IJCATR Volume 5 Issue 5

Energy Conservation in a Smart Home via an Embedded Platform

Rahul Sivaram Shashank Kumar Sahil Budhwani Vikash Kumar
10.7753/IJCATR0505.1002
keywords : Energy Conservation, Embedded Platform, Bayesian Belief Network, Pervasive Computing.

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Home automation is a popular field of application which combines the concepts of embedded systems and pervasive computing to control a living space for modern times. A smart home system aims to free up the user to carry out his or her daily tasks without worrying on the trivial aspects of personal home management, while at the same time providing the user with more control of the home than ever before. The implementation comprises of a large number of sensors which can be used to control or monitor objects distributed in three-dimensional space around the house. The sensors can be specialized in measuring temperature, humidity, pressure, light, noise, dust air, and upon intelligently computed triggers, compel the system to perform a specific task, or a set of tasks. In this project, a solution to transform a normal house into a smart, autonomous house in order to reduce the energy consumption of the household is proposed. This can be realized with the help of wired sensor networks where we control and interface with electronic appliances via a Raspberry Pi, an embedded development platform. The embedded platform can be controlled remotely to turn switches on and off, and eventually aims to become as autonomous as possible via the help of a Bayesian Network. The base workings of the project are aimed at being as scalable as possible, to be able to potentially fit into industrial as well as office environments in the future.
@artical{ 552016ijcatr05051002,
Title = "Energy Conservation in a Smart Home via an Embedded Platform",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "5",
Issue ="5",
Pages ="241 - 244",
Year = "2016",
Authors =" Rahul Sivaram Shashank Kumar Sahil Budhwani Vikash Kumar "}
  • Study and attempt to model usage patterns of appliances and machines.
  • Determine optimal methods of eHCI and iHCI.
  • Determine environmental benefits, particularly cost reductions in energy usage due to autonomous automation of appliances and machines.
  • Simulate and observe the interconnectivity of Bayesian network models for different appliances and machines.