› › Data Driven Modeling Monitoring And Control For Smart And Connected Systems

Handbook of Research on Data-Driven Mathematical Modeling in Smart Cities

Author : Pramanik, Sabyasachi

Publisher : IGI Global

Page : 499 pages

File Size : 11,99 MB

Release : 2023-02-17

Category : Mathematics

ISBN : 1668464101

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Book Description

A smart city utilizes ICT technologies to improve the working effectiveness, share various data with the citizens, and enhance political assistance and societal wellbeing. The fundamental needs of a smart and sustainable city are utilizing smart technology for enhancing municipal activities, expanding monetary development, and improving citizens’ standards of living. The Handbook of Research on Data-Driven Mathematical Modeling in Smart Cities discusses new mathematical models in smart and sustainable cities using big data, visualization tools in mathematical modeling, machine learning-based mathematical modeling, and more. It further delves into privacy and ethics in data analysis. Covering topics such as deep learning, optimization-based data science, and smart city automation, this premier reference source is an excellent resource for mathematicians, statisticians, computer scientists, civil engineers, government officials, students and educators of higher education, librarians, researchers, and academicians.



Machine Learning Approach for Cloud Data Analytics in IoT

Author : Sachi Nandan Mohanty

Publisher : John Wiley & Sons

Page : 528 pages

File Size : 12,74 MB

Release : 2021-07-14

Category : Computers

ISBN : 1119785855

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Book Description

Machine Learning Approach for Cloud Data Analytics in IoT The book covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications Sustainable computing paradigms like cloud and fog are capable of handling issues related to performance, storage and processing, maintenance, security, efficiency, integration, cost, energy and latency in an expeditious manner. In order to expedite decision-making involved in the complex computation and processing of collected data, IoT devices are connected to the cloud or fog environment. Since machine learning as a service provides the best support in business intelligence, organizations have been making significant investments in this technology. Machine Learning Approach for Cloud Data Analytics in IoT elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.



Smart Sustainable Cities of the Future

Author : Simon Elias Bibri

Publisher : Springer

Page : 685 pages

File Size : 28,13 MB

Release : 2018-02-24

Category : Political Science

ISBN : 3319739816

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Book Description

This book is intended to help explore the field of smart sustainable cities in its complexity, heterogeneity, and breadth, the many faces of a topical subject of major importance for the future that encompasses so much of modern urban life in an increasingly computerized and urbanized world. Indeed, sustainable urban development is currently at the center of debate in light of several ICT visions becoming achievable and deployable computing paradigms, and shaping the way cities will evolve in the future and thus tackle complex challenges. This book integrates computer science, data science, complexity science, sustainability science, system thinking, and urban planning and design. As such, it contains innovative computer–based and data–analytic research on smart sustainable cities as complex and dynamic systems. It provides applied theoretical contributions fostering a better understanding of such systems and the synergistic relationships between the underlying physical and informational landscapes. It offers contributions pertaining to the ongoing development of computer–based and data science technologies for the processing, analysis, management, modeling, and simulation of big and context data and the associated applicability to urban systems that will advance different aspects of sustainability. This book seeks to explicitly bring together the smart city and sustainable city endeavors, and to focus on big data analytics and context-aware computing specifically. In doing so, it amalgamates the design concepts and planning principles of sustainable urban forms with the novel applications of ICT of ubiquitous computing to primarily advance sustainability. Its strength lies in combining big data and context–aware technologies and their novel applications for the sheer purpose of harnessing and leveraging the disruptive and synergetic effects of ICT on forms of city planning that are required for future forms of sustainable development. This is because the effects of such technologies reinforce one another as to their efforts for transforming urban life in a sustainable way by integrating data–centric and context–aware solutions for enhancing urban systems and facilitating coordination among urban domains. This timely and comprehensive book is aimed at a wide audience across science, academia industry, and policymaking. It provides the necessary material to inform relevant research communities of the state–of–the–art research and the latest development in the area of smart sustainable urban development, as well as a valuable reference for planners, designers, strategists, and ICT experts who are working towards the development and implementation of smart sustainable cities based on big data analytics and context–aware computing.



Intelligent Data-Driven Modelling and Optimization in Power and Energy Applications

Author : B Rajanarayan Prusty

Publisher : CRC Press

Page : 253 pages

File Size : 10,34 MB

Release : 2024-05-09

Category : Technology & Engineering

ISBN : 1040016111

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Book Description

This book provides a comprehensive understanding of how intelligent data-driven techniques can be used for modelling, controlling, and optimizing various power and energy applications. It aims to develop multiple data-driven models for forecasting renewable energy sources and to interpret the benefits of these techniques in line with first-principles modelling approaches. By doing so, the book aims to stimulate deep insights into computational intelligence approaches in data-driven models and to promote their potential applications in the power and energy sectors. Its key features include: an exclusive section on essential preprocessing approaches for the data-driven model a detailed overview of data-driven model applications to power system planning and operational activities specific focus on developing forecasting models for renewable generations such as solar PV and wind power, and showcasing the judicious amalgamation of allied mathematical treatments such as optimization and fractional calculus in data-driven model-based frameworks This book presents novel concepts for applying data-driven models, mainly in the power and energy sectors, and is intended for graduate students, industry professionals, research, and academic personnel.





