Evidence map›Paper›PMID 34205763›Full record

ArticleSensors (Basel, Switzerland)2021

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

Petr Marcoň, Jiří Janoušek, Josef Pokorný, Josef Novotný, Eliška Vlachová Hutová, Anna Širůčková, Martin Čáp, Jana Lázničková, Radim Kadlec, Petr Raichl and 3 more

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
2.4field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 20 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 1 institution in 1 country.

Petr MarcoňFaculty of Electrical Engineering and Communication, Brno University of Technology, 61600 Brno, Czech Republic.ORCID 0000-0001-7349-8426
Jiří JanoušekFaculty of Electrical Engineering and Communication, Brno University of Technology, 61600 Brno, Czech Republic.ORCID 0000-0002-9940-4966
Josef PokornýFaculty of Electrical Engineering and Communication, Brno University of Technology, 61600 Brno, Czech Republic.
Josef NovotnýFaculty of Electrical Engineering and Communication, Brno University of Technology, 61600 Brno, Czech Republic.
Eliška Vlachová HutováFaculty of Electrical Engineering and Communication, Brno University of Technology, 61600 Brno, Czech Republic.
Anna ŠirůčkováFaculty of Electrical Engineering and Communication, Brno University of Technology, 61600 Brno, Czech Republic.
Martin ČápFaculty of Electrical Engineering and Communication, Brno University of Technology, 61600 Brno, Czech Republic.
Jana LázničkováFaculty of Electrical Engineering and Communication, Brno University of Technology, 61600 Brno, Czech Republic.
Radim KadlecFaculty of Electrical Engineering and Communication, Brno University of Technology, 61600 Brno, Czech Republic.
Petr RaichlFaculty of Electrical Engineering and Communication, Brno University of Technology, 61600 Brno, Czech Republic.
Přemysl DohnalFaculty of Electrical Engineering and Communication, Brno University of Technology, 61600 Brno, Czech Republic.
Miloslav SteinbauerFaculty of Electrical Engineering and Communication, Brno University of Technology, 61600 Brno, Czech Republic.ORCID 0000-0002-1358-6974
Eva GescheidtováFaculty of Electrical Engineering and Communication, Brno University of Technology, 61600 Brno, Czech Republic.ORCID 0000-0003-4048-6108
Brno University of Technology · CZ

Funding

Technology Agency of the Czech Republic TJ04000441
6 · The paper itself

Abstract

Flocks 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.

Indexed as

Artificial IntelligenceFruitAnimalsBirdsNeural Networks, Computerbird detectionconvolutional neural networkdeterrent systemflocks of birdsfruitfruit cropsstarlings

Identifiers

PMID34205763
PMCPMC8234036
OpenAlexW3173227807

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.