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The Method of Time Distribution for Environment Monitoring Using Unmanned Aerial Vehicles According to an Inverse Priority

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Języki publikacji
EN
Abstrakty
EN
This paper presents a time-saving method for monitoring the ecology of a dispersed territory using the delivery of measurement units provided by unmanned aerial vehicles with measurement sensors according to a reverse priority algorithm. It is achievable because of the decreasing mean waiting time of the order inside a queue during low-priority order servicing. The experimental research that confirms the efficiency of the proposed method in the case of delivery distributed measurement systems for low-priority measurement is carried out. The experimental research of the proposed method in the case of one-channel and many-channel SMD that can have an option of order rejection or an in-queue waiting option is conducted in WeBots. The probability distributions in the case of this system applying are compared with similar probability distributions in the case of systems of direct priority applying. Comparison and analysis enable us to conclude that the probability distribution in the case of SMD with a direct priority of delivery tends to decrease and approximates zero. This is related to the fact that means at the end of the queue to be handled have a lower priority, as these means of measurement take longer to handle the order than those at the head of the queue. Thus, the means of a low priority will be serviced in the last charge and there is a constant possibility that in some cases such orders will be rejected. The proposed method enables moderate this situation by using increasing the possibility of servicing the low-priority orders. The method can increase the efficiency of environmental monitoring and pollution emission control.
Rocznik
Strony
179--187
Opis fizyczny
Bibliogr. 9 poz., rys.
Twórcy
  • Lublin University of Technology, ul. Nadbystrzycka 38a, 20-618, Lublin, Poland
  • Institute Information and Computational Technologies CS MES RK, Pushkin St 125, 050000, Almaty, Kazakhstan
  • Vinnytsya National Technical University, 95, Khmelnytsky Hwy, 21021, Vinnytsya, Ukraine
  • Vinnytsya National Technical University, 95, Khmelnytsky Hwy, 21021, Vinnytsya, Ukraine
  • Vinnytsya National Technical University, 95, Khmelnytsky Hwy, 21021, Vinnytsya, Ukraine
  • Vinnytsya National Medical University, 56, Pirogova St, 21018, Vinnytsya, Ukraine
  • Vasyl' Stus Donetsk National University, 21, 600-Richchya St, 21000, Vinnytsia, Ukraine
  • Vinnytsia Mykhailo Kotsiubynskyi State Pedagogical University, Ostroz'koho St, 32, 21000, Vinnytsia, Ukraine
  • Vinnytsya National Technical University, 95, Khmelnytsky Hwy, 21021, Vinnytsya, Ukraine
  • East Kazakhstan State University, 30-Y Gvardeyskoy Divizii, 070000 Ust'-Kamenogorsk, Kazakhstan
  • Turan University, Satpaev Street 16А, Almaty 050013, Kazachstan
  • M.Kh. Dulaty Taraz Regional University, Tole Bi St, 40, Taraz, Kazachstan
  • Satbayev University, Satpaev Street 22, 050000, Almaty, Kazachstan
  • Satbayev University, Satpaev Street 22, 050000, Almaty, Kazachstan
Bibliografia
  • 1. Bekon D., Kharrys H. 2004. Operation systems. Parallel and distributed systems. Pyter, Sankt Petersburg. (in Russian)
  • 2. Blackstock K.L., et al. 2017. Monitoring and Evaluation for Ecosystem Management (MEEM)-Comparing theory and documented practice across Europe. Technical Report, James Hutton Institute, 96. https://www.researchgate.net/publication/330450321_Monitoring_and_Evaluation_for_Ecosystem_Management_MEEM-Comparing_theory_and_documented_practice_across_Europe
  • 3. Dogan A. 2003. Probabilistic approach in path planning for UAVs. Intelligent Control. 2003 IEEE International Symposium, 608–613.
  • 4. Knysh B.P., Kulyk Y.A., Baraban M.V. 2018a. Classification of unmanned aerial vehicles and their use for goods delivery. Herald of Khmelnytskyy National University, 3, 246–252. (in Ukrainian)
  • 5. Knysh B.P., Kulyk Y.A., Lisovenko А.І. 2018b. Metod rozpodilu chasu na dostavku tovariv za do- pomohoiu bezpilotnykh litalnykh aparativ zhidno priorytetu. Herald of Khmelnytskyy national university, 6, 232–240. (in Ukrainian) http://nbuv.gov.ua/UJRN/Vchnu_tekh_2018_3_42
  • 6. Romanyuk O.N., Pavlov S.V., Melnyk O.V., Romanyuk S.O., Smolarz A., Bazarova M. 2015. Method of anti-aliasing with the use of the new pixel model, Proc. SPIE 9816, 981617. DOI: 10.1117/12.2229013
  • 7. Viunenko O.B., Voronets L.P. 2008. Research of operations. System of mass service. SNAU, Sumy. (in Ukrainian)
  • 8. Yang X., Koziel S., Leifsson L. 2014. Computational optimization, modelling and simulation: Past, present and future. Procedia Computer Science, 29, 754–758.
  • 9. Zhu X., Liu Z., Yang J. 2015. Model of Collaborative UAV Swarm Toward Coordination and Control Mechanisms Study. Procedia Computer Science, 51, 493–502.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-6cf95e28-337e-4404-8abf-74263b815ad8
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