Journal of the Semiconductor & Display Technology (반도체디스플레이기술학회지)

The Korean Society Of Semiconductor & Display Technology (한국반도체디스플레이기술학회)
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A Real-time Bus Arrival Notification System for Visually Impaired Using Deep Learning

딥 러닝을 이용한 시각장애인을 위한 실시간 버스 도착 알림 시스템

  • Seyoung Jang (Dept. of Computer Science and Engineering, Soongsil University) ;
  • In-Jae Yoo (Beyoundgtech Inc.) ;
  • Seok-Yoon Kim (Dept. of Computer Science and Engineering, Soongsil University) ;
  • Youngmo Kim (Dept. of Computer Science and Engineering, Soongsil University)
  • Received : 2023.05.09
  • Accepted : 2023.06.21
  • Published : 2023.06.30
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Abstract

In this paper, we propose a real-time bus arrival notification system using deep learning to guarantee movement rights for the visually impaired. In modern society, by using location information of public transportation, users can quickly obtain information about public transportation and use public transportation easily. However, since the existing public transportation information system is a visual system, the visually impaired cannot use it. In Korea, various laws have been amended since the 'Act on the Promotion of Transportation for the Vulnerable' was enacted in June 2012 as the Act on the Movement Rights of the Blind, but the visually impaired are experiencing inconvenience in using public transportation. In particular, from the standpoint of the visually impaired, it is impossible to determine whether the bus is coming soon, is coming now, or has already arrived with the current system. In this paper, we use deep learning technology to learn bus numbers and identify upcoming bus numbers. Finally, we propose a method to notify the visually impaired by voice that the bus is coming by using TTS technology.

Keywords

Acknowledgement

This research was supported by the MSIT(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW)(2018-0-00209) supervised by the IITP (Institute of Information & communications Technology Planning & Evaluation).

References

  1. S. N. Moon, J. S. Park, "Urban Railway, Opens the Era of Gull-scale Public Transportation," Monthly KOTI Magazine on Transport, Vol. 2016, No. 8, pp. 24-27, Aug, 2016. 
  2. G. Y. Yoo, "Development of Public Transportation Seen Through the Eyes of 'Latte~'," Monthly KOTI Magazine on Transport, Vol. 2021, No. 9, pp. 55-61, Sep, 2021. 
  3. Public Transportation Usage Status, Seoul https://news.seoul.go.kr/traffic/archives/31616. 
  4. C. S. Hoon, S. S. Il, Y. I, Lee, C. J. Lee, "A Methodology of Multimodal Public Transportation Network Building and Path Searching Using Transportation Card Data," Journal of Korean Society of Transportation, Vol. 26, No. 3, pp. 233-243, Jun, 2008. 
  5. D. B. Kim, "If the bus use rate is low, can the accessibility of the disabled be ignored?," Albenews, http://m.ablenews.co.kr/News/NewsContent.aspx?NewsCode=004820210914121320277077&CategoryCode=0048. 
  6. Y. S. Kim, J. H. Park, D. M. Kim, "Transportation service status and improvement plan to improve the convenience of moving between regions of the disabled," Legislative and Policy Reports, Vol. 35, Dec, 2019. 
  7. K. Y. Ryu, "Is it a Public Transport Powerhouse? "It is Still Difficult to Use the Bus for the Visually Impaired"," SOCIAL FOCUS, Dec. 2019. 
  8. S. K. Lee, "Citizen Petition for 'Even Visually Impaired Want to Ride the Bus'," Ablenews, Nov, 2019. 
  9. S. Y. Park, "Rep. Kim Ye-ji "It is essential to guarantee the right to move for the visually impaired"," http://www.welfarenews.net/news/articleView.html?idxno=81480, Apr, 2022. 
  10. Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg, "SSD: Single Shot MultiBox Detector," Computer Vision - ECCV 2016, pp. 21-37, Sep, 2016. DOI:10.1007/978-3-319-46448-0_2. 
  11. Optical character recognition; OCR, https://en.wikipedia.org/wiki/Optical_character_recognition. 
  12. Ray Smith, "An Overview of the Tesseract OCR Engine," Google Inc, 2007. 
  13. Google, "Text-to-Speech: Lifelike Speech Synthesis," https://cloud.google.com/text-to-speech.