Environmental quality assessment is transforming ecosystem monitoring as AI automates data collection, analysis, and pollution trend prediction. The integration of machine learning, neural networks, sensor-based systems, remote sensing, and predictive analytics drives intelligent solutions for sustainable ecosystem management.
Environmental quality assessment has evolved through the integration of artificial intelligence, enabling faster and more accurate monitoring of ecosystems. AI enhances environmental management by automating data collection, analysis, and prediction of pollution trends. Environmental Monitoring Using Artificial Intelligence explains the use of machine learning, neural networks, and sensor-based systems in tracking environmental parameters. The book explores applications in air and water quality analysis, climate modeling, and biodiversity assessment. It also highlights emerging technologies such as remote sensing and predictive analytics. Through practical examples and algorithmic insights, it guides scientists and engineers in developing intelligent monitoring solutions for sustainable ecosystems.
