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http://dx.doi.org/10.13067/JKIECS.2021.16.1.175

Artificial Intelligence-Based Harmful Birds Detection Control System  

Sim, Hyun (Industry-Academic Cooperation Group, Sunchon National University)
Publication Information
The Journal of the Korea institute of electronic communication sciences / v.16, no.1, 2021 , pp. 175-182 More about this Journal
Abstract
The purpose of this paper is to develop a machine learning-based marine drone to prevent the farming from harmful birds such as ducks. Existing drones have been developed as marine drones to solve the problem of being lost if they collide with birds in the air or are in the sea. We designed a CNN-based learning algorithm to judge harmful birds that appear on the sea by maritime drones operating by autonomous driving. It is designed to transmit video to the control PC by connecting the Raspberry Pi to the camera for location recognition and tracking of harmful birds. After creating a map linked with the location GPS coordinates in advance at the mobile-based control center, the GPS location value for the location of the harmful bird is received and provided, so that a marine drone is dispatched to combat the harmful bird. A bird fighting drone system was designed and implemented.
Keywords
Drone; Machine Learning; Atonomous Driving; Control Systems; Harmful Birds;
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