Integrating sensing systems for ongoing monitoring of individual and population health

物联网(IoT)和工业IoT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大量应用提供监控功能。这也创造了为关键应用开发新传感器的机会，在这种情况下，连续收集和分析数据的能力允许在开发关键场景之前及早识别趋势和干预。例如，检测老年人体内水分的变化可能会让严重的潜在疾病及早被发现。这需要对个体进行持续的、非侵入性的检测，但目前还没有合适的监测方法。我们团队的初步工作表明，微波信号作为一种创新的传感解决方案具有潜力，但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，特别是在定时繁殖方面。然而，创新的传感技术仍有很大的空间，可以提供新的数据来帮助管理大型动物群。微波信号有可能提供关于四肢健康的反馈，这会影响到例如乳制品的生产。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正在出现的疾病。同样，我们的初步可行性研究需要转化为实用的传感器和集成系统，适合在牲畜作业中部署。因此，这项提案的总体目标是定义从传感器到数据收集和分析的综合系统，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、生物识别技术以及带机器学习的数据分析。我们在补水和动物健康方面拥有专业知识的合作伙伴确保技术解决方案符合最终用户的特定要求。这使我们有效地为下一阶段的融资以及通过许可或初创公司进行技术翻译做好了准备。

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.