Artificial Intelligence and Data Science in Environmental Sensing

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Author :
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 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.

Current Trends and Advances in Computer-Aided Intelligent Environmental Data Engineering

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Publisher : Academic Press
ISBN 13 : 0323855989
Total Pages : 475 pages
Book Rating : 4.83/5 ( download)

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Book Synopsis Current Trends and Advances in Computer-Aided Intelligent Environmental Data Engineering by : Goncalo Marques

Download or read book Current Trends and Advances in Computer-Aided Intelligent Environmental Data Engineering written by Goncalo Marques and published by Academic Press. This book was released on 2022-03-20 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: Current Trends and Advances in Computer-Aided Intelligent Environmental Data Engineering merges computer engineering and environmental engineering. The book presents the latest finding on how data science and AI-based tools are being applied in environmental engineering research. This application involves multiple domains such as data science and artificial intelligence to transform the data collected by intelligent sensors into relevant and reliable information to support decision-making. These tools include fuzzy logic, knowledge-based systems, particle swarm optimization, genetic algorithms, Monte Carlo simulation, artificial neural networks, support vector machine, boosted regression tree, simulated annealing, ant colony algorithm, decision tree, immune algorithm, and imperialist competitive algorithm. This book is a fundamental information source because it is the first book to present the foundational reference material in this new research field. Furthermore, it gives a critical overview of the latest cross-domain research findings and technological developments on the recent advances in computer-aided intelligent environmental data engineering. Captures the application of data science and artificial intelligence for a broader spectrum of environmental engineering problems Presents methods and procedures as well as case studies where state-of-the-art technologies are applied in actual environmental scenarios Offers a compilation of essential and critical reviews on the application of data science and artificial intelligence to the entire spectrum of environmental engineering

Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing

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Publisher : CRC Press
ISBN 13 : 1498774342
Total Pages : 508 pages
Book Rating : 4.45/5 ( download)

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Book Synopsis Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing by : Ni-Bin Chang

Download or read book Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing written by Ni-Bin Chang and published by CRC Press. This book was released on 2018-02-21 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last few years the scientific community has realized that obtaining a better understanding of interactions between natural systems and the man-made environment across different scales demands more research efforts in remote sensing. An integrated Earth system observatory that merges surface-based, air-borne, space-borne, and even underground sensors with comprehensive and predictive capabilities indicates promise for revolutionizing the study of global water, energy, and carbon cycles as well as land use and land cover changes. The aim of this book is to present a suite of relevant concepts, tools, and methods of integrated multisensor data fusion and machine learning technologies to promote environmental sustainability. The process of machine learning for intelligent feature extraction consists of regular, deep, and fast learning algorithms. The niche for integrating data fusion and machine learning for remote sensing rests upon the creation of a new scientific architecture in remote sensing science that is designed to support numerical as well as symbolic feature extraction managed by several cognitively oriented machine learning tasks at finer scales. By grouping a suite of satellites with similar nature in platform design, data merging may come to help for cloudy pixel reconstruction over the space domain or concatenation of time series images over the time domain, or even both simultaneously. Organized in 5 parts, from Fundamental Principles of Remote Sensing; Feature Extraction for Remote Sensing; Image and Data Fusion for Remote Sensing; Integrated Data Merging, Data Reconstruction, Data Fusion, and Machine Learning; to Remote Sensing for Environmental Decision Analysis, the book will be a useful reference for graduate students, academic scholars, and working professionals who are involved in the study of Earth systems and the environment for a sustainable future. The new knowledge in this book can be applied successfully in many areas of environmental science and engineering.

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.

Machine Learning Methods in the Environmental Sciences

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Publisher : Cambridge University Press
ISBN 13 : 0521791928
Total Pages : 364 pages
Book Rating : 4.22/5 ( download)

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Book Synopsis Machine Learning Methods in the Environmental Sciences by : William W. Hsieh

Download or read book Machine Learning Methods in the Environmental Sciences written by William W. Hsieh and published by Cambridge University Press. This book was released on 2009-07-30 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: A graduate textbook that provides a unified treatment of machine learning methods and their applications in the environmental sciences.

Reshaping Environmental Science Through Machine Learning and IoT

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Publisher : IGI Global
ISBN 13 :
Total Pages : 459 pages
Book Rating : 4.26/5 ( download)

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Book Synopsis Reshaping Environmental Science Through Machine Learning and IoT by : Gupta, Rajeev Kumar

Download or read book Reshaping Environmental Science Through Machine Learning and IoT written by Gupta, Rajeev Kumar and published by IGI Global. This book was released on 2024-05-06 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the face of escalating environmental challenges such as climate change, air and water pollution, and natural disasters, traditional approaches to understanding and addressing these issues have yet to be proven sufficient. Academic scholars are compelled to seek innovative solutions that marry digital intelligence and natural ecosystems. Reshaping Environmental Science Through Machine Learning and IoT serves as a comprehensive exploration into the transformative potential of Machine Learning (ML) and the Internet of Things (IoT) to address critical environmental challenges. The book establishes a robust foundation in ML and IoT, explaining their relevance to environmental science. As the narrative unfolds, it delves into diverse applications, providing theoretical insights alongside practical knowledge. From interpreting weather patterns to predicting air and water quality, the book navigates through the intricate web of environmental complexities. Notably, it unveils approaches to disaster management, waste sorting, and climate change monitoring, showcasing the symbiotic relationship between digital intelligence and natural ecosystems. This book is ideal for audiences from students and researchers to data scientists and disaster management professionals with a nuanced understanding of IoT, ML, and Artificial Intelligence (AI).

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:

Environmental Software Systems. Data Science in Action

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Publisher : Springer Nature
ISBN 13 : 3030398153
Total Pages : 284 pages
Book Rating : 4.56/5 ( download)

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Book Synopsis Environmental Software Systems. Data Science in Action by : Ioannis N. Athanasiadis

Download or read book Environmental Software Systems. Data Science in Action written by Ioannis N. Athanasiadis and published by Springer Nature. This book was released on 2020-01-29 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 13th IFIP WG 5.11 International Symposium on Environmental Software Systems, ISESS 2020, held in Wageningen, The Netherlands, in February 2020. The 22 full papers and 3 short papers were carefully reviewed and selected from 29 submissions. The papers cover a wide range of topics on environmental informatics, including data mining, artificial intelligence, high performance and cloud computing, visualization and smart sensing for environmental, earth, agricultural and food applications.