Decision Analytics For Sustainable Development In Smart Society 50

Author : Vikram Bali
Publisher : Springer Nature
ISBN 13 : 9811916896
Total Pages : 332 pages
Book Rating : 4.92/5 ( download)

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Download or read book Decision Analytics for Sustainable Development in Smart Society 5.0 written by Vikram Bali and published by Springer Nature. This book was released on 2022-06-23 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers sustainable development in smart society’s 5.0 using data analytics. The data analytics is the approach of integrating diversified heterogeneous data for predictive analysis to accredit innovation, decision making, business analysis, and strategic decision making. The data science brings together the research in the field of data analytics, online information analytics, and big data analytics to synthesize issues, challenges, and opportunities across smart society 5.0. Accordingly, the book offers an interesting and insightful read for researchers in the areas of decision analytics, cognitive analytics, big data analytics, visual analytics, text analytics, spatial analytics, risk analytics, graph analytics, predictive analytics, and analytics-enabled applications.

Author : Jorge Marx Gómez
Publisher : Springer Nature
ISBN 13 : 3031125274
Total Pages : 195 pages
Book Rating : 4.70/5 ( download)

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Download or read book Sustainable Development Through Data Analytics and Innovation written by Jorge Marx Gómez and published by Springer Nature. This book was released on 2022-09-26 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Simon Elias Bibri
Publisher : Springer
ISBN 13 : 3030173127
Total Pages : 337 pages
Book Rating : 4.28/5 ( download)

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Download or read book Big Data Science and Analytics for Smart Sustainable Urbanism written by Simon Elias Bibri and published by Springer. This book was released on 2019-05-30 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: We are living at the dawn of what has been termed ‘the fourth paradigm of science,’ a scientific revolution that is marked by both the emergence of big data science and analytics, and by the increasing adoption of the underlying technologies in scientific and scholarly research practices. Everything about science development or knowledge production is fundamentally changing thanks to the ever-increasing deluge of data. This is the primary fuel of the new age, which powerful computational processes or analytics algorithms are using to generate valuable knowledge for enhanced decision-making, and deep insights pertaining to a wide variety of practical uses and applications. This book addresses the complex interplay of the scientific, technological, and social dimensions of the city, and what it entails in terms of the systemic implications for smart sustainable urbanism. In concrete terms, it explores the interdisciplinary and transdisciplinary field of smart sustainable urbanism and the unprecedented paradigmatic shifts and practical advances it is undergoing in light of big data science and analytics. This new era of science and technology embodies an unprecedentedly transformative and constitutive power—manifested not only in the form of revolutionizing science and transforming knowledge, but also in advancing social practices, producing new discourses, catalyzing major shifts, and fostering societal transitions. Of particular relevance, it is instigating a massive change in the way both smart cities and sustainable cities are studied and understood, and in how they are planned, designed, operated, managed, and governed in the face of urbanization. This relates to what has been dubbed data-driven smart sustainable urbanism, an emerging approach based on a computational understanding of city systems and processes that reduces urban life to logical and algorithmic rules and procedures, while also harnessing urban big data to provide a more holistic and integrated view or synoptic intelligence of the city. This is increasingly being directed towards improving, advancing, and maintaining the contribution of both sustainable cities and smart cities to the goals of sustainable development. This timely and multifaceted book is aimed at a broad readership. As such, it will appeal to urban scientists, data scientists, urbanists, planners, engineers, designers, policymakers, philosophers of science, and futurists, as well as all readers interested in an overview of the pivotal role of big data science and analytics in advancing every academic discipline and social practice concerned with data–intensive science and its application, particularly in relation to sustainability.

Author : Kaile Zhou
Publisher : Springer Nature
ISBN 13 : 9811693609
Total Pages : 317 pages
Book Rating : 4.01/5 ( download)

