RAPID: SaTC: COVID19: Science of using wirelessly powered sensors to quickly scale up verifiable decontamination of individual N95 respirator masks

确保一线医护人员在照顾 COVID-19 患者时能够获得 N95 口罩的供应，对于我们国家的健康极其重要。 全球N95口罩短缺，导致紧急建设各种净化系统，以重复使用医护人员佩戴的一次性口罩。虽然最好的选择是新口罩，但在新冠病毒可能卷土重来期间，当新口罩供应短缺时，去污可以作为紧急备用措施。 除了确保有害水平的生物负载失活之外，任何净化都必须防止口罩过滤性能受损。 湿热是易于部署的净化方法之一。 设置为特定温度的烤箱可能会有热点和冷点，从而导致可以通过传感器技术检测到的净化风险。 然而，为每个面罩连接温度和湿度传感器既麻烦又耗时，而且难以扩大规模。在受控临床环境之外的高威胁环境中，传感器还必须承受对抗性干扰。 对手可以利用国际无线电干扰来欺骗传感器，使其在模拟层看到虚假的现实。 例如，如果对手欺骗温度传感器看到错误的低温，低温室可能会导致存储的样本意外解冻。因此，该研究项目进一步研究了如何在具有信号注入能力的对手可访问的高威胁环境中保护大量温度和湿度传感器免受恶意干扰。更广泛的影响包括对 N95decon.org 的贡献，N95decon.org 是一个由来自世界各地大学和医疗机构的科学家、工程师和临床医生组成的志愿者联盟，致力于研究 N95 口罩净化。以多种语言进行的技术报告、出版物和教育培训网络研讨会有助于保护全球医护人员，从而产生更广泛的影响。 此外，值得信赖的传感器技术科学可以扩展到保护其他 COVID-19 环境，例如运送患者的车队或需要技术来验证社交距离期间去污过程有效性的办公空间。该研究项目解决了迫切的研究需求：(1) 确保并告知医护人员在已知不均匀加热风险的烤箱中进行口罩去污过程所需的条件，(2) 迅速鼓励部署高度可扩展且值得信赖的传感器网络技术，用于监控和验证个人口罩使用无线供电的计算 RFID 标签进行净化，(3) 通过防止恶意干扰破坏传感器数据的完整性、可用性和机密性，增进对基于传感器的系统安全性的认识和理解。 该方法的关键是设计和部署基于 Intel WISP 和 UMass Moo 的无线供电计算 RFID 标签，并配有传感器来测量湿热净化过程。通过移除电线和电池，该方法可以更快速地部署监控，而无需对净化系统进行重大修改。 该研究对缺乏便利的专用 N95 口罩净化系统的小型诊所、农村设施和发展中国家特别有利。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

It's extremely important for the health of our nation to ensure that front-line healthcare workers have access to a supply of N95 masks while caring for COVID-19 patients. A global shortage of N95 respirator masks has led to the emergency construction of various decontamination systems for reuse of disposable masks worn by healthcare workers. While the best choice is a new mask, decontamination serves as an emergency backup when new masks are in short supply during likely COVID19 resurgence. Any decontamination must protect against damage to the masks' filter performance in addition to ensuring inactivation of harmful levels of bioburdens. Moist heat is one of the readily deployable decontamination methods. An oven set to a particular temperature will likely have hot spots and cold spots, leading to a decontamination risk that can be detected with sensor technology. However, wiring temperature and humidity sensors for each mask is cumbersome, time consuming, and difficult to scale up. In high threat environments beyond a controlled clinical environment, sensors must also withstand adversarial interference. An adversary could use international radio interference to fool sensors into seeing a false reality at the analog layer. For instance, cryogenic chambers may cause unintended thawing of stored specimens if an adversary tricks a temperature sensor into seeing false, cold temperatures. Thus, this research project further investigates how to protect large numbers of temperature and humidity sensors from malicious interference in high-threat environments accessible by an adversary with signal injection capabilities. The broader impact includes contributions to N95decon.org, a volunteer consortium of scientists, engineers, and clinicians from universities and healthcare facilities across the world to study N95 mask decontamination. Technical reports, publications, and educational training webinars conducted in multiple languages contribute to broader impact by helping to protect healthcare workers globally. Moreover, the science of trustworthy sensor technology can extend to protecting other COVID-19 environments such as fleets of vehicles transporting patients or office spaces needing technology to verify the effectiveness of decontamination processes during social distancing.This research project tackles the urgent research needs to (1) assure and inform healthcare workers of the conditions necessary for mask decontamination processes in ovens with known risks of non-uniform heating, (2) rapidly encourage the deployment of highly scalable and trustworthy sensor network technology for monitoring and validation of individual mask decontamination by using wirelessly powered computational RFID tags, (3) advance the knowledge and understanding of sensor-based systems security by preventing malicious interference from violating the integrity, availability, and confidentiality of sensor data. Key to the approach is the design and deployment of a wirelessly powered computational RFID tag based on the Intel WISP and UMass Moo with sensors to measure the moist heat decontamination processes. By removing wires and batteries, the approach enables more rapid deployment of monitoring without requiring significant modification to decontamination systems. The research has particular benefit to small clinics, rural facilities, and developing countries that lack convenient access to dedicated N95 mask decontamination systems.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.