Institute of Applied Mechanics, National Taiwan University, Taipei, 106319, Taiwan.
Department of Bio-Industrial Mechatronics Engineering, National Chung Hsing University, Taichung, 402202, Taiwan.
Sci Rep. 2024 Jul 10;14(1):15924. doi: 10.1038/s41598-024-66920-2.
Wild bird repulsion is critical in agriculture because it helps avoid agricultural food losses and mitigates the risk of avian influenza. Wild birds transmit avian influenza in poultry farms and thus cause large economic losses. In this study, we developed an automatic wild bird repellent system that is based on deep-learning-based wild bird detection and integrated with a laser rotation mechanism. When a wild bird appears at a farm, the proposed system detects the bird's position in an image captured by its detection unit and then uses a laser beam to repel the bird. The wild bird detection model of the proposed system was optimized for detecting small pixel targets, and trained through a deep learning method by using wild bird images captured at different farms. Various wild bird repulsion experiments were conducted using the proposed system at an outdoor duck farm in Yunlin, Taiwan. The statistical test results of our experimental data indicated that the proposed automatic wild bird repellent system effectively reduced the number of wild birds in the farm. The experimental results indicated that the developed system effectively repelled wild birds, with a high repulsion rate of 40.3% each day.
鸟类驱离在农业中至关重要，因为它有助于避免农业食物损失并减轻禽流感的风险。野生鸟类在家禽养殖场传播禽流感，因此会造成巨大的经济损失。在本研究中，我们开发了一种基于深度学习的自动鸟类驱离系统，该系统结合了激光旋转机构。当农场出现野鸟时，所提出的系统会检测到其检测单元拍摄的图像中的鸟的位置，然后使用激光束驱离鸟。所提出系统的野生鸟类检测模型经过优化，可用于检测小像素目标，并通过在不同农场拍摄的野生鸟类图像使用深度学习方法进行训练。在台湾云林的一个户外养鸭场使用所提出的系统进行了各种鸟类驱离实验。我们的实验数据的统计测试结果表明，所提出的自动鸟类驱离系统有效地减少了农场中的鸟类数量。实验结果表明，所开发的系统有效地驱离了鸟类，每天的驱离率高达 40.3%。
