Partly due to the difficulties in programming, home automation has never become a widely available and accepted technology. In contrast to standard computerized homes that can be programmed to perform various functions, the crux of our project is to develop a home that essentially programs itself by observing the lifestyle and desires of the inhabitants, and learning to anticipate and accommodate their needs. If the actions can be reliably anticipated, the system can perform the actions automatically, freeing the occupants from manual control of the home. A secondary consideration of the system is to conserve energy resources, when possible. Control systems in the residence are based on neural network reinforcement learning and prediction techniques.
Neural networks are artificial learning devices inspired by the workings of the human brain.
These networks are made up of hundreds or thousands of simple neuron-like processing units, which, through their interactions, achieve complex behaviors, and have the ability to learn from experience. By inferring ocupancy and usage patterns in the home, the system can make life more comfortable and conserve energy at the same time.