Artificial Intelligence And Data Science In Environmental Sensing

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Artificial Intelligence and Data Science in Environmental Sensing

Mohsen Asadnia,Amir Razmjou,Amin Beheshti
Artificial Intelligence and Data Science in Environmental Sensing Book PDF

Author : Mohsen Asadnia,Amir Razmjou,Amin Beheshti
Publisher : Academic Press
Page : 326 pages
File Size : 54,8 Mb
Release : 2022-02-09
Category : Computers
ISBN : 9780323905077

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Artificial Intelligence and Data Science in Environmental Sensing by Mohsen Asadnia,Amir Razmjou,Amin Beheshti Pdf

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

Artificial Intelligence Methods in the Environmental Sciences

Sue Ellen Haupt,Antonello Pasini,Caren Marzban
Artificial Intelligence Methods in the Environmental Sciences Book PDF

Author : Sue Ellen Haupt,Antonello Pasini,Caren Marzban
Publisher : Springer Science & Business Media
Page : 418 pages
File Size : 45,8 Mb
Release : 2008-11-28
Category : Science
ISBN : 9781402091193

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Artificial Intelligence Methods in the Environmental Sciences by Sue Ellen Haupt,Antonello Pasini,Caren Marzban Pdf

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.

Data Science Applied to Sustainability Analysis

Jennifer Dunn,Prasanna Balaprakash
Data Science Applied to Sustainability Analysis Book PDF

Author : Jennifer Dunn,Prasanna Balaprakash
Publisher : Elsevier
Page : 312 pages
File Size : 46,9 Mb
Release : 2021-05-11
Category : Science
ISBN : 9780128179772

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Data Science Applied to Sustainability Analysis by Jennifer Dunn,Prasanna Balaprakash Pdf

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

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

Goncalo Marques,Joshua O. Ighalo
Current Trends and Advances in Computer Aided Intelligent Environmental Data Engineering Book PDF

Author : Goncalo Marques,Joshua O. Ighalo
Publisher : Academic Press
Page : 475 pages
File Size : 41,9 Mb
Release : 2022-03-20
Category : Computers
ISBN : 9780323855983

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Current Trends and Advances in Computer-Aided Intelligent Environmental Data Engineering by Goncalo Marques,Joshua O. Ighalo Pdf

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

Ni-Bin Chang,Kaixu Bai
Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing Book PDF

Author : Ni-Bin Chang,Kaixu Bai
Publisher : CRC Press
Page : 508 pages
File Size : 54,6 Mb
Release : 2018-02-21
Category : Technology & Engineering
ISBN : 9781498774345

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Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing by Ni-Bin Chang,Kaixu Bai Pdf

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.

Machine Learning Methods in the Environmental Sciences

William W. Hsieh
Machine Learning Methods in the Environmental Sciences Book PDF

Author : William W. Hsieh
Publisher : Cambridge University Press
Page : 364 pages
File Size : 53,9 Mb
Release : 2009-07-30
Category : Computers
ISBN : 9780521791922

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Machine Learning Methods in the Environmental Sciences by William W. Hsieh Pdf

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

Gupta, Rajeev Kumar,Jain, Arti,Wang, John,Pateriya, Rajesh Kumar
Reshaping Environmental Science Through Machine Learning and IoT Book PDF

Author : Gupta, Rajeev Kumar,Jain, Arti,Wang, John,Pateriya, Rajesh Kumar
Publisher : IGI Global
Page : 459 pages
File Size : 53,9 Mb
Release : 2024-05-06
Category : Technology & Engineering
ISBN : 9798369323526

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Reshaping Environmental Science Through Machine Learning and IoT by Gupta, Rajeev Kumar,Jain, Arti,Wang, John,Pateriya, Rajesh Kumar Pdf

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).

Environmental Software Systems. Data Science in Action

Ioannis N. Athanasiadis,Steven P. Frysinger,Gerald Schimak,Willem Jan Knibbe
Environmental Software Systems Data Science in Action Book PDF

Author : Ioannis N. Athanasiadis,Steven P. Frysinger,Gerald Schimak,Willem Jan Knibbe
Publisher : Springer Nature
Page : 284 pages
File Size : 41,5 Mb
Release : 2020-01-29
Category : Computers
ISBN : 9783030398156

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Environmental Software Systems. Data Science in Action by Ioannis N. Athanasiadis,Steven P. Frysinger,Gerald Schimak,Willem Jan Knibbe Pdf

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.

