BIG TRAJECTORY DATA: A DISTRIBUTED COMPUTING PERSPECTIVE

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ANBAROĞLU B., Alter Y.

7th International Conference on Smart City Applications, SCA 2022, Castelo Branco, Portekiz, 19 - 21 Ekim 2022, cilt.48, ss.21-27 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 48
  • Doi Numarası: 10.5194/isprs-archives-xlviii-4-w3-2022-21-2022
  • Basıldığı Şehir: Castelo Branco
  • Basıldığı Ülke: Portekiz
  • Sayfa Sayıları: ss.21-27
  • Anahtar Kelimeler: 3V, big spatial data, cloud computing, Distributed computing, trajectory
  • Hacettepe Üniversitesi Adresli: Evet

Özet

© 2022 International Society for Photogrammetry and Remote Sensing. All rights reserved.Trajectory data constitute location of objects at specified time intervals. The continuous availability of GNSS signals, or discrete availability of sensor systems such as license plate recognition cameras are used to generate trajectory data. Consequently, in a smart city context, big trajectory data are being generated on a daily basis. The analysis of big trajectory data entails the use of a distributed environment to conduct analysis, and at least two data sources. The literature review conducted in this paper shows that the two Vs of big data, Volume and Variety, may not be satisfied since researchers usually rely on a centralised computing environment, and analyse data coming from a single data source. Out of the 17 papers published from 2020 in Scopus, only five of them relied on a distributed computing environment, and two of them utilised more than one data source.