A System Using Artificial Intelligence to Detect and Scare Bird Flocks in the Protection of Ripening Fruit

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dc.contributor.authorMarcoň, Petrcs
dc.contributor.authorJanoušek, Jiřícs
dc.contributor.authorPokorný, Josefcs
dc.contributor.authorNovotný, Josefcs
dc.contributor.authorVlachová Hutová, Eliškacs
dc.contributor.authorŠirůčková, Annacs
dc.contributor.authorČáp, Martincs
dc.contributor.authorLázničková, Janacs
dc.contributor.authorKadlec, Radimcs
dc.contributor.authorRaichl, Petrcs
dc.contributor.authorDohnal, Přemyslcs
dc.contributor.authorSteinbauer, Miloslavcs
dc.contributor.authorGescheidtová, Evacs
dc.coverage.issue12cs
dc.coverage.volume21cs
dc.date.accessioned2021-07-14T06:53:25Z
dc.date.available2021-07-14T06:53:25Z
dc.date.issued2021-06-20cs
dc.description.abstractFlocks of birds may cause major damage to fruit crops in the ripening phase. This problem is addressed by various methods for bird scaring; in many cases, however, the birds become accustomed to the distraction, and the applied scaring procedure loses its purpose. To help eliminate the difficulty, we present a system to detect flocks and to trigger an actuator that will scare the objects only when a flock passes through the monitored space. The actual detection is performed with artificial intelligence utilizing a convolutional neural network. Before teaching the network, we employed videocameras and a differential algorithm to detect all items moving in the vineyard. Such objects revealed in the images were labeled and then used in training, testing, and validating the network. The assessment of the detection algorithm required evaluating the parameters precision, recall, and F1 score. In terms of function, the algorithm is implemented in a module consisting of a microcomputer and a connected videocamera. When a flock is detected, the microcontroller will generate a signal to be wirelessly transmitted to the module, whose task is to trigger the scaring actuator.en
dc.formattextcs
dc.format.extent1-16cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationSENSORS. 2021, vol. 21, issue 12, p. 1-16.en
dc.identifier.doi10.3390/s21124244cs
dc.identifier.issn1424-8220cs
dc.identifier.other171859cs
dc.identifier.urihttp://hdl.handle.net/11012/200491
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofSENSORScs
dc.relation.urihttps://www.mdpi.com/1424-8220/21/12/4244/htmcs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/1424-8220/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectbird detectionen
dc.subjectconvolutional neural networken
dc.subjectdeterrent systemen
dc.subjectflocks of birdsen
dc.subjectfruiten
dc.subjectfruit cropsen
dc.subjectstarlingsen
dc.titleA System Using Artificial Intelligence to Detect and Scare Bird Flocks in the Protection of Ripening Fruiten
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versiondraften
sync.item.dbidVAV-171859en
sync.item.dbtypeVAVen
sync.item.insts2021.08.10 12:53:14en
sync.item.modts2021.08.10 12:14:46en
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav teoretické a experimentální elektrotechnikycs
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