Zhu, XiaoeXiaoeZhuProf. LI Yi Man, RitaRitaProf. LI Yi Man2022-06-072022-06-0720212021 International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML 2021)http://hdl.handle.net/20.500.11861/7137Construction is a high-risk industry. The ability of construction workers to recognize hazards and the speed of response affects the likelihood of accidents happening on sites or the level of severity of construction events. Eye-tracking is a measure of people’s situational awareness in response to environments. Although prior research attempted to do experiments by using eye-tracking technology to analyze the hazard recognition ability and visual attention of tower crane operators, design and cost engineers construction industry practitioners, few studies are using artificial intelligence eye tracking. There is even fewer eye-tracking experiment for workers on construction site. This research attempts to analyze the online eye-tracking data of three groups of construction-related practitioners, including data such as heat map images, visual distribution, mouse clicks, opacity images, and facial expression changes. The analysis results show that different construction workers’ visual distribution and emotional changes are significantly different. Tower crane operators have a broader focus, and their emotional distribution is significantly different from that of indoor and cost engineers and is also significantly different from green leaf engineers or site supervisors.enConference Paper