Have a personal or library account? Click to login
Oil Spill Detection Using Multi Remote Piloted Aircraft for the Environmental Monitoring of Sea Aquatorium Cover

Oil Spill Detection Using Multi Remote Piloted Aircraft for the Environmental Monitoring of Sea Aquatorium

Open Access
|Jan 2020

References

  1. [1] Urbahs A., Zavtkevics V. Oil Pollution Monitoring of Sea Aquatorium Features with Using Unmanned Aerial Vehicles. Presented at the 18th International Conference Kaunas, Lithuania 2014:75–78.
  2. [2] Brekke C., Solbergb A. Oil spill detection by satellite remote sensing [Online]. [Accessed 30.11.2017]. Available: https://pdfs.semanticscholar.org/af8d/474288595d6bb7b1b90e530c16ca17d647c8.pdf
  3. [3] Muttin F. Modeling of captive Unmanned Aerial System tele detecting oil pollution on sea surface. John Wiley & Sons, 2014. https://doi.org/10.1002/9781119003021.ch710.1002/9781119003021.ch7
  4. [4] Urbahs A., Jonaite I. Features of the use of unmanned aerial vehicles for agriculture applications. Aviation 2013:17:170–175. https://doi.org/10.3846/16487788.2013.86122410.3846/16487788.2013.861224
  5. [5] Fingas M., Brown C. Review of Oil Spill Remote Sensing. Marine Pollution Bulletin 2014:83:9–23. https://doi.org/10.1016/j.marpolbul.2014.03.05910.1016/j.marpolbul.2014.03.05924759508
  6. [6] Urbahs A., Zavtkevics V. Remote Piloted Aircraft using for sampling of oil spill. Presented in the proceedings of Transport Means 2017. The 21st international scientific conference. Part 2, Kaunas, Lithuania, 2017.
  7. [7] Urbahs A., Zavtkevics V. Remotely Piloted Aircraft route optimization when performing oil pollution monitoring of the sea aquatorium. Aviation 2017:21:170–175. https://doi.org/10.3846/16487788.2017.134413910.3846/16487788.2017.1344139
  8. [8] Dijkstra E. A note on two problems in connection with graphs. Numerische Mathematik 1959:1:269–271. https://doi.org/10.1007/BF0138639010.1007/BF01386390
  9. [9] Dantzig G., Fulkerson R., Johnson S. Solution of a Large-Scale Traveling-Salesman Problem. Journal of the Operations Research Society of America 1954:2:393–410. https://doi.org/10.1287/opre.2.4.39310.1287/opre.2.4.393
  10. [10] Adubi S., Misra S. A comparative study on the ant colony optimization algorithms. Presented in the 11th International Conference on Electronics, Computer and Computation (ICECCO), Abuja, Nigeria, 2014.10.1109/ICECCO.2014.6997567
  11. [11] Walter B., Sannier A., Reiners D., Oliver J. UAV Swarm Control: Calculating Digital Pheromone Fields with the GPU. The Journal of Defense Modeling and Simulation Applications, Methodology, Technology 2006:3:167–176. https://doi.org/10.1177%2F15485129060030030410.1177/154851290600300304
  12. [12] Niccolini M., Pollini L., Innocenti L. Cooperative Control for Multiple Autonomous Vehicles Using Descriptor Functions. The Journal of Sensor and Actuator Networks 2014:3:26–43. https://doi.org/10.3390/jsan301002610.3390/jsan3010026
  13. [13] Eaton C., Chong K., Maciejewski A. Multiple-Scenario Unmanned Aerial System Control: A Systems Engineering Approach and Review of Existing Control Methods. Aerospace 2016:3. http://dx.doi.org/10.3390/aerospace301000110.3390/aerospace3010001
  14. [14] Rubio J. C., Vagners J., Rysdyk R. Adaptive path planning for autonomous UAV oceanic search missions. Presented at the Intelligent Systems Technical Conference, Chicago, USA, 2004. https://doi.org/10.2514/6.2004-622810.2514/6.2004-6228
  15. [15] Cottam R., Ranson W., Vounckx R. Autocreative hierarchy II: dynamics self-organization, emergence and level-changing. Presented at the International Conference on Integration of Knowledge Intensive Multi-Agent Systems, Cambridge, USA, 2003. https://doi.org/10.1109/KIMAS.2003.124513410.1109/KIMAS.2003.1245134
  16. [16] Sun A., Liu H. Cooperative UAV Search for Moving Targets Using a Modified Diffusion Uncertainty Model, 2009. http://dx.doi.org/10.2514/6.2009-577910.2514/6.2009-5779
