AI in Monitoring and Improving Air and Water Quality for Green Innovation

Abstract

Environmental sustainability is a pressing global challenge, with air and water quality being critical indicators of ecological health. Artificial Intelligence (AI) offers transformative solutions for monitoring, analyzing, and improving these parameters, driving green innovation and sustainable practices. This chapter explores the role of AI in environmental monitoring, emphasizing its applications in real-time data collection, predictive modeling, and optimization strategies. Key topics include the integration of AI with IoT-enabled sensors for precise air and water quality assessment, machine learning algorithms for predictive analytics, and AI-driven decision-making tools for pollution mitigation. Case studies highlight successful implementations in urban air quality management and water resource optimization, demonstrating AI's potential to foster resilience against environmental degradation. By addressing challenges such as data scarcity, system scalability, and ethical considerations, this chapter underscores AI's pivotal role in advancing sustainable development and achieving environmental targets.