Integrating Face Recognition and IoT Sensors to Realize Smart Application of Health Monitoring at Home

In this study, we construct a smart home health monitoring application using IoT sensing devices, a Wi-Fi network, and face recognition technologies. The daily activity data of elderly people around their homes can be collected by sensors and transmitted to Google spreadsheets via the IFTTT service platform by using the IEEE 802.11 protocol. Caregivers can use the application (app) developed in this study to monitor the visual data from the mobile network to inquire about the daily activity data of elderly people. Furthermore, it allows real-time monitoring to distinguish whether elderly people with health problems are meeting daily basic activity conditions. On the basis of the IoT architecture model, we develop programs within the sensing, network, and application layers. The sensing layer can use webcams to actively recognize the faces of elderly people and collect their activity data, the network layer program uploads data to the cloud via a Wi-Fi network, and the application layer displays long-term activity data for elderly people around their homes through the mobile network. The application layer of the app provides caregivers with an understanding of the activity status of elderly people through visual charts. The system implemented in this study can be further applied to smart care services for elderly people at home in the future. The services include fall detection and reporting when elderly people walk and also the heart rate monitoring of home residents through the app interface, thus realizing more intelligent care applications.