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Image processing method for cargo container identification in a stack within the cargo temperature control and fire safety system on container ships

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Języki publikacji
EN
Abstrakty
EN
The current research is focused on the identification of cargo containers in a stack from their images in the infrared and visible spectra, in order to locate the container-origin of ignition within the cargo temperature control and fire safety system. The relevance of the topic is reinforced by the functional requirements for shipboard safety, which are embodied in Chapter II-2 of the Safety of Life at Sea (SOLAS) Convention, and demanded by the necessity of enhancing safety measures during cargo transportation by the world container fleet. The thermal imager’s field of view (FOV) and the coordinate dependencies between the object and its image have been studied and modelled, and an algorithm for fire detection has been defined within the scope of the current research in connection with the containers within the camera’s FOV. A corresponding verification has been carried out by means of simulation modelling using the Unity and C# programming language capabilities.
Rocznik
Tom
Strony
114--120
Opis fizyczny
Bibliogr. 19 poz., rys., tab.
Twórcy
  • National University „Odessa Maritime Academy”, Odesa, Ukraine
Bibliografia
  • 1. European Maritime Safety Agency, “European Maritime Safety Report 2022,” European Maritime Safety Agency, EMSA TN-AA-22-00, 2022. [Online]. Available: https://emsa.europa. eu/publications/item/4735-emsafe-report.html. [Accessed: Feb. 18, 2023].
  • 2. J. Ellis, “Undeclared dangerous goods – Risk implications for maritime transport,” WMU Journal of Maritime Affairs, vol. 9(1), pp. 5–27, 2010, doi: 10.1007/bf03195163.
  • 3. European Maritime Safety Agency, “Safety Analysis of Data Reported in EMCIP – Analysis on Marine Casualties and Incidents involving Container Vessels,” European Maritime Safety Agency, EMSA, 2020. [Online]. Available: https://www. emsa.europa.eu/newsroom/latest-news/item/4276-safetyanalysis-of-data-reported-in-emcip-analysis-onmarinecasualties-and-incidents-involving-container-vessels.html. [Accessed: Feb. 18, 2023].
  • 4. IMO, Consolidated Text of the International Convention for the Safety of Life at Sea, 1974, and its Protocol of 1988: Articles, Annexes and Certificates. Incorporating all amendments in effect from 1 January 2020. London: IMO, 2020.
  • 5. IMO, International Code for Fire Safety Systems. London: IMO, 2015.
  • 6. Fire Training Manual including Fire Safety Operations, 2nd ed. Broadstone: I.C. Brindle, 2011.
  • 7. The Maritime Executive, “Call for Better Fire Fighting Systems on Container Ships,” The Maritime Executive, Sep. 19, 2017. [Online]. Available: https://maritime-executive.com/article/ call-for-better-fire-fighting-systems-on-container-ships. [Accessed: Feb. 18, 2023].
  • 8. W. Zeńczak and A. Krystosik-Gromadzińska, “Improvements to a fire safety management system,” Polish Maritime Research, vol. 26, no. 4, pp. 117–123, Dec. 2019, doi: 10.2478/ pomr-2019-0073.
  • 9. A. Salem, “Vehicle-deck fires aboard Ropax ships: A comparison between numerical modelling and experimental results,” Polish Maritime Research, vol. 26, no. 2, pp. 155–162, Jun. 2019, doi: 10.2478/pomr-2019-0035.
  • 10. Z. Xiong, B. Xiang, Y. Chen, and B. Chen, “Research on the risk classification of cruise ship fires based on an Attention-Bp Neural Network,” Polish Maritime Research, vol. 29, no. 3, pp. 61–68, Sep. 2022, doi: 10.2478/pomr-2022-0026.
  • 11. K. L. B. L. Xavier and V. K. Nanayakkara, “Development of an early fire detection technique using a passive infrared sensor and deep neural networks,” Fire Technology, vol. 58, pp. 3529‒3552, 2022, doi: 10.1007/s10694-022-01319-x.
  • 12. H. Wang, Y. Zhang, and X. Fan, “Rapid early fire smoke detection system using slope fitting in video image histogram,” Fire Technology, vol. 56, pp. 695–714, 2020, doi: 10.1007/ s10694-019-00899-5.
  • 13. X. Cheng, J. Wu, X. Yuan, and H. Zhou, “Principles for a video fire detection system,” Fire Safety Journal, vol. 33(1), pp. 57–69, 1999, doi: 10.1016/s0379-7112(98)00047-2.
  • 14. V. Konon and V. Savchuk, “Infrared thermography in the context of fire safety in container transportation by sea,” Shipping & Navigation, vol. 33, pp. 43–53, 2022, doi: 10.31653/2306-5761.33.2022.43-53.
  • 15. V. Konon and N. Konon, “Application perspective of digital neural networks in the context of marine technologies,” TransNav, The International Journal on Marine Navigation and Safety of Sea Transportation, vol. 16, no. 4, pp. 743‒747, 2022, doi:10.12716/1001.16.04.16.
  • 16. D. F. Rogers, Procedural Elements of Computer Graphics. New York: WCB/McGraw-Hill, 1997.
  • 17. T. Szkodny, “Calculation of the Location Coordinates of an Object Observed by a Camera,” in Man-Machine Interactions 3. Advances in Intelligent Systems and Computing, vol. 242, D. Gruca, T. Czachórski, S. Kozielski, Eds. Cham: Springer, 2014, pp. 139–151, doi: 10.1007/978-3-319-02309-0_15.
  • 18. J. Duh, “Photogrammetry: DTM Extraction & Editing,” Portland State University, 2017. [Online]. Available: https:// web.pdx.edu/~jduh/courses/geog493f17/Week03.pdf [Accessed: Feb. 18, 2023].
  • 19. A. Berg, Detection and Tracking in Thermal Infrared Imagery. Licentiate [Dissertation]. Linköping, Sweden: Linköping University Electronic Press, 2016. [Online]. Available: DiVA – Academic Archive Online, doi: 10.3384/lic.diva-126955.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-98bdb26b-fe0b-4280-8e5b-992e6398392a
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