This comprehensive reference text is a collection of important research findings on the latest developments in network modeling for optimization of smart cities. Such models can be used from outlining the fundamental concepts of urban development to the description and optimization of physical networks, such as power, water or telecommunications. Networks help us understand city economics and various aspects of human interactions within cities with particular applications in quality of life and the flow of people and goods. Finally, the natural environment and even the climate of cities can be modeled and managed as networks.

This Handbook presents a comprehensive and rigorous overview of the state-of-the-art on Smart Cities. It provides the reader with an authoritative, exhaustive one-stop reference on how the field has evolved and where the current and future challenges lie. From the foundations to the many overlapping dimensions (human, energy, technology, data, institutions, ethics etc.), each chapter is written by international experts and amply illustrated with figures and tables with an emphasis on current research. The Handbook is an invaluable desk reference for researchers in a wide variety of fields, not only smart cities specialists but also by scientists and policy-makers in related disciplines that are deeply influenced by the emergence of intelligent cities. It should also serve as a key resource for graduate students and young researchers entering the area, and for instructors who teach courses on these subjects. The handbook is also of interest to industry and business innovators.

Machine learning approaches has the capability to learn and adapt to the constantly evolving demands of large Internet-of-energy (IoE) network. The focus of this book is on using the machine learning approaches to present various solutions for IoE network in smart cities to solve various research gaps such as demand response management, resource management and effective utilization of the underlying ICT network. It provides in-depth knowledge to build the technical understanding for the reader to pursue various research problems in this field. Moreover, the example problems in smart cities and their solutions using machine learning are provided as relatable to the real-life scenarios. Aimed at Graduate Students, Researchers in Computer Science, Electrical Engineering, Telecommunication Engineering, Internet of Things, Machine Learning, Green computing, Smart Grid, this book: Covers all aspects of Internet of Energy (IoE) and smart cities including research problems and solutions. Points to the solutions provided by machine learning to optimize the grids within a smart city set-up. Discusses relevant IoE design principles and architecture. Helps to automate various services in smart cities for energy management. Includes case studies to show the effectiveness of the discussed schemes.

A unique examination of the civic use, regulation, and politics of communication and data technologies City life has been reconfigured by our use—and our expectations—of communication, data, and sensing technologies. This book examines the civic use, regulation, and politics of these technologies, looking at how governments, planners, citizens, and activists expect them to enhance life in the city. Alison Powell argues that the de facto forms of citizenship that emerge in relation to these technologies represent sites of contention over how governance and civic power should operate. These become more significant in an increasingly urbanized and polarized world facing new struggles over local participation and engagement. The author moves past the usual discussion of top-down versus bottom-up civic action and instead explains how citizenship shifts in response to technological change and particularly in response to issues related to pervasive sensing, big data, and surveillance in "smart cities".

This book explores the methodological and application developments of network design in transportation and logistics. It identifies trends, challenges and research perspectives in network design for these areas. Network design is a major class of problems in operations research where network flow, combinatorial and mixed integer optimization meet. The analysis and planning of transportation and logistics systems continues to be one of the most important application areas of operations research. Networks provide the natural way of depicting such systems, so the optimal design and operation of networks is the main methodological area of operations research that is used for the analysis and planning of these systems. This book defines the current state of the art in the general area of network design, and then turns to its applications to transportation and logistics. New research challenges are addressed. Network Design with Applications to Transportation and Logistics is divided into three parts. Part I examines basic design problems including fixed-cost network design and parallel algorithms. After addressing the basics, Part II focuses on more advanced models. Chapters cover topics such as multi-facility network design, flow-constrained network design, and robust network design. Finally Part III is dedicated entirely to the potential application areas for network design. These areas range from rail networks, to city logistics, to energy transport. All of the chapters are written by leading researchers in the field, which should appeal to analysts and planners.

Collective Intelligence for Smart Cities begins with an overview of the fundamental issues and concepts of smart cities. Surveying the current state-of-the-art research in the field, the book delves deeply into key smart city developments such as health and well-being, transportation, safety, energy, environment and sustainability. In addition, the book focuses on the role of IoT cloud computing and big data, specifically in smart city development. Users will find a unique, overarching perspective that ties together these concepts based on collective intelligence, a concept for quantifying mass activity familiar to many social science and life science researchers.Sections explore how group decision-making emerges from the consensus of the collective, collaborative and competitive activities of many individuals, along with future perspectives. - Provides collective intelligence-based solutions to enhance smart city well-being - Recommends strategies to ensure smart city sustainability and optimization, including smart transportation - Considers cloud-based data processing approaches for managing data collected from smart city applications - Uses case studies to shows successful application in a variety of smart city contexts