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@article{194364,
        author = {Sujal M. Girolkar and Pritesh R. Gumble and Mansi N. Daga and Shivam S. Kadu and Shreya S. Khandar and Lekraj P. Thakare and Yash M. Bobade},
        title = {IoT-Based Vehicle Accident Detection and Real- Time Monitoring System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {4092-4096},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=194364},
        abstract = {Road accidents cause over 1.35 million fatalities annually worldwide. Delayed emergency response significantly worsens outcomes. This paper presents a low-cost, realtime vehicle accident detection and monitoring system built on the ESP32 microcontroller, integrating an MPU6050 IMU for tilt and roll sensing, dual piezoelectric sensors for front and rear vibration- based impact detection, and a NEO-6M GPS module for location tracking. Upon accident detection, the system automatically sends an SMS to a pre-stored emergency number containing the alert cause (Tilt / Roll / Vibration), GPS coordinates, and a clickable Google Maps link that opens the precise vehicle location in the recipient's browser. All sensor data is simultaneously streamed to the Thinger.io IoT cloud platform for real-time dashboard monitoring. Thresholds are remotely configurable via interactive dashboard sliders and persisted in EEPROM. Experimental validation on a prototype car chassis demonstrates tilt sensing error < 2%, GPS accuracy within 3.4 m, and 90% accident detection accuracy with zero false positives across ten simulated scenarios.},
        keywords = {ESP32; MPU6050; Piezoelectric; GPS NEO6M; Thinger.io; SMS Alert; Google Maps; EEPROM; IoT Monitoring},
        month = {March},
        }