Implementing Data-Driven Strategies in Smart Cities

Author : Didier Grimaldi

Publisher : Elsevier

Page : 258 pages

File Size : 38,71 MB

Release : 2021-09-18

Category : Social Science

ISBN : 0128211237

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Book Description

Implementing Data-Driven Strategies in Smart Cities is a guidebook and roadmap for practitioners seeking to operationalize data-driven urban interventions. The book opens by exploring the revolution that big data, data science, and the Internet of Things are making feasible for the city. It explores alternate topologies, typologies, and approaches to operationalize data science in cities, drawn from global examples including top-down, bottom-up, greenfield, brownfield, issue-based, and data-driven. It channels and expands on the classic data science model for data-driven urban interventions – data capture, data quality, cleansing and curation, data analysis, visualization and modeling, and data governance, privacy, and confidentiality. Throughout, illustrative case studies demonstrate successes realized in such diverse cities as Barcelona, Cologne, Manila, Miami, New York, Nancy, Nice, São Paulo, Seoul, Singapore, Stockholm, and Zurich. Given the heavy emphasis on global case studies, this work is particularly suitable for any urban manager, policymaker, or practitioner responsible for delivering technological services for the public sector from sectors as diverse as energy, transportation, pollution, and waste management. - Explores numerous specific urban interventions drawn from global case studies, helping readers understand real urban challenges and create data-driven solutions - Provides a step-by-step and applied holistic guide and methodology for immediate application in the reader's own business agenda - Presents cutting edge technology presentation with coverage of innovations such as the Internet of Things, robotics, 5G, edge/fog computing, blockchain, intelligent transport systems, and connected-automated mobility



Dynamic Mode Decomposition

Author : J. Nathan Kutz

Publisher : SIAM

Page : 241 pages

File Size : 12,8 MB

Release : 2016-11-23

Category : Science

ISBN : 1611974496

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Book Description

Data-driven dynamical systems is a burgeoning field?it connects how measurements of nonlinear dynamical systems and/or complex systems can be used with well-established methods in dynamical systems theory. This is a critically important new direction because the governing equations of many problems under consideration by practitioners in various scientific fields are not typically known. Thus, using data alone to help derive, in an optimal sense, the best dynamical system representation of a given application allows for important new insights. The recently developed dynamic mode decomposition (DMD) is an innovative tool for integrating data with dynamical systems theory. The DMD has deep connections with traditional dynamical systems theory and many recent innovations in compressed sensing and machine learning. Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems, the first book to address the DMD algorithm, presents a pedagogical and comprehensive approach to all aspects of DMD currently developed or under development; blends theoretical development, example codes, and applications to showcase the theory and its many innovations and uses; highlights the numerous innovations around the DMD algorithm and demonstrates its efficacy using example problems from engineering and the physical and biological sciences; and provides extensive MATLAB code, data for intuitive examples of key methods, and graphical presentations.



Proceedings of Sixth International Congress on Information and Communication Technology

Author : Xin-She Yang

Publisher : Springer Nature

Page : 1058 pages

File Size : 10,76 MB

Release : 2021-09-09

Category : Technology & Engineering

ISBN : 9811617813

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Book Description

This book gathers selected high-quality research papers presented at the Sixth International Congress on Information and Communication Technology, held at Brunel University, London, on February 25–26, 2021. It discusses emerging topics pertaining to information and communication technology (ICT) for managerial applications, e-governance, e-agriculture, e-education and computing technologies, the Internet of things (IoT) and e-mining. Written by respected experts and researchers working on ICT, the book offers a valuable asset for young researchers involved in advanced studies. The book is presented in four volumes.



IEC 61850-Based Smart Substations

Author : Yubo Yuan

Publisher : Academic Press

Page : 456 pages

File Size : 11,61 MB

Release : 2019-06-12

Category : Technology & Engineering

ISBN : 0128151595

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Book Description

IEC 61850-Based Smart Substations: Principles, Testing, Operation and Maintenance systematically presents principles, testing approaches, and the operation and maintenance technologies of such substations from the perspective of real-world application. The book consists of chapters that cover a review of IEC 61850 based smart substations, substation configuration technology, principles and testing technologies for the smart substation, process bus, substation level, time setting and synchronization, and cybersecurity. It gives detailed information on testing processes and approaches, operation and maintenance technologies, and insights gained through practical experience. As IEC 61850 based smart substations have played a significant role in smart grids, realizing information sharing and device interoperation, this book provides a timely resource on the topics at hand. - Contributes to the overall understanding of standard IEC 61850, analyzing principles and features - Introduces best practices derived from hundreds of smart substation engineering applications - Summarizes current research and insights gained from practical experience in the testing, operation and maintenance of smart substation projects in China - Gives systematic and detailed information on testing technology - Introduces novel technologies for next-generation substations



Data-Driven Modelling and Predictive Analytics in Business and Finance

Author : Alex Khang

Publisher : CRC Press

Page : 443 pages

File Size : 46,80 MB

Release : 2024-07-24

Category : Computers

ISBN : 1040088465

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Book Description

Data-driven and AI-aided applications are next-generation technologies that can be used to visualize and realize intelligent transactions in finance, banking, and business. These transactions will be enabled by powerful data-driven solutions, IoT technologies, AI-aided techniques, data analytics, and visualization tools. To implement these solutions, frameworks will be needed to support human control of intelligent computing and modern business systems. The power and consistency of data-driven competencies are a critical challenge, and so is developing explainable AI (XAI) to make data-driven transactions transparent. Data- Driven Modelling and Predictive Analytics in Business and Finance covers the need for intelligent business solutions and applications. Explaining how business applications use algorithms and models to bring out the desired results, the book covers: Data-driven modelling Predictive analytics Data analytics and visualization tools AI-aided applications Cybersecurity techniques Cloud computing IoT-enabled systems for developing smart financial systems This book was written for business analysts, financial analysts, scholars, researchers, academics, professionals, and students so they may be able to share and contribute new ideas, methodologies, technologies, approaches, models, frameworks, theories, and practices.