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Download or read book Smart Energy Management written by Kaile Zhou and published by Springer Nature. This book was released on 2022-02-04 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a relatively whole view of data-driven decision-making methods for energy service innovation and energy system optimization. Through personalized energy services provision and energy efficiency improvement, the book can contribute to the green transformation of energy system and the sustainable development of the society. The book gives a new way to achieve smart energy management, based on various data mining and machine learning methods, including fuzzy clustering, shape-based clustering, ensemble clustering, deep learning, and reinforcement learning. The applications of these data-driven methods in improving energy efficiency and supporting energy service innovation are presented. Moreover, this book also investigates the role of blockchain in supporting peer-to-peer (P2P) electricity trading innovation, thus supporting smart energy management. The general scope of this book mainly includes load clustering, load forecasting, price-based demand response, incentive-based demand response, and energy blockchain-based electricity trading. The intended readership of the book includes researchers and engineers in related areas, graduate and undergraduate students in university, and some other general interested audience. The important features of the book are: (1) it introduces various data-driven methods for achieving different smart energy management tasks; (2) it investigates the role of data-driven methods in supporting various energy service innovation; and (3) it explores energy blockchain in P2P electricity trading, and thus supporting smart energy management.

Author : Ting Yu
Publisher : CRC Press
ISBN 13 : 1439895945
Total Pages : 443 pages
Book Rating : 4.48/5 ( download)

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Download or read book Computational Intelligent Data Analysis for Sustainable Development written by Ting Yu and published by CRC Press. This book was released on 2013-04-04 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 presents novel methodologies for automatically processing these types of data to support rational decision making for sustainable development. Through numerous case studies and applications, it illustrates important data analysis methods, including mathematical optimization, machine learning, signal processing, and temporal and spatial analysis, for quantifying and describing sustainable development problems. With a focus on integrated sustainability analysis, the book presents a large-scale quadratic programming algorithm to expand high-resolution input-output tables from the national scale to the multinational scale to measure the carbon footprint of the entire trade supply chain. It also quantifies the error or dispersion between different reclassification and aggregation schemas, revealing that aggregation errors have a high concentration over specific regions and sectors. The book summarizes the latest contributions of the data analysis community to climate change research. A profuse amount of climate data of various types is available, providing a rich and fertile playground for future data mining and machine learning research. The book also pays special attention to several critical challenges in the science of climate extremes that are not handled by the current generation of climate models. It discusses potential conceptual and methodological directions to build a close integration between physical understanding, or physics-based modeling, and data-driven insights. The book then covers the conservation of species and ecologically valuable land. A case study on the Pennsylvania Dirt and Gravel Roads Program demonstrates that multiple-objective linear programming is a more versatile and efficient approach than the widely used benefit targeting selection process. Moving on to renewable energy and the need for smart grids, the book explores how the ongoing transformation to a sustainable energy system of renewable sources leads to a paradigm shift from demand-driven generation to generation-driven demand. It shows how to maximize renewable energy as electricity by building a supergrid or mixing renewable sources with demand management and storage. It also presents intelligent data analysis for real-time detection of disruptive events from power system frequency data collected using an existing Internet-based frequency monitoring network as well as evaluates a set of computationally intelligent techniques for long-term wind resource assessment. In addition, the book gives an example of how temporal and spatial data analysis tools are used to gather knowledge about behavioral data and address important social problems such as criminal offenses. It also applies constraint logic programming to a planning problem: the environmental and social impact assessment of the regional energy plan of the Emilia-Romagna region of Italy. Sustainable development problems, such as global warming, resource shortages, global species loss, and pollution, push researchers to create powerful data analysis approaches that analysts can then use to gain insight into these issues to support rational decision making. This volume shows both the data analysis and sustainable development communities how to use intelligent data analysis tools to address practical problems and encourages researchers to develop better methods.

Author : Amit Joshi
Publisher : Springer Nature
ISBN 13 : 9813349018
Total Pages : 282 pages
Book Rating : 4.18/5 ( download)

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Download or read book Sustainable Intelligent Systems written by Amit Joshi and published by Springer Nature. This book was released on 2021-03-06 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses issues related to ICT, intelligent systems, data science, AI, machine learning, sustainable development and overall their impacts on sustainability. It provides an overview of the technologies of future. The book also discusses novel intelligent algorithms and their applications to move from a data-centric world to sustainable world. It includes research paradigms on sustainable development goals and societal impacts. The book provides an overview of cutting-edge techniques toward sustainability and ideas to help researchers who want to understand the challenges and opportunities of using smart management perspective for sustainable society. It serves as a reference to wide ranges of readers from computer science, data analysts, AI technocrats and management researchers.

