Low-cost fibre optic matting for direct live-mapping of livestock weight to improve feed efficiency. Development, demonstration & imaging integration.
Low-cost fibre optic matting for direct live-mapping of livestock weight to improve feed efficiency. Development, demonstration & imaging integration.
批准号:
NE/P007945/1
负责人:
Bruce Grieve
金额:
$25.74万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2016
资助国家:
英国
项目状态:
已结题
起止时间:
2016 至 --
中文摘要
该项目利用了曼彻斯特大学(UoM)传感器系统设计的现有技术和专有技术,该技术先前已用于绘制人类步态并测试了估计体重的能力。这将被转化为SRUC的参考猪单位,以证明该技术可以在垫子上对猪进行称重,随后的数据可以与SRUC和商业合作伙伴开发的商业和原型猪成像硬件集成,包括猪体重估计。布里斯托尔机器人实验室(BRL)提供了一种能力,可以确定是否可以开发基于视觉的生物识别技术,结合断层扫描脚步声“签名”或成像系统,来自主识别每头猪,并为每头猪分配体重,而不需要使用射频识别(RFID)标签,这需要一个单独的扫描仪单元。此外,表面标签很容易被动物损坏,而皮下标签由于在皮肤下迁移而不可行,使它们既不可读又成为肉类污染的来源。我们的目标是证明一种或多种适合猪场环境的猪称重方法的可行性。为了实现这一目标,我们将设计和测试智能垫子系统外壳和电子设备的稳健性;我们将部署并测试一个光学称重系统;我们还将演示非接触式技术,以识别和分配估计的体重给每头猪。
英文摘要
This project exploits prior art and know-how in sensor systems design at the University of Manchester (UoM), which has previously been utilised for mapping human gait and tested for the ability to estimate weight. This will be translated into a reference pig unit, at SRUC, to prove that the technology can be made suitably robust for weighing pigs on a mat and that the subsequent data may then be integrated with commercial and prototype pig imaging hardware, as developed by SRUC and commercial partners, including estimation of pig weight. The Bristol Robotics Laboratory (BRL) contributes the capability to determine if vision-based biometrics, combined with the tomographic footfall 'signatures' or imaging system, could feasibly be developed to autonomously identify individual pigs and assign weights to each of them, without using Radio Frequency Identification (RFID) tags, which requires a separate scanner unit. Furthermore, surface tags are prone to damage by the animals, whereas subcutaneous tags are not viable due to migration under the skin, rendering them both unreadable and acting as a source of meat contamination.We aim to demonstrate the feasibility of one or more pig weighing methods suitable for the pig farm environment. To achieve that, we'll design and test for robustness a smart mat system enclosure and electronics; we'll deploy and test an optical weighing system; we'll also demonstrate non-contact technology to identify and assign the estimated weight to individual pigs.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
Floor Sensors of Animal Weight and Gait for Precision Livestock Farming
用于精准畜牧业的动物体重和步态地面传感器
DOI:
--
发表时间:
2017
期刊:
影响因子:
--
作者:
[Vaughan J]
通讯作者:
Vaughan J
DOI:
10.1016/j.compind.2018.02.016
发表时间:
2018-06-01
期刊:
COMPUTERS IN INDUSTRY
影响因子:
10
作者:
[Hansen, Mark E., Smith, Melvyn L., Grieve, Bruce]
通讯作者:
Grieve, Bruce
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