Mobility Data Driven Urban Traffic Monitoring


Mobility Data Driven Urban Traffic Monitoring
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Mobility Data Driven Urban Traffic Monitoring


Mobility Data Driven Urban Traffic Monitoring
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Author : Zhidan Liu
language : en
Publisher: Springer Nature
Release Date : 2021-05-18

Mobility Data Driven Urban Traffic Monitoring written by Zhidan Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-18 with Computers categories.


This book introduces the concepts of mobility data and data-driven urban traffic monitoring. A typical framework of mobility data-based urban traffic monitoring is also presented, and it describes the processes of mobility data collection, data processing, traffic modelling, and some practical issues of applying the models for urban traffic monitoring. This book presents three novel mobility data-driven urban traffic monitoring approaches. First, to attack the challenge of mobility data sparsity, the authors propose a compressive sensing-based urban traffic monitoring approach. This solution mines the traffic correlation at the road network scale and exploits the compressive sensing theory to recover traffic conditions of the whole road network from sparse traffic samplings. Second, the authors have compared the traffic estimation performances between linear and nonlinear traffic correlation models and proposed a dynamical non-linear traffic correlation modelling-based urban traffic monitoring approach. To address the challenge of involved huge computation overheads, the approach adapts the traffic modelling and estimations tasks to Apache Spark, a popular parallel computing framework. Third, in addition to mobility data collected by the public transit systems, the authors present a crowdsensing-based urban traffic monitoring approach. The proposal exploits the lightweight mobility data collected from participatory bus riders to recover traffic statuses through careful data processing and analysis. Last but not the least, the book points out some future research directions, which can further improve the accuracy and efficiency of mobility data-driven urban traffic monitoring at large scale. This book targets researchers, computer scientists, and engineers, who are interested in the research areas of intelligent transportation systems (ITS), urban computing, big data analytic, and Internet of Things (IoT). Advanced level students studying these topics benefit from this book as well.



Data Driven Solutions To Transportation Problems


Data Driven Solutions To Transportation Problems
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Author : Yinhai Wang
language : en
Publisher: Elsevier
Release Date : 2018-12-04

Data Driven Solutions To Transportation Problems written by Yinhai Wang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-04 with Transportation categories.


Data-Driven Solutions to Transportation Problems explores the fundamental principle of analyzing different types of transportation-related data using methodologies such as the data fusion model, the big data mining approach, computer vision-enabled traffic sensing data analysis, and machine learning. The book examines the state-of-the-art in data-enabled methodologies, technologies and applications in transportation. Readers will learn how to solve problems relating to energy efficiency under connected vehicle environments, urban travel behavior, trajectory data-based travel pattern identification, public transportation analysis, traffic signal control efficiency, optimizing traffic networks network, and much more. Synthesizes the newest developments in data-driven transportation science Includes case studies and examples in each chapter that illustrate the application of methodologies and technologies employed Useful for both theoretical and technically-oriented researchers



Logic Driven Traffic Big Data Analytics


Logic Driven Traffic Big Data Analytics
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Author : Shaopeng Zhong
language : en
Publisher: Springer Nature
Release Date : 2022-02-01

Logic Driven Traffic Big Data Analytics written by Shaopeng Zhong and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-01 with Business & Economics categories.


This book starts from the relationship between urban built environment and travel behavior and focuses on analyzing the origin of traffic phenomena behind the data through multi-source traffic big data, which makes the book unique and different from the previous data-driven traffic big data analysis literature. This book focuses on understanding, estimating, predicting, and optimizing mobility patterns. Readers can find multi-source traffic big data processing methods, related statistical analysis models, and practical case applications from this book. This book bridges the gap between traffic big data, statistical analysis models, and mobility pattern analysis with a systematic investigation of traffic big data’s impact on mobility patterns and urban planning.



Handbook Of Smart Cities


Handbook Of Smart Cities
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Author : Juan Carlos Augusto
language : en
Publisher: Springer
Release Date : 2021-07-17

Handbook Of Smart Cities written by Juan Carlos Augusto and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-17 with Computers categories.


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.



Big Data And Mobility As A Service


Big Data And Mobility As A Service
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Author : Haoran Zhang
language : en
Publisher: Elsevier
Release Date : 2021-10-01

Big Data And Mobility As A Service written by Haoran Zhang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-01 with Transportation categories.


