Implementation of a Deep Learning Platform for Post-Accident Response in Motorcycle Accidents 


Vol. 49,  No. 4, pp. 645-651, Apr.  2024
10.7840/kics.2024.49.4.645


PDF
  Abstract

This paper presents the implementation of a rapid accident detection and response platform for motorcycle rider safety in the event of an accident. The platform aims to utilize deep learning for forward vision analysis, IMU sensors for accident detection, and GPS for location tracking to enable swift accident response. Enhancements in image recognition speed were achieved through deep learning-based license plate recognition of front vehicles, and the IMU's tilt values were used to detect whether the motorcycle is operating normally. Additionally, the GPS tracks the motorcycle's location every second, allowing for rapid determination of the rider's location in the event of an accident. The collected location and front vision information are merged and transmitted to a server via a wireless communication module, facilitating initial accident response. Overall, the platform is developed with a focus on motorcycle accident detection and response, and its reliability has been validated through performance testing. The paper also proposes potential uses of the platform and future service development.

  Statistics
Cumulative Counts from November, 2022
Multiple requests among the same browser session are counted as one view. If you mouse over a chart, the values of data points will be shown.


  Related Articles
  Cite this article

[IEEE Style]

J. Park, M. K. Choi, D. H. Kwon, S. Shin, "Implementation of a Deep Learning Platform for Post-Accident Response in Motorcycle Accidents," The Journal of Korean Institute of Communications and Information Sciences, vol. 49, no. 4, pp. 645-651, 2024. DOI: 10.7840/kics.2024.49.4.645.

[ACM Style]

Jaehan Park, Mun Kyu Choi, Dae Hyeon Kwon, and Soo-young Shin. 2024. Implementation of a Deep Learning Platform for Post-Accident Response in Motorcycle Accidents. The Journal of Korean Institute of Communications and Information Sciences, 49, 4, (2024), 645-651. DOI: 10.7840/kics.2024.49.4.645.

[KICS Style]

Jaehan Park, Mun Kyu Choi, Dae Hyeon Kwon, Soo-young Shin, "Implementation of a Deep Learning Platform for Post-Accident Response in Motorcycle Accidents," The Journal of Korean Institute of Communications and Information Sciences, vol. 49, no. 4, pp. 645-651, 4. 2024. (https://doi.org/10.7840/kics.2024.49.4.645)
Vol. 49, No. 4 Index

Search
(IN TITLE, AUTHOR, ABSTRACT,KEYWORDS)

Advanced Search ▼

POPULAR KEYWORDS
(TOP 10 KEYWORDS)

Recent Publications
(LAST 3 YEARS)






pISSN : 1226 - 4717
eISSN : 2287 - 3880