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  1. Proceedings of the 5th ACM SIGSPATIAL International Workshop on GeoStreaming (IWGS '14)
  2. Processing real-time sensor data streams for 3D web visualization
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Evaluating stream predicates over dynamic fields
On the locality of keywords in Twitter streams
Temporal coverage aggregates over moving region streams
Crowd-sourced prediction of pedestrian congestion for bike navigation systems
Road network compression techniques in spatiotemporal embedded systems: a survey
Predicting next location using a variable order Markov model
Modelling movement patterns using topological relations between a directed line and a region
Enumeration of complete set of flock patterns in trajectories
The CMR model of moving regions
Processing real-time sensor data streams for 3D web visualization
Shopaholic: a crowd-sourced spatio-temporal product-deals evaluation system (demo paper)
The vanishing firefly project: engaging citizen scientists with a mobile technology and real-time reporting framework

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Processing real-time sensor data streams for 3D web visualization

Content Provider ACM Digital Library
Author Reitz, Thorsten Vial, David Bröring, Arne
Abstract Today, myriads of sensors are surrounding us. Their usage ranges from environmental monitoring (e.g., weather and air quality), over sensor-equipped smart buildings, to the quantified self and other human observing applications. The data streams produced by such sensors often update with high frequencies, resulting in large data volumes. Being able to analyze those real-time sensor data streams requires efficient visualization techniques. In our work, we explore how 3D visualizations can be used to extend the available information space. More specifically, we present an approach for processing real-time sensor data streams to enable scalable Web-based 3D visualizations. Based on an event-driven architecture, our key contribution is the presentation of three processing patterns to optimize transmission of sensor data streams to 3D Web clients.
Starting Page 72
Ending Page 80
Page Count 9
File Format PDF
ISBN 9781450331395
DOI 10.1145/2676552.2676556
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2014-11-04
Publisher Place New York
Access Restriction Subscribed
Subject Keyword 3d visualization Event processing Sensor data
Content Type Text
Resource Type Article
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