Development of energy consumption forecasting and autonomous management system in smart house environment

In this research, the architecture solution of energy data monitoring and power device management system is proposed, adapted for the heterogeneous networks. Seeking to ensure such possibility, that the system could respond to the environment not only by providing information about ongoing events, but also by proposing decisions on how to manage the subsystems, existing in the environment. The aim is to develop the autonomous energy forecasting and management system, and to propose its architecture, which would enable the data collection, transmission, analysis and forecasting functions in the mobile and adaptive network topology, seeking for more efficient management of energy consumption. The prototype of autonomous ECMS, enabling to connect the embedded sensor nodes under mobile and adaptive topology network conditions, was developed. •To interconnect the embedded devices (sensors and controllers), the mobile network application layer and communication interface was developed. The results of experimental research with ECMS revealed that the introduction of the task schedule leads to more efficient operation of the energy management system. When the system operates in an autonomous manner, the real-time forecasting-based lighting management algorithm allows to save energy consumption