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SpatioTemporal Data Streams (SpringerBriefs in Computer Science),Used
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This SpringerBrief presents the fundamental concepts of a specialized class of data stream, spatiotemporal data streams, and demonstrates their distributed processing using Big Data frameworks and platforms. It explores a consistent framework which facilitates a thorough understanding of all different facets of the technology, from basic definitions to stateoftheart techniques. Key topics include spatiotemporal continuous queries, distributed stream processing, SQLlike language embedding, and trajectory stream clustering. Over the course of the book, the reader will become familiar with spatiotemporal data streams management and data flow processing, which enables the analysis of huge volumes of locationaware continuous data streams. Applications range from mobile object tracking and realtime intelligent transportation systems to traffic monitoring and complex event processing. SpatioTemporal Data Streams is a valuable resource for researchers studying spatiotemporal data streams and Big Data analytics, as well as data engineers and data scientists solving data management and analytics problems associated with this class of data.
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