Data Science Applied to Sustainability Analysis

Data Science Applied to Sustainability Analysis
Author: Jennifer Dunn,Prasanna Balaprakash
Publsiher: Elsevier
Total Pages: 312
Release: 2021-05-11
Genre: Science
ISBN: 9780128179772

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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

Sustainable Development Through Data Analytics and Innovation

Sustainable Development Through Data Analytics and Innovation
Author: Jorge Marx Gómez,Lawal O. Yesufu
Publsiher: Springer Nature
Total Pages: 195
Release: 2022-09-26
Genre: Computers
ISBN: 9783031125270

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Sustainable development is based on the idea that societies should advance without compromising their future development requirements. This book explores how the application of data analytics and digital technologies can ensure that development changes are executed on the basis of factual data and information. It addresses how innovations that rely on digital technologies can support sustainable development across all sectors and all social, economic, and environmental aspects and help us achieve the Sustainable Development Goals (SDGs). The book also highlights techniques, processes, models, tools, and practices used to achieve sustainable development through data analysis. The various topics covered in this book are critically evaluated, not only theoretically, but also from an application perspective. It will be of interest to researchers and students, especially those in the fields of applied data analytics, business intelligence and knowledge management.

Computational Intelligent Data Analysis for Sustainable Development

Computational Intelligent Data Analysis for Sustainable Development
Author: Ting Yu,Nitesh Chawla,Simeon Simoff
Publsiher: CRC Press
Total Pages: 443
Release: 2016-04-19
Genre: Business & Economics
ISBN: 9781439895955

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Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. Computational Intelligent Data Analysis for Sustainable Development present

Artificial Intelligence and Data Science in Environmental Sensing

Artificial Intelligence and Data Science in Environmental Sensing
Author: Mohsen Asadnia,Amir Razmjou,Amin Beheshti
Publsiher: Academic Press
Total Pages: 326
Release: 2022-02-09
Genre: Computers
ISBN: 9780323905077

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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

Novel AI and Data Science Advancements for Sustainability in the Era of COVID 19

Novel AI and Data Science Advancements for Sustainability in the Era of COVID 19
Author: Victor Chang,Mohamed Abdel-Basset,Muthu Ramachandran,Nicolas Green,Gary Wills
Publsiher: Academic Press
Total Pages: 294
Release: 2022-04-05
Genre: Medical
ISBN: 9780323903783

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Novel AI and Data Science Advancements for Sustainability in the Era of COVID-19 discusses how the role of recent technologies applied to health settings can help fight virus outbreaks. Moreover, it provides guidelines on how governments and institutions should prepare and quickly respond to drastic situations using technology to support their communities in order to maintain life and functional as efficiently as possible. The book discusses topics such as AI-driven histopathology analysis for COVID-19 diagnosis, bioinformatics for subtype rational drug design, deep learning-based treatment evaluation and outcome prediction, sensor informatics for monitoring infected patients, and machine learning for tracking and prediction models. In addition, the book presents AI solutions for hospital management during an epidemic or pandemic, along with real-world solutions and case studies of successful measures to support different types of communities. This is a valuable source for medical informaticians, bioinformaticians, clinicians and other healthcare workers and researchers who are interested in learning more on how recently developed technologies can help us fight and minimize the effects of global pandemics. Discusses AI advancements in predictive and decision modeling and how to design mobile apps to track contagion spread Presents the smart contract concept in blockchain and cryptography technology to guarantee security and privacy of people’s data once their information has been used to fight the pandemic Encompasses guidelines for emergency preparedness, planning, recovery and continuity management of communities to support people in emergencies like a virus outbreak

CIGOS 2021 Emerging Technologies and Applications for Green Infrastructure

CIGOS 2021  Emerging Technologies and Applications for Green Infrastructure
Author: Cuong Ha-Minh,Anh Minh Tang,Tinh Quoc Bui,Xuan Hong Vu,Dat Vu Khoa Huynh
Publsiher: Springer Nature
Total Pages: 1861
Release: 2021-10-28
Genre: Science
ISBN: 9789811671609

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This book highlights the key role of green infrastructure (GI) in providing natural and ecosystem solutions, helping alleviate many of the environmental, social, and economic problems caused by rapid urbanization. The book gathers the emerging technologies and applications in various disciplines involving geotechnics, civil engineering, and structures, which are presented in numerous high-quality papers by worldwide researchers, practitioners, policymakers, and entrepreneurs at the 6th CIGOS event, 2021. Moreover, by sharing knowledge and experiences around emerging GI technologies and policy issues, the book aims at encouraging adoption of GI technologies as well as building capacity for implementing GI practices at all scales. This book is useful for researchers and professionals in designing, building, and managing sustainable buildings and infrastructure.

Research Handbook on Big Data Law

Research Handbook on Big Data Law
Author: Roland Vogl
Publsiher: Edward Elgar Publishing
Total Pages: 544
Release: 2021-05-28
Genre: Law
ISBN: 9781788972826

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This state-of-the-art Research Handbook provides an overview of research into, and the scope of current thinking in, the field of big data analytics and the law. It contains a wealth of information to survey the issues surrounding big data analytics in legal settings, as well as legal issues concerning the application of big data techniques in different domains.

Introduction to Environmental Data Science

Introduction to Environmental Data Science
Author: Jerry Davis
Publsiher: CRC Press
Total Pages: 492
Release: 2023-03-13
Genre: Business & Economics
ISBN: 9781000842418

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Introduction to Environmental Data Science focuses on data science methods in the R language applied to environmental research, with sections on exploratory data analysis in R including data abstraction, transformation, and visualization; spatial data analysis in vector and raster models; statistics and modelling ranging from exploratory to modelling, considering confirmatory statistics and extending to machine learning models; time series analysis, focusing especially on carbon and micrometeorological flux; and communication. Introduction to Environmental Data Science is an ideal textbook to teach undergraduate to graduate level students in environmental science, environmental studies, geography, earth science, and biology, but can also serve as a reference for environmental professionals working in consulting, NGOs, and government agencies at the local, state, federal, and international levels. Features • Gives thorough consideration of the needs for environmental research in both spatial and temporal domains. • Features examples of applications involving field-collected data ranging from individual observations to data logging. • Includes examples also of applications involving government and NGO sources, ranging from satellite imagery to environmental data collected by regulators such as EPA. • Contains class-tested exercises in all chapters other than case studies. Solutions manual available for instructors. • All examples and exercises make use of a GitHub package for functions and especially data.