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AI-Powered Enhanced Air Quality Monitoring
Abstract
Air monitoring assesses atmospheric quality by analyzing data on pollutants and environmental factors, tracking parameters like temperature and pollutant levels to detect hazards and guide air quality management. This chapter introduces air monitoring fundamentals and explores AI's role in enhancing these activities. Beginning with the principles of air quality monitoring, it examines advanced methods for data collection and AI-driven analysis. Emphasis is placed on sensors that gather real-time data on pollutants and temperature, using machine learning models to predict future air quality from real-time and historical data. This predictive approach identifies issues like pollutant surges and temperature spikes. Additionally, the chapter highlights AI's role in creating energy-efficient monitoring systems, optimizing energy use while ensuring accurate real-time data analysis.
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