A Data-driven Human Responsibility Management System

TL;DR

This paper proposes a smart safety management system leveraging big data and IoT to monitor workplace safety, enhance responsibility fulfillment, and reduce accidents through real-time supervision and automated alerts.

Contribution

It introduces a novel data-driven safety management system integrating IoT and big data analysis for real-time safety supervision and responsibility management.

Findings

Improved accountability performance in safety management.

Enhanced responsibility fulfillment through real-time supervision.

Reduction in workplace accidents and damages.

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.