Book

Description

Environmental and air pollution present significant health risks to humans, often leading to previously unrecognized health complications. One critical factor is that the impact of indoor air quality on respiratory and overall physical health can be more pronounced than outdoor air quality. While research has explored the connection between health and the environment, there is an increasing focus on analyzing public and large-scale synergistic data. However, many of these studies lack real-time data analysis. This book focuses on developing an environmental detection sensor system that utilizes devices to monitor air quality for indoor and outdoor applications. In addition, this book focuses on developing an environmental detection sensor system that utilizes devices to monitor air quality for indoor and outdoor applications. Furthermore, this investigation highlights the importance of real-time verification, collection, and analysis of health and environmental data from various sources to implement effective health monitoring systems. Techniques such as fuzzy logic, artificial intelligence, machine learning, and deep learning have proven valuable in accurately predicting health outcomes and identifying hazardous situations. Additionally, this work explores strategies for preventing respiratory and related diseases, emphasizing minimizing health risks.