Buch, Englisch, 442 Seiten, Format (B × H): 156 mm x 234 mm
Buch, Englisch, 442 Seiten, Format (B × H): 156 mm x 234 mm
Reihe: Advances in Computational Collective Intelligence
ISBN: 978-1-032-89702-8
Verlag: Taylor & Francis Ltd
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 realworld 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 the following:
• 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.
Zielgruppe
Academic
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
- Geowissenschaften Umweltwissenschaften Umwelttechnik
- Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Betriebliches Energie- und Umweltmanagement
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
- Technische Wissenschaften Umwelttechnik | Umwelttechnologie Umwelttechnik
Weitere Infos & Material
1. AI and Climate Change: Modeling the Future for Global Impact 2. Green AI: Future Trends and Innovations 3. AI: Revolutionizing Environmental Innovations 4. Sustainability in New Emerging Technologies: A Focus on Artificial Intelligence in the Digital Era 5. Scrutinizing Stand-Alone and Web-Based Database Architectures and API Integration 6. Green AI: Future Trends and Innovations 7. Generative AI and Computational Intelligence 8. Energy Consumption of AI Systems 9. Enhancing Agricultural Supply Chains Through AI and Blockchain Integration 10. Detecting Microplastics in Aquatic Bodies Using Object Detection Models 11. Sustainable Policy Frameworks: AI's Role in International Trade 12. Innovative Advances of AI in Augmented Reality and Virtual Reality for Environmental Education 13. AI and Environmental Justice: Legal Perspectives and Challenges 14. Innovative Approaches to Environmental Stewardship: The Potential of Artificial Intelligence 15. Revolutionizing Climate Science With Artificial Intelligence 16. AI-Enhanced Responsible Consumption and Waste Management 17. Future Farming: Harnessing AI for Sustainability 18. Innovations and Impacts on Agricultural Practices: Improving Weed Management with Artificial Intelligence 19. Artificial Intelligence (AI) in Renewable Energy Systems: A Brief Overview for Conserving and Efficiently Utilizing Renewable Resources 20. Sustainability Future of Green AI and Its Application: A Review 21. AI in Climate Research: Enhancing Accuracy and Understanding of Climate Patterns 22. Green Computing: Reducing the Carbon Footprint of AI Systems Through Sustainable Practices




