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Batch Simplification Algorithm for Trajectories over Road Networks

Bibliographic Data

ID22034672
AuthorsGary Reyes (0000-0002-3711-1906, University of Guayaquil, corresponding author), Vivian Estrada (University of Information Science), Roberto Tolozano-Benites (0000-0002-4164-5839, Universidad Bolivariana del Ecuador), Victor Maquilón (0000-0003-3611-3560, University of Guayaquil)
Year2023
Volume12
Issue10
Pages399
Publication date2023-09-30
Open AccessYes
TypeARTICLE
VenueISPRS International Journal of Geo-Information (JOURNAL)
Journal identifiersISSN: 2220-9964 • E-ISSN: 2220-9964
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/ijgi12100399
OpenAlexW4387264813
LanguageEN
References cited45

The steady increase in data generation by GPS systems poses storage challenges. Previous studies show the need to address trajectory compression. The demand for accuracy and the magnitude of data require effective compression strategies to reduce storage. It is posited that the combination of TD-TR simplification, Kalman noise reduction, and analysis of road network information will improve the compression ratio and margin of error. The GR algorithm is developed, integrating noise reduction and path compression techniques. Experiments are applied with trajectory data sets collected in the cities of California and Beijing. The GR algorithm outperforms similar algorithms in compression ratio and margin of error, improving storage efficiency by up to 89.090%. The combination of proposed techniques presents an efficient solution for GPS trajectory compression, allowing to improve storage in trajectory analysis applications

Algorithm · Compression ratio · Computer data storage · Data compression · Data mining · Global Positioning System · Kalman filter · Machine learning · Noise reduction · Real-time computing · Telecommunications · Trajectory · Computer Science · Data Management and Algorithms · Engineering · Human Mobility and Location-Based Analysis · Mathematics · Traffic Prediction and Management Techniques · Artificial Intelligence

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