Emerging AI Applications in Earth Sciences Challenges, Impact and Analysis /
This proposed book provides deeper insights into artificial intelligence techniques and procedures available for earth sciences. This book unveils several applications of metaheuristic approaches (i.e., swarm intelligence and IoT technologies) in collaboration with AI for earth sciences. It presents...
محفوظ في:
| مؤلف مشترك: | |
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| مؤلفون آخرون: | , , , |
| التنسيق: | الكتروني كتاب الكتروني |
| اللغة: | الإنجليزية |
| منشور في: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2025.
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| الطبعة: | 1st ed. 2025. |
| سلاسل: | Sustainable Artificial Intelligence-Powered Applications, IEREK Interdisciplinary Series for Sustainable Development,
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://doi.org/10.1007/978-3-031-84583-3 |
| الوسوم: |
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| 245 | 1 | 0 | |a Emerging AI Applications in Earth Sciences |h [electronic resource] : |b Challenges, Impact and Analysis / |c edited by Chander Prabha, Md. Mehedi Hassan, Farhana Yasmin, Asif Karim. |
| 250 | |a 1st ed. 2025. | ||
| 264 | 1 | |a Cham : |b Springer Nature Switzerland : |b Imprint: Springer, |c 2025. | |
| 300 | |a 1 online resource (VI, 228 p. 70 illus.). |b 61 illus. in color. | ||
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| 490 | 1 | |a Sustainable Artificial Intelligence-Powered Applications, IEREK Interdisciplinary Series for Sustainable Development, |x 3005-1770 | |
| 505 | 0 | |a Chapter 1 Introduction to AI and IoT in the field of Earth Sciences -- Chapter 2. Growing Beyond the Earth: The Potential of Extra-Terrestrial Agriculture from Earth to Space -- Chapter 3. A Spatiotemporal Urban Growth Assessment in Bhopal, India from 1992 To 2042 using Machine Learning Algorithms -- Chapter 4. Emerging Areas and Applications in the Field of Earth Sciences -- Chapter 5. Integrating Deep Learning and IoT for Enhanced Monitoring and Sustainable Mining Practices -- Chapter 6. AI-Driven Insights into Fault Movements and Earthquake Dynamics -- Chapter 7. Harnessing Ai for Seismic Hazard Detection and Prediction: Innovations and Challenges -- Chapter 8. AI Techniques for Remote Monitoring -- Chapter 9. Role of AI in Estimating Potential Aftershocks During Earthquake -- Chapter 10. Advancements in Ozone Monitoring: Leveraging AI and ML for Environmental Protection -- Chapter 11. Quantum Computing in the Field of Earth Sciences -- Chapter 12. Machine Learning Approaches for Yield Prediction and Crop Management Optimization: A SLR -- Chapter 13. Resource Allocation in agriculture and Water Management fields -- Chapter 14. Optimising Crop Yields with Machine learning: Techniques and Applications -- Chapter 15. AI Trends Concerning Patterns, Anomalies, and Correlations for Predicting Earthquake Patterns -- Chapter 16. Future Trends and Challenges of AI And IoT for Earth Sciences. | |
| 520 | |a This proposed book provides deeper insights into artificial intelligence techniques and procedures available for earth sciences. This book unveils several applications of metaheuristic approaches (i.e., swarm intelligence and IoT technologies) in collaboration with AI for earth sciences. It presents the science behind smart technologies that reveal the power of artificial intelligence and IoT. These methodologies help to extract meaningful insights from earth sciences big data analytics. These advanced technologies used in earth science practices can remove geographical barriers, locally adaptive, operationally feasible, and economically affordable. The areas can be explored with the aim of digitizing the whole world. Technological advancement also impacts the financial aspect involved in managing the earth sciences. Intelligent AI applications have made significant strides in the field of earth sciences, offering novel solutions to complex challenges, driving impactful research, and revolutionizing data analysis and interpretation. This intersection of artificial intelligence and earth sciences has paved the way for an enhanced understanding of our planet and its various phenomena. | ||
| 532 | 8 | |a Accessibility summary: This PDF has been created in accordance with the PDF/UA-1 standard to enhance accessibility, including screen reader support, described non-text content (images, graphs), bookmarks for easy navigation, keyboard-friendly links and forms and searchable, selectable text. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. Please note that a more accessible version of this eBook is available as ePub. | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
| 588 | |a Print version record. | ||
| 650 | 0 | |a Computer science. | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Earth sciences. | |
| 650 | 1 | 4 | |a Computer Science. |
| 650 | 2 | 4 | |a Artificial Intelligence. |
| 650 | 2 | 4 | |a Machine Learning. |
| 650 | 2 | 4 | |a Earth Sciences. |
| 700 | 1 | |a Prabha, Chander. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Hassan, Md. Mehedi. |e editor. |0 (orcid)0000-0002-9890-0968 |1 https://orcid.org/0000-0002-9890-0968 |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Yasmin, Farhana. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Karim, Asif. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
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