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.
The research project "Low Energy Living" pursues the aim to create a techno-economic system to increase the energy efficiency in a network of lodgers, housing societies and providers (for example of electric power, thermal energy, natural gas or water). The necessary cross-linking and the use of different housing technologies like smart meters, heating and security installations for building automation with housekeeping and multimedia equipment is called intelligent living or, to be precise, smart home. These applications are connected and regulated by the established EIB/KNX field bus via electric cables, radio, double wire line or Ethernet. The technological basis for smart homes was developed to a great extent recently and is available at the market. Nevertheless, the potentials of these technologies aren't utilized to the full. Currently the housing technology and automation is deployed in commercial and public used large-scale buildings. In contrast to this the utilization of modern building technology in the living area is just at the beginning. For this reason, the target is to integrate intelligent building bus engineering and their automation on the basis of a demonstration object.
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