A proactive workers' safety risk evaluation framework based on position and posture data fusion

Construction workers' safety risk evaluation mainly relies on manual observation with safety expert's experience. The manual process is labor intensive and time-consuming. A proactive workers' safety risk evaluation framework is needed to handle this issue. In this paper, the position and posture have been identified as the two key quantitative features, and a position and posture fusion principle is proposed for the evaluation of construction workers' behaviors safety risks. Three participants are invited to involve in the indoor construction activities with working at height three times, and the participants' locations, postures, and video are recorded using sensing devices. The participants' risk levels are evaluated based on posture, location, and posture-location fusion respectively. A comparison of the risk level evaluated based on those three approaches and the ground truth provided by the experts. The results show that the accuracy of automatic safety risk level evaluation based on location and posture fusion is 83%, compared with 81% and 57% achieved by the single-feature based risk level evaluation using location and posture respectively. Thus, the position and posture fusion-based evaluation is more reliable in real situations.