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Review of Internet of Things-Based Artificial Intelligence Analysis Method through Real-Time Indoor Air Quality and Health Effect Monitoring: Focusing on Indoor Air Pollution That Are Harmful to the Respiratory Organ.
Mun, EunMi; Cho, Jaehyuk.
Afiliación
  • Mun E; Department of Software Engineering, Jeonbuk National University, Jeonju, Republic of Korea.
  • Cho J; Department of Software Engineering, Jeonbuk National University, Jeonju, Republic of Korea.
Tuberc Respir Dis (Seoul) ; 86(1): 23-32, 2023 Jan.
Article en En | MEDLINE | ID: mdl-36288738
Everyone is aware that air and environmental pollutants are harmful to health. Among them, indoor air quality directly affects physical health, such as respiratory rather than outdoor air. However, studies that have examined the correlation between environmental and health information have been conducted with public data targeting large cohorts, and studies with real-time data analysis are insufficient. Therefore, this research explores the research with an indoor air quality monitoring (AQM) system based on developing environmental detection sensors and the internet of things to collect, monitor, and analyze environmental and health data from various data sources in real-time. It explores the usage of wearable devices for health monitoring systems. In addition, the availability of big data and artificial intelligence analysis and prediction has increased, investigating algorithmic studies for accurate prediction of hazardous environments and health impacts. Regarding health effects, techniques to prevent respiratory and related diseases were reviewed.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Tuberc Respir Dis (Seoul) Año: 2023 Tipo del documento: Article Pais de publicación: Corea del Sur

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Tuberc Respir Dis (Seoul) Año: 2023 Tipo del documento: Article Pais de publicación: Corea del Sur