Energy demand for household appliances in smart homes is nowadays becoming a serious challenge, due to economic and environmental reasons. Effective automated approaches must therefore take into account basic information about users, such as the prediction of their daily activities. User activity and behavior is considered as a key element and has long been used for control of various devices such as artificial light, heating, and air conditioning. Our approach aims at recognizing daily living activities of residents inside the home by simply relying on the analysis of environmental sensory data to minimize peak of energy consumption and thereby guaranteeing that maximum demands do not exceed a given threshold.
Keywords: Activity Recognition, Sensor, Automation, RFID, Arduino, Energy Management, Intelligent Building