  17. [17] Cummings M., Bruni S., Mercier S., Mitchell P. Automation Architecture for Single Operator, Multiple UAV Command and Control. International C2 Journal 2007.
  18. [18] AeroVations Associates. Autonomous Civil Unmanned Aircraft Systems Software Quality Assessment and Safety Assurance. Autonomous Unmanned Aircraft Systems 2914, 2007.
  19. [19] Belta C., Kumar V. Abstractions and control for groups of robots. IEEE Transactions on Robotics 2004:20:865–875. https://doi.org/10.1109/TRO.2004.82949810.1109/TRO.2004.829498
  20. [20] Bertuccelli L., How J. Robust UAV Search for Environments with Imprecise Probability Maps. Presented at the IEEE Conference on Decision and Control, and the European Control Conference, Seville, Spain, 2005. https://doi.org/10.1109/CDC.2005.158306810.1109/CDC.2005.1583068
  21. [21] Zhang C., Pei H. Oil Spills Boundary Tracking Using Universal Kriging and Model Predictive Control by UAV. Presented at the 11th World Congress on Intelligent Control and Automation, Shenyang, China, 2014.
  22. [22] Hirsch M. J., Schroeder D. On the Decentralized Cooperative Control of Multiple Autonomous Vehicles. Handbook of Unmanned Aerial Vehicles. Springer, 2015. https://doi.org/10.1007/978-90-481-9707-1_11210.1007/978-90-481-9707-1_112
  23. [23] Beni G. From swarm intelligence to swarm robotics. Swarm Robotics. Berlin: Springer, 2004. https://doi.org/10.1007/978-3-540-30552-1_110.1007/978-3-540-30552-1_1
  24. [24] Fallahi K., Leung H., Chandana S. An Integrated ACO-AHP Approach for Resource Management Optimization. Presented at the IEEE International Conference on Systems, Man, and Cybernetics, San Antonio, USA, 2009.10.1109/ICSMC.2009.5346794
  25. [25] Koparan C., Koc A., Privette C., Sawyer C. Evaluation of a UAV-Assisted Autonomous water Sampling. Water 2018:10(5):655. https://doi.org/10.3390/w1005065510.3390/w10050655
  26. [26] Soysal O., Sahin E. A macroscopic model for self-organized aggregation in swarm robotic systems. Swarm Robotics. Berlin: Springer, 2007:27–42. https://doi.org/10.1007/978-3-540-71541-2_310.1007/978-3-540-71541-2_3
  27. [27] Urbahs A., Zavtkevics V. Unmanned aerial vehicle for collecting samples from the surface of water. EU patent EP3112840 (A1).
  28. [28] Urbahs A., Zavtkevics V. Water sampling method of oil pollution and for analysis using unmanned aerial vehicle with fixed wings and device for method perform. LV patent application P-15-88 2015-08-20.
  29. [29] Kittipongvises S. Assessment of Environmental Impacts of Limestone Quarrying Operations in Thailand. Environmental and Climate Technologies 2017:20:67–83. https://doi.org/10.1515/rtuect-2017-001110.1515/rtuect-2017-0011
  30. [30] Avotniece Z., Briede A., Klavins M., Aniskevich S. Remote Sensing Observations of Thunderstorm Features in Latvia. Environmental and Climate Technologies 2017:21:28–46. https://doi.org/10.1515/rtuect-2017-001410.1515/rtuect-2017-0014
  31. [31] Dagiliute R., Juozapaitiene G. Stakeholders in the EIA Process: What is Important for Them? The Case of Road Construction. Environmental and Climate Technologies 2018:22:69–82. https://doi.org/10.2478/rtuect-2018-000510.2478/rtuect-2018-0005
  32. [32] Bajcinovci B. Environment Quality: Impact from Traffic, Power Plant and Land Morphology, a Case Study of Prishtina. Environmental and Climate Technologies 2017:19:65–74. https://doi.org/10.1515/rtuect-2017-000610.1515/rtuect-2017-0006
DOI: https://doi.org/10.2478/rtuect-2020-0001 | Journal eISSN: 2255-8837 | Journal ISSN: 1691-5208
Language: English
Page range: 1 - 22
Published on: Jan 19, 2020
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2020 Aleksandrs Urbahs, Vladislavs Zavtkevics, published by Riga Technical University
This work is licensed under the Creative Commons Attribution 4.0 License.