Model of Surveillance in Complex Environment Using a Swarm of Unmanned Aerial Vehicles

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG42__%2F21%3A00556834" target="_blank" >RIV/60162694:G42__/21:00556834 - isvavai.cz</a>
Result on the web
<a href="https://www.springer.com/series/558" target="_blank" >https://www.springer.com/series/558</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-70740-8_15" target="_blank" >10.1007/978-3-030-70740-8_15</a>

Result language
angličtina
Original language name
Model of Surveillance in Complex Environment Using a Swarm of Unmanned Aerial Vehicles
Original language description
This paper examines the model of autonomous surveillance using a swarm of unmanned aerial vehicles with the simultaneous detection principle. This model enables to specify a number of sensors needed to detect an object of interest located in the area of interest; objects are detected only if scanned by the specified number of sensors simultaneously. The model plans deployment of individual vehicles in the swarm during the surveillance operation in a such a way that the surveillance is performed in the maximum quality; the quality is measured as a percentage of the area of interest that is covered during the operation. Furthermore, the surveillance is assumed to be conducted in the complex area of operations (including urban environments, build-up areas, or mountain environments with very uneven terrain) where occlusions caused by obstacles or terrain may occur often. For solution, the metaheuristic algorithm based on the simulated annealing is proposed. This algorithm deploys the number of waypoints, from which the monitoring is performed, maximizing the surveillance quality and taking the simultaneous detection principle into consideration. The algorithm is verified by a set of experiments based on typical surveillance scenarios.
Czech name
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Czech description
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Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISBN
978-3-030-70739-2
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
19
Pages from-to
231-249
Publisher name
Springer Science and Business Media Deutschland GmbH
Place of publication
Cham
Event location
Virtual, Online
Event date
Oct 21, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000763018100015

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