Big Data Analytics for Time-Critical Mobility Forecasting: From Raw Data to Trajectory-Oriented Mobility Analytics in the Aviation and Maritime Domains

This 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 discusses state-of-the-art methods for processing, managing, detecting, and predicting trajectories and important events related to moving entities, along with advanced visual analytics methods, over multiple heterogeneous, voluminous, fluctuating, and noisy data streams from moving entities. It is divided into six parts and covers topics such as motivation and background, big data quality assessment and processing, processing and managing big spatio-temporal data, mobility analytics methods, integration in big data architectures, and ethical issues.

Format: Paperback / softback
Length: 361 pages
Publication date: 24 June 2021
Publisher: Springer Nature Switzerland AG

This comprehensive book delves into intricate details of big data solutions for the task of activity detection and forecasting across vast geographical areas, encompassing a substantial number of moving entities. It presents cutting-edge techniques for processing, managing, detecting, and predicting trajectories and significant events associated with these moving entities, along with advanced visual analytics methods, applied to diverse, voluminous, fluctuating, and noisy data streams originating from these entities. These data streams are correlated with data from archived data sources, encompassing entities' characteristics, geographical information, mobility patterns, mobility regulations, and intentional data.

The book is structured into six parts:

Part I explores the motivation and background of mobility forecasting, supported by trajectory-oriented analytics, specifically addressing challenges in the aviation (air-traffic management) and maritime domains.

Part II delves into assessing the quality of big data, crucial for mobility analytics, and introduces novel technologies tailored for various components of mobility analysis.

Part III focuses on processing and managing large spatio-temporal data, enriching data streams and integrating them with archived data to provide comprehensive views of mobility. It also discusses the storage of integrated mobility data in large distributed knowledge graphs for efficient query-answering.

Part IV highlights mobility analytics methods that leverage processed, synopsized, and enriched data streams, as well as integrated, archived mobility data. It explores future location and trajectory prediction techniques, distinguishing between short-term and more complex long-term predictions.

Part V examines the integration of methods addressing data management, data processing, and mobility analytics, emphasizing their interconnectedness and contributions to advancing the field.

By presenting state-of-the-art methodologies and comprehensive insights, this book serves as a valuable resource for researchers, practitioners, and professionals in the domains of mobility forecasting, big data analytics, and spatial information systems. It empowers them to effectively handle the challenges posed by large-scale mobility data and extract valuable insights for decision-making and strategic planning.

Weight: 605g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030451660
Edition number: 1st ed. 2020