Tang, XuejiaoQiu, JiongChen, RuijunZhang, WenbinIosifidis, VasileiosLiu, ZhenMeng, WeiZhang, MingliZhang, Ji2021-05-202021-05-202021-03-19Tang, Xuejiao; Qiu, Jiong; Chen, Ruijun; Zhang, Wenbin; Iosifidis, Vasileios; Liu, Zhen; Meng, Wei; Zhang, Mingli; Zhang, Ji; A Data-driven Human Responsibility Management System; 2020 IEEE International Conference on Big Data (Big Data); https://ieeexplore.ieee.org/document/9378484https://doi.org/10.1109/BigData50022.2020.9378484http://hdl.handle.net/11603/215752020 IEEE International Conference on Big Data (Big Data)An ideal safe workplace is described as a place where staffs fulfill responsibilities in a well-organized order, potential hazardous events are being monitored in real-time, as well as the number of accidents and relevant damages are minimized. However, occupational-related death and injury are still increasing and have been highly attended in the last decades due to the lack of comprehensive safety management. A smart safety management system is therefore urgently needed, in which the staffs are instructed to fulfill responsibilities as well as automating risk evaluations and alerting staffs and departments when needed. In this paper, a smart system for safety management in the workplace based on responsibility big data analysis and the internet of things (IoT) are proposed. The real world implementation and assessment demonstrate that the proposed systems have superior accountability performance and improve the responsibility fulfillment through real-time supervision and self-reminder.5 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.Text