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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
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License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 9

Published on: September 2026

IOT-BASED AUTOMATIC VEHICLE ACCIDENT DETECTION AND RESCUE SYSTEM

Dr. Nahid Khan Rohan Kishor Pawar Sandeep Ashok Rathod Vaibhavi Manoj Uplenchwar Tanushree Prakash Raghatate Shraddha Dnyaneshwar Kelzarkar

Department of Electrical Engineering, Tulsiramji Gaikwad Patil College of Engineering and Technology, Mohgaon, Nagpur, India
DOI:https://doi.org/10.55041/ijcope.v2i9.198

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Abstract

In a road accident, the minutes that follow the impact often matter as much as the impact itself. Victims on highways, at night, or in low-traffic stretches frequently wait for help simply because nobody has raised the alarm. This paper presents a low-cost, retrofittable system that detects a crash on its own, estimates how serious it is, and notifies an emergency contact and a fleet dashboard with the vehicle’s location, without requiring any action from the driver. The design splits the workload across two edge platforms. An ESP32 microcontroller handles time-critical tasks: impact and rollover detection from an MPU6050 inertial sensor, flame and temperature monitoring with relay-driven suppression, a manual SOS input, GSM calling and SMS through a SIM800L module, and MQTT telemetry. A Raspberry Pi 4B running OpenCV performs the two visionheavy tasks: continuous driver drowsiness monitoring using the eye aspect ratio and PERCLOS, and post-impact severity estimation that fuses impact magnitude, rollover state, occupant motion and a lightweight CNN damage score into a Minor, Moderate or Severe tag. A dedicated ESP32-CAM uploads a photograph of the scene. A 10-second cancellation window suppresses false alarms, and severity analysis runs inside that window so that it adds no delay to the alert. The paper details the architecture, detection logic, interfaces, power and timing budgets, and the evaluation protocol for the prototype.

Index Terms—accident detection, Internet

How to Cite this Paper

Khan, N., Pawar, R. K., Rathod, S. A., Uplenchwar, V. M., Raghatate, T. P. & Kelzarkar, S. D. (2026). IOT-Based Automatic Vehicle Accident Detection and Rescue System. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(9), 1-9. https://doi.org/10.55041/ijcope.v2i9.198

Khan, Nahid, et al.. "IOT-Based Automatic Vehicle Accident Detection and Rescue System." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 9, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijcope.v2i9.198.

Khan, Nahid,Rohan Pawar,Sandeep Rathod,Vaibhavi Uplenchwar,Tanushree Raghatate, and Shraddha Kelzarkar. "IOT-Based Automatic Vehicle Accident Detection and Rescue System." International Journal of Creative and Open Research in Engineering and Management 02, no. 9 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijcope.v2i9.198.

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References


  • [1] World Health Organization, Global Status Report on Road Safety 2023. Geneva, Switzerland: WHO, 2023. [2] Transport Research Wing, Ministry of Road Transport and Highways, Government of India, “Road accidents in India— 2022,” New Delhi, India, 2023.

  • A. Cowley, “A total emergency medical system for the State of Maryland,” Maryland State Med. J., vol. 24, no. 7, pp. 37– 45, 1975.

  • Regulation (EU) 2015/758 of the European Parliament and of the Council concerning type-approval requirements for the deployment of the eCall in-vehicle system based on the 112 service, J. Eur. Union, L 123, May 2015.

  • Automotive Research Association of India, “Intelligent transportation systems (ITS)—Requirements for public transport vehicle operation,” AIS-140, 2016.

  • White, C. Thompson, H. Turner, B. Dougherty, and D. C. Schmidt, “WreckWatch: Automatic traffic accident detection and notification with smartphones,” Mobile Netw. Appl., vol. 16, no. 3, pp. 285–303, 2011.

  • Soukupová and J. Čech, “Real-time eye blink detection using facial landmarks,” in Proc. 21st Comput. Vis. Winter Workshop, Rimske Toplice, Slovenia, 2016.

  • Kazemi and J. Sullivan, “One millisecond face alignment with an ensemble of regression trees,” in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), 2014, pp. 1867–1874.

  • E. King, “Dlib-ml: A machine learning toolkit,” J. Mach. Learn. Res., vol. 10, pp. 1755–1758, 2009.

  • Y. Kartynnik, A. Ablavatski, I. Grishchenko, and M. Grundmann, “Real-time facial surface geometry from monocular video on mobile GPUs,” arXiv:1907.06724, 2019.

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  • •Published on: Sep 26 2026
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