Review of IoT-based AI analysis method through real-time indoor air quality and health effect monitoring - Focusing on indoor air pollution that are harmful to the respiratory organ

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 analyzed the correlation between environment and health information have been conducted through public data targeting large-scale cohorts, and dissertations through real-time data analysis are insufficient. Therefore, in order to collect environmental and health data from various data sources and monitor and analyze real-time, this dissertation will review environmental detection sensor development and indoor air quality monitoring system studies based on Internet of things, and research how to use wearable devices for health monitoring systems. In addition, availability of big data and artificial intelligence analysis and prediction have increased, investigating algorithmic studies for accurate prediction of hazardous environments and health effects. In terms of health effects, techniques to prevent respiratory and related diseases were reviewed.