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Online Event Recognition from Moving Vehicles: Application Paper

Published online by Cambridge University Press:  20 September 2019

EFTHIMIS TSILIONIS
Affiliation:
National Center for Scientific Research ‘Demokritos’, Athens, Greece, (e-mail: eftsilio@iit.demokritos.gr)
NIKOLAOS KOUTROUMANIS
Affiliation:
University of Piraeus, Piraeus, Greece, (e-mails: koutroumanis@unipi.gr, nikp@unipi.gr, cdoulk@unipi.gr)
PANAGIOTIS NIKITOPOULOS
Affiliation:
University of Piraeus, Piraeus, Greece, (e-mails: koutroumanis@unipi.gr, nikp@unipi.gr, cdoulk@unipi.gr)
CHRISTOS DOULKERIDIS
Affiliation:
University of Piraeus, Piraeus, Greece, (e-mails: koutroumanis@unipi.gr, nikp@unipi.gr, cdoulk@unipi.gr)
ALEXANDER ARTIKIS
Affiliation:
National Center for Scientific Research ‘Demokritos’, Athens, Greece, and University of Piraeus, Piraeus, Greece, (e-mail: a.artikis@unipi.gr)

Abstract

We present a system for online composite event recognition over streaming positions of commercial vehicles. Our system employs a data enrichment module, augmenting the mobility data with external information, such as weather data and proximity to points of interest. In addition, the composite event recognition module, based on a highly optimised logic programming implementation of the Event Calculus, consumes the enriched data and identifies activities that are beneficial in fleet management applications. We evaluate our system on large, real-world data from commercial vehicles, and illustrate its efficiency.

Type
Original Article
Copyright
© Cambridge University Press 2019 

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