Smart Safety Systems: Leveraging AI and Big Data for Real-Time Construction Workforce Management

As construction sites grow in scale and complexity, ensuring worker safety has become a paramount concern in civil engineering. Traditional safety management systems often rely on manual oversight, resulting in inefficiencies and inconsistencies. This paper presents a novel framework for integrating artificial intelligence (AI) and big data technologies to transform construction workforce safety management. By utilizing image recognition, real-time monitoring, predictive analytics, and intelligent decision systems, this approach offers a data-driven model for identifying potential hazards, detecting unsafe behaviors, and enhancing compliance with safety protocols. The proposed system architecture not only reduces the reliance on human supervision but also increases the precision and responsiveness of safety interventions. This research bridges a critical gap between digital innovation and field-level safety practices, paving the way for smarter, safer, and more sustainable construction environments.