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De Sola-Morales Serra, PauAuthorBariviera A.Author

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March 6, 2025
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Data Stream Processing Method for Clustering of Trajectories

Publicated to:Applied Computer Sciences In Engineering. 1658 CCIS 151-163 - 2022-01-01 1658 CCIS(), DOI: 10.1007/978-3-031-19961-5_11

Authors: Reyes G; Lanzarini L; Estrebou C; Bariviera A

Affiliations

Facultad de Informatica, Universidad Nacional de La Plata - Author
Universidad de Guayaquil - Author
Universitat Rovira i Virgili - Author

Abstract

The constant advances in techniques for recording and collecting GPS trajectory information, the increase in the number of devices that collect this type of information such as video cameras, traffic sensors, smart phones, etc., has resulted in a large volume of information. Being able to process this information through data streams that allow intelligent analysis of the data in real time is an area where many researchers are currently making efforts to identify solutions. GPS trajectory clustering techniques allow the identification of vehicle patterns over large volumes of data. This paper presents a method that processes data streams for dynamic clustering of vehicular GPS trajectories. The proposed method here receives a GPS data stream, processes it using a buffer memory and the creation of a grid with the use of indexes, and subsequently analyzes each cell of the grid with the use of a dynamic clustering technique that extracts the characteristics of reduced zones of the study area, visualizing common speed ranges in interactive maps. To validate the proposed method, two data sets from Rome-Italy and Guayaquil-Ecuador were used, and measurements were made of execution time, used memory and silhouette coefficient. The obtained results are satisfactory.

Keywords

Buffer memoryCellsClustersData streamTrajectories

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2025-07-16:

  • Open Alex: 1
  • Scopus: 1

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-07-16:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 5 (PlumX).

Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Argentina; Ecuador.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: Last Author (Fernández Bariviera, Aurelio).