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현장 조사와 ICT 동향 분석을 통한 스몸비 현황과 개선 방안 연구

A Study on the Current Situation and Improved Method for the Smombie through Field Survey and ICT Trend Analysis

  • 이동훈 (한국정보통신기술협회 정보통신시험인증연구소) ;
  • 오혜수 (한국정보통신기술협회 정보통신시험인증연구소) ;
  • 장재민 (한국정보통신기술협회 정보통신시험인증연구소) ;
  • 정종운 (한국정보통신기술협회 정보통신시험인증연구소) ;
  • 양상운 (한국정보통신기술협회 정보통신시험인증연구소)
  • Lee, Dong Hoon (IT Testing&Certification Laboratory, Telecommunications Technology Association) ;
  • Oh, Hye Soo (IT Testing&Certification Laboratory, Telecommunications Technology Association) ;
  • Jang, Jae Min (IT Testing&Certification Laboratory, Telecommunications Technology Association) ;
  • Jeong, Jong Woon (IT Testing&Certification Laboratory, Telecommunications Technology Association) ;
  • Yang, Sang Oon (IT Testing&Certification Laboratory, Telecommunications Technology Association)
  • 투고 : 2020.09.02
  • 심사 : 2020.09.21
  • 발행 : 2020.10.31

초록

Smart phone zombie or Smombie means pedestrians who walk without attention to their surroundings because they are focused upon their smart phone. Because the traffic accidents and injuries caused by Smombie have been increased rapidly in recent years, the social attention and policies are needed to prevent it. This study was conducted to analyze Smombie's current status and some solutions used before and to propose new improved method through the latest ICT trend. In this study, we did the field survey to check Smombies at several places in Seoul through people counting, and found that a lot of pedestrians still use the smart phone while walking. And we analyzed many case studies about some solutions to prevent Smombies previously. The case studies include legal regulations, government policies, smart phone app services and facilities that are used before. We studied them through internet searches and reference studies and we also checked the current operating situation as visiting several places that the solutions actually has been operated. Therefore, we found there are some limitations in previous solutions in terms of effectiveness and management. To consider new solution that can be expected to overcome the limitations, we analyzed the latest ICT trends focused on features to utilize the Smombie prevention, especially video recognition and digital signage. In these days, video recognition has been developed rapidly with assistance of AI technology and it can recognize the specific pedestrian's characteristics such as holding smart phone as well as hair style, clothes, backpack and etc. On the other hands, the digital signage is the convergence device that includes big display, network connection and various IoT sensors. It can be used as public media in many places for public services as well as advertising. Through these analysis results, we show the requirements and the user scenario for the improved method to prevent Smombie. Finally, we propose to develop R&D technology to recognize Smombie exactly as pedestrian attributes and to spread creative contents to increase pedestrian's interest and engagement for Smombie prevention through digital signage.

키워드

참고문헌

  1. National Information Society Agency (NIA), "2019 The Survey on Smart Phone Overdependence", 2020.
  2. Hyundai Marine & Fire Insurance Co., Ltd Official Blog, "A Study on the Dangers of using a Smart Phone While Walking", 2019.
  3. Samsung Fire Insurance, "Traffic Accident Statistics due to Distraction when Walking", 2017.
  4. The Korea University News, 7 April, 2019.
  5. The Economic Review, 16 November, 2018.
  6. Young Hyundai Online Magazine, 26 December, 2018.
  7. LOUD Project Official Blog, 17 October, 2018.
  8. Me Me We GangNam, 10 March, 2019.
  9. The Yonhap News, 9 May, 2018.
  10. H. Ivaniv, "Smombie App", Prezi, 17 December, 2019.
  11. The Construction Technology News, 26 February, 2019.
  12. Ministry of Science and ICT Blog, 22 July, 2016.
  13. Momentum Infinity Blog, 25 July, 2017.
  14. Y. S. R. Kim and S. J. Lee, "A Study on the Characteristics and Effects of Digital Signage Advertising in the Free Outdoor Advertising Zone", The Korean Advertising & PR Practitioners Society Journal, Vol. 12, No. 1, pp. 29-60, 2019.
  15. The Youtube, "The Virtual Crash Billboard", 4 June, 2017.
  16. The Youtube, "Bone VS. Steel", 12 November, 2018.
  17. Mania Consulting Group Blog, 7 March, 2016.
  18. J. S. Lee, S. K. Lee, D. W. Kim, S. J. Hong and S. I. Yang, "Trends on Object Detection Techniques Based on Deep Learning", Electronics and Telecommunications Trends, Vol. 33, No. 4, pp. 23-32, 2018. https://doi.org/10.22648/ETRI.2018.J.330403
  19. S. Chung and M.G. Chung, "Pedestrian Classification using CNN's Deep Features and Transfer Learning", Journal of Internet Computing and Services, Vol. 20, No. 4, pp. 91-102, 2019.
  20. Laon People Blog, 16 January, 2017.
  21. X. Wang, S. Zheng, R. Yang, B. Luo and J. Tang, "Pedestrian Attribute Recognition: A Survey", arXiv.org, 22 January, 2019.
  22. X. Liu, H. Zhao, M. Tian, L. Sheng, J. Shao, S. Yi, J. Yan and X. Wang, " HydraPlus-Net: Attentive Deep Features for Pedestrian Analysis", arXiv.org, pp. 350-359, 2017.
  23. S. Yoo and S. Kang, "A Study on the Risk of Traffic Accidents using Smart Devices while Walking", J. Korean Soc. Saf., Vol. 32, No. 3, pp. 74-82, 2017. https://doi.org/10.14346/JKOSOS.2017.32.3.74
  24. M. H. Kim, S. W. Shin and Y. Y. Suh, "Application of Deep Learning Algorithm for Detecting Construction Workers Wearing Safety Helmet Using Computer Vision", J. Korean Soc. Saf., Vol. 34, No. 6, pp. 29-37, 2019. https://doi.org/10.14346/JKOSOS.2019.34.6.29
  25. D. Ka, D. Lee and H. Yeo, "Development of Predictive Pedestrian Collision Warning Service Considering Pedestrian Characteristics", The Journal of The Korea Institute of Intelligent Transport Systems, Vol. 18, No. 3, pp. 68-83, 2019. https://doi.org/10.12815/kits.2019.18.3.68