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Designing a smart safe transportation system within a university using object detection algorithm

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2024, 29(1), pp.51-59
  • DOI : 10.9708/jksci.2024.29.01.051
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : January 3, 2024
  • Accepted : January 26, 2024
  • Published : January 31, 2024

Na Young Lee 1 Geon Lee 1 Min Seop Lee 1 Yun Jung Hong 1 In-Beom Yang 1 Jiyoung Woo 1

1순천향대학교

Accredited

ABSTRACT

In this paper, we propose a novel traffic safety system designed to reduce pedestrian traffic accidents and enhance safety on university campuses. The system involves real-time detection of vehicle speeds in designated areas and the interaction between vehicles and pedestrians at crosswalks. Utilizing the YOLOv5s model and Deep SORT method, the system performs speed measurement and object tracking within specified zones. Second, a condition-based output system is developed for crosswalk areas using the YOLOv5s object detection model to differentiate between pedestrians and vehicles. The functionality of the system was validated in real-time operation. Our system is cost-effective, allowing installation using ordinary smartphones or surveillance cameras. It is anticipated that the system, applicable not only on university campuses but also in similar problem areas, will serve as a solution to enhance safety for both vehicles and pedestrians.

Citation status

* References for papers published after 2022 are currently being built.

This paper was written with support from the National Research Foundation of Korea.