an application. This application runs in a Virtual Environment allowing portability. </li></ul>
    6. 6. Methodology <ul><li>Incremental Methodology </li></ul><ul><ul><li>Generates working software quickly </li></ul></ul><ul><ul><li>More flexible </li></ul></ul><ul><ul><li>Easier to manage risk </li></ul></ul><ul><li>Incremental Stages </li></ul><ul><ul><li>Smarthome prototype – using streams </li></ul></ul><ul><ul><li>ZigBee coordinator to terminal – communication of sensor values </li></ul></ul><ul><ul><li>ZigBee to Java Class – communication of sensor values </li></ul></ul><ul><ul><li>Smarthome prototype two – Java RMI </li></ul></ul><ul><ul><li>Smarthome Client Interface </li></ul></ul><ul><ul><li>ZigBee to Java Class – changing states. </li></ul></ul>
    7. 7. Design – Three Tire & Distributed
    8. 8. Implementation <ul><li>Familiarise with ZigBee node firmware </li></ul><ul><li>Modify functions for applications </li></ul><ul><li>Test communication with HyperTerminal and Mincom with coordinator </li></ul><ul><li>Create classes to communicate with coordinator </li></ul><ul><li>Java RMI for Smart server </li></ul><ul><li>Java Interfaces – JFrameBuilder </li></ul>
    9. 9. Is the Smarthome smart? <ul><li>Any type of software which has the ability to change the state of a device can be discredited as being smart. </li></ul><ul><li>Is the setting of temperature threshold smart? </li></ul><ul><li>An IF statement that invokes some function when the conditions are met, is that smart? </li></ul><ul><li>The user can change these thresholds, so they are effectively in full control of the application. </li></ul><ul><li>This is not Smart! </li></ul>
    10. 10. Machine Learning <ul><li>” 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].” </li></ul><ul><li>Classifier: Decision Tree </li></ul><ul><li>Classifier: Naïve Bayes </li></ul>
    11. 11. Machine Learning – Decision Tree <ul><li>Generates a set of rule for the system </li></ul><ul><ul><li>If day =Friday and time = 4am and temperature = t<26 and window = closed then = on </li></ul></ul><ul><ul><li>If day = Friday and time = 4am and temperature = t>26 and window = closed then = off </li></ul></ul>
    12. 12. Machine Learning – Naïve Bayes <ul><li>Nave Bayes works on the probability of an event happening based on some other value occurring. </li></ul><ul><ul><li>P(h|X) = probability of h being true after we have been the observed data x </li></ul></ul><ul><ul><li>P (on) = (Day x Hour x Temp x Window) x On = .062 </li></ul></ul><ul><ul><li>P (off) = (Day x Hour x Temp x Window) x Off = .056 </li></ul></ul><ul><ul><li>The probability of On is higher </li></ul></ul><ul><li>The two classifiers can produce models that can be imported into application as a serialised object. </li></ul>
    13. 13. Conclusion <ul><li>Conclusion </li></ul><ul><ul><li>Successful implementation </li></ul></ul><ul><ul><li>ZigBee node very flexible and recommended for further research </li></ul></ul><ul><ul><li>Serial connection challenge must be addressed </li></ul></ul><ul><ul><li>A different approach to address challenges with smartness of application </li></ul></ul><ul><li>Future Work </li></ul><ul><ul><li>ZigBee Node – Firmware for longer use </li></ul></ul><ul><ul><li>Serial Connection </li></ul></ul><ul><ul><li>J2ME – Java RMI package </li></ul></ul><ul><ul><li>Machine Learning – Other classifiers and integration </li></ul></ul><ul><ul><li>Look at intelligent agents </li></ul></ul>
    14. 14. References <ul><li>[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. </li></ul><ul><li>[2]http://www.gisdevelopment.net/proceedings/mapmiddleeast/2006/land%20administration/images/mme06044_2.jpg </li></ul>

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