Journal of the Korea Convergence Society (한국융합학회논문지)

Korea Convergence Society (한국융합학회)
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Development and Operation of Remote Lone-Senior Monitoring System Based on Heterogeneous IoT Sensors and Deep Learning

이종 사물인터넷 센서와 딥러닝에 기반한 독거노인 원격 모니터링 시스템의 개발 및 운영 사례 연구

  • Yoon, Young (Department of Computer Engineering Hongik University) ;
  • Kim, Hyunmin (Neouly Inc.) ;
  • Lee, Siwoo (Department of Computer Engineering Graduate School of Hongik University) ;
  • Pouri, Safa Siavash (Department of Computer Engineering Graduate School of Hongik University)
  • Received : 2021.10.13
  • Accepted : 2022.01.20
  • Published : 2022.01.28
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Abstract

This paper presents a system that remotely monitors lone seniors at home and promptly alarms caregivers to recommend appropriate medical care services upon detecting abnormal behavior and critical conditions such as collapsing, excessive coughing, degradation of sleep quality, fever, and unusual indoor moving lines. Our system offers contactless monitoring techniques based on heterogeneous IoT sensors and deep learning to minimize the disruption to lone senior's daily life. In addition to the design and implementation of the sensor data collection and analysis system, we share our experience in installation, deployment, configuration, maintenance of the system through the case study conducted on the actual lone seniors living in Seoul Metropolitan. Based on our research, we recommend further development directions to prepare for the nationwide expansion of our system.

본 논문은 독거노인의 복합적 행태를 이종 사물인터넷 센서들과 딥러닝 기법을 활용하여 인지하고 낙상, 잦은 기침, 수면의 질 감소, 발열 및 비정상적 생활 동선의 발생 등 위급하거나 건강이 저하되는 상황을 적시에 보호자 및 의료복지 담당자에게 알리고 적정한 후속 서비스를 추천 및 수행할 수 있는 시스템을 논한다. 독거노인들의 생활을 최대한 방해하지 않기 위하여 전면 비접촉식 상황 인식 기술을 선보인다. 본 논문은 센서 데이터의 수집 및 분석 체계의 설계와 구현 방법은 물론, 서울시 총 5개구 거주 독거노인들을 대상으로 실증한 경험을 통해 설치, 설정, 운영 및 유지 보수 측면에서의 다양한 문제점들을 서술하고 해당 시스템의 전국 확산에 대비한 향후 발전 방향을 제언한다.

Keywords

Acknowledgement

This research was supported by Basic Science Research Programs through the National Research Foundation of Korea (NRF) funded by Ministry of Education (2020R1F1A104826411), by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (Grant Number: HI19C0542020020), by the Ministry of Trade, Industry \& Energy (MOTIE) and the Korea Institute for Advancement of Technology (KIAT), under Grants P0014268 Smart HVAC demonstration support and by 2021 Hongik University Research Fund.

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