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Online Event Recognition from Moving Vehicles: Application Paper

Published online by Cambridge University Press:  20 September 2019

EFTHIMIS TSILIONIS Open the ORCID record for EFTHIMIS TSILIONIS [Opens in a new window] ,
NIKOLAOS KOUTROUMANIS ,
PANAGIOTIS NIKITOPOULOS ,
CHRISTOS DOULKERIDIS  and
ALEXANDER ARTIKIS
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)
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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.

Keywords

Event Pattern MatchingEvent CalculusData Enrichment
Type
Original Article
Information
Theory and Practice of Logic Programming , Volume 19 , Special Issue 5-6: 35th International Conference on Logic Programming , September 2019 , pp. 841 - 856
Copyright
© Cambridge University Press 2019 

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