I-Corps: Data-Driven Health and Location Monitoring of Livestock

I-Corps：数据驱动的牲畜健康和位置监控

• 批准号: 1924776
• 负责人: Delia Valles-Rosales
• 金额: $ 5万
• 依托单位: New Mexico State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-06-15 至 2020-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1924776&HistoricalAwards=false
• 关键词: Corps; Data; Driven; Health; Location

The broader impact/commercial potential of this I-Corps project are new and innovative products that support sustainable agriculture through precise, automated livestock herd management. Beef cattle is anticipated to be the initial application as beef cattle are largely inspected and managed manually. This is a labor-intensive process and can be prone to mistakes, as lose of tracking of animals in the pastures and rangelands. There is a lack of commercially viable technologies for tracking and monitoring cattle beyond a relatively short range. This innovation directly addresses this shortfall through location tracking and providess health monitoring of individual animals over long distances, enabling beef producers to save management time and labor, avoid losses, maximize herd fertility and nutrition, and sustainably manage rangelands to prevent environmental damage.This I-Corps project develops a new technology platform that generates high quality, geospatially enabled data with the ability to significantly advance the scientific understanding of livestock productivity and management. This innovation applies recent advances in internet of things (IoT) communications and mobile computing hardware to create a low-power system that collects, analyzes and transmits animal health and location information. This innovation builds upon research that demonstrated the feasibility and design path for the technical approach, and initial animal testing that demonstrated sensor functionality for non-invasive data collection from livestock. The platform has potential to determine biomarkers for early detection of disease, quantify the effect of external stressors on livestock fertility and productivity, enable tools and and procedures for automated/machine-assisted herding, and quantify the ecological benefit of sustainable grazing practices. Sufficiently large datasets will enable advanced algorithms for assessing animal health states.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个I-Corps项目的更广泛的影响/商业潜力是通过精确的自动化牲畜群管理支持可持续农业的创新产品。预计肉牛将是最初的应用，因为肉牛主要是人工检查和管理的。 这是一个劳动密集型的过程，可能容易出错，因为失去了牧场和牧场的动物跟踪。 目前缺乏商业上可行的技术，用于在较短范围以外跟踪和监测牛只。这一创新通过位置跟踪和远距离个体动物健康监测直接解决了这一不足，使牛肉生产商能够节省管理时间和劳动力，避免损失，最大限度地提高牛群生育力和营养，并可持续地管理牧场以防止环境破坏。I-Corps项目开发了一种新的技术平台，利用地理空间数据，能够大大提高对畜牧业生产力和管理的科学认识。这项创新应用了物联网（IoT）通信和移动的计算硬件的最新进展，以创建一个低功耗系统，收集，分析和传输动物健康和位置信息。这项创新建立在研究的基础上，研究证明了技术方法的可行性和设计路径，以及初步的动物试验，证明了传感器功能，可用于从牲畜中收集非侵入性数据。该平台有可能确定疾病早期检测的生物标志物，量化外部压力对牲畜生育力和生产力的影响，实现自动化/机器辅助放牧的工具和程序，并量化可持续放牧实践的生态效益。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。