基于射频识别技术的笼养雏鸡运动监测研究

Movement Monitoring of Caged Chicken Using Radio Frequency Identification

为了解笼养雏鸡的运动行为和健康状况,研究设计了一种基于射频识别技术(RFID)的笼养鸡个体实时运动监测系统。研究首先搭建了一个模拟的试验环境,其包括一个超高频的射频识别读写器,三个天线和若干标签,一台计算机以及射频识别读写软件;随后使用机器学习的方法拟合出当前环境下不同天线接收信号强度与距离之间的关系,并进行性能比较;通过对数据进行预处理,使用获得的距离模型计算出标签与不同天线之间的距离,使用多点定位计算出所建立坐标系下标签的位置信息,实现对不同标签的运动轨迹可视化。结果显示,选定的6个电子标签测试时间为30 min,标签的计算位置与真实位置的最小欧式误差距离为4.52 cm,所有测试点的平均误差距离为9.56 cm;对比标签的真实运动轨迹和计算运动轨迹,RFID监测系统能够动态地识别活动量减少或不活动的病鸡。研究表明,基于RFID建立的笼养鸡个体实时运动检测系统能够实时监测笼养鸡个体活动情况,为家禽健康监测和疾病预防提供技术支持。

In order to understand the movement behavior and health status of caged chicken,a real-time movement monitor-ing system for caged chickens based on radio frequency identification(RFID)was designed.Firstly,a simulated experimental en-vironment was built,which included a ultra-high-frequency RFID reader,three antennas,several tags,a computer and RFID reader software.Then,the relationship between the received signal strength and the distance of different antennas in the current environment was fitted by using the machine learning method,and the performance was compared.The distance model was used to calculate the distance between the tag and different antennas,and the multi-point positioning was used to calculate the position information of the tag in the established coordinate system.Finally,the movement trajectories of different tags were visualized.The results showed that for the six selected tags,the test time was 30 min,the minimum Euclidean error distance between the cal-culated position of the tag and the real position was 4.52 cm,and the average error distance of all test points was 9.56 cm.By com-paring the real movement trajectory of the tag with the calculated movement trajectory,the RFID monitoring system could dynami-cally identify the sick chicken with reduced activity or inactivity.It′s indicated that the established real-time movement monitor-ing system for caged chickens based on RFID could use for monitoring the individual movement of caged chicken,which could provide technical support for health monitoring and disease prevention in poultry.