Smart Highway Accident Detection and Emergency Alert System
Keywords:
Accident detection system, GPS-GSM communication, IoT, Microcontroller, Road safety, Smart highway, YOLOv8Abstract
Road accidents continue to be a major global concern, often leading to severe injuries and fatalities, especially when emergency response is delayed. To address this issue, this paper proposes a smart highway accident detection and emergency alert system that enables automatic detection and rapid communication during accident events. The system utilises an ESP32 microcontroller integrated with GPS and GSM modules to facilitate real-time monitoring and instant transmission of location-based alerts. To improve detection accuracy, the YOLOv8 deep learning model is employed to analyse traffic conditions and identify genuine accident scenarios while minimising false alarms caused by minor disturbances. Once an accident is detected, the system immediately sends precise location details and alert messages to nearby hospitals, emergency responders, traffic authorities, and registered contacts, ensuring faster medical assistance. Additionally, the system incorporates IoT capabilities, allowing accident data to be stored and monitored on a cloud platform for further analysis, such as identifying accident-prone areas and improving traffic management strategies. Experimental evaluations demonstrate that the system performs reliably under various environmental and traffic conditions, making it a scalable, efficient, and cost-effective solution for enhancing road safety and emergency response on highways.
References
L. Moura De Oliveira, M. Berrehil El Kattel, E. Eloi Dos Santos Filho, J. C. Vasquez, J. M. Guerrero and F. L. M. Antunes, "Recurrence-Based Techniques for Data-Driven Fault Diagnosis and Monitoring in Neutral-Point-Clamped Inverters," in IEEE Access, vol. 13, pp. 135475-135488, 2025.
N. Pathik, R. K. Gupta, Y. Sahu, A. Sharma, M. Masud, and M. Baz, “AI Enabled Accident Detection and Alert System Using IoT and Deep Learning for Smart Cities,” Sustainability, vol. 14, no. 13, p. 7701, Jun. 2022
P. B. H. K. S. Thakur, S. Moseen and V. Deepa, "Real- Time Accident Detection Using CCTV Footage Analysis," 2024 Third International Conference on Artificial Intelligence, Computational Electronics and Communication System (AICECS), MANIPAL, India, 2024, pp. 1-6
T. Huang, S. Wang, and A. Sharma, “Highway crash detection and risk estimation using deep learning,” Accident Analysis & Prevention, vol. 135, p. 105392, Feb. 2020.
N. B. M, E. Babu, G. S. S, S. K. O, and Sriganesh G, “Accident Detection & Rescue System Using IoT,” International Journal of Engineering Research & Technology, vol. 10, no. 11, Aug. 2022.
G. Sharma, P. Maheshwari, S. Singh, A. Agarwal, and N. Ahlawat, “Real time vehicle collision detection using deep learning,” International Journal of Scientific Development and Research, vol. 8, no. 7, pp. 323–329, 2023.
M. A. Baballe, “Accident Detection System with GPS, Gsm, and Buzzer,” TMP Universal Journal of Research and Review Archives, vol. 2, no. 1, Mar. 2023.
S. Ghosh, S. J. Sunny and R. Roney, "Accident Detection Using Convolutional Neural Networks," 2019 International Conference on Data Science and Communication (IconDSC), Bangalore, India, 2019, pp. 1-6.
A. Bochkovskiy, C.-Y. Wang, H.-Y. Mark Liao, “YOLOv4: Optimal Speed and Accuracy of Object Detection,” arXiv, pp. 1–10, 2020.
J. Redmon, S. Divvala, R. Girshick and A. Farhadi, “You Only Look Once: Unified, Real-Time Object Detection,” 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA, 2016, pp. 779–788
V. Suresh, A. N. S, Maclin Vinola P, and R. Janapriyan, “IoT-Based Smart Accident Detection and Alert System,” Advances in computational intelligence and robotics book series, pp. 322–337, Jun. 2023.
S. Nalawade, S. Kurhade, S. Khajuria, P. Landekar, and I. Barhate, “Computing and Intelligent Systems, SCRS, In-dia,” pp. 107–113, 2023.
G. Rajesh, A. R. Benny, A. Harikrishnan, J. Jacob Abraham, and N. P. John, “A Deep Learning based Accident Detection System,” 2020 International Conference on Communication and Signal Processing (ICCSP), pp. 1322–1325, Jul. 2020.
C. Divate et al., “Smart Accident Detection and Emergency Alert System. International Research Journal of Engineering and Technology (IRJET). Volume: 13 Issue: 01, Jan 2026.
M. Q. Kheder and A. A. Mohammed, “Real-time traffic monitoring system using IoT-aided robotics and deep learning techniques,” Kuwait Journal of Science, vol. 51, no. 1, Nov. 2023
