The Improvement of Industrial Safety Measures Using AI and IOT

The convergence of Artificial Intelligence (AI) and the Internet of Things (IoT) has emerged as a transformative approach to enhancing industrial safety by enabling intelligent decision-making, predictive analytics, and real-time monitoring. Industrial environments are inherently exposed to risks such as equipment failure, toxic exposure, and human error, all of which can lead to accidents, injuries, and financial losses. AI-driven predictive analytics, when combined with IoT-enabled sensor networks, offers a proactive framework to mitigate these hazards before they escalate into critical incidents. Smart sensors continuously capture data related to equipment performance, environmental conditions, and worker behavior, which is then analyzed by AI algorithms to detect anomalies, predict failures, and trigger timely alerts. This integration enhances workplace safety, minimizes unplanned downtime, optimizes resource utilization, and ensures compliance with regulatory standards. Moreover, AI-powered automation and robotics can take over high-risk tasks, reducing direct human exposure to hazardous conditions. Wearable IoT devices further strengthen worker protection by monitoring vital health indicators and adherence to safety protocols. Overall, the integration of AI and IoT transforms reactive safety systems into proactive and predictive strategies, fostering an industrial ecosystem that is safer, more intelligent, and environmentally sustainable.

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Publication Details

Journal
Journal of Advances in Science and Technology
Published
2025-04-01
DOI
https://doi.org/10.29070/y03wq389
Citations
2
Primary Topic
Technology and Data Analysis
Type
article
Field-Weighted Citation Impact
6.49
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article

The Improvement of Industrial Safety Measures Using AI and IOT

Vidya Sagar, Dhiraj Kumar
2 citations
Journal of Advances in Science and Technology
Technology and Data Analysis
6.49
article

The Improvement of Industrial Safety Measures Using AI and IOT

Vidya Sagar, Dhiraj Kumar
article en
2 citations

Abstract

The convergence of Artificial Intelligence (AI) and the Internet of Things (IoT) has emerged as a transformative approach to enhancing industrial safety by enabling intelligent decision-making, predictive analytics, and real-time monitoring. Industrial environments are inherently exposed to risks such as equipment failure, toxic exposure, and human error, all of which can lead to accidents, injuries, and financial losses. AI-driven predictive analytics, when combined with IoT-enabled sensor networks, offers a proactive framework to mitigate these hazards before they escalate into critical incidents. Smart sensors continuously capture data related to equipment performance, environmental conditions, and worker behavior, which is then analyzed by AI algorithms to detect anomalies, predict failures, and trigger timely alerts. This integration enhances workplace safety, minimizes unplanned downtime, optimizes resource utilization, and ensures compliance with regulatory standards. Moreover, AI-powered automation and robotics can take over high-risk tasks, reducing direct human exposure to hazardous conditions. Wearable IoT devices further strengthen worker protection by monitoring vital health indicators and adherence to safety protocols. Overall, the integration of AI and IoT transforms reactive safety systems into proactive and predictive strategies, fostering an industrial ecosystem that is safer, more intelligent, and environmentally sustainable.

Journal of Advances in Science and TechnologyVol. 22(2)
ITM University (IN)
Openalex Percentile: Top 3%
Technology and Data Analysis
6.49
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The Improvement of Industrial Safety Measures Using AI and IOT — Vidya Sagar, Dhiraj Kumar · Journal of Advances in Science and Technology (2025) | TGRS Research Map | TGRS