农业工程2025，Vol.15Issue(6)：31-38,8.DOI:10.19998/j.cnki.2095-1795.202506306
基于YOLOv8s的鸡群活动量异常监控方法
Anomaly monitoring method for chicken flock activity based on YOLOv8s
徐文龙 1仝志民 1班浩 1范峻岭 1潘越新1
作者信息
- 1. 青岛农业大学机电工程学院,山东 青岛 266000
- 折叠
摘要
Abstract
Chicken activity level is an important indicator reflecting their health.By monitoring activity level of chicken flock,poten-tial health issues can be identified in time to prevent disease spread.Therefore,an anomaly monitoring method for chicken flock activity based on YOLOv8s and BoT-SORT algorithm was proposed.Cameras were used to capture chicken activity videos,YOLOv8s was used to extract appearance and motion features of chickens,and BoT-SORT algorithm was integrated to achieve multi-object tracking.By analyzing movement trajectories,activity level of each chicken was quantified,and an automatic comparison with preset activity thresholds was done to provide timely alerts for abnormal conditions.Experimental results showed that method achieved a multi-object tracking precision(MOTP)of 94.33%,effectively monitoring chicken activity levels and providing early warnings for potential problems.关键词
鸡群/健康监控/YOLOv8s/BoT-SORT/活动量监控/多目标跟踪Key words
chicken flock/health monitor/YOLOv8s/BoT-SORT/activity monitoring/multi-object tracking分类
农业科技引用本文复制引用
徐文龙,仝志民,班浩,范峻岭,潘越新..基于YOLOv8s的鸡群活动量异常监控方法[J].农业工程,2025,15(6):31-38,8.
