신종 바이러스에 대응하는 스마트 고령자지원 시스템의 연구
A Study on the Smart Elderly Support System in response to the New Virus Disease
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참고문헌
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초록
최근 COVID-19와 같은 신종 바이러스 감염증이 확산하여 심각한 공중 보건 문제를 제기하고 있다. 특히 이러한 질병은 고령자에게 치명적으로 작용하여, 생명을 위협하고 심각한 사회적, 경제적 손실을 초래하였다. 이에 많은 산업분야에서사물 인터넷(IoT) 및 인공 지능(AI)을 응용한 원격진료, 헬스케어, 질병예방 등의 애플리케이션이 소개되어 질병 감지, 모니터링 및 검역 성능을 향상하고 있다. 하지만 기존기술은 갑작스러운 전염병의 출현에 신속하고 통합적으로 적용되지 않기 때문에, 사회 속에 감염병이 대규모 감염 및 전국적 확산되는 것을 차단하지 못하였다. 따라서 본 논문에서는 바이러스 질병 정보수집기를 통해 지역적 한계가 있는 다양한 감염 정보를 수집하고, AI 브로커를 통해 AI 분석 및 심각도 매칭을 수행하여 감염의 확산을 예측하고자 한다. 최종에는 질병관리본부를 통해 고령자에게 위험경보 발령, 확산 차단 문자 발송 및 감염지역 대피정보를 신속하게 제공한다. 현실적인 고령자 지원시스템은 감염자 발생지역 정보와 고령자의 위치정보를 비교하여 증강현실 기반의 스마트폰 애플리케이션으로 직관적인 위험지역(감염지역) 회피기능을 제공하고 감염지역 방문이 확인되면 자동으로 방역관리 서비스를 제공한다. 향후 제안시스템은 위치기반의 사용자 밀집도를 파악함으로써 갑작스런 인파 집중으로 인한압사 사고를 사전에 예방하는 방법으로도 활용 가능할 것이다.
Abstract
Recently, novel viral infections such as COVID-19 have spread and pose a serious public health problem. In particular, these diseases have a fatal effect on the elderly, threatening life and causing serious social and economic losses. Accordingly, applications such as telemedicine, healthcare, and disease prevention using the Internet of Things (IoT) and artificial intelligence (AI) have been introduced in many industries to improve disease detection, monitoring, and quarantine performance. However, since existing technologies are not applied quickly and comprehensively to the sudden emergence of infectious diseases, they have not been able to prevent large-scale infection and the nationwide spread of infectious diseases in society. Therefore, in this paper, we try to predict the spread of infection by collecting various infection information with regional limitations through a virus disease information collector and performing AI analysis and severity matching through an AI broker. Finally, through the Korea Centers for Disease Control and Prevention, danger alerts are issued to the elderly, messages are sent to block the spread, and information on evacuation from infected areas is quickly provided. A realistic elderly support system compares the location information of the elderly with the information of the infected area and provides an intuitive danger area (infected area) avoidance function with an augmented reality-based smartphone application. When the elderly visit an infected area is confirmed, quarantine management services are provided automatically. In the future, the proposed system can be used as a method of preventing a crushing accident due to sudden crowd concentration in advance by identifying the location-based user density.
참고문헌 (28)
- 서경현, "고령화 사회에서 한국인의 건강과 삶의 질", 한국심리학회지: 문화 및 사회문제, 12, pp.133~147 (2006), 한국문화및사회문제심리학회
- D. J. Kim, "Social difficulties of the elderly living alone and social welfare policy alternative", Journal of Social Welfare Support, 7(1), pp.217~239 (2012)
- L. Gao, "A novel fingerprint map of SARS-CoV with visualization analysis", Third International Conference on Image and Graphics (ICIG'04), pp.1~4 (2004)
- A. Zarrad, "The Evaluation of the Public Opinion - A Case Study:MERS-CoV Infection Virus in KSA", 2014 IEEE, 2014, 664~670
- "Features, evaluation and treatment coronavirus (COVID-19)" (2020)[URL]
- World Health Organization, "Coronavirus disease (COVID-19) Pandemic", ~ (2020)
- S. H. Sim, "A study on Web service supporting mobility of users using ICTbased autonomous feedback knowledge information", Personal and Ubiquitous Computing, 23(3-4), pp.1~11 (2019)
- V. Chamola, "A Comprehensive Review of the COVID-19Pandemic and the Role of IoT, Drones, AI, Blockchain, and 5G in Managing its Impac", IEEE Access, 8(1), pp.90225~90262 (2020)
- V. Hassija, "A survey on IoT security : Application areas, security threats, and solution architectures", IEEE Access, 7(1), pp.82721~82743 (2019)
- S. Vihnu, "Internet of Medical Things (IoMT)-An Overview", International Conference on Devices, Circuits and Systems (ICDCS), pp.10~13 (2020)
- S. Arora, "IoMT (Internet of Medical Things):Reducing Cost While Improving Patient Care", IEEE Access, 11(5), pp.24~27 (2020)
- J. J. P. C. Rodrigues, "Enabling technologies for the Internet of health things", IEEE Access, 6(1), pp.13129~13141 (2018)
- "Can smart thermometers track the spread of the Coronavirus?" (2020)[URL]
- "IoT Set to Play a Growing Role in the COVID-19 Response Omdia" (2020)[URL]
- "Life Signals to Roll Out Biosensor Patch for COVID-19 Monitoring" (2020)[URL]
- F. J. Dian, "Wearables and the Internet of Things (IoT), Applications, Opportunities, and Challenges: A Survey", IEEE Access, 8(1), pp.69200~69211 (2020)
- "Could Fitness Wearables Help Detect Early Signs of COVID-19?" (2020)[URL]
- S. Berryhill, "Effect of wearables on sleep in healthy individuals: A randomized cross-over trial and validation study", Journal of Clin. Sleep Med, pp.8356~8360 (2020)[DOI]
- J. R Barr, "Telemedicine, Homecare in the Era of COVID-19 & Beyond", 2020 Third International Conference on Artificial Intelligence for Industries (AI4I), pp.48~51 (2020)
- T. H. Davenport, "Good Doctor Technology: Intelligent Telemedicine in Southeast Asia", pp.115~123 (2022), MIT Press
- X. Huang, "Application analysis of AI reasoning engine in microblog culture industry", Personal and Ubiquitous Computing, 24(1), pp.393~403 (2020)
- "COVID-19: AI can help but the right human input is key" (2020)[URL]
- B. Kaur, "Artificial Intelligence in the Fight Against Covid-19 (Coronavirus)", 2021 Sixth International Conference on Image Information Processing (ICIIP), pp.10~15 (2021)
- Q. An, "A Survey of Machine Learning Technologies for COVID-19 Pandemic", 2022 14th International Conference on Computer Research and Development (ICCRD), pp.7~11 (2022)
- L. Mertz, "AI-Driven COVID-19 Tools to Interpret, Quantify Lung Images", IEEE Pulse, 11(4), pp.2~7 (2020)
- C. Qin, "Improved protein structure prediction using potentials from deep learning", Nature, 577(7792), pp.706~710 (2020)
- X. Jiang, "Towards an artificial intelligence framework for data-driven prediction of coronavirus clinical severity", Computers, Materials & Continua 2020, 63(1), pp.537~551 (2020)
- "Case Definitions for National Notifiable Infectious Disease" (2022)[URL]