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  4. Autonomous Detection and Deterrence of Pigeons on Buildings by Drones
 
research article

Autonomous Detection and Deterrence of Pigeons on Buildings by Drones

Schiano, Fabrizio  
•
Natter, Dominik
•
Zambrano, Davide  
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2022
IEEE Access

Pigeons may transmit diseases to humans and cause damages to buildings, monuments, and other infrastructure. Therefore, several control strategies have been developed, but they have been found to be either ineffective or harmful to animals and often depend on human operation. This study proposes a system capable of autonomously detecting and deterring pigeons on building roofs using a drone. The presence and position of pigeons were detected in real time by a neural network using images taken by a video camera located on the roof. Moreover, a drone was utilized to deter the animals. Field experiments were conducted in a real-world urban setting to assess the proposed system by comparing the number of animals and their stay durations for over five days against the 21-day- trial experiment without the drone. During the five days of experiments, the drone was automatically deployed 55 times and was significantly effective in reducing the number of birds and their stay durations without causing any harm to them. In conclusion, this study has proven the effectiveness of this system in deterring birds, and this approach can be seen as a fully autonomous alternative to the already existing methods.

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Type
research article
DOI
10.1109/ACCESS.2021.3137031
Author(s)
Schiano, Fabrizio  
•
Natter, Dominik
•
Zambrano, Davide  
•
Floreano, Dario  
Date Issued

2022

Published in
IEEE Access
Volume

10

Start page

1745

End page

1755

Subjects

Artificial intelligence

•

neural networks

•

object recognition

•

pest control

•

unmanned aerial vehicles

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LIS  
FunderGrant Number

FNS-NCCR

NCCR Robotics

Available on Infoscience
January 10, 2022
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/184347
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