Intensive animal husbandry is becoming more and more popular with the adoption of modern livestock farming technologies. In such circumstances, it is required that the welfare of animals be continuously monitored in a real-time way. To this end, this study describes one on-farm welfare monitoring system for goats, with a combination of Internet of Things and machine learning. First, the system was designed for uninterruptedly monitoring goat growth in a multifaceted and multilevel manner, by means of collecting on-farm videos and representative environmental data. Second, the monitoring hardware and software systems were presented in detail, aiming at supporting remote operation and maintenance, and convenience for further development. Third, several key approaches were put forward, including goat behavior analysis, anomaly data detection, and processing based on machine learning. Through practical deployment in the real situation, it was demonstrated that the developed system performed well and had good potential for offering real-time monitoring service for goats’ welfare, with the help of accurate environmental data and analysis of goat behavior.

中文翻译：

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基于物联网和机器学习的山羊农场福利监测系统

随着现代畜牧业技术的采用，集约化畜牧业越来越受欢迎。在这种情况下，需要以实时方式持续监测动物的福利。为此，本研究描述了一种结合物联网和机器学习的山羊农场福利监测系统。首先，该系统旨在通过收集农场视频和具有代表性的环境数据，以多方面和多层次的方式不间断地监测山羊的生长。其次，详细介绍了监控硬件和软件系统，旨在支持远程操作和维护，方便进一步开发。第三，提出了若干关键方法，包括山羊行为分析、异常数据检测、和基于机器学习的处理。通过在实际情况下的实际部署，证明了所开发的系统性能良好，具有良好的潜力，可借助准确的环境数据和山羊行为分析，为山羊的福利提供实时监测服务。