Author : Carlos Filipe da Silva Portela
Publisher : Springer Nature
ISBN 13 : 3031305140
Total Pages : 457 pages
Book Rating : 4.46/5 ( download)

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Download or read book Sustainable, Innovative and Intelligent Societies and Cities written by Carlos Filipe da Silva Portela and published by Springer Nature. This book was released on 2023-06-09 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book combines two main topics applied to cities and societies: innovation and sustainability. The book begins by showing a brief overview of the book's main topics; then, the book addresses four main areas which allow our communities to be more attractive, engaging and fun; analytical, descriptive and predictive; healthy, secure and sustainable; and innovative, connected and monitored. This book represents a union of inputs from researchers and practitioners where each chapter has distinct, valuable and practical contributions that turn it unique. The content ranges from theoretical, like studies or analyses to practical, like industrial solutions or engaging systems. Both branches focus on turning our society more attractive, intelligent, inclusive, sustainable, and ready for the future.

Author : Uttam Ghosh
Publisher : Springer Nature
ISBN 13 : 3030720659
Total Pages : 411 pages
Book Rating : 4.50/5 ( download)

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Download or read book Machine Intelligence and Data Analytics for Sustainable Future Smart Cities written by Uttam Ghosh and published by Springer Nature. This book was released on 2021-05-31 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest advances in computational intelligence and data analytics for sustainable future smart cities. It focuses on computational intelligence and data analytics to bring together the smart city and sustainable city endeavors. It also discusses new models, practical solutions and technological advances related to the development and the transformation of cities through machine intelligence and big data models and techniques. This book is helpful for students and researchers as well as practitioners.

Author : Priyanka Mishra
Publisher : Springer Nature
ISBN 13 : 3031333543
Total Pages : 257 pages
Book Rating : 4.45/5 ( download)

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Download or read book Sustainable Smart Cities written by Priyanka Mishra and published by Springer Nature. This book was released on 2023-09-04 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the architecture, design and implementation of critical components of Sustainable Smart Cities to support governance, transportation, energy, healthcare, factories, technologies, securities, agriculture and education. The authors discuss the background of sustainable smart cities architectures and technologies and describe the problems that arise in design and implementation. In particular, this book discusses a proposed, 6G-based framework and architecture of IoT based sustainable smart cities. The authors describe the use of artificial intelligence in many zones of cities to increase the system's performance and efficiency. With the detailed discussion of energy management in smart cities, they have also presented how Internet of Vehicles (IoV) uses wireless communication and sensing technology to establish a network of information exchange between vehicles, infrastructure, and the environment. The discussion also includes Internet of Medical Things (IoMT) as well as Unmanned Aerial Vehicles (UAVs) for IoT based sustainable smart cities. This book explores societal, economic, and practical reforms that would promote smart cities, based on a variety of case studies.

Author : Neha Sharma
Publisher : Springer Nature
ISBN 13 : 9813343125
Total Pages : 314 pages
Book Rating : 4.22/5 ( download)

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Download or read book Open Data for Sustainable Community written by Neha Sharma and published by Springer Nature. This book was released on 2020-12-01 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an attempt to bring value to the enterprise pursuits in the areas of research and innovation around the specific issues in terms of topic selection, open data resources and researcher orientation. Over the last 300 years, industrial revolutions have had game-changing impact on societies. Presently, by and large, we are at the crossroads of the fourth industrial revolution, where phygital systems are going to play a massive role, where digital systems can simulate and go beyond the limitations of the physical world, thereby enabling a new world order. This transformation is cutting across every sphere known to mankind. The world will become a globally localized marketplace. In today’s business world, sustainability is a corporate agenda. Enterprises are also aiming to be purpose-driven, adaptive and resilient to disruptions. The contributions to community and environment are part of their corporate branding. The book explores and presents a part of the open data sets from government institutions to achieve the sustainable goals at local level, in turn contributing towards global mission. As the topic suggests, the authors are looking at some of the specific issues in the areas of environment, agriculture and health care through the lens of data science. The authors believe that the above three areas chosen have deep relevance in today’s world. The intent is to explore these issues from a data and analytics perspective and identify cracks through which deeper inroads can be made. Conscious efforts have been taken to make use of all the major data science techniques like prediction, classification, clustering, and correlation. Given the above background, deeper waters will be explored through the contents of this book.