ISCF WAVE 1 AGRI TECH: Early Detection of Lameness in Dairy Cows through Multi-format Data Synthesis

在世界各地的乳制品国家，奶牛的跛行日益被认为是一个日益严重的经济和福利问题。英国180万头奶牛的跛行程度仍然高得令人无法接受；最近的研究表明，在任何一天，大约每三头奶牛中就有一头明显跛行。研究表明，及早发现和治疗跛行极大地减少了跛行的流行，从而导致牛奶产量的增加和奶牛福利的提高。很早就发现跛行是困难的，而识别疾病临床前阶段的技术将极大地推动这一领域的发展。这项研究的目的是综合来自多个来源的数据，包括最先进的热像仪、活动/位置监测和反胃传感器，以准确预测奶牛临床前跛行的开始，以便进行早期干预。

Lameness in dairy cattle is increasingly recognised as a growing and significant economic and welfare problem in dairy nations around the world. Lameness remains at unacceptably high levels amongst the UK's 1.8 million dairy cattle; recent work suggests that approximately one in three cows are identifiably lame on any given day. Research has indicated that very early detection and treatment of lameness substantially reduces the prevalence of lameness which leads to increased milk production as well as enhanced cow welfare. Very early detection of lameness is difficult and technologies to identify the pre-clinical stages of disease would dramatically advance this area. The aim of this research is to synthesis data from multiple sources, including state-of-the-art thermography, activity/location monitoring and rumination sensors, to accurately predict pre-clinical onset of lameness in dairy cows such that early stage interventions are possible.