This research describes a Smart Human Monitoring System that applies the Internet of Things (IoT) and Multitask Deep Learning (MTDL) to improve worker’s safety, security, and well-being at the workplace. The system employs a smartwatch that operates on an IoTbased wearable device to provide continuous monitoring of workers’ physiological parameters such as heart rate, body temperature and blood pressure throughout the day, in real time. In addition, the system uses facial data captured by cameras located throughout the workplace to recognize workers’ identity and emotions (stress and fatigue) using a Multitask Deep Learning model. The system also uses rule-based and anomaly detection methodologies to monitor and detect employees’ usage patterns when logging into computers and using applications or browsing the internet so that abnormal or irregular activity can be detected quickly. All of this data provides a comprehensive assessment of worker status and is displayed on a centralized dashboard which provides real-time alerts to management for timely interventions. The system is designed to be an automated, unified and scalable system for providing proactive risk identification and workplace safety, as well as improved organizational performance..
Panchetti et al. (Wed,) studied this question.