Handbook of Mobility Data Mining Volume 3

Handbook of Mobility Data Mining  Volume 3
Author: Haoran Zhang
Publsiher: Elsevier
Total Pages: 244
Release: 2023-01-29
Genre: Business & Economics
ISBN: 9780443184239

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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

Handbook of Mobility Data Mining Volume 2

Handbook of Mobility Data Mining  Volume 2
Author: Haoran Zhang
Publsiher: Elsevier
Total Pages: 212
Release: 2023-01-29
Genre: Business & Economics
ISBN: 9780443184253

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Handbook of Mobility Data Mining, Volume Two: Mobility Analytics and Prediction 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 introduces how to design MDM platforms that adapt to the evolving mobility environment and new types of transportation and users. This helpful guide provides a basis for how to simulate and predict mobility data. After an introductory theory chapter, the book then covers crucial topics such as long-term mobility pattern analytics, mobility data generators, user information inference, Grid-based population density prediction, and more. The book concludes with a chapter on graph-based mobility data analytics. The information in this work is crucial for researchers, engineers, operators, company administrators, and policymakers in related fields, to comprehensively understand current technologies' infra-knowledge structure and limitations. Discusses how to efficiently simulate massive and large-scale people movement and predict mobility at an urban scale Introduces both online detection methods, which can sequentially process data, and offline detection methods, which are usually more robust 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

Handbook of Mobility Data Mining Volume 1

Handbook of Mobility Data Mining  Volume 1
Author: Haoran Zhang
Publsiher: Elsevier
Total Pages: 222
Release: 2023-01-15
Genre: Business & Economics
ISBN: 9780443184284

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Handbook of Mobility Data Mining, Volume One: Data Preprocessing and Visualization 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. Further, the book introduces how to design MDM platforms that adapt to the evolving mobility environment, 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 volume focuses on how to efficiently pre-process mobile big data to extract and utilize critical feature information of high-dimensional city people flow. The book first provides a conceptual theory and framework, then discusses data sources, trajectory map-matching, noise filtering, trajectory data segmentation, data quality assessment, and more, concluding with a chapter on privacy protection in mobile big data mining. Introduces the characteristics of different mobility data sources, like GPS, CDR, and sensor-based mobility data Summarizes existing visualization technologies of the current transportation system into a multi-view frame, covering the perspective of the three leading actors Provides recommendations for practical open-source tools and libraries for system visualization 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

Handbook of Mobility Data Mining Volume 1

Handbook of Mobility Data Mining  Volume 1
Author: Haoran Zhang
Publsiher: Elsevier
Total Pages: 224
Release: 2023-01-29
Genre: Business & Economics
ISBN: 9780443184291

Download Handbook of Mobility Data Mining Volume 1 Book in PDF, Epub and Kindle

Handbook of Mobility Data Mining, Volume One: Data Preprocessing and Visualization 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. Further, the book introduces how to design MDM platforms that adapt to the evolving mobility environment, 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 volume focuses on how to efficiently pre-process mobile big data to extract and utilize critical feature information of high-dimensional city people flow. The book first provides a conceptual theory and framework, then discusses data sources, trajectory map-matching, noise filtering, trajectory data segmentation, data quality assessment, and more, concluding with a chapter on privacy protection in mobile big data mining. Introduces the characteristics of different mobility data sources, like GPS, CDR, and sensor-based mobility data Summarizes existing visualization technologies of the current transportation system into a multi-view frame, covering the perspective of the three leading actors Provides recommendations for practical open-source tools and libraries for system visualization 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

Handbook of Mobile Data Privacy

Handbook of Mobile Data Privacy
Author: Aris Gkoulalas-Divanis,Claudio Bettini
Publsiher: Springer
Total Pages: 403
Release: 2018-10-26
Genre: Computers
ISBN: 9783319981611

