The integration of fuzzy logic with multi-agent systems represents a significant advancement in handling the inherent uncertainties in environmental data while distributing intelligence across monitoring networks. This book explores how fuzzy reasoning enhances decision-making capabilities in pollution detection, source identification, and remediation planning. It demonstrates how multi-agent architectures facilitate coordination among distributed sensors and actuators, enabling more comprehensive environmental coverage and resilient system operation. The AIoT dimension adds the critical capability of real-time data processing, pattern recognition, and autonomous response to environmental threats.

Each chapter combines theoretical foundations with practical implementation guidelines, supported by real-world case studies across air, water, and soil monitoring applications. Special attention is given to system design methodologies, sensor integration, data fusion techniques, and decision support frameworks. This book culminates in a discussion of emerging technologies and future research directions, making it an invaluable resource for students, researchers, environmental agencies, and industry professionals working at the intersection of artificial intelligence and environmental science.