Harnessing 3D cameras and deep learning for on-the-fly automated body condition and mobility analysis to improve cattle welfare

利用 3D 摄像头和深度学习进行动态自动化身体状况和活动性分析，以改善牛的福利

• 批准号: 2593504
• 金额: --
• 依托单位: University of Bristol
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2593504
• 关键词: Harnessing; 3D; cameras; deep; learning

A growing world population and climate change are stressing food availability. High animal welfare and health practices are more important than ever to satisfy societal demands for the livestock sector. The use of precision monitoring instrumentation for dairy cattle is key to optimising production while maintaining animal health. In this PhD project, 3D video technology with the latest Intel cameras will be used to unobtrusively provide stress-free monitoring of incremental changes in individual cow mobility and body condition with the aim of understanding behavioural cues preceding observed lameness to improve cow health, welfare and productivity and hence increase the climate and environmental sustainability of milk production. These traits are currently measured by manual visual assessment, requiring high skill levels and training, but are nevertheless open to the subjectivity of individuals and rarely capture the longitudinally detail needed for novel behaviour research. This will realise a system that can be transplanted into farms without extensive instrumentation, allowing farmers and others in the value chain such as vets, nutritionists and livestock advisers to make use of much more precise, consistent and frequent measurements, creating greater opportunities to improve cow performance and welfare. The studentship would suit either a mathematical or computational student interested in sustainable food production, or someone with veterinary or biosciences expertise who wishes to build up artificial intelligence skills - in either case a tailored training package will be developed to suit. The student will learn the key facets of animal welfare assessment, and use this and cutting edge AI to build and apply the system across the studentship timeline so we can develop a better understanding of lameness. The student will be based 50%/50% at two leading, geographically close institutes - Bristol Robotics Laboratory at the University of West of England, and Bristol Veterinary School & Visual Information Laboratory at the University of Bristol, and will benefit from a broad cross-disciplinary supervision team, led by Prof Melvyn Smith (Machine Vision) and Prof Andrew Dowsey (One Health Data Science), who have published state-of-the art work in this area that will be built upon (see https://doi.org/10.1016/j.compind.2018.02.011 , https://arxiv.org/abs/2006.09205, https://www.biorxiv.org/content/10.1101/2020.08.03.234203v2). Data collection and validation will harness the Bristol Veterinary School's John Oldacre Centre for Sustainability and Welfare in Dairy Production, a new research centre based at our Wyndhurst dairy farm, which will include blanket 24/7 video coverage of all our 185 cows linked to data on production, emissions and veterinary assessments (https://www.bristol.ac.uk/vet-school/research/john-oldacre-centre--farm-research-data-platform)

不断增长的世界人口和气候变化正在给粮食供应带来压力。高动物福利和健康实践比以往任何时候都更加重要，以满足畜牧业的社会需求。奶牛使用精密监测仪器是在保持动物健康的同时优化生产的关键。在这个博士项目中，采用最新英特尔摄像头的3D视频技术将用于无压力地监测个体奶牛移动性和身体状况的增量变化，目的是了解观察到的跛行之前的行为线索，以改善奶牛健康，福利和生产力，从而提高牛奶生产的气候和环境可持续性。这些特征目前是通过人工视觉评估来测量的，需要很高的技能水平和培训，但仍然对个人的主观性开放，很少捕捉到新行为研究所需的纵向细节。这将实现一个无需大量仪器就可以移植到农场的系统，使农民和价值链中的其他人，如兽医，营养师和牲畜顾问，能够使用更精确，一致和频繁的测量，为提高奶牛的性能和福利创造更多的机会。该奖学金将适合对可持续食品生产感兴趣的数学或计算学生，或者希望建立人工智能技能的兽医或生物科学专业知识的人-在任何一种情况下，都将开发量身定制的培训包。学生将学习动物福利评估的关键方面，并使用这一点和尖端的人工智能来建立和应用整个学生时间轴系统，使我们可以更好地了解跛行。学生将在两个领先的，地理位置接近的研究所-西英格兰大学的布里斯托机器人实验室和布里斯托大学的布里斯托兽医学院和视觉信息实验室各占50%，并将受益于由Melvyn Smith教授领导的广泛的跨学科监督团队（机器视觉）和Andrew Dowsey教授（One Health Data Science），他们已经发表了这一领域的最先进的工作，将建立在此基础上（见https://doi.org/10.1016/j.compind.2018.02.011，https：//arxiv.org/abs/2006.09205，https：//www.biorxiv.org/content/10.1101/2020.08.03.234203v2）。数据收集和验证将利用布里斯托兽医学院的John Oldacre乳制品生产可持续性和福利中心，这是一个新的研究中心，位于我们的Wyndhurst奶牛场，其中将包括与生产，排放和兽医评估数据相关的所有185头奶牛的全天候视频报道（https：//www.bristol.ac.uk/vet-school/research/john-oldacre-centre-farm-research-data-platform）