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001 978-3-030-45164-6
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020 _a9783030451646
_9978-3-030-45164-6
024 7 _a10.1007/978-3-030-45164-6
_2doi
050 4 _aQA76.9.D3
072 7 _aUN
_2bicssc
072 7 _aCOM021000
_2bisacsh
072 7 _aUN
_2thema
082 0 4 _a005.74
_223
245 1 0 _aBig Data Analytics for Time-Critical Mobility Forecasting
_h[electronic resource] :
_bFrom Raw Data to Trajectory-Oriented Mobility Analytics in the Aviation and Maritime Domains /
_cedited by George A. Vouros, Gennady Andrienko, Christos Doulkeridis, Nikolaos Pelekis, Alexander Artikis, Anne-Laure Jousselme, Cyril Ray, Jose Manuel Cordero, David Scarlatti.
250 _a1st ed. 2020.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2020.
300 _aXXXII, 361 p. 126 illus., 100 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aPart I: Time Critical Mobility Operations and Data: A Perspective from the Maritime and Aviation Domains -- Mobility Data: A Perspective from the Maritime Domain -- The Perspective on Mobility Data from the Aviation Domain -- Part II: Visual Analytics and Trajectory Detection and Summarization: Exploring Data and Constructing Trajectories -- Visual Analytics in the Aviation and Maritime Domains -- Trajectory Detection and Summarization over Surveillance Data Streams -- Part III: Trajectory Oriented Data Management for Mobility Analytics -- Modeling Mobility Data and Constructing Large Knowledge Graphs to Support Analytics: The datAcron Ontology -- Integrating Data by Discovering Topological and Proximity Relations Among Spatiotemporal Entities -- Distributed Storage of Large Knowledge Graphs with Mobility Data -- Part IV: Analytics Towards Time Critical Mobility Forecasting -- Future Location and Trajectory Prediction -- Event Processing for Maritime Situational Awareness -- Offline Trajectory Analytics -- Part V Big Data Architectures for Time Critical Mobility Forecasting -- The δ Big Data Architecture for Mobility Analytics -- Part VI: Ethical Issues for Time Critical Mobility Analytics -- Ethical Issues in Big Data Analytics for Time Critical Mobility Forecasting.
520 _aThis book provides detailed descriptions of big data solutions for activity detection and forecasting of very large numbers of moving entities spread across large geographical areas. It presents state-of-the-art methods for processing, managing, detecting and predicting trajectories and important events related to moving entities, together with advanced visual analytics methods, over multiple heterogeneous, voluminous, fluctuating and noisy data streams from moving entities, correlating them with data from archived data sources expressing e.g. entities’ characteristics, geographical information, mobility patterns, mobility regulations and intentional data. The book is divided into six parts: Part I discusses the motivation and background of mobility forecasting supported by trajectory-oriented analytics, and includes specific problems and challenges in the aviation (air-traffic management) and the maritime domains. Part II focuses on big data quality assessment and processing, and presents novel technologies suitable for mobility analytics components. Next, Part III describes solutions toward processing and managing big spatio-temporal data, particularly enriching data streams and integrating streamed and archival data to provide coherent views of mobility, and storing of integrated mobility data in large distributed knowledge graphs for efficient query-answering. Part IV focuses on mobility analytics methods exploiting (online) processed, synopsized and enriched data streams as well as (offline) integrated, archived mobility data, and highlights future location and trajectory prediction methods, distinguishing between short-term and more challenging long-term predictions. Part V examines how methods addressing data management, data processing and mobility analytics are integrated in big data architectures with distinctive characteristics compared to other known big data paradigmatic architectures. Lastly, Part VI covers important ethical issues that research on mobility analytics should address. Providing novel approaches and methodologies related to mobility detection and forecasting needs based on big data exploration, processing, storage, and analysis, this book will appeal to computer scientists and stakeholders in various application domains.
650 0 _aDatabase management.
650 0 _aComputer science
_xMathematics.
650 0 _aMathematical statistics.
650 0 _aTransportation engineering.
650 0 _aTraffic engineering.
650 1 4 _aDatabase Management.
650 2 4 _aProbability and Statistics in Computer Science.
650 2 4 _aTransportation Technology and Traffic Engineering.
700 1 _aVouros, George A.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aAndrienko, Gennady.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aDoulkeridis, Christos.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aPelekis, Nikolaos.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aArtikis, Alexander.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aJousselme, Anne-Laure.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aRay, Cyril.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aCordero, Jose Manuel.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aScarlatti, David.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030451639
776 0 8 _iPrinted edition:
_z9783030451653
776 0 8 _iPrinted edition:
_z9783030451660
856 4 0 _uhttps://doi.org/10.1007/978-3-030-45164-6
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
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