Smart Home Electricity Demand Forecasting System Based on Edge Computing

As the development of the Internet of Things, many terminal devices are continually intelligent. However, with the increase of distributed terminal equipment and the diversification of business, cloud computing technology cannot meet the needs of smart home. In consideration of the advantages of edge computing and the demand of smart home, this paper proposes an smart home electricity demand forecasting system based on Edge Computing with a short-term (24-steps) electricity demand forecasting. Our system utilizes intelligent home gateway to store heterogeneous data into a central repository where it will be processed and analyzed, and these analyzed data would then be used for forecasting local bundled resident electricity demand mainly at intelligent home gateway by acting as a local computing unit to provide edge computing service for residents. Besides, our system can also report the historical and real-time environmental data (indoor and outdoor) and electric data from intelligent home gateway. The experimental results demonstrate our system can provide better service quality and scalability with limited computing resources compared with simply using cloud computing system only.