Developing an AI-Powered Occupational Health Surveillance System for Real-Time Detection and Management of Workplace Health Hazards
Year: 2026
Type: article
Abstract: The increasing complexity of workplace environments necessitates advanced solutions for monitoring and managing occupational health risks. Traditional occupational health surveillance systems often struggle with inefficiencies, delayed hazard detection, and limited adaptability to dynamic workplace conditions. This study proposes the development of an Artificial Intelligence (AI)-powered occupational health surveillance system designed to enable real-time detection, assessment, and management of workplace health hazards. The system leverages machine learning (ML) algorithms, predictive analytics, and Internet of Things (IoT) devices to enhance workplace safety and improve health outcomes for employees. Central to the proposed system is the integration of wearable devices and IoT sensors to collect real-time data on environmental conditions, such as air quality, noise levels, and temperature, as well as employee health metrics, including heart rate, stress levels, and fatigue. These data streams are processed using AI algorithms capable of identifying patterns, detecting anomalies, and predicting potential risks. Predictive analytics further support proactive interventions, enabling organizations to mitigate hazards before they escalate into critical incidents. The system incorporates a user-friendly dashboard for visualizing insights, generating automated reports, and delivering actionable recommendations to managers and employees. Additionally, the framework supports compliance with occupational safety regulations by providing detailed documentation and audit trails. By combining real-time monitoring with AI-driven insights, the system promotes a culture of safety, minimizes workplace injuries, and enhances employee well-being. Moreover, the scalability of the framework allows it to be adapted across industries, addressing sector-specific challenges and operational requirements. This innovative approach bridges the gap between emerging technologies and occupational health, providing a comprehensive solution for organizations aiming to foster safe and healthy work environments. The study concludes by highlighting the potential impact of AI-powered surveillance systems on r
Author: Cynthia Obianuju Ozobu
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W7214780828