Visualization Techniques For Climate Change With Machine Learning And Artificial Intelligence
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Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence
Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence covers computer-aided artificial intelligence and machine learning technologies as related to the impacts of climate change and its potential to prevent/remediate the effects. As such, different types of algorithms, mathematical relations and software models may help us to understand our current reality, predict future weather events and create new products and services to minimize human impact, chances of improving and saving lives and creating a healthier world. This book covers different types of tools for the prediction of climate change and alternative systems which can reduce the levels of threats observed by climate change scientists. Moreover, the book will help to achieve at least one of 17 sustainable development goals i.e., climate action. - Includes case studies on the application of AI and machine learning for monitoring climate change effects and management - Features applications of software and algorithms for modeling and forecasting climate change - Shows how real-time monitoring of specific factors (temperature, level of greenhouse gases, rain fall patterns, etc.) are responsible for climate change and possible mitigation efforts to achieve environmental sustainability
Artificial Intelligence and Machine Learning for Enhancing Resilience: Concepts, Applications, and Future Directions
As contemporary societies face unprecedented challenges such as mounting mental health issues, environmental crises, and socioeconomic insecurity, the urgency of developing objective, scalable, and dynamic methodologies to study resilience has never been greater. This book arises at the intersection of cutting-edge technology and human insight. It focuses on the possibility for AI and ML to transform resilience assessment, prediction, and interventions across the individual, organizational, and ecological levels. The chapters included in this book represent an organized synthesis of cutting-edge science, pragmatic applications, and prospective potential. With machine learning algorithms to estimate psychological resilience and AI-based models for climate change adaptation and ecosystem management, this book demonstrates the rich innovations that are emerging at the cross-sector of technology and resilience science. Perhaps most importantly, this book does not gloss over the urgent ethical, technical, and regulatory issues that arise when AI is introduced to sensitive topics such as mental health and environmental management. Questions about data privacy, algorithmic bias, model interpretability, and equitable technology deployment are thoroughly investigated, providing lessons learned and suggestions for moving ahead. A significant strength of this work is its global focus. Showcasing work from contributors of various methodologies and regions provides the latest views on new methodologies, strategies for practical implementation, and on what still needs to be invented. This guarantees that the publication engages with the messy socio-cultural and environmental contexts in which these interventions work and that it doesn’t just mirror technological possibilities. For academicians, practitioners, technologists, and policymakers, this book is both a fundamental reference and an outlook resource. It provides: Holistic examination of AI and ML in the context of psychological, organizational, and ecological resilience. In-depth reviews on methodological innovations, such as deep learning, natural language processing, and sensor-based assessments. Unprecedented appraisals of barriers to implementation, with ethical and regulatory considerations. We trust that this book will inspire conversation, fuel innovation, and support a future in which technology supplements, rather than replaces, human ability to adapt, recover, and flourish. We encourage readers to critique the content, to reflect on how AI, ML, and resilience intersect in their particular contexts, and to join us in shaping a future where technological and human resilience evolve together.
AI and Ecological Change for Sustainable Development
Artificial intelligence is a powerful tool when addressing ecological challenges and driving sustainable development. Using AI can optimize company resource management, reduce carbon footprints, and enhance biodiversity conversation. AI also allows companies to monitor environmental changes and improve climate growth and ecological preservation. As the world grapples with climate change and resource depletion, integrating AI into sustainability efforts offers innovative solutions to create a resilient, eco-friendly future, fostering harmony between technological progress and environmental stewardship. AI and Ecological Change for Sustainable Development explores the diverse array of case studies that highlight the AI initiatives and projects preserving ecology and sustainable development. It provides real-world examples from various countries and their effective use of AI to address environmental problems. This book covers topics such as AI, ecology, and sustainable development, and is an excellent resource for academics, researchers, educators, environmental scientists, and government officials.