Methods for Optical Monitoring of Oil Pollution of Sea Water Basins Using Unmanned Aerial Vehicles

Abstract

We present the results of devising new techniques and technical means for utilizing small-sized unmanned aerial vehicles (UAVs) in ecological monitoring of marine water basins in compliance with the MARPOL 73/78 international convention. The development of a hardware-software complex is described for the system of recognizing oil spills using elements of artificial intelligence. The laboratory experiments on identifying oil spills by laser induced fluorescence (LIF) methods are presented, as well as the methods of recording the spectrum of upward solar radiation.

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REFERENCES

  1. 1

    Press Releases. https://eu.oceana.org/en/press-center/ press-releases/every-six-minutes-illegal-hydrocarbon-dumping-incident-takes-place. Cited December 18, 2018.

  2. 2

    M. Julian, MARPOL 73/78: The International Convention for the Prevention of Pollution from Ships (Maritime Studies, 2000), p. 16–23

  3. 3

    The dumping of hydrocarbons from ships into the seas and ocean of Europe. https://oceana.org/reports/dumping-hydrocarbons-ships-seas-and-oceans-europe-other-side-oil-slicks. Cited December 18, 2018.

  4. 4

    I. Leifer, B. Lehr, D. Simecek-Beatty, E. Bradley, and R. Clark, “State of the art satellite and airborne oil spill remote sensing: Application to the BP deepwater horizon oil spill,” Remote Sens. Environ. 124, 185–209 (2012).

    ADS  Article  Google Scholar 

  5. 5

    O. A. Bukin, D. Yu. Proschenko, A. A. Chekhlenok, S. S. Golik, I. O. Bukin, A. Yu. Mayor, and V. F. Yurchik, “Laser spectroscopic sensors for the development of anthropomorphic robot sensitivity,” Sensors 18 (6), 1680 (2018).

    Article  Google Scholar 

  6. 6

    O. A. Bukin, A. Yu. Mayor, D. Y. Proschenko, I. O. Bukin, V. V. Bolotov, A. A. Chekhlenok, and S. A. Mun, “Laser spectroscopy methods in the development of laser sensor elements for underwater robotics,” Atmos. Oceanic Opt. 30 (5), 475–480 (2017).

    Article  Google Scholar 

  7. 7

    http://www.oilspillprevention.org/~/media/oil-spill-prevention/spillprevention/r-and-d/oil-sensing-and-tracking/1144-e1-final.pdf. Cited January 3, 2018.

  8. 8

    www.bonnagreement.org/site/assets/files/1081/aerial_ operations_handbook.pdf. Cited December 18, 2018.

  9. 9

    https://youtu.be/DlYfUyZmWM8. Cited February 4, 2018.

  10. 10

    http://lprosoft.at.ua/load/1-1-0-4-lpSquarev5.0 for Windows. Cited December 18, 2018.

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Correspondence to O. A. Bukin or D. Yu. Proschenko or A. A. Chekhlenok or D. A. Korovetskiy.

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The authors declare that they have no conflicts of interest.

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Translated by O. Bazhenov

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Bukin, O.A., Proschenko, D.Y., Chekhlenok, A.A. et al. Methods for Optical Monitoring of Oil Pollution of Sea Water Basins Using Unmanned Aerial Vehicles. Atmos Ocean Opt 32, 459–463 (2019). https://doi.org/10.1134/S102485601904002X

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Keywords:

  • ecological monitoring
  • artificial intelligence
  • machine learning
  • laser-induced fluorescence
  • spectroscopy
  • UAVs