July 1, 2022
Data Fusion of Real-Time Location Sensing and Physiological Status Monitoring for Ergonomics Analysis of Construction Workers
Cheng, Tao; Migliaccio, Giovanni C.; Teizer, Jochen; Gatti, Umberto C. (2013). Data Fusion of Real-Time Location Sensing and Physiological Status Monitoring for Ergonomics Analysis of Construction Workers. Journal Of Computing In Civil Engineering, 27(3), 320 – 335.
Abstract
Previous research and applications in construction resource optimization have focused on tracking the location of material and equipment. There is a lack of studies on remote monitoring for improving safety and health of the construction workforce. This paper presents a new approach for monitoring ergonomically safe and unsafe behavior of construction workers. The study relies on a methodology that utilizes fusion of data from continuous remote monitoring of construction workers' location and physiological status. To monitor construction workers activities, the authors deployed nonintrusive real-time worker location sensing (RTLS) and physiological status monitoring (PSM) technology. This paper presents the background and need for a data fusion approach, the framework, the test bed environment, and results to some case studies that were used to automatically identify unhealthy work behavior. Results of this study suggest a new approach for automating remote monitoring of construction workers safety performance by fusing data on their location and physical strain. DOI: 10.1061/(ASCE)CP.1943-5487.0000222. (C) 2013 American Society of Civil Engineers.
Keywords
Civil Engineering Computing; Construction Industry; Ergonomics; Occupational Health; Occupational Safety; Personnel; Sensor Fusion; Psm Technology; Rtls Technology; Construction Workforce Health; Construction Workforce Safety; Equipment Location; Material Location; Construction Resource Optimization; Construction Worker; Ergonomics Analysis; Physiological Status Monitoring; Realtime Location Sensing; Data Fusion; Exposure; Tracking; Demands; Sensors; System; Construction Worker Behavior; Remote Location Sensing; Work Sampling; Workforce Safety And Health
