Data Analytics And Artificial Intelligence For Earth Resource Management
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Data Analytics and Artificial Intelligence for Earth Resource Management
Data Analytics and Artificial Intelligence for Earth Resource Management offers a detailed look at the different ways data analytics and artificial intelligence can help organizations make better-informed decisions, improve operations, and minimize the negative impacts of resource extraction on the environment. The book explains several different ways data analytics and artificial intelligence can improve and support earth resource management. Predictive modeling can help organizations understand the impacts of different management decisions on earth resources, such as water availability, land use, and biodiversity.Resource monitoring tracks the state of earth resources in real-time, identifying issues and opportunities for improvement. Providing managers with real-time data and analytics allows them to make more informed choices. Optimizing resource management decisions help to identify the most efficient and effective ways to allocate resources. Predictive maintenance allows organizations to anticipate when equipment might fail and take action to prevent it, reducing downtime and maintenance costs. Remote sensing with image processing and analysis can be used to extract information from satellite images and other remote sensing data, providing valuable information on land use, water resources, and other earth resources. - Provides a comprehensive understanding of data analytics and artificial intelligence (AI) for earth resource management - Includes real-world case studies and examples to demonstrate the practical applications of data analytics and AI in earth resource management - Presents clear illustrations, diagrams, and pictures that make the content more understandable and engaging
Big Data, Artificial Intelligence, and Data Analytics in Climate Change Research
This book explores the potential of big data, artificial intelligence (AI), and data analytics to address climate change and achieve the Sustainable Development Goals (SDGs). Furthermore, the book covers a wide range of related topics, including climate change data sources, big data analytics techniques, remote sensing, renewable energy, open data, public–private partnerships, ethical and legal issues, and case studies of successful applications. The book also discusses the challenges and opportunities presented by these technologies and provides insights into future research directions. In order to address climate change and achieve the SDGs, it is crucial to understand the complex interplay between climate and environmental factors. The use of big data, AI, and data analytics can play a vital role in this effort by providing the means to collect, process, and analyze vast amounts of environmental data. This book is an essential resource for researchers, policymakers, and practitioners interested in leveraging these technologies to tackle the pressing challenge of climate change and achieve the SDGs.
AI Innovation for Water Policy and Sustainability
Author: Manish Kumar Goyal
language: en
Publisher: Springer Nature
Release Date: 2024-10-05
In the face of unprecedented challenges in managing water resources, the integration of artificial intelligence (AI) emerges as a revolutionary force, reshaping the landscape of water conservation, treatment, irrigation, policy formulation, watershed management, and the monitoring of groundwater and surface water. This book explores the transformative role of AI in the water domain, exploring cutting-edge applications and innovative solutions that promise to address pressing issues in sustainable water management. As we navigate the complexities of a changing climate, population growth, and urbanization, the chapters within this book offer insights into how AI technologies can enhance efficiency, optimize resource utilization, and provide data-driven strategies for ensuring the resilience and sustainability of our vital water ecosystems. From intelligent water treatment systems to precision agriculture and policy decision support, each chapter unfolds a narrative of AI-driven advancements, providing a comprehensive guide for researchers, practitioners, and policymakers navigating the intersection of artificial intelligence and water management.