Automatic Identification of Unsafe Bending Behavior of Construction Workers Using Real-Time Location Sensing and Physiological Status Monitoring

Nowadays, remote sensing technology allows for autonomous and remote data collection of construction resources. Data collected from various sources can be used to infer higher-level information about the entities being observed. This process, called data fusion, has been used in construction for tracking the location of material and equipment with a lack of studies on the use of data fusion for improving knowledge of workforce. This study explored the utilization of a data fusion approach for a continuous remote monitoring of construction workers' location and health. To this end, the authors deployed non-intrusive real-time worker location sensing (RTLS) and physiological status monitoring (PSM) technology, and later, used data fusion to analyze data from these devices.