Conference paper Open Access

Border surveillance using computer vision enabled robotic swarms for semantically enriched situational awareness

George Orfanidis; Savvas Apostolidis; George Prountzos; Marina Riga; Athanasios Kapoutsis; Konstantinos Ioannidis; Elias Kosmatopoulos; Stefanos Vrochidis; Ioannis Kompatsiaris


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  <identifier identifierType="DOI">10.5281/zenodo.3961453</identifier>
  <creators>
    <creator>
      <creatorName>George Orfanidis</creatorName>
      <affiliation>CERTH</affiliation>
    </creator>
    <creator>
      <creatorName>Savvas Apostolidis</creatorName>
      <affiliation>CERTH</affiliation>
    </creator>
    <creator>
      <creatorName>George Prountzos</creatorName>
      <affiliation>CERTH</affiliation>
    </creator>
    <creator>
      <creatorName>Marina Riga</creatorName>
      <affiliation>CERTH</affiliation>
    </creator>
    <creator>
      <creatorName>Athanasios Kapoutsis</creatorName>
      <affiliation>CERTH</affiliation>
    </creator>
    <creator>
      <creatorName>Konstantinos Ioannidis</creatorName>
      <affiliation>CERTH</affiliation>
    </creator>
    <creator>
      <creatorName>Elias Kosmatopoulos</creatorName>
      <affiliation>CERTH</affiliation>
    </creator>
    <creator>
      <creatorName>Stefanos Vrochidis</creatorName>
      <affiliation>CERTH</affiliation>
    </creator>
    <creator>
      <creatorName>Ioannis Kompatsiaris</creatorName>
      <affiliation>CERTH</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Border surveillance using computer vision enabled robotic swarms for semantically enriched situational awareness</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <subjects>
    <subject>Border surveillance</subject>
    <subject>Autonomous systems</subject>
    <subject>Visual detection</subject>
    <subject>Semantic representations</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2019-10-29</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="ConferencePaper"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3961453</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3961452</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://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;Abstract.&lt;br&gt;
Cross-border crime utilizes recent advanced systems to perform their illegal activities. Innovative sensory systems and specialized equipment are examples that were used for tracking of human and of various illicit materials. The increasing challenges that border personnel must resolve require the usage of recent technological advances as&lt;br&gt;
well. Thus, the utilization of pioneer technologies seems imperative to precede technologically organized crime. Towards this objective, the introduction of Unmanned Vehicles (UxV) and the advances of relevant sub-systems has created a new solution to fight cross-border crime. Utilizing a combination of UxVs enriched with enhanced detection capabilities comprises an effective solution. The chapter will introduce and present the capability of an autonomous navigation system by exploiting swarm intelligence principles towards simplifying the overall operation. Computer vision advances and semantically enrichment of the acquired information are incorporated to deliver cutting edge technologies. The described architecture and services can provide a complete solution for optimal border&amp;nbsp; surveillance and increased situation awareness.&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/740593/">740593</awardNumber>
      <awardTitle>autonomous swarm of heterogeneous RObots for BORDER surveillance</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
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