PDF(Pubmed)
Abstract：
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.
摘要：
野生鸟类排斥在农业中至关重要，因为它有助于避免农业粮食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，从而造成巨大的经济损失。在这项研究中,我们开发了一种自动驱鸟系统，该系统基于基于深度学习的野鸟检测，并与激光旋转机构集成。当一只野鸟出现在农场时，所提出的系统在其检测单元捕获的图像中检测到鸟的位置，然后使用激光束击退鸟。该系统的野鸟检测模型进行了优化，用于检测小像素目标，并使用在不同农场拍摄的野鸟图像通过深度学习方法进行训练。在云林的一个户外养鸭场，使用拟议的系统进行了各种野鸟排斥实验，台湾。我们的实验数据的统计测试结果表明，所提出的自动野生鸟类驱除系统有效地减少了农场中野生鸟类的数量。实验结果表明，开发的系统有效地驱除了野生鸟类，每天40.3%的高排斥率。
