ABSTRACT Construction workers often suffer from musculoskeletal disorders due to awkward postures and weight-carrying in hot environments. Previous studies have focused on posture, neglecting weight-carrying or the environment. This study develops an automated real-time version of the RULA-based posture assessment method, identifying a worker’s posture and load weight using an RGB-D Microsoft Kinect sensing camera. The method includes ambient workplace temperature and is tested on a small-scale bricklaying and reinforcement task. Laboratory tests show the method improves assessment efficiency significantly. This is the first of its kind to fully automate the assessment of construction worker WMSD propensity, providing a continuous warning system to replace manual supervision.