Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings |
| Subtitle of host publication | 2020 IEEE International Conference on Big Data, Big Data 2020 |
| Editors | Xintao Wu, Chris Jermaine, Li Xiong, Xiaohua Tony Hu, Olivera Kotevska, Siyuan Lu, Weijia Xu, Srinivas Aluru, Chengxiang Zhai, Eyhab Al-Masri, Zhiyuan Chen, Jeff Saltz |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 5834-5838 |
| Number of pages | 5 |
| ISBN (electronic) | 9781728162515 |
| ISBN (print) | 978-1-7281-6252-2 |
| Publication status | Published - 2020 |
| Event | 8th IEEE International Conference on Big Data, Big Data 2020 - Virtual, Atlanta, United States Duration: 10 Dec 2020 → 13 Dec 2020 |
Abstract
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.
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
- Computer Science(all)
- Information Systems
- Decision Sciences(all)
- Information Systems and Management
- Engineering(all)
- Safety, Risk, Reliability and Quality
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Proceedings: 2020 IEEE International Conference on Big Data, Big Data 2020. ed. / Xintao Wu; Chris Jermaine; Li Xiong; Xiaohua Tony Hu; Olivera Kotevska; Siyuan Lu; Weijia Xu; Srinivas Aluru; Chengxiang Zhai; Eyhab Al-Masri; Zhiyuan Chen; Jeff Saltz. Institute of Electrical and Electronics Engineers Inc., 2020. p. 5834-5838 9378484.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - A Data-driven Human Responsibility Management System
AU - Tang, Xuejiao
AU - Qiu, Jiong
AU - Chen, Ruijun
AU - Zhang, Wenbin
AU - Iosifidis, Vasileios
AU - Liu, Zhen
AU - Meng, Wei
AU - Zhang, Mingli
AU - Zhang, Ji
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85103828469&partnerID=8YFLogxK
U2 - 10.1109/BigData50022.2020.9378484
DO - 10.1109/BigData50022.2020.9378484
M3 - Conference contribution
AN - SCOPUS:85103828469
SN - 978-1-7281-6252-2
SP - 5834
EP - 5838
BT - Proceedings
A2 - Wu, Xintao
A2 - Jermaine, Chris
A2 - Xiong, Li
A2 - Hu, Xiaohua Tony
A2 - Kotevska, Olivera
A2 - Lu, Siyuan
A2 - Xu, Weijia
A2 - Aluru, Srinivas
A2 - Zhai, Chengxiang
A2 - Al-Masri, Eyhab
A2 - Chen, Zhiyuan
A2 - Saltz, Jeff
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th IEEE International Conference on Big Data, Big Data 2020
Y2 - 10 December 2020 through 13 December 2020
ER -