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A Framework and IoT-Based Accident Detection System to Securely Report an Accident and the Driver’s Private Information

Author

Listed:
  • Amal Hussain Alkhaiwani

    (Computer Science Department, College of Computer and Information Sciences, Imam Mohammed Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia)

  • Badr Soliman Alsamani

    (Information Systems Department, College of Computer and Information Sciences, Imam Mohammed Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia)

Abstract

Road traffic accidents in Saudi Arabia have become a serious issue because many of these accidents lead to deaths, injuries, and financial losses. Human lives are often lost in road accidents due to the delay in accident detection by medical assistance. In fact, the accident’s location and the driver’s personal information are considered critical information that plays a vital role in preserving human life. Additionally, previous studies have found a limitation in the encryption of sensitive data; in fact, a leak of private information is thought to be one of the challenges that restrict the use of IoT devices. To resolve this problem, this research presents an intelligent security framework, and an Internet-of-Things-based system is proposed for immediate accident detection. Thus, this system requires the highest level of security and privacy to maintain the driver’s privacy. Moreover, the design science research methodology was followed to design and evaluate the artifacts. Thus, the study’s research resulted in the ability to design a secure and effective IoT-based system to detect and report a car accident instantly. In addition, the message is encrypted using Elliptic Curve Integrated Encryption and sent through Message Queuing Telemetry Transport over GSM. The study’s overall results show the flexibility with which the proposed artifact can be used for other purposes related to the IoT security framework to send and encrypt critical information.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:10:p:8314-:d:1151277
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