The power of data : driving climate change with data science and artificial intelligence innovations / / edited by Aboul Ella Hassanien and Ashraf Darwish

• Record Nr.: UNISA996547968103316
• Pubbl/distr/stampa: Cham, Switzerland : , : Springer, , [2023]; ©2023
• ISBN: 3-031-22456-6
• Edizione: [1st ed. 2023.]
• Descrizione fisica: 1 online resource (255 pages)
• Collana: Studies in Big Data, , 2197-6511 ; ; 118
• Disciplina: 060
• Soggetti: Artificial intelligence; Environmental protection - Data processing; Green technology - Technological innovations
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Part 1: Artificial Intelligence in climate change Applications -- Chapter 1. Artificial Intelligence for Predicting Floods: A Climatic Change Phenomenon -- Chapter 2. Prediction of Climate Change Impact based on Air Flight CO2 Emissions Using Machine Learning: Towards Green Air Flights -- Chapter 3. The Impact of Artificial Intelligence on Waste Management for Climate Change -- Chapter 4. A Machine Learning-based Model for Predicting Temperature under the Effects of Climate Change -- Part 2: Emerging Technologies in Industry and Energy Sector -- Chapter 5. Prediction of CO2 Emission in Cars using Machine Learning Algorithms -- Chapter 6. Climate change: the challenge of Tunisia and previsions for renewable energy production -- Chapter 7. Clean Energy Management based on Internet of Things and Sensor Networks for Climate Change Problems -- Chapter 8. Digital Twin Technology for Energy Management Systems to Tackle Climate Change Challenges -- Chapter 9. The Role of Internet of Things in Mitigating the Effect of Climate Change: Case study: An ozone prediction model -- Part 3: Emerging Climate Change Technology in Agriculture Sector -- Chapter 10. Optimized Multi-Kernel Predictive Model for the Crop Prediction with Climate Factors and Soil Properties Optimized Multi-Kernel Predictive Model for the Crop Prediction with Climate Factors ; and Soil Properties -- Chapter 11. An Intelligent Crop Recommendation Model for the Three Strategic Crops in Egypt based on Climate Change Data -- Chapter 12. Cost Effective Decision Support System for Smart Water Management System -- Chapter 13. The Role of Artificial Intelligence in Water Management in Agriculture for Climate Change Impacts -- Part 4: Emerging Climate Change Technologies in Healthcare Sector -- Chapter 14. The Influence of Climate Change on the Re-Emergence of Malaria Using Artificial Intelligence.
• Sommario/riassunto: This book discusses the advances of artificial intelligence and data sciences in climate change and provides the power of the climate data that is used as inputs to artificial intelligence systems. It is a good resource for researchers and professionals who work in the field of data sciences, artificial intelligence, and climate change applications.