Conference paper Open Access

On-the-fly mobility event detection over aircraft trajectories

Kostas Patroumpas; Nikos Pelekis; Yannis Theodoridis


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  <identifier identifierType="URL">https://zenodo.org/record/2469981</identifier>
  <creators>
    <creator>
      <creatorName>Kostas Patroumpas</creatorName>
      <affiliation>IMSI, Athena Research Center, Hellas</affiliation>
    </creator>
    <creator>
      <creatorName>Nikos Pelekis</creatorName>
      <affiliation>University of Piraeus, Hellas</affiliation>
    </creator>
    <creator>
      <creatorName>Yannis Theodoridis</creatorName>
      <affiliation>University of Piraeus, Hellas</affiliation>
    </creator>
  </creators>
  <titles>
    <title>On-the-fly mobility event detection over aircraft trajectories</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2018</publicationYear>
  <subjects>
    <subject>air traffic management, geostreaming, mobility events, trajectories</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2018-11-06</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Text">Conference paper</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/2469981</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1145/3274895.3274970</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/h2020_datacron</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;We present an application framework that consumes streaming positions from a large fleet of flying aircrafts monitored in real time over a wide geographical area. Tailored for aviation surveillance, this online processing scheme only retains locations conveying salient mobility events along each flight, and annotates them as stop, change of speed, heading or&amp;nbsp; altitude, etc. Such evolving trajectory synopses must keep in pace with the incoming raw streams so as to get incrementally annotated with minimal loss in accuracy. We also develop one-pass heuristics to eliminate inherent noise and provide reliable trajectory representations. Our prototype implementation on top of Apache Flink and Kafka has been tested against various real and synthetic datasets offering concrete evidence of its timeliness, scalability, and compression efficiency, with tolerable concessions to the quality of resulting trajectory approximations.&lt;/p&gt;</description>
    <description descriptionType="Other">K. Patroumpas, N. Pelekis, and Y. Theodoridis: "On-the-fly Mobility Event Detection over Aircraft Trajectories".  In proceeding of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2018), November 6 -  9, 2018 Seattle, Washington, USA</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/687591/">687591</awardNumber>
      <awardTitle>Big Data Analytics for Time Critical Mobility Forecasting</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
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