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@article{203782,
        author = {Satyam Kutpelli and Vanita Babanne and Aryan Kale and Devanshu Jadhav and Mayuresh Kale},
        title = {An Intelligent Driver Safety System for Heavy Commercial Vehicles: Real-Time Drowsiness Detection, Obstacle Avoidance, and Emergency Alerting Using Low-Cost Embedded Sensors},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {311-318},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=203782},
        abstract = {Driver fatigue and distraction remain leading causes of fatal accidents involving heavy commercial vehicles, including trucks and tankers. Existing safety systems predominantly rely on computer vision or passive warning mechanisms that are expensive, computationally intensive, and ineffective for retrofitting onto older diesel vehicles. This paper presents a low- cost, hardware-first driver safety system that integrates real- time drowsiness detection, obstacle-based speed regulation, driver presence verification, and emergency location alerting into a unified embedded platform. Using an Arduino UNO as the central controller, the system employs an infrared (IR) sensor for eye- blink monitoring, an ultrasonic sensor for continuous distance measurement, a force-sensitive resistor (FSR) for driver presence validation, and GPS-GSM modules for automated emergency communication. The system implements a 5-second no-blink threshold to classify drowsiness, triggering audible and vibratory alerts while simultaneously reducing motor speed. For obstacle avoidance, a linear PWM-based speed mapping function adjusts vehicle velocity inversely to detected distance. When critical conditions arise, the GSM module transmits SMS alerts containing live Google Maps location data. Experimental results demonstrate 100% drowsiness detection accuracy at the 5-second threshold, linear distance-to-speed mapping with ±5% variance, and 94% SMS delivery success rate. The total system cost is under $50, making it suitable for widespread deployment across existing commercial vehicle fleets. Unlike vision-dependent or alert-only solutions, this work offers a retrofittable, tamper-proof safety system for both mechanical and ECU-controlled diesel trucks.},
        keywords = {Driver drowsiness detection, obstacle avoidance, active speed control, Arduino UNO, ultrasonic sensor, IR sensor, GPS-GSM module, diesel truck safety, retrofittable safety system, embedded systems, commercial vehicles.},
        month = {June},
        }