Computers in Earth and Environmental Sciences

Hamid Reza Pourghasemi
Computers in Earth and Environmental Sciences Book PDF

Author : Hamid Reza Pourghasemi
Publisher : Elsevier
Page : 704 pages
File Size : 47,8 Mb
Release : 2021-09-22
Category : Computers
ISBN : 9780323886154

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Computers in Earth and Environmental Sciences by Hamid Reza Pourghasemi Pdf

Computers in Earth and Environmental Sciences: Artificial Intelligence and Advanced Technologies in Hazards and Risk Management addresses the need for a comprehensive book that focuses on multi-hazard assessments, natural and manmade hazards, and risk management using new methods and technologies that employ GIS, artificial intelligence, spatial modeling, machine learning tools and meta-heuristic techniques. The book is clearly organized into four parts that cover natural hazards, environmental hazards, advanced tools and technologies in risk management, and future challenges in computer applications to hazards and risk management. Researchers and professionals in Earth and Environmental Science who require the latest technologies and advances in hazards, remote sensing, geosciences, spatial modeling and machine learning will find this book to be an invaluable source of information on the latest tools and technologies available. Covers advanced tools and technologies in risk management of hazards in both the Earth and Environmental Sciences Details the benefits and applications of various technologies to assist researchers in choosing the most appropriate techniques for purpose Expansively covers specific future challenges in the use of computers in Earth and Environmental Science Includes case studies that detail the applications of the discussed technologies down to individual hazards

Introduction to Environmental Data Science

William W. Hsieh
Introduction to Environmental Data Science Book PDF

Author : William W. Hsieh
Publisher : Cambridge University Press
Page : 650 pages
File Size : 50,6 Mb
Release : 2022-12-31
Category : Science
ISBN : 9781009301800

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Introduction to Environmental Data Science by William W. Hsieh Pdf

Statistical and machine learning methods have many applications in the environmental sciences, including prediction and data analysis in meteorology, hydrology and oceanography, pattern recognition for satellite images from remote sensing, management of agriculture and forests, assessment of climate change, and much more. With rapid advances in machine learning in the last decade, this book provides an urgently needed, comprehensive guide to machine learning and statistics for students and researchers interested in environmental data science. It includes intuitive explanations covering the relevant background mathematics, with examples drawn from the environmental sciences. A broad range of topics are covered, including correlation, regression, classification, clustering, neural networks, random forests, boosting, kernel methods, evolutionary algorithms, and deep learning, as well as the recent merging of machine learning and physics. End-of-chapter exercises allow readers to develop their problem-solving skills and online data sets allow readers to practise analysis of real data.

AI 2022: Advances in Artificial Intelligence

Haris Aziz,Débora Corrêa,Tim French
AI 2022 Advances in Artificial Intelligence Book PDF

Author : Haris Aziz,Débora Corrêa,Tim French
Publisher : Springer Nature
Page : 825 pages
File Size : 50,9 Mb
Release : 2022-12-02
Category : Computers
ISBN : 9783031226953

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AI 2022: Advances in Artificial Intelligence by Haris Aziz,Débora Corrêa,Tim French Pdf

This book constitutes the refereed proceedings of the 35th Australasian Joint Conference on Artificial Intelligence, AI 2022, which took place in Perth, WA, Australia, in December 5–8, 2022. The 56 full papers included in this book were carefully reviewed and selected from 90 submissions. They were organized in topical sections as follows: Computer Vision; Deep Learning; Ethical/Explainable AI; Genetic Algorithms; Knowledge Representation and NLP; Machine Learning; Medical AI; Optimization; and Reinforcement Learning.

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

Gaurav Tripathi,Achala Shakya,Shruti Kanga,Suraj Kumar Singh,Praveen Kumar Rai
Big Data Artificial Intelligence and Data Analytics in Climate Change Research Book PDF

Author : Gaurav Tripathi,Achala Shakya,Shruti Kanga,Suraj Kumar Singh,Praveen Kumar Rai
Publisher : Springer
Page : 0 pages
File Size : 40,5 Mb
Release : 2024-06-08
Category : Science
ISBN : 9819716845

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Big Data, Artificial Intelligence, and Data Analytics in Climate Change Research by Gaurav Tripathi,Achala Shakya,Shruti Kanga,Suraj Kumar Singh,Praveen Kumar Rai Pdf

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.

