The Improvement of Industrial Safety Measures Using AI and IOT
Year: 2025
Type: article
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.
DOI: 10.29070/y03wq389
Authors: Dhiraj Kumar, Vivek Chandra Sagar
Institution: Vikrant University
Language: English
Subfield: Radiological and Ultrasound Technology
Field: Health Professions
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4414025928