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Artificial intelligence (AI) has emerged as a powerful tool in addressing pressing environmental challenges. From climate change and biodiversity loss to pollution and resource management, AI-driven solutions transform how we understand and mitigate environmental risks. By utilizing vast amounts of data, AI technologies can optimize energy consumption, predict climate patterns, track deforestation, and identify areas for conservation, while enhancing the efficiency of renewable energy systems and waste management strategies. These innovations offer improved approaches to environmental conservation while providing valuable insights for policymakers and businesses looking to adopt sustainable practices. As AI continues to evolve, its potential to drive meaningful changes in environmental sustainability improves, and further exploration of these solutions may build a more resilient and sustainable future. Cases on AI-Driven Solutions to Environmental Challenges explores the transformative role of AI in promoting sustainability across various fields. It delves into case studies that demonstrate innovative applications of AI in addressing environmental challenges, improving resource efficiency, and fostering sustainable development. This book covers topics such as data science, green chemistry, and sustainable development, and is a useful resource for environmental scientists, computer engineers, conservationists, academicians, and researchers.
