Toward resident behavior prediction in Wireless Sensor Network-Based smart homes

The smart home has gained widespread attention due to its flexible integration into everyday life. This next-generation green home system transparently unifies various home appliances, smart sensors, and wireless communication technologies. It can integrate diversified physical sensed information and control various consumer home devices, with the support of active sensor networks having both sensor and actuator components. Although smart homes are gaining popularity due to their energy saving and better living benefits, there is no standardized design for smart homes. In this chapter, we take one step toward modeling the resident behavior in smart home equipped with noninvasive sensors.We put forward a concept by designing and implementing a smart home system that can classify and predict the state of home. In this system, various sensors collect the home information over the course of a few months. These historical data are utilized as an input in a supervised machine learning technique to predict the current state of the home. This enables us to recognize any potential abnormal conditions and notify authorities in case of emergencies. A possible application of this model would be in senior care facilities to assure the resident safety with minimal human supervision.