Smart Safety Monitoring for Construction Sites

Abstract

On-site construction safety management continues to face significant challenges due to reliance on manual inspections, paper-based documentation, and reactive safety practices. The absence of automated and data-driven monitoring mechanisms limits timely risk identification and informed decision-making. This paper addresses this gap by proposing a conceptual design of a Smart Safety Monitoring and Decision Support System (DSS) that integrates Internet of Things (IoT) sensors and computer vision technologies. The proposed system is designed to capture real-time environmental data from IoT sensors, detect unsafe behaviours and conditions using computer vision techniques, and consolidate all information in a centralized monitoring dashboard. By enabling continuous data acquisition and real-time analysis, the system aims to support proactive safety management and improve the accuracy of on-site risk identification and safety-related decision-making. Although the study is limited to a conceptual design and does not include empirical implementation or validation, it demonstrates the potential of data-driven technologies to transform construction safety management from a reactive to a proactive approach. The paper contributes to the existing literature by providing a structured conceptual framework for smart, technology-enabled safety monitoring systems in construction environments.