IIARD International Institute of Academic Research and Development

WORLD JOURNAL OF INNOVATION AND MODERN TECHNOLOGY (WJIMT )

E-ISSN 2504-4766
P-ISSN 2682-5910
VOL. 9 NO. 1 2025
DOI: 10.56201/wjimt.v9.no1.2025.pg156.185

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Developing an AI-Powered Occupational Health Surveillance System for Real-Time Detection and Management of Workplace Health Hazards

Cynthia Obianuju Ozobu, Friday Emmanuel Adikwu, Cynthia, Oladipo Odujobi, Fidelis Othuke Onyeke, Emmanuella Onyinye Nwulu

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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 betw

keywords:

Artificial Intelligence, Occupational Health, Workplace Safety, Hazard Detection, Predictive Analytics, IoT Sensors, Real-Time Monitoring, Health Surveillance, Machine Learning, Employee Well-Being

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