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.
Table of Contents:
Preface xiii
1 Harnessing Artificial Intelligence to Address Global Environmental Challenges: A Cross-Domain Review 1
Suresh K.S., Dafik, Nagendar Yamsani, Rayappan Lotus, S. Mathumohan and Anurag Singh
2 Innovative AI Paradigms for Achieving Environmental Sustainability: From Concept to Practice 21
Sudhir Ramadass, R. Sundar, V. Elanangai, Divya Lalita, Banashree Chatterjee and Gayatri Parasa
3 Deep Learning Approaches for Real-Time Climate Monitoring and Anomaly Detection in Meteorological Systems 41
Manyam Thaile, Baby Anusha, Nagendar Yamsani, Balakrishnan, Umasree Mariappan and Sunder R.
4 Federated Learning for Privacy-Preserving Environmental Monitoring Across Distributed Sensor Networks 57
Kireet Muppavaram, Manyam Thaile, T. Srinivasulu, T. Srikanth, Anita Pradhan and Siva Shankar S.
5 Quantum AI in Environmental Modeling: Opportunities for Accelerating Ecosystem Simulations 75
Fathimathul Rajeena P.P., Rahoof P. P. and Sunder R.
6 Developing Digital Twin Ecosystems for Dynamic Environmental Analysis and Predictive Sustainability Planning 91
Ann Rija Paul, Amutha. S., M. Sakthivanitha, M. Mohamed Sirajudeen, N. Anandakrishnan and S. Suresh
7 AI-Driven Optimization of Renewable Energy Systems: Forecasting, Load Balancing, and Grid Efficiency 107
Raghavendra Kulkarni, P. Manikandaprabhu, Disha Sushant Wankhede, Bura Vijay Kumar, M. Vasuki and Rasmi A.
8 Intelligent Systems for Pollution Detection and Control: Integrating AI in Urban and Industrial Environments 127
K. Dhana Sree Devi, Ika Hesti Agustin, Talluri Lakshmi Siva Rama Krishna, Bura Vijay Kumar, Rishabh Garg and K. Kaliraj
9 Smart Agriculture Using AI: Enhancing Crop Yield, Soil Health, and Resource Efficiency 145
M. Vamsikrishna, Tholkapiyan M., Divya Kumari Tankala, Gotte Ranjith Kumar, Sandeep Kaur and P. Eswaran
10 Preserving Biodiversity through AI: Automated Species Monitoring and Habitat Conservation Strategies 163
Eshwar Dara, Bui Thanh Hung, Rayappan Lotus, Gotte Ranjith Kumar, C. Parameswari and Rajakumar Perumal
11 Explainable AI in Environmental Decision-Making: Enhancing Trust and Transparency in Sustainability Models 181
Sreejith R., Kapil Aggarwal, Nagendar Yamsani, T. Amalraj Victoire, G. Susan Shiny and Rasmi A.
12 Ethical Implications of AI in Environmental Policy Formulation: Balancing Innovation and Responsibility 199
Muralidhar Vejendla, Nor Asilah Wati Abdul Hamid, P. Jyothi, Kanegonda Ravi Chythanya, Sudheer S. Marar and Umesh Kumar Lihore
13 Shaping a Sustainable Future: The Role of AI in Driving Green Innovation and Environmental Equity 213
Madhura S., P. Sridhar, R. Karthikeyan, Patil Mounica, R. Archana Reddy and Umesh Kumar Lihore
14 Decades of Transformation: Predictive Analysis of Land Use Changes in Dhanbad Using Deep Learning and Remote Sensing 231
A. Anitha and Nikhil Raj
15 AI for Biodiversity and Ecosystem Conservation 261
Hina Hashmi, Aman Kumar and Danish Raza Rizvi
16 Pneumonia Detection in Chest Based on Respiratory Variability Using Deep Learning 291
Ritu Aggarwal and Eshaan Aggarwal
17 Integrated Optimization Strategies for High-Efficiency Solar PV Plants: From AI to Bifacial Technologies 309
S. Dayana Priyadharshini and M. Arvindhan
Bibliography 323
Index 327
About the Author :
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.
