Neural networks for smart homes and energy-efficiency

Abstract

In a project to reduce energy consumption, the use of technology which helps metering and controlling lifestyle effects is essential. Smart meters and intelligent systems that contribute to environmental arwareness enable private homeowners or tenants to see and actively control their cost of lifestyle. As a part of Smart Home systems neural networks are considered to be of assistance for user-based systems and consumption prediction. The observation of collected data over a period of time offers many opportunities to disvocer potential applications that help optimizing specific tasks. Controlling the target temperature at a specific time of day, based on the habits and preferences of a tenant is one first chosen way to make daily life easier and at the same time make it possible to design Smart homes that compromise between energy-efficieny and personal comfort. For that purpose a neural network is designed and tested under varying premises. The results are promising and the insights will enable future works in following projects.