Pandey Santosh, Kalwa Upender, Kong Taejoon, Guo Baoqing, Gauger Phillip C, Peters David J, Yoon Kyoung-Jin
Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.
Center for Defense Acquisition and Requirements Analysis, Korea Institute for Defense Analyses, 37 Hoegi-ro, Dongdaemun-gu, Seoul 02455, Korea.
Animals (Basel). 2021 Sep 10;11(9):2665. doi: 10.3390/ani11092665.
Precision swine production can benefit from autonomous, noninvasive, and affordable devices that conduct frequent checks on the well-being status of pigs. Here, we present a remote monitoring tool for the objective measurement of some behavioral indicators that may help in assessing the health and welfare status-namely, posture, gait, vocalization, and external temperature. The multiparameter electronic sensor board is characterized by laboratory measurements and by animal tests. Relevant behavioral health indicators are discussed for implementing machine learning algorithms and decision support tools to detect animal lameness, lethargy, pain, injury, and distress. The roadmap for technology adoption is also discussed, along with challenges and the path forward. The presented technology can potentially lead to efficient management of farm animals, targeted focus on sick animals, medical cost savings, and less use of antibiotics.
精准养猪生产可受益于能对猪的健康状况进行频繁检查的自主、非侵入性且价格合理的设备。在此，我们展示一种远程监测工具，用于客观测量一些行为指标，这些指标可能有助于评估猪的健康和福利状况，即姿势、步态、发声和体表温度。多参数电子传感器板通过实验室测量和动物测试进行了特性描述。讨论了相关行为健康指标，以实施机器学习算法和决策支持工具来检测动物跛行、嗜睡、疼痛、损伤和痛苦。还讨论了技术采用的路线图以及挑战和未来方向。所展示的技术有可能实现农场动物的高效管理，有针对性地关注患病动物，节省医疗成本，并减少抗生素的使用。
