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Spatio-Temporal Data Streams

  • Book
  • © 2016

Overview

Authors:
  1. Zdravko Galić

    1. Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia

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Part of the book series: SpringerBriefs in Computer Science (BRIEFSCOMPUTER)

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Table of contents (4 chapters)

  1. Front Matter

    Pages i-xiv
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  2. Introduction

    • Zdravko Galić
    Pages 1-15

  3. Spatio-Temporal Continuous Queries

    • Zdravko Galić
    Pages 17-45

  4. Spatio-Temporal Data Streams and Big Data Paradigm

    • Zdravko Galić
    Pages 47-69

  5. Spatio-Temporal Data Stream Clustering

    • Zdravko Galić
    Pages 71-103

  6. Back Matter

    Pages 105-107
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Keywords

About this book

This SpringerBrief presents the fundamental concepts of a specialized class of data stream, spatio-temporal 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 state-of-the-art techniques. Key topics include spatio-temporal continuous queries, distributed stream processing, SQL-like language embedding, and trajectory stream clustering. 
 
Over the course of the book, the reader will become familiar with spatio-temporal data streams management and data flow processing, which enables the analysis of huge volumes of location-aware continuous data streams. Applications range from mobile object tracking and real-time intelligent transportation systems to traffic monitoring and complex event processing.
 
Spatio-Temporal Data Streams is a valuable resource for researchers studying spatio-temporal 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.






Authors and Affiliations

  • Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia

    Zdravko Galić

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