Big Data and Mobility as a Service explores MaaS platforms that can be adaptable to the ever-evolving mobility environment. It looks at multi-mode urban crowd data to assess urban mobility characteristics, their shared transportation potential, and their performance conditions and constraints. The book analyzes the roles of multimodality, travel behavior, urban mobility dynamics and participation. Combined with insights on using big data to analyze market and policy decisions, this book is an essential tool for urban transportation management researchers and practitioners. Summarizes current fundamental MaaS technologies Shows how to utilize anonymous big data for transportation analysis and problem-solving Illustrates, with data-enabled shared transportation service examples from different countries, the similarities and differences within a global urban mobility framework



Handbook Of Mobility Data Mining Volume 3


Handbook Of Mobility Data Mining Volume 3
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Author : Haoran Zhang
language : en
Publisher: Elsevier
Release Date : 2023-01-29

Handbook Of Mobility Data Mining Volume 3 written by Haoran Zhang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-29 with Business & Economics categories.


Handbook of Mobility Data Mining: Volume Three: Mobility Data-Driven Applications introduces the fundamental technologies of mobile big data mining (MDM), advanced AI methods, and upper-level applications, helping readers comprehensively understand MDM with a bottom-up approach. The book explains how to preprocess mobile big data, visualize urban mobility, simulate and predict human travel behavior, and assess urban mobility characteristics and their matching performance as conditions and constraints in transport, emergency management, and sustainability development systems. The book contains crucial information for researchers, engineers, operators, administrators, and policymakers seeking greater understanding of current technologies' infra-knowledge structure and limitations. The book introduces how to design MDM platforms that adapt to the evolving mobility environment—and new types of transportation and users—based on an integrated solution that utilizes sensing and communication capabilities to tackle significant challenges faced by the MDM field. This third volume looks at various cases studies to illustrate and explore the methods introduced in the first two volumes, covering topics such as Intelligent Transportation Management, Smart Emergency Management—detailing cases such as the Fukushima earthquake, Hurricane Katrina, and COVID-19—and Urban Sustainability Development, covering bicycle and railway travel behavior, mobility inequality, and road and light pollution inequality. Introduces MDM applications from six major areas: intelligent transportation management, shared transportation systems, disaster management, pandemic response, low-carbon transportation, and social equality Uses case studies to examine possible solutions that facilitate ethical, secure, and controlled emergency management based on mobile big data Helps develop policy innovations beneficial to citizens, businesses, and society Stems from the editor’s strong network of global transport authorities and transport companies, providing a solid knowledge structure and data foundation as well as geographical and stakeholder coverage



Mobility Patterns Big Data And Transport Analytics


Mobility Patterns Big Data And Transport Analytics
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Author : Constantinos Antoniou
language : en
Publisher: Elsevier
Release Date : 2018-11-27

Mobility Patterns Big Data And Transport Analytics written by Constantinos Antoniou and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-27 with Social Science categories.


Mobility Patterns, Big Data and Transport Analytics provides a guide to the new analytical framework and its relation to big data, focusing on capturing, predicting, visualizing and controlling mobility patterns - a key aspect of transportation modeling. The book features prominent international experts who provide overviews on new analytical frameworks, applications and concepts in mobility analysis and transportation systems. Users will find a detailed, mobility ‘structural’ analysis and a look at the extensive behavioral characteristics of transport, observability requirements and limitations for realistic transportation applications and transportation systems analysis that are related to complex processes and phenomena. This book bridges the gap between big data, data science, and transportation systems analysis with a study of big data’s impact on mobility and an introduction to the tools necessary to apply new techniques. The book covers in detail, mobility ‘structural’ analysis (and its dynamics), the extensive behavioral characteristics of transport, observability requirements and limitations for realistic transportation applications, and transportation systems analysis related to complex processes and phenomena. The book bridges the gap between big data, data science, and Transportation Systems Analysis with a study of big data’s impact on mobility, and an introduction to the tools necessary to apply new techniques. Guides readers through the paradigm-shifting opportunities and challenges of handling Big Data in transportation modeling and analytics Covers current analytical innovations focused on capturing, predicting, visualizing, and controlling mobility patterns, while discussing future trends Delivers an introduction to transportation-related information advances, providing a benchmark reference by world-leading experts in the field Captures and manages mobility patterns, covering multiple purposes and alternative transport modes, in a multi-disciplinary approach Companion website features videos showing the analyses performed, as well as test codes and data-sets, allowing readers to recreate the presented analyses and apply the highlighted techniques to their own data



Smart Urban Mobility


Smart Urban Mobility
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Author : Ivana Cavar Semanjski
language : en
Publisher: Elsevier
Release Date : 2023-02-08

Smart Urban Mobility written by Ivana Cavar Semanjski and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-08 with Political Science categories.


