Abstract

The continuous improvement of workplace safety hinges on the adoption of proactive hazard recognition and near miss reporting systems. These systems play a critical role in identifying and mitigating potential risks before they result in incidents or injuries. Recent advancements have enhanced the effectiveness of these systems through the integration of new technologies, real-time data analysis, and behavioral insights. This paper reviews the latest developments in proactive hazard recognition systems, including the application of artificial intelligence (AI) and machine learning (ML) for pattern recognition and predictive analytics. Additionally, it explores the growing importance of near miss reporting systems, which have evolved from traditional manual processes to digital, real-time platforms that encourage employee engagement and accountability. The paper examines the role of IoT-enabled devices in hazard identification and the integration of augmented reality (AR) tools to provide immersive training and real-time hazard visualization. The influence of organizational culture and the importance of fostering an environment where near miss reporting is not only accepted but encouraged are also discussed. This review highlights various industry case studies and identifies the challenges and limitations of current systems, such as data quality issues, resistance to reporting, and the need for consistent training. The paper concludes by proposing a roadmap for the future, where smarter hazard recognition systems are integrated into safety management platforms, providing a holistic approach to risk prevention and a safety-first culture.