College of Water Conservancy & Civil Engineering, China Agricultural University, Beijing 100083, China.
Key Lab of Agricultural Engineering in Structure and Environment, Ministry of Agriculture, Beijing 100083, China.
Sensors (Basel). 2018 Sep 1;18(9):2906. doi: 10.3390/s18092906.
Due to the increasing scale of farms, it is increasingly difficult for farmers to monitor their animals in an automated way. Because of this problem, we focused on a sound technique to monitor laying hens. Sound analysis has become an important tool for studying the behaviour, health and welfare of animals in recent years. A surveillance system using microphone arrays of Kinects was developed for automatically monitoring birds' abnormal vocalisations during the night. Based on the principle of time-difference of arrival (TDOA) of sound source localisation (SSL) method, Kinect sensor direction estimations were very accurate. The system had an accuracy of 74.7% in laboratory tests and 73.6% in small poultry group tests for different area sound recognition. Additionally, flocks produced an average of 40 sounds per bird during feeding time in small group tests. It was found that, on average, each normal chicken produced more than 53 sounds during the daytime (noon to 6:00 p.m.) and less than one sound at night (11:00 p.m.⁻3:00 a.m.). This system can be used to detect anomalous poultry status at night by monitoring the number of vocalisations and area distributions, which provides a practical and feasible method for the study of animal behaviour and welfare.
由于农场规模的不断扩大，农民越来越难以对其动物进行自动化监测。由于这个问题，我们专注于一种监测蛋鸡的声音技术。近年来，声音分析已成为研究动物行为、健康和福利的重要工具。我们开发了一个使用 Kinect 麦克风阵列的监控系统，用于自动监测鸟类夜间的异常发声。基于声源定位（SSL）方法的到达时间差（TDOA）原理，Kinect 传感器的方向估计非常准确。该系统在实验室测试中的准确率为 74.7%，在小家禽群测试中的准确率为 73.6%，可用于不同区域声音识别。此外，在小群体测试中，鸡群在进食时平均每只鸡发出 40 个声音。结果发现，平均而言，每只正常鸡在白天（中午至下午 6 点）发出的声音超过 53 次，而在夜间（晚上 11 点至凌晨 3 点）发出的声音不到 1 次。该系统可通过监测发声数量和区域分布来检测夜间异常家禽状态，为动物行为和福利研究提供了一种实用可行的方法。
