Detection of children's activities in smart home based on deep learning approach

Monitoring behavior of children in the home is the extremely important to avoid the possible injuries. Therefore, an automated monitoring system for monitoring behavior of children by researchers has been considered. The first step for designing and executing an automated monitoring system on children's behavior in closed spaces is possible with recognize their activity by the sensors in the environment, collect data, and then use learning algorithms. In this paper, a deep learning algorithm to recognize and classify children activity in smart home is proposed which data collected from sensors in a smart environment. Experimental result on ARAS dataset indicates that this type of reorganization is highly effective and practical.