Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
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Web-Based Behavioral Tracking Management System for Elderly Care Automation

  • Seokjin Kim (School of Computer Software, Daegu Catholic University) ;
  • June Hong Park (School of Computer Software, Daegu Catholic University) ;
  • Dongmahn Seo (School of Computer Software, Daegu Catholic University)
  • Received : 2021.09.09
  • Accepted : 2022.03.13
  • Published : 2023.06.30
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Abstract

Since the proportion of elderly citizens is increasing every year, the social interest is increasing for the health and the safety of the elderly. The nursing home is continually being created to care for more elderly people. However, the quality of service is not enough due to the lack of elderly caregivers. Elderly care and management services are being studied to replace the shortage of caregivers. Existing research for the implementation of an automatic care system has a high initial system cost. Furthermore, it lacks the ability to store and manage large amounts of data. In this paper, we propose a system that manages a large amount of data continuously generated through CCTV and provides a streaming service with a high level of quality-of-service (QoS) to users with collected video. Through the proposed system, it is possible to record and manage the behavioral information of the elderly occurring in the nursing home together with the video. In addition, according to the user's request, it has built a service that streams the video and behavioral information according to the date and time in real-time.

Keywords

Acknowledgement

This research was supported by research grants from Daegu Catholic University in 2020.

References

  1. Statistics Korea, "2018 Statistics on the Aged," 2018 [Online]. Available: http://kostat.go.kr.
  2. S. Kang, "A study on u-Care service for the health and safety of the elderly living alone," Convergence Security Journal, vol. 17, no. 3, pp. 59-64, 2017.
  3. S. Y. Jo and J. W. Jeong, "Design and implementation of hospital room management system based on IoT CareBots," The Journal of Korea Institute of Information, Electronics, and Communication Technology, vol. 11, no. 4, pp. 370-378, 2018. https://doi.org/10.17661/JKIIECT.2018.11.4.370
  4. T. W. Lee and J. Chung, "Structural factors influencing the quality management activities in nursing homes," Journal of Korean Academy of Nursing Administration, vol. 16, no. 2, pp. 162-171, 2010. https://doi.org/10.11111/jkana.2010.16.2.162
  5. D. S. Ko and J. D. Kwon, "A design of the next-generation emergency care system of elderly living alone (ECSELA)," Journal of Korean Institute of Information Technology, vol. 12, no. 7, pp. 1-7, 2014. https://doi.org/10.14801/kiitr.2014.12.7.1
  6. J. W. Li, Y. C. Chang, M. X. Xu, and D. Y. Huang, "A health management service with beacon-based identification for preventive elderly care," Journal of Information Processing Systems, vol. 16, no. 3, pp. 648-662, 2020. https://doi.org/10.3745/JIPS.04.0173
  7. H. Alshammari, S. A. El-Ghany, and A. Shehab, "Big IoT healthcare data analytics framework based on fog and cloud computing," Journal of Information Processing Systems, vol. 16, no. 6, pp. 1238-1249, 2020. https://doi.org/10.3745/JIPS.04.0193
  8. G. Cicceri, F. De Vita, D. Bruneo, G. Merlino, and A. Puliafito, "A deep learning approach for pressure ulcer prevention using wearable computing," Human-centric Computing and Information Sciences, vol. 10, article no. 5, 2020. https://doi.org/10.1186/s13673-020-0211-8
  9. F. Gerina, S. M. Massa, F. Moi, D. Reforgiato Recupero, and D. Riboni, "Recognition of cooking activities through air quality sensor data for supporting food journaling," Human-centric Computing and Information Sciences, vol. 10, article no. 27, 2020. https://doi.org/10.1186/s13673-020-00235-9
  10. J. Kunhoth, A. Karkar, S. Al-Maadeed, and A. Al-Ali, "Indoor positioning and wayfinding systems: a survey," Human-centric Computing and Information Sciences, vol. 10, article no. 18, 2020. https://doi.org/10.1186/s13673-020-00222-0
  11. H. Schulzrinne, A. Rao, and R. Lanphier, "Real time streaming protocol (RTSP)," Internet Engineering Task Force, Fremont, CA, RFC 2326, 1998.
  12. H. Parmar and M. Thornburgh, "Adobe's real time messaging protocol," 2012 [Online]. Available: https://rtmp.veriskope.com/pdf/rtmp_specification_1.0.pdf.
  13. R. Pantos and W. May, "HTTP live streaming," Internet Engineering Task Force, Fremont, CA, RFC 8216, 2017.
  14. FFmpeg/FFserver [Online]. Available: https://www.ffmpeg.org/.
  15. Live555 streaming media [Online]. Available: http://www.live555.com/.
  16. Matroska Server Mk2 [Online]. Available: https://github.com/klaxa/mkvserver_mk2
  17. Red5 [Online]. Available: https://github.com/Red5.
  18. hls.js [Online]. Available: https://github.com/video-dev/hls.js.
  19. flowplayer [Online]. Available: https://flowplayer.com/.