Exploring the Effectiveness of AI and Wearable Technology in Predicting Workplace Accidents in High-Risk Industries

Abstract

Abstract: Workplace accidents pose significant threats to worker safety and productivity, especially in high-risk industries such as construction, manufacturing, and mining. This research explores the potential of Artificial Intelligence and wearable technology to predict and prevent workplace accidents. By analyzing data collected from wearable sensors, AI algorithms can identify patterns and anomalies indicative of potential hazards, enabling timely interventions. This paper reviews the existing literature on wearable sensors, AI algorithms, and their application in workplace safety. A proposed methodology outlines a framework for data collection, processing, and model training. The potential results of such a system are discussed, including improved hazard identification, personalized safety recommendations, and real-time alerts. The discussion section analyzes the challenges and limitations of implementing AI-powered wearable systems, such as data privacy, sensor reliability, and algorithm accuracy. Finally, the conclusion summarizes the potential benefits and future directions of this technology in revolutionizing workplace safety.