Smart Urban Mobility: Transport Planning in the Age of Big Data and Digital Twins explores the data-driven paradigm shift in urban mobility planning and examines how well-established practices and strong data analytics efforts can be better aligned to fit transport planning practices and "smart" mobility management needs. The book provides a comprehensive survey of the major big data and technology resources derived from smart cities research which are collectively poised to transform urban mobility. Chapters highlight the important aspects of each data source affecting applicability, along with the outcomes of smart mobility measures and campaigns.Transport planners, urban policymakers, public administrators, city managers, data scientists, and consulting companies managing smart city interventions and data-driven urban transformation projects will gain a better understanding of this up-and-coming research from this book’s detailed overview and numerous practical examples and best practices for operational deployment. Addresses key principles underlying smart mobility, as well as opportunities and challenges of integrating big data-driven insights into transport planning and smart cities Presents practical advice on how to implement smart mobility advances, providing a benchmark reference by best practice examples in the field Examines synthesis of existing gaps, limitations, and big data potential beyond traditional data needs for transport planning, as well as examples of the best practices



Data Analytics Paving The Way To Sustainable Urban Mobility


Data Analytics Paving The Way To Sustainable Urban Mobility
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Author : Eftihia G. Nathanail
language : en
Publisher: Springer
Release Date : 2018-12-11

Data Analytics Paving The Way To Sustainable Urban Mobility written by Eftihia G. Nathanail and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-11 with Technology & Engineering categories.


This book aims at showing how big data sources and data analytics can play an important role in sustainable mobility. It is especially intended to provide academicians, researchers, practitioners and decision makers with a snapshot of methods that can be effectively used to improve urban mobility. The different chapters, which report on contributions presented at the 4th Conference on Sustainable Urban Mobility, held on May 24-25, 2018, in Skiathos Island, Greece, cover different thematic areas, such as social networks and traveler behavior, applications of big data technologies in transportation and analytics, transport infrastructure and traffic management, transportation modeling, vehicle emissions and environmental impacts, public transport and demand responsive systems, intermodal interchanges, smart city logistics systems, data security and associated legal aspects. They show in particular how to apply big data in improving urban mobility, discuss important challenges in developing and implementing analytics methods and provide the reader with an up-to-date review of the most representative research on data management techniques for enabling sustainable urban mobility



Handbook Of Research On Ai And Ml For Intelligent Machines And Systems


Handbook Of Research On Ai And Ml For Intelligent Machines And Systems
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Author : Gupta, Brij B.
language : en
Publisher: IGI Global
Release Date : 2023-11-27

Handbook Of Research On Ai And Ml For Intelligent Machines And Systems written by Gupta, Brij B. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-27 with Computers categories.


The Handbook of Research on AI and ML for Intelligent Machines and Systems offers a comprehensive exploration of the pivotal role played by artificial intelligence (AI) and machine learning (ML) technologies in the development of intelligent machines. As the demand for intelligent machines continues to rise across various sectors, understanding the integration of these advanced technologies becomes paramount. While AI and ML have individually showcased their capabilities in developing robust intelligent machine systems and services, their fusion holds the key to propelling intelligent machines to a new realm of transformation. By compiling recent advancements in intelligent machines that rely on machine learning and deep learning technologies, this book serves as a vital resource for researchers, graduate students, PhD scholars, faculty members, scientists, and software developers. It offers valuable insights into the key concepts of AI and ML, covering essential security aspects, current trends, and often overlooked perspectives that are crucial for achieving comprehensive understanding. It not only explores the theoretical foundations of AI and ML but also provides guidance on applying these techniques to solve real-world problems. Unlike traditional texts, it offers flexibility through its distinctive module-based structure, allowing readers to follow their own learning paths.