An Intelligent Cloud-based Home Energy Management System Based on Machine to Machine Communications in Future Energy Environments

Abstract — Recent advances in machine-to-machine communication technologies facilitate location/context-aware home energy management system that can provide predefined services. Such systems can establish the context model about the structural situations and the interrelations between dynamic events and services. These systems also can reason the adaptive services according to the policy construction and user requirements. However, due to their architectural limitations, the recent systems are not so flexible with respect to system scalability and availability. The important issues, such as the enhancement of the personalized service, the energy-aware service prediction of the multi situations, and the scalability of the various service domains, have not been adequately considered in the recent researches. Therefore, this paper proposes an intelligent cloud-based home energy management system (CHEMS), considering these issues. We employ cloud computing methods to deal with problems that the existing systems have. Cloud computing technologies can help the existing HEMS to deal with a large amount of computational and storage resources required to use enormous energy management data effectively. We implemented CHEMS in the test bed and conducted an experiment to verify the efficiency of the proposed system. The results show that the proposed system reduces the service response time up to 39.4 percent. Keywords-cloud computing; home energy management system; machine to machine communications; pattern learning I