Smart Helmet–Based Wearable Intelligence for Interpreting Worker Health and Safety Conditions

Author(s)	Ms. Legavarshini S, Ms. Premalatha P, Ms. Sandhiya M, Dr. Kavitha Margret M
Country	India
Abstract	Occupational safety in industrial sectors is often compromised by hazards such as toxic gases, high temperatures, sudden falls, and unnoticed health irregularities. To address these challenges, this paper proposes SafeHelmet-AI (Smart Artificial Intelligence–enabled Helmet for Industrial Safety), a real-time multimodal monitoring framework that integrates physiological, environmental, and motion sensing. The system incorporates a MAX30100 sensor for heart rate and SpO2 measurement, a MEMS accelerometer and gyroscope for fall and movement detection, gas sensors for hazardous substance monitoring, and a temperature sensor for heat stress evaluation. A CatBoost-based machine learning model is deployed to identify abnormal condi- tions such as irregular vital signs, elevated gas concentrations, fall incidents, and excessive thermal exposure. By combining multimodal sensing, machine learning with edge-level decision- making and ThingSpeak-based cloud remote monitoring, Safe Helmet-AI enhances data privacy, reduces latency, and offers a scalable, cost-effective solution for safeguarding workers in high- risk environments. This framework demonstrates the potential of AI-powered wearables to revolutionize occupational health and safety practices.
Field	Engineering
Published In	Volume 8, Issue 2, March-April 2026
Published On	2026-03-14

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