Harness the power of the digital frontier to save our planet with this essential guide, which demonstrates how deep learning, genetic engineering, and AI-based robotics can be integrated to track biodiversity, restore genetic diversity, and rebuild fragile ecosystems with unprecedented precision.

From satellite imagery to genetic sequencing, AI is helping researchers track biodiversity, predict ecosystem changes, and monitor endangered species with unprecedented precision. This book delves into the exciting ways that artificial intelligence (AI), particularly deep learning, is being used to analyze complex ecological data. It offers an in-depth look at how these AI-driven technologies are transforming how we approach biodiversity conservation on a global scale, examining the role of genetic engineering, guided by AI, in restoring genetic diversity and helping species adapt to rapidly changing environments. Additionally, the book highlights how AI is revolutionizing ecosystem restoration, using AI-based robotics and reinforcement learning to restore habitats such as forests, wetlands, and coral reefs. It looks at real-world applications where AI systems are actively being used to rebuild damaged ecosystems, suggesting new ways to restore balance to nature. Through a combination of practical case studies and theoretical insights, this guide serves as an essential resource for anyone interested in the future of conservation, whether you are an AI specialist, an environmental scientist, or simply someone passionate about protecting the planet. By blending the latest in AI research with real-world biodiversity challenges, this book paints a picture of a future where technology and nature work hand in hand to safeguard life on Earth.

Umesh Kumar Lilhore, PhD is a Professor in the Department of Computer Science and Engineering at Galgotias University. He has authored ten books, more than 100 research articles in journals, and filed 50 patents across India and the UK. His research interests include artificial intelligence, machine learning, and software engineering.

Sarita Simaiya, PhD is a Professor of Computer Science and Engineering at Galgotias University with more than 17 years of teaching and research experience. She has published more than 140 articles in international journals and conferences. Her research focuses on machine learning, Internet of Things, and AI.

Surjeet Dalal, PhD is a Professor and researcher with more than 20 years of experience in teaching and research in Computer Science and Engineering. He has published more than 140 articles in international journals and conferences. His research interests include artificial intelligence and cloud computing.

Martin Margala, PhD is the Director of the School of Computing at the University of Louisiana at Lafayette with more than 25 years of experience in teaching and research. He has more than 400 publications to his credit, including in international journal articles and conference proceedings. He specializes in exascale computing, ultra-high frequency design, and design for reliability.