[PDF] Handbook Of Mobility Data Mining Volume 1 eBook

Author : Haoran Zhang
Publisher : Elsevier
Page : 222 pages
File Size : 35,9 MB
Release : 2023-01-15
Category : Business & Economics
ISBN : 0443184283

GET BOOK

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

Author : Haoran Zhang
Publisher : Elsevier
Page : 224 pages
File Size : 25,25 MB
Release : 2023-01-29
Category : Business & Economics
ISBN : 0443184291

GET BOOK

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

Author : Haoran Zhang
Publisher : Elsevier
Page : 212 pages
File Size : 19,60 MB
Release : 2023-01-29
Category : Business & Economics
ISBN : 0443184259

GET BOOK

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

Author : Haoran Zhang
Publisher : Elsevier
Page : 244 pages
File Size : 22,80 MB
Release : 2023-01-29
Category : Business & Economics
ISBN : 0443184232

GET BOOK

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

Author : Fosca Giannotti
Publisher : Springer Science & Business Media
Page : 415 pages
File Size : 11,37 MB
Release : 2008-01-12
Category : Computers
ISBN : 3540751777

GET BOOK

Mobile communications and ubiquitous computing generate large volumes of data. Mining this data can produce useful knowledge, yet individual privacy is at risk. This book investigates the various scientific and technological issues of mobility data, open problems, and roadmap. The editors manage a research project called GeoPKDD, Geographic Privacy-Aware Knowledge Discovery and Delivery, and this book relates their findings in 13 chapters covering all related subjects.

Author : Chiara Renso
Publisher : Cambridge University Press
Page : 393 pages
File Size : 24,18 MB
Release : 2013-10-14
Category : Computers
ISBN : 1107292360

GET BOOK

Mobility of people and goods is essential in the global economy. The ability to track the routes and patterns associated with this mobility offers unprecedented opportunities for developing new, smarter applications in different domains. Much of the current research is devoted to developing concepts, models, and tools to comprehend mobility data and make it manageable for these applications. This book surveys the myriad facets of mobility data, from spatio-temporal data modeling, to data aggregation and warehousing, to data analysis, with a specific focus on monitoring people in motion (drivers, airplane passengers, crowds, and even animals in the wild). Written by a renowned group of worldwide experts, it presents a consistent framework that facilitates understanding of all these different facets, from basic definitions to state-of-the-art concepts and techniques, offering both researchers and professionals a thorough understanding of the applications and opportunities made possible by the development of mobility data.

Author : Constantinos Antoniou
Publisher : Elsevier
Page : 0 pages
File Size : 48,84 MB
Release : 2018-11-27
Category : Social Science
ISBN : 9780128129708

GET BOOK

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.

Author : Nong Ye
Publisher : CRC Press
Page : 720 pages
File Size : 50,90 MB
Release : 2003-04-01
Category : Computers
ISBN : 1410607518

GET BOOK

Created with the input of a distinguished International Board of the foremost authorities in data mining from academia and industry, The Handbook of Data Mining presents comprehensive coverage of data mining concepts and techniques. Algorithms, methodologies, management issues, and tools are all illustrated through engaging examples and real-world applications to ease understanding of the materials. This book is organized into three parts. Part I presents various data mining methodologies, concepts, and available software tools for each methodology. Part II addresses various issues typically faced in the management of data mining projects and tips on how to maximize outcome utility. Part III features numerous real-world applications of these techniques in a variety of areas, including human performance, geospatial, bioinformatics, on- and off-line customer transaction activity, security-related computer audits, network traffic, text and image, and manufacturing quality. This Handbook is ideal for researchers and developers who want to use data mining techniques to derive scientific inferences where extensive data is available in scattered reports and publications. It is also an excellent resource for graduate-level courses on data mining and decision and expert systems methodology.

Author : Muhammad Imran Malik
Publisher : Elsevier
Page : 802 pages
File Size : 26,25 MB
Release : 2024-01-18
Category : Technology & Engineering
ISBN : 0323955126

GET BOOK

Handbook of Nanomaterials: Electronics, Information Technology, Energy, Transportation, and Consumer Products offers a comprehensive resource that introduces the role of nanotechnology and nanomaterials in a broad range of areas, covering fundamentals, methods, and applications. In this volume, the initial chapters introduce the core concepts of nanotechnology, and synthesis methods and characterization techniques for nanomaterials. This is followed by dedicated sections focusing on key application areas across electronics, information technology, energy, transportation, and consumer products. In each chapter, detailed but concise information is provided on a specific application, covering methods and latest advances. This book is of interest to researchers and advanced students approaching nanotechnology from a range of disciplines, including materials science and engineering, chemistry, chemical engineering, electronics, energy, biomedicine, environmental science, food science, and agriculture, as well as scientists, engineers, and R&D professionals with an interest in the use of nanomaterials across a range of industries. Introduces the reader to key applications of nanomaterials Provides broad, systematic, concise coverage, supporting readers from a range of disciplines Covers applications across electronics, information technology, energy, transportation, and consumer products

Author : Dr. Sajimon Abraham, Dr. P Sojan Lal and Dr. Dais George
Publisher : Lulu.com
Page : 162 pages
File Size : 22,14 MB
Release : 2018-06-09
Category : Education
ISBN : 1387868632

GET BOOK

Spatial and temporal properties are key aspects of many data analysis problems in business, government, and science. GPS technology is quickly enabling a number of new applications, including tracking fleets of vehicles, navigating boats and ships, pedestrian's tracking and tracking of wildlife. Another popular application of this technology is in cellular phones with embedded GPS sensors for vehicle and pedestrian's tracking. Through the availability of cheap sensor devices, we have witnessed an exponential growth of geo-tagged data in the last few years resulting in the availability of fine-grained spatial data at small temporal sampling intervals. Therefore, the actual challenge in spatio-temporal analysis is moving from acquiring the right data towards large-scale analysis of the available data. As this multidimensional data add more complexities in storing, indexing and querying, efficient methodologies have to be derived to manage these data using existing data base technology.