Integrating sensing systems for ongoing monitoring of individual and population health

物联网（IoT）和工业物联网依赖于不断增加的设备和传感器连接，从而为从个人健身到工业过程和控制的各种应用提供监控功能。这也为开发用于关键应用的新型传感器创造了机会，在这些应用中，持续收集和分析数据的能力允许在关键场景发展之前早期识别趋势并进行干预。例如，检测老年人体内水合作用的变化，可能有助于及早发现严重的潜在疾病。这需要对个体进行持续的、非侵入性的感知，但目前还没有适当的监测方法。我们团队的初步工作表明，微波信号有潜力作为一种创新的传感解决方案，但是需要将这一初步工作转化为实际系统。第二个应用是监测动物健康，特别是在计时繁殖方面获得了关注。然而，创新的传感技术有很大的发展空间，可以提供新的数据，协助管理大型动物群。微波信号有可能对四肢的健康状况提供反馈，比如对乳制品生产产生影响。当与机器学习技术相结合时，这些传感器有可能识别动物群体中的新情况。同样，我们的初步可行性研究需要转化为实用的传感器和适合在畜牧业中部署的综合系统。因此，本提案的总体目标是定义综合系统，从传感器到数据收集和分析，用于水合作用和动物健康监测。这综合了我们现有研究项目的专业知识，包括传感器和算法开发、通信协议、生物识别技术和机器学习数据分析。我们的合作伙伴在水合作用和动物健康方面具有专业知识，确保技术解决方案符合最终用户的具体要求。这使我们能够有效地进行下一阶段的融资，以及通过授权或初创公司进行技术翻译。

The Internet of Things (IoT) and industrial IoT rely on increasing connectivity of devices and sensors, leading to monitoring capabilities for a vast array of applications that range from personal fitness to industrial process and control. This also creates opportunities to develop new sensors for key applications, where the ability to continuously collect and analyze data permits early identification of trends and intervention prior to development of critical scenarios. For example, detecting changes in hydration in older adults may allow serious underlying medical conditions to be flagged early. This requires ongoing, non-invasive sensing of individuals, however an appropriate monitoring approach is not yet available. Preliminary work by our team suggests that microwave signals have potential as an innovative sensing solution, however there is a need to translate this initial work into a practical system. A second application is monitoring animal health, which has gained traction particularly for timing reproduction. However, there is significant scope for innovative sensing technologies that provide new data to assist in the management of herds of large animals. Microwave signals have the potential to provide feedback on the health of extremities, which impacts, for example, dairy production. When combined with machine learning techniques, these sensors have the potential to identify emerging conditions in groups of animals. Again, our initial feasibility studies require translation into practical sensors and integrated systems suitable for deployment in livestock operations. Therefore, the overall goal of this proposal is to define integrated systems, ranging from sensors to data collection and analysis, for hydration and animal health monitoring. This synthesizes expertise from our existing research programs, including sensor and algorithm development, communications protocols, biometric technologies, and data analysis with machine learning. Our collaborators with expertise in hydration and animal health ensure that the technology solutions are informed by the specific requirements of the end-users. This positions us effectively for next-stage funding, as well as technology translation through either licensing or start-up companies.