Autorentext

Dr. Rajeev Kumar is an experienced academic and administrator with over 15 years of expertise in developing strategies for professional education. He is currently a Professor in the Computer Science and Engineering Department at Moradabad Institute of Technology, Moradabad, Uttar Pradesh, India. Dr. Kumar holds a Ph.D. in Computer Science, a D.Sc. (Post-Doctoral Degree) in Computer Science, and a Postdoctoral Fellowship in Malaysia. He has earned certifications in Data Science and Machine Learning using Python and R programming from IIM Raipur, as well as certifications from IBM, Google, and other organizations. He is a senior member of IEEE, a core team member of the IEEE Young Professionals Committee, and a member of the Computer Society of India and SIEEE. Dr. Kumar has participated in various leadership training programs and delivers expert talks on curriculum development, program outcomes (PO), program-specific outcomes (PSO), program educational objectives (PEOs), and vision and mission design and implementation. His academic interests include Artificial Intelligence, Cloud Computing, e-Governance, and Networking.

Dr. Saurabh Srivastava is an Assistant Professor in the Department of Computer Science and Engineering (Data Science) at Moradabad Institute of Technology, Moradabad, India. He earned his Ph.D. from Integral University, Lucknow, in 2023 and a Master of Computer Applications (MCA) from Dr. A.P.J. Abdul Kalam Technical University, Lucknow, in 2015. Dr. Srivastava has been actively involved in research since completing his MCA and has approximately 10 years of research experience. His areas of expertise include Computer Vision, Image Processing, Satellite Image Interpretation and Analysis, Land Cover Mapping, Time Series Analysis, Requirement Engineering, Multi-Agent Systems, Cybersecurity, and Social Engineering. He has published extensively in reputable journals and presented his research at numerous national and international conferences. Dr. Srivastava is committed to fostering critical thinking and innovation among students and actively mentors emerging scholars.

Dr. Sheng-Lung Peng is a Professor in the Department of Creative Technologies and Product Design and serves as the Dean of the College of Innovative Design and Management at National Taipei University of Business, Taiwan. He earned his Ph.D. from the Computer Science Department at National Tsing Hua University, Taiwan. Dr. Peng is an honorary Professor at Beijing Information Science and Technology University and a visiting Professor at Ningxia Institute of Science and Technology in China. He also holds adjunct professorships at National Dong Hwa University in Taiwan, Mandsaur University, and Kazi Nazrul University in India. Dr. Peng has edited several special issues for journals such as Frontiers in Public Health, Journal of Internet Technology, IEEE Internet of Things Magazine, Computers and Electrical Engineering, and Sensors. His research interests include algorithm design in artificial intelligence, bioinformatics, combinatorics, data mining, and networking.

Klappentext

Artificial Intelligence (AI) plays a pivotal role in advancing environmental stewardship by enabling innovative solutions to address pressing ecological challenges. Through its ability to process vast amounts of data, AI empowers researchers and policymakers to monitor environmental changes, predict future trends, and develop strategies for sustainable resource management. By integrating AI into environmental efforts, societies can transition toward more sustainable practices, ensuring the preservation of natural ecosystems for future generations. Its transformative potential underscores the importance of leveraging AI as a critical tool in fostering global environmental resilience and sustainability.

AI for Environmental Innovation and Stewardship examines this transformative potential by covering fundamental concepts, innovative methodologies, and real-world applications of AI in environmental contexts. It highlights the role of machine learning, data analytics, generative AI, supply chains, augmented reality, and virtual reality in providing new insights and solutions for managing complex ecological systems. It explains how AI is advancing environmental monitoring, enhancing predictive capabilities, optimizing resource usage, and supporting evidence-based decision-making. Highlights include:

• Legal perspectives and challenges of using AI in environmental justice
• Enhancing agricultural supply chains through AI and Blockchain integration
• AI innovations in Augmented Reality and Virtual Reality for environmental education
• AI to promote responsible consumption and waste management With its wide-ranging and holistic view of AI in environmental stewardship, the book is a resource for researchers, students, policymakers, and industry professionals, who seek to promote innovation and collaboration at the intersection of AI and the environment.

Inhalt

1. AI and Climate Change: Modeling the Future for Global Impact2. Green AI: Future Trends and Innovations3. AI: Revolutionizing Environmental Innovations4. Sustainability in New Emerging Technologies: A Focus on Artificial Intelligence in the Digital Era5. Scrutinizing Stand-Alone and Web-Based Database Architectures and API Integration6. Green AI: Future Trends and Innovations7. Generative AI and Computational Intelligence8. Energy Consumption of AI Systems9. Enhancing Agricultural Supply Chains Through AI and Blockchain Integration10. Detecting Microplastics in Aquatic Bodies Using Object Detection Models11. Sustainable Policy Frameworks: AI's Role in International Trade12. Innovative Advances of AI in Augmented Reality and Virtual Reality for Environmental Education13. AI and Environmental Justice: Legal Perspectives and Challenges14. Innovative Approaches to Environmental Stewardship: The Potential of Artificial Intelligence15. Revolutionizing Climate Science With Artificial Intelligence16. AI-Enhanced Responsible Consumption and Waste Management17. Future Farming: Harnessing AI for Sustainability18. Innovations and Impacts on Agricultural Practices: Improving Weed Management with Artificial Intelligence19. Artificial Intelligence (AI) in Renewable Energy Systems: A Brief Overview for Conserving and Efficiently Utilizing Renewable Resources20. Sustainability Future of Green AI and Its Application: A Review21. AI in Climate Research: Enhancing Accuracy and Understanding of Climate Patterns22. Green Computing: Reducing the Carbon Footprint of AI Systems Through Sustainable Practices