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Continuous detection of black holes for moving objects at sea

Published: 31 October 2016 Publication History

Abstract

The main objectives of moving objects queries are to search for objects that either lie in some specific areas (i.e., range queries) or are close to one specific location (i.e., kNN queries). Such queries have been previously studied considering either offline database processes using some index techniques or online approaches where incoming data are processed to answer those queries "on the fly". The research presented in this paper considers hybrid queries applied to historical data as well as streaming data. When considering the specific context of the maritime domain and moving objects at sea, a key issue is to make a difference between covered and non covered areas (i.e., regions from where AIS positioning signals are either received or not received). This leads us to introduce the concept of "Black Holes" query where the objective is to identify regions respectively covered and non covered, this providing useful insights for maritime authorities in charge of the regulation of maritime transportation.

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  • (2021)ISOLA: An Innovative Approach to Cyber Threat Detection in Cruise ShippingDevelopments and Advances in Defense and Security10.1007/978-981-16-4884-7_7(71-81)Online publication date: 29-Oct-2021
  • (2021)Uncertainty Handling for Maritime Route DeviationGuide to Maritime Informatics10.1007/978-3-030-61852-0_9(263-297)Online publication date: 9-Feb-2021
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cover image ACM Other conferences
IWGS '16: Proceedings of the 7th ACM SIGSPATIAL International Workshop on GeoStreaming
October 2016
93 pages
ISBN:9781450345798
DOI:10.1145/3003421
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • ESRI
  • amazon: amazon
  • Google Inc.
  • Microsoft: Microsoft
  • ORACLE: ORACLE
  • Facebook: Facebook

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 31 October 2016

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Author Tags

  1. black holes
  2. hybrid processing
  3. maritime monitoring
  4. moving objects

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SIGSPATIAL'16
Sponsor:
  • amazon
  • Microsoft
  • ORACLE
  • Facebook

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Overall Acceptance Rate 7 of 9 submissions, 78%

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Cited By

View all
  • (2021)Data fusion challenges for AIS anti-piracy measuresOCEANS 2021: San Diego – Porto10.23919/OCEANS44145.2021.9705709(1-4)Online publication date: 20-Sep-2021
  • (2021)ISOLA: An Innovative Approach to Cyber Threat Detection in Cruise ShippingDevelopments and Advances in Defense and Security10.1007/978-981-16-4884-7_7(71-81)Online publication date: 29-Oct-2021
  • (2021)Uncertainty Handling for Maritime Route DeviationGuide to Maritime Informatics10.1007/978-3-030-61852-0_9(263-297)Online publication date: 9-Feb-2021
  • (2020)Data integrity assessment for maritime anomaly detectionExpert Systems with Applications: An International Journal10.1016/j.eswa.2020.113219147:COnline publication date: 1-Jun-2020
  • (2020)Towards a Modelling and Optimisation of the Recovery of Marine Floating PlasticWeb and Wireless Geographical Information Systems10.1007/978-3-030-60952-8_21(214-229)Online publication date: 22-Oct-2020
  • (2019)Heterogeneous Integrated Dataset for Maritime Intelligence, Surveillance, and ReconnaissanceData in Brief10.1016/j.dib.2019.104141(104141)Online publication date: Jun-2019
  • (2018)Past, present, and future of the satellite-based automatic identification system: areas of applications (2004–2016)WMU Journal of Maritime Affairs10.1007/s13437-018-0151-617:3(311-345)Online publication date: 10-Sep-2018

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