Data Analytics and Artificial Intelligence for Earth Resource Management

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Publisher : Elsevier
ISBN 13 : 0443235961
Total Pages : 0 pages
Book Rating : 4.62/5 ( download)

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Book Synopsis Data Analytics and Artificial Intelligence for Earth Resource Management by : Deepak Kumar

Download or read book Data Analytics and Artificial Intelligence for Earth Resource Management written by Deepak Kumar and published by Elsevier. This book was released on 2024-11-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Data Science in Agriculture and Natural Resource Management

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Publisher : Springer Nature
ISBN 13 : 9811658471
Total Pages : 326 pages
Book Rating : 4.71/5 ( download)

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Book Synopsis Data Science in Agriculture and Natural Resource Management by : G. P. Obi Reddy

Download or read book Data Science in Agriculture and Natural Resource Management written by G. P. Obi Reddy and published by Springer Nature. This book was released on 2021-10-11 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to address emerging challenges in the field of agriculture and natural resource management using the principles and applications of data science (DS). The book is organized in three sections, and it has fourteen chapters dealing with specialized areas. The chapters are written by experts sharing their experiences very lucidly through case studies, suitable illustrations and tables. The contents have been designed to fulfil the needs of geospatial, data science, agricultural, natural resources and environmental sciences of traditional universities, agricultural universities, technological universities, research institutes and academic colleges worldwide. It will help the planners, policymakers and extension scientists in planning and sustainable management of agriculture and natural resources. The authors believe that with its uniqueness the book is one of the important efforts in the contemporary cyber-physical systems.

Artificial Intelligence and Data Science in Environmental Sensing

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Publisher : Academic Press
ISBN 13 : 0323905072
Total Pages : 326 pages
Book Rating : 4.77/5 ( download)

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Book Synopsis Artificial Intelligence and Data Science in Environmental Sensing by : Mohsen Asadnia

Download or read book Artificial Intelligence and Data Science in Environmental Sensing written by Mohsen Asadnia and published by Academic Press. This book was released on 2022-02-09 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence and Data Science in Environmental Sensing provides state-of-the-art information on the inexpensive mass-produced sensors that are used as inputs to artificial intelligence systems. The book discusses the advances of AI and Machine Learning technologies in material design for environmental areas. It is an excellent resource for researchers and professionals who work in the field of data processing, artificial intelligence sensors and environmental applications. Presents tools, connections and proactive solutions to take sustainability programs to the next level Offers a practical guide for making students proficient in modern electronic data analysis and graphics Provides knowledge and background to develop specific platforms related to environmental sensing, including control water, air and soil quality, water and wastewater treatment, desalination, pollution mitigation/control, and resource management and recovery

Data Science Applied to Sustainability Analysis

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Publisher : Elsevier
ISBN 13 : 0128179775
Total Pages : 312 pages
Book Rating : 4.72/5 ( download)

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Book Synopsis Data Science Applied to Sustainability Analysis by : Jennifer Dunn

Download or read book Data Science Applied to Sustainability Analysis written by Jennifer Dunn and published by Elsevier. This book was released on 2021-05-11 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science Applied to Sustainability Analysis focuses on the methodological considerations associated with applying this tool in analysis techniques such as lifecycle assessment and materials flow analysis. As sustainability analysts need examples of applications of big data techniques that are defensible and practical in sustainability analyses and that yield actionable results that can inform policy development, corporate supply chain management strategy, or non-governmental organization positions, this book helps answer underlying questions. In addition, it addresses the need of data science experts looking for routes to apply their skills and knowledge to domain areas. Presents data sources that are available for application in sustainability analyses, such as market information, environmental monitoring data, social media data and satellite imagery Includes considerations sustainability analysts must evaluate when applying big data Features case studies illustrating the application of data science in sustainability analyses

Artificial Intelligence Applied to Satellite-based Remote Sensing Data for Earth Observation

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Author :
Publisher : IET
ISBN 13 : 1839532122
Total Pages : 283 pages
Book Rating : 4.22/5 ( download)

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Book Synopsis Artificial Intelligence Applied to Satellite-based Remote Sensing Data for Earth Observation by : Maria Pia Del Rosso

Download or read book Artificial Intelligence Applied to Satellite-based Remote Sensing Data for Earth Observation written by Maria Pia Del Rosso and published by IET. This book was released on 2021-09-14 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows how artificial intelligence, including neural networks and deep learning, can be applied to the processing of satellite data for Earth observation. The authors explain how to develop a set of libraries for the implementation of artificial intelligence that encompass different aspects of research.

