Real-time sensing in residential area using IoT technology for finding usage patterns to suggest action plan to conserve energy

To conserve energy in a residential sector, showing action plans how to conserve energy is important. However, we need to consider both energy efficiency and indoor comfort. The usage patterns in the residential sector change according to their life style and some people would try to maintain the indoor comfort at high level even paying high energy cost. It is necessary to understand home energy usage patterns in terms of the relationships between indoor comfort and electricity consumption in order to provide appropriate energy saving action plans to the residential sector. For this purpose, in this study we have collected real time data of electricity consumption and indoor temperature using IoT devices and sensors installed to 13 households for about one month in Summer at Sumida ward in Tokyo, Japan. Then, we have analyzed the data using three types of method, which are a clustering algorism to delineate the electricity usage pattern which characterize the household life style, conducted correlation analysis to look at the relationship between electricity consumption, and the indoor temperature for households living in condominium apartments and detached houses with different building structure and ages.