AI-Powered Occupational Health Surveillance System (AI-OHSS) for Enhanced Worker Safety in Aluminum Smelters

The primary aluminum smelting industry poses significant occupational health and safety (OHS) risks, including exposure to high heat, noxious fumes (e.g., fluoride, sulfur dioxide), molten metal, and strenuous physical labor. Traditional OHS methods are often reactive. This paper proposes the AI-Powered Occupational Health Surveillance System (AI-OHSS), a novel, proactive, and real-time monitoring system utilizing the Internet of Things (IoT) and Machine Learning (ML). AI-OHSS integrates data from wearable biometrics, environmental sensors, and visual analytics to provide comprehensive surveillance. The system is designed to detect and predict immediate hazards (e.g., heat stress, gas leaks, fatigue) and long-term health risks, significantly enhancing worker safety and well-being in the potroom and casting areas. (advancing_ohs_iiard)

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-17
DOI
https://doi.org/10.5281/zenodo.17966432
Primary Topic
Occupational exposure and asthma
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-Powered Occupational Health Surveillance System (AI-OHSS) for Enhanced Worker Safety in Aluminum Smelters

Zenodo (CERN European Organization for Nuclear Research)
Occupational exposure and asthma
article

AI-Powered Occupational Health Surveillance System (AI-OHSS) for Enhanced Worker Safety in Aluminum Smelters

article en

Abstract

The primary aluminum smelting industry poses significant occupational health and safety (OHS) risks, including exposure to high heat, noxious fumes (e.g., fluoride, sulfur dioxide), molten metal, and strenuous physical labor. Traditional OHS methods are often reactive. This paper proposes the AI-Powered Occupational Health Surveillance System (AI-OHSS), a novel, proactive, and real-time monitoring system utilizing the Internet of Things (IoT) and Machine Learning (ML). AI-OHSS integrates data from wearable biometrics, environmental sensors, and visual analytics to provide comprehensive surveillance. The system is designed to detect and predict immediate hazards (e.g., heat stress, gas leaks, fatigue) and long-term health risks, significantly enhancing worker safety and well-being in the potroom and casting areas. (advancing_ohs_iiard)

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 28%
Occupational exposure and asthma
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