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Title Efficient Generation of Approximate Region-based Geo-maps from Big Geotagged Data
ID_Doc 44673
Authors Al Jawarneh, IM; Foschini, L; Corradi, A
Title Efficient Generation of Approximate Region-based Geo-maps from Big Geotagged Data
Year 2023
Published
DOI 10.1109/CAMAD59638.2023.10478398
Abstract smart city applications scenarios, such as traffic monitoring, require regularly generating region-based geographical maps (geo-maps) such as choropleth, to uncover statistical patterns in the data, therefore helping municipalities to achieve better urban planning. However, with tremendous avalanches of big data arriving in fast streams, it is becoming cumbersome and inefficient to achieve the visualization task in a timely manner. Having said that, spatial approximate query processing presents itself as an indispensable and reliable solution in cases of data overloading. In this paper, we focus on presenting a novel system for generating efficiently region-based geo-maps from fast arriving big georeferenced data streams. We specifically present ApproxGeoViz. It is a system for generating approximate region-based maps from fast arriving data relying on a novel stratified-like spatial sampling method. We have built a standard-compliant prototype and tested its performance on real smart city data. Our results show that ApproxGeoViz is efficient in terms of time-based and accuracy-based QoS constraints such as running time and approximate map accuracy.
Author Keywords heat maps and choropleth; earth mover's distance; geospatial visualization; spatial data sampling; geohash; approximate query processing
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Conference Proceedings Citation Index - Science (CPCI-S)
EID WOS:001196100300016
WoS Category Computer Science, Hardware & Architecture; Engineering, Electrical & Electronic; Telecommunications
Research Area Computer Science; Engineering; Telecommunications
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