From raw data to trajectory-oriented mobility analytics in the aviation and maritime domains
Spatiotemporal mobility data has significant role and impact on the global economy and our everyday lives. The improvements along the last decades in terms of data management, planning of operations, security of operations, information provision to operators and end-users, has been driven by location-centred information. While a shift of paradigm regarding mobility data towards trajectory-oriented tasks is emerging, the ever-increasing volume of data emphasizes the need for advanced methods supporting detection and prediction of events and trajectories, supplemented by advanced visual analytic methods, over multiple heterogeneous, voluminous, fluctuating, and noisy data streams of moving entities.
This book provides a comprehensive and detailed description of Big Data solutions towards activity detection and forecasting in very large numbers of moving entities spread across large geographical areas. Specifically, following a trajectory oriented approach, this book reports on state of the art methods for the detection and prediction of 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, among others, entities’ characteristics, geographical information, mobility patterns, regulations and intentional data (e.g. planned routes), in a timely manner. Solutions provided are motivated, validated and evaluated in user-defined challenges focusing on increasing the safety, efficiency and economy of operations concerning moving entities in the Air-Traffic Management and Maritime domains.
- End-to-end big data analytics solutions for Mobility Forecasting.
- State of the art solutions for Big Data challenges: Data Management, Data Processing, Predictive Analytics, Visual Analytics with comprehensive description and illustration of methods used in real-world cases.
- More than 100 drawings and images illustrating real-world cases of mobility, explaining concepts, motivating methods and providing evidence for methods' benefits.
- Motivating examples and validation results from challenging scenarios in the maritime and aviation domains.
- Supplementary material is provided in this dedicated website.
- Chapters focus on mobility data in two critical domains covering in a comprehensive way interests of many Big Data stakeholders: Aviation and maritime experts and researchers, data management, data processing, data analysis and visual analytics experts and researchers.
- Big Mobility Data Management & Processing researchers
- Big Mobility Data Analytics researchers
- Big Mobility Data Visual Analytics researchers
- Aviation researchers on mobility data
- Maritime researchers on mobility data
No. of pages
Approx. 450 Pgs
|Surname Name||Title(s)||Address(work)||Email - URL|
|Vouros George||Professor||University of Piraeus, Greece||
|Andrienko Gennady||Researcher||IAIS Fraunhofer, Germany||
|Doulkeridis Christos||Assist. Professor||University of Piraeus, Greece||
|Pelekis Nikolaos||Assist. Professor||University of Piraeus, Greece||
|Artikis Alexandros||Assist. Professor||NCSR “Demokritos”, Greece||
|Jousselme Anne-Laure||Researcher||NATO CMRE, Italy||
|Ray Cyril||Assoc. Professor||Arts & Metiers-Paris Tech, France||
|Cordero Jose Manuel||Researcher||CRIDA, Spain||
|Scarlatti David||Researcher||Boeing R&T- Europe, Spain||