Big Data, Artificial Intelligence, and Data Analytics in Climate Change Research

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Publisher : Springer
ISBN 13 : 9789819716845
Total Pages : 0 pages
Book Rating : 4.45/5 ( download)

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Book Synopsis Big Data, Artificial Intelligence, and Data Analytics in Climate Change Research by : Gaurav Tripathi

Download or read book Big Data, Artificial Intelligence, and Data Analytics in Climate Change Research written by Gaurav Tripathi and published by Springer. This book was released on 2024-06-08 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Big Data, Artificial Intelligence, and Data Analytics in Climate Change Research

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Author :
Publisher : Springer Nature
ISBN 13 : 9819716853
Total Pages : 339 pages
Book Rating : 4.52/5 ( download)

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Book Synopsis Big Data, Artificial Intelligence, and Data Analytics in Climate Change Research by : Gaurav Tripathi

Download or read book Big Data, Artificial Intelligence, and Data Analytics in Climate Change Research written by Gaurav Tripathi and published by Springer Nature. This book was released on with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Federal Data Science

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Publisher : Academic Press
ISBN 13 : 012812444X
Total Pages : 258 pages
Book Rating : 4.44/5 ( download)

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Book Synopsis Federal Data Science by : Feras A. Batarseh

Download or read book Federal Data Science written by Feras A. Batarseh and published by Academic Press. This book was released on 2017-09-21 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Federal Data Science serves as a guide for federal software engineers, government analysts, economists, researchers, data scientists, and engineering managers in deploying data analytics methods to governmental processes. Driven by open government (2009) and big data (2012) initiatives, federal agencies have a serious need to implement intelligent data management methods, share their data, and deploy advanced analytics to their processes. Using federal data for reactive decision making is not sufficient anymore, intelligent data systems allow for proactive activities that lead to benefits such as: improved citizen services, higher accountability, reduced delivery inefficiencies, lower costs, enhanced national insights, and better policy making. No other government-dedicated work has been found in literature that addresses this broad topic. This book provides multiple use-cases, describes federal data science benefits, and fills the gap in this critical and timely area. Written and reviewed by academics, industry experts, and federal analysts, the problems and challenges of developing data systems for government agencies is presented by actual developers, designers, and users of those systems, providing a unique and valuable real-world perspective. Offers a range of data science models, engineering tools, and federal use-cases Provides foundational observations into government data resources and requirements Introduces experiences and examples of data openness from the US and other countries A step-by-step guide for the conversion of government towards data-driven policy making Focuses on presenting data models that work within the constraints of the US government Presents the why, the what, and the how of injecting AI into federal culture and software systems

The Power of Data: Driving Climate Change with Data Science and Artificial Intelligence Innovations

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Author :
Publisher : Springer Nature
ISBN 13 : 3031224566
Total Pages : 255 pages
Book Rating : 4.60/5 ( download)

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Book Synopsis The Power of Data: Driving Climate Change with Data Science and Artificial Intelligence Innovations by : Aboul Ella Hassanien

Download or read book The Power of Data: Driving Climate Change with Data Science and Artificial Intelligence Innovations written by Aboul Ella Hassanien and published by Springer Nature. This book was released on 2023-03-11 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Artificial Intelligence Methods in the Environmental Sciences

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Publisher : Springer Science & Business Media
ISBN 13 : 1402091192
Total Pages : 418 pages
Book Rating : 4.93/5 ( download)

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Book Synopsis Artificial Intelligence Methods in the Environmental Sciences by : Sue Ellen Haupt

Download or read book Artificial Intelligence Methods in the Environmental Sciences written by Sue Ellen Haupt and published by Springer Science & Business Media. This book was released on 2008-11-28 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can environmental scientists and engineers use the increasing amount of available data to enhance our understanding of planet Earth, its systems and processes? This book describes various potential approaches based on artificial intelligence (AI) techniques, including neural networks, decision trees, genetic algorithms and fuzzy logic. Part I contains a series of tutorials describing the methods and the important considerations in applying them. In Part II, many practical examples illustrate the power of these techniques on actual environmental problems. International experts bring to life ways to apply AI to problems in the environmental sciences. While one culture entwines ideas with a thread, another links them with a red line. Thus, a “red thread“ ties the book together, weaving a tapestry that pictures the ‘natural’ data-driven AI methods in the light of the more traditional modeling techniques, and demonstrating the power of these data-based methods.