Approaches of user activity detection and a new fuzzy logic-based method to determine the risk amount of user unusual activity in the smart home

In recent years, the number of sick and elderly people that are living alone in their homes and need care has grown. This is why the smart home is needed for the awareness of their condition. Identification of the patient's activity using environment sensors is the first step in implementing a smart home. In such a home, the patient's relatives can leave the patient alone with less concern. In this research, various methods of recognizing user’s activity in the smart home are presented, and then a new method is introduced to diagnose the risk amount of Alzheimer's patients in which fuzzy-logic is used in cases such as start-up time of the activity. This system uses fuzzy logic in three phases. Since this method is considered for specific patients, the wearing sensors are not used because they have difficulties for the elderly and even an Alzheimer's patient may forget to wear them. However, the implementation of this layer also achieved good results, i.e., 84% accuracy.