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A Review of Internet of Things Approaches for Vehicle Accident Detection and Emergency Notification

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  • Mohammad Ali Sahraei

    (Department of Civil Engineering, College of Engineering, University of Buraimi, Al Buraimi 512, Oman)

  • Said Ramadhan Mubarak Al Mamari

    (Department of Civil Engineering, College of Engineering, University of Buraimi, Al Buraimi 512, Oman)

Abstract

The inspiration behind this specific research is based on addressing the growing need to improve road safety via the application of the Internet of Things (IoT) system. Although several investigations have discovered the possibility of IoT-based accident recognition, recent research remains fragmented, usually concentrating on outdated science or specific use cases. This study aims to fill that gap by carefully examining and conducting a comparative analysis of 101 peer-reviewed articles published between 2008 and 2025, with a focus on IoT systems for accident recognition techniques. The review categorizes approaches depending on the sensor used, incorporation frameworks, and recognition techniques. The study examines numerous sensors, such as Global System for Mobile Communications/Global Positioning System (GSM/GPS), accelerometers, vibration, and many other superior sensors. The research shows the constraints and advantages of existing techniques, concentrating on the significance of multi-sensor utilization in enhancing recognition precision and dependability. Findings indicate that, although substantial improvements have been made in the use of IoT-based systems for accident recognition, problems such as substantial implementation costs, weather conditions, and data precision issues persist. Moreover, the research acknowledges deficiencies in standardization, as well as the requirement for strong communication systems to enhance the responsiveness of emergency services. As a result, the study suggests a plan for upcoming developments, concentrating on the incorporation of IoT-enabled infrastructure, sensor fusion approaches, and artificial intelligence. This study improves knowledge by offering an extensive viewpoint on IoT-based accident recognition, providing insights for upcoming research, and suggesting policies to facilitate implementation, eventually enhancing worldwide road safety.

Suggested Citation

  • Mohammad Ali Sahraei & Said Ramadhan Mubarak Al Mamari, 2025. "A Review of Internet of Things Approaches for Vehicle Accident Detection and Emergency Notification," Sustainability, MDPI, vol. 17(14), pages 1-43, July.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:14:p:6510-:d:1703182
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    References listed on IDEAS

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    1. Nikhlesh Pathik & Rajeev Kumar Gupta & Yatendra Sahu & Ashutosh Sharma & Mehedi Masud & Mohammed Baz, 2022. "AI Enabled Accident Detection and Alert System Using IoT and Deep Learning for Smart Cities," Sustainability, MDPI, vol. 14(13), pages 1-24, June.
    2. Amal Hussain Alkhaiwani & Badr Soliman Alsamani, 2023. "A Framework and IoT-Based Accident Detection System to Securely Report an Accident and the Driver’s Private Information," Sustainability, MDPI, vol. 15(10), pages 1-26, May.
    3. Hong Tan & Fuquan Zhao & Han Hao & Zongwei Liu, 2021. "Evidence for the Crash Avoidance Effectiveness of Intelligent and Connected Vehicle Technologies," IJERPH, MDPI, vol. 18(17), pages 1-12, September.
    4. Mohammed Balfaqih & Soltan Abed Alharbi & Moutaz Alzain & Faisal Alqurashi & Saif Almilad, 2021. "An Accident Detection and Classification System Using Internet of Things and Machine Learning towards Smart City," Sustainability, MDPI, vol. 14(1), pages 1-13, December.
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