IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i22p2874-d677353.html
   My bibliography  Save this article

Generalized Net Model of Forest Zone Monitoring by UAVs

Author

Listed:
  • Krassimir T. Atanassov

    (Department of Bioinformatics and Mathematical Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. Georgi Bonchev Str., Bl. 105, 1113 Sofia, Bulgaria
    These authors contributed equally to this work.)

  • Peter Vassilev

    (Department of Bioinformatics and Mathematical Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. Georgi Bonchev Str., Bl. 105, 1113 Sofia, Bulgaria
    These authors contributed equally to this work.)

  • Vassia Atanassova

    (Department of Bioinformatics and Mathematical Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. Georgi Bonchev Str., Bl. 105, 1113 Sofia, Bulgaria
    These authors contributed equally to this work.)

  • Olympia Roeva

    (Department of Bioinformatics and Mathematical Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. Georgi Bonchev Str., Bl. 105, 1113 Sofia, Bulgaria
    These authors contributed equally to this work.)

  • Rosen Iliev

    (Bulgarian Defence Institute, 2 Professor Tzvetan Lazarov Blvd., 1592 Sofia, Bulgaria
    These authors contributed equally to this work.)

  • Dafina Zoteva

    (Faculty of Mathematics and Informatics, Sofia University “St. Kliment Ohridski”, 5 James Bourchier Blvd., 1164 Sofia, Bulgaria
    These authors contributed equally to this work.)

  • Veselina Bureva

    (Intelligent Systems Laboratory, “Prof. Dr. Assen Zlatarov” University, 1 “Prof. Yakim Yakimov” Blvd., 8010 Burgas, Bulgaria
    These authors contributed equally to this work.)

  • Deyan Mavrov

    (Intelligent Systems Laboratory, “Prof. Dr. Assen Zlatarov” University, 1 “Prof. Yakim Yakimov” Blvd., 8010 Burgas, Bulgaria
    These authors contributed equally to this work.)

  • Alexander Alexandrov

    (Department of Agricultural and Forestry Sciences, Forest Research Institute, Bulgarian Academy of Sciences, 132 Kliment Ohridski Blvd., 1756 Sofia, Bulgaria
    These authors contributed equally to this work.)

Abstract

The paper presents a generalized net (GN) model of the process of terrain observation with the help of unmanned aerial vehicles (UAVs) for the prevention and rapid detection of wildfires. Using a GN, the process of monitoring a zone (through a UAV, which is further called a reconnaissance drone) and the localization of forest fires is described. For a more indepth study of the terrain, the reconnaissance drone needs to coordinate with a second UAV, called a specialized drone, so that video and sensory information is provided to the supervising fire command operational center. The proposed GN model was developed to assist in the decision-making process related to the coordination of the operation of both UAVs under dynamically changing terrain circumstances, such as those related to preventing or quickly containing wildfires. It describes the stages (transitions), logical determinants (transition predicate matrices), and directions of information flow (token characteristics) within the process of localization of fires using the pair of reconnaissance and specialized drones.

Suggested Citation

  • Krassimir T. Atanassov & Peter Vassilev & Vassia Atanassova & Olympia Roeva & Rosen Iliev & Dafina Zoteva & Veselina Bureva & Deyan Mavrov & Alexander Alexandrov, 2021. "Generalized Net Model of Forest Zone Monitoring by UAVs," Mathematics, MDPI, vol. 9(22), pages 1-10, November.
  • Handle: RePEc:gam:jmathe:v:9:y:2021:i:22:p:2874-:d:677353
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/22/2874/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/9/22/2874/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Josué Toledo-Castro & Pino Caballero-Gil & Nayra Rodríguez-Pérez & Iván Santos-González & Candelaria Hernández-Goya & Ricardo Aguasca-Colomo, 2018. "Forest Fire Prevention, Detection, and Fighting Based on Fuzzy Logic and Wireless Sensor Networks," Complexity, Hindawi, vol. 2018, pages 1-17, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      Corrections

      All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:9:y:2021:i:22:p:2874-:d:677353. See general information about how to correct material in RePEc.

      If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

      If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

      For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

      Please note that corrections may take a couple of weeks to filter through the various RePEc services.

      IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.