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This handbook covers the fundamental principles and theory, and the state-of-the-art research, systems and applications, in the area of mobility data privacy. It is primarily addressed to computer science and statistics researchers and educators, who are interested in topics related to mobility privacy. This handbook will also be valuable to industry developers, as it explains the state-of-the-art algorithms for offering privacy. By discussing a wide range of privacy techniques, providing in-depth coverage of the most important ones, and highlighting promising avenues for future research, this handbook also aims at attracting computer science and statistics students to this interesting field of research. The advances in mobile devices and positioning technologies, together with the progress in spatiotemporal database research, have made possible the tracking of mobile devices (and their human companions) at very high accuracy, while supporting the efficient storage of mobility data in data warehouses, which this handbook illustrates. This has provided the means to collect, store and process mobility data of an unprecedented quantity, quality and timeliness. As ubiquitous computing pervades our society, user mobility data represents a very useful but also extremely sensitive source of information. On one hand, the movement traces that are left behind by the mobile devices of the users can be very useful in a wide spectrum of applications such as urban planning, traffic engineering, and environmental pollution management. On the other hand, the disclosure of mobility data to third parties may severely jeopardize the privacy of the users whose movement is recorded, leading to abuse scenarios such as user tailing and profiling. A significant amount of research work has been conducted in the last 15 years in the area of mobility data privacy and important research directions, such as privacy-preserving mobility data management, privacy in location sensing technologies and location-based services, privacy in vehicular communication networks, privacy in location-based social networks, privacy in participatory sensing systems which this handbook addresses.. This handbook also identifies important privacy gaps in the use of mobility data and has resulted to the adoption of international laws for location privacy protection (e.g., in EU, US, Canada, Australia, New Zealand, Japan, Singapore), as well as to a large number of interesting technologies for privacy-protecting mobility data, some of which have been made available through open-source systems and featured in real-world applications.

Handbook of Research on Geographic Information Systems Applications and Advancements

Handbook of Research on Geographic Information Systems Applications and Advancements
Author: Faiz, Sami,Mahmoudi, Khaoula
Publsiher: IGI Global
Total Pages: 650
Release: 2016-10-21
Genre: Science
ISBN: 9781522509387

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The proper management of geographic data can provide assistance to a number of different sectors within society. As such, it is imperative to continue advancing research for spatial data analysis. The Handbook of Research on Geographic Information Systems Applications and Advancements presents a thorough overview of the latest developments in effective management techniques for collecting, processing, analyzing, and utilizing geographical data and information. Highlighting theoretical frameworks and relevant applications, this book is an ideal reference source for researchers, academics, professionals, and students actively involved in the field of geographic information systems.

Handbook of Research on Machine Learning Innovations and Trends

Handbook of Research on Machine Learning Innovations and Trends
Author: Hassanien, Aboul Ella,Gaber, Tarek
Publsiher: IGI Global
Total Pages: 1093
Release: 2017-04-03
Genre: Computers
ISBN: 9781522522300

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Continuous improvements in technological applications have allowed more opportunities to develop automated systems. This not only leads to higher success in smart data analysis, but it increases the overall probability of technological progression. The Handbook of Research on Machine Learning Innovations and Trends is a key resource on the latest advances and research regarding the vast range of advanced systems and applications involved in machine intelligence. Highlighting multidisciplinary studies on decision theory, intelligent search, and multi-agent systems, this publication is an ideal reference source for professionals and researchers working in the field of machine learning and its applications.

Handbook of Big Geospatial Data

Handbook of Big Geospatial Data
Author: Martin Werner,Yao-Yi Chiang
Publsiher: Springer Nature
Total Pages: 641
Release: 2021-05-07
Genre: Computers
ISBN: 9783030554620

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This handbook covers a wide range of topics related to the collection, processing, analysis, and use of geospatial data in their various forms. This handbook provides an overview of how spatial computing technologies for big data can be organized and implemented to solve real-world problems. Diverse subdomains ranging from indoor mapping and navigation over trajectory computing to earth observation from space, are also present in this handbook. It combines fundamental contributions focusing on spatio-textual analysis, uncertain databases, and spatial statistics with application examples such as road network detection or colocation detection using GPUs. In summary, this handbook gives an essential introduction and overview of the rich field of spatial information science and big geospatial data. It introduces three different perspectives, which together define the field of big geospatial data: a societal, governmental, and governance perspective. It discusses questions of how the acquisition, distribution and exploitation of big geospatial data must be organized both on the scale of companies and countries. A second perspective is a theory-oriented set of contributions on arbitrary spatial data with contributions introducing into the exciting field of spatial statistics or into uncertain databases. A third perspective is taking a very practical perspective to big geospatial data, ranging from chapters that describe how big geospatial data infrastructures can be implemented and how specific applications can be implemented on top of big geospatial data. This would include for example, research in historic map data, road network extraction, damage estimation from remote sensing imagery, or the analysis of spatio-textual collections and social media. This multi-disciplinary approach makes the book unique. This handbook can be used as a reference for undergraduate students, graduate students and researchers focused on big geospatial data. Professionals can use this book, as well as practitioners facing big collections of geospatial data.