SmartGuard: An IoT-Enabled Intelligent Helmet System with GPS Tracking, Collision Detection, and Emergency Response for Enhanced Road Safety
DOI:
https://doi.org/10.67308/irjist.067Keywords:
Accident Detection, Bio-Impedance Sensing, Emergency Response, GPS Tracking, Internet of Things (IoT), Road Safety, Smart HelmetAbstract
Road traffic fatalities continue to pose a critical global challenge, with powered two-wheelers accounting for a disproportionate share of casualties in developing nations. This paper presents SmartGuard, a novel IoT-enabled intelligent helmet system that integrates real-time GPS tracking, multi-axis fall and collision detection, bio-impedance alcohol sensing, electrooculography (EOG)-based drowsiness monitoring, photoplethysmography (PPG) vital-sign acquisition, and cloud-based emergency response into a single wearable device. A convolutional neural network (CNN) model deployed on an ESP32-S3 microcontroller achieves 97.4% accident-detection accuracy with 18 ms inference latency. A patented bio-impedance chin-strap sensor estimates blood-alcohol concentration (BAC) with a mean absolute error of 0.0028% w/v, triggering a dual-condition vehicle ignition interlock when BAC exceeds 0.03% w/v or the helmet is not worn. Field trials spanning 48,600 km and 120 participants over six months validate GPS accuracy of ±2.3 m and emergency notification latency of 2.7 seconds. SmartGuard provides a scalable, non-intrusive, and cost-effective framework for substantially reducing road fatalities and improving post-accident survivability.
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Copyright (c) 2026 Sairaj Jadhav, Shwet Jain, Prof. Pravin Hujare (Author)
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