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Interactive Energy Consumption Monitoring with the Use of Mobile Devices

Student name: 
Andreas Schmid
Assignment Date: 
May 15, 2011
Completion Date: 
June 15, 2013

Home automation systems that automatically control a variety of appliances, sensors and actuators (e.g., heating, ventilation, air conditioning, lighting, alarm devices, leakage detectors, fire detectors, etc.) in their interaction with users, can offer significant contribution to the comfort and safety of living, pollution reduction, environment protection, and what is getting increasingly important, energy conservation. To achieve an efficient energy management in such user-responsive smart environments, a tight integration among a system that measures the energy consumption, and provides information about the available energy and its cost (known as Smart Metering systems), and the environment automation system, in addition to the user input and the state of the environment and devices, must be established. Energy efficient smart home is characterized with complex interactions between people and devices, and at the higher hierarchical level, it itself is involved in interactions with other energy consumers and energy suppliers, that needs to be supported by modern mobile and Web applications. This thesis project will aim at designing and construction energy efficiency applications (based on the chosen by the student platform: Web, iPhone, Android, Facebook, etc.), for example:

  • Querying and displaying weather, traffic, and energy pricing data on the mobile phone so that the user can make informed decisions which routes to take or which (energy-relevant) services to use remotely, e.g. deciding on switching the washing machine on depending on the current tariff of the user's home, or setting the heating and climate control remotely (before coming home) based on the current weather reports.
  • Reading the user's calendar (for planning ahead in terms of service control, e.g. heating not turning on when the user has an evening appointment in their calendar) or the location (for prediction of home occupancy times) and pushing this data to "the" SESAME-S service in a semantic form so that the policy engine can make use of it for providing recommendations to the user's home control system.
  • Aggregating data from multiple homes and displaying the results on the mobile phone for social network apps ("how does my last month's electricity usage compare to my friend or family usage patterns, when do they spend less/more than I do, and which appliances are the biggest consumers in all homes in my neighbourhood?").
  • Allowing the user to communicate with the SESAME-S system, by e.g. easily sending the meter readings to the system via the mobile phone.

The proposed thesis work will be associated with an FFG project SESAME-S: SEmantic SmArt MEtering – Services for Energy Efficient Houses

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