Intelligent Data Engineering and Automated Learning – IDEAL 2023

Paulo Quaresma,David Camacho,Hujun Yin,Teresa Gonçalves,Vicente Julian,Antonio J. Tallón-Ballesteros
Intelligent Data Engineering and Automated Learning IDEAL 2023 Book PDF

Author : Paulo Quaresma,David Camacho,Hujun Yin,Teresa Gonçalves,Vicente Julian,Antonio J. Tallón-Ballesteros
Publisher : Springer Nature
Page : 561 pages
File Size : 53,5 Mb
Release : 2023-12-16
Category : Computers
ISBN : 9783031482328

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Intelligent Data Engineering and Automated Learning – IDEAL 2023 by Paulo Quaresma,David Camacho,Hujun Yin,Teresa Gonçalves,Vicente Julian,Antonio J. Tallón-Ballesteros Pdf

This book constitutes the proceedings of the 24th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2023, held in Évora, Portugal, during November 22–24, 2023. The 45 full papers and 4 short papers presented in this book were carefully reviewed and selected from 77 submissions. IDEAL 2023 is focusing on big data challenges, machine learning, deep learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspired models, agents and hybrid intelligent systems, and real-world applications of intelligence techniques and AI. The papers are organized in the following topical sections: main track; special session on federated learning and (pre) aggregation in machine learning; special session on intelligent techniques for real-world applications of renewable energy and green transport; and special session on data selection in machine learning.

Evolutionary Computing and Mobile Sustainable Networks

V. Suma,Noureddine Bouhmala,Haoxiang Wang
Evolutionary Computing and Mobile Sustainable Networks Book PDF

Author : V. Suma,Noureddine Bouhmala,Haoxiang Wang
Publisher : Springer Nature
Page : 975 pages
File Size : 43,9 Mb
Release : 2020-07-31
Category : Technology & Engineering
ISBN : 9789811552588

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Evolutionary Computing and Mobile Sustainable Networks by V. Suma,Noureddine Bouhmala,Haoxiang Wang Pdf

This book features selected research papers presented at the International Conference on Evolutionary Computing and Mobile Sustainable Networks (ICECMSN 2020), held at the Sir M. Visvesvaraya Institute of Technology on 20–21 February 2020. Discussing advances in evolutionary computing technologies, including swarm intelligence algorithms and other evolutionary algorithm paradigms which are emerging as widely accepted descriptors for mobile sustainable networks virtualization, optimization and automation, this book is a valuable resource for researchers in the field of evolutionary computing and mobile sustainable networks.

Intelligent Environmental Data Monitoring for Pollution Management

Siddhartha Bhattacharyya,Naba Kumar Mondal,Jan Platos,Vaclav Snasel,Pavel Kromer
Intelligent Environmental Data Monitoring for Pollution Management Book PDF

Author : Siddhartha Bhattacharyya,Naba Kumar Mondal,Jan Platos,Vaclav Snasel,Pavel Kromer
Publisher : Academic Press
Page : 346 pages
File Size : 51,8 Mb
Release : 2020-10-22
Category : Technology & Engineering
ISBN : 9780128199244

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Intelligent Environmental Data Monitoring for Pollution Management by Siddhartha Bhattacharyya,Naba Kumar Mondal,Jan Platos,Vaclav Snasel,Pavel Kromer Pdf

Intelligent Environmental Data Monitoring for Pollution Management discusses evolving novel intelligent algorithms and their applications in the area of environmental data-centric systems guided by batch process-oriented data. Thus, the book ushers in a new era as far as environmental pollution management is concerned. It reviews the fundamental concepts of gathering, processing and analyzing data from batch processes, followed by a review of intelligent tools and techniques which can be used in this direction. In addition, it discusses novel intelligent algorithms for effective environmental pollution data management that are on par with standards laid down by the World Health Organization. Introduces novel intelligent techniques needed to address environmental pollution for the well-being of the global environment Offers perspectives on the design, development and commissioning of intelligent applications Provides reviews on the latest intelligent technologies and algorithms related to state-of-the-art methodologies surrounding the monitoring and mitigation of environmental pollution Puts forth insights on future generation intelligent pollution monitoring techniques