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患者的同时获得N95口罩供应，对我们国家的健康至关重要。全球N95口罩短缺导致紧急建设各种净化系统，以重复使用卫生保健工作者佩戴的一次性口罩。虽然最好的选择是新口罩，但在covid - 19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。除确保有害水平的生物负荷失活外，任何净化都必须防止损害口罩的过滤性能。湿热是一种容易部署的去污方法。设定在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去污染风险。然而，为每个口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。在超出受控临床环境的高威胁环境中，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虚假的低温，低温室可能会导致储存的标本意外解冻。因此，本研究项目进一步研究了如何在具有信号注入能力的攻击者可以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，旨在研究N95口罩的去污染。以多种语言开展的技术报告、出版物和教育培训网络研讨会有助于在全球范围内保护卫生保健工作者，从而产生更广泛的影响。此外，可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。该研究项目解决了以下迫切的研究需求：(1)确保并告知医护人员在已知存在加热不均匀风险的烤箱中进行口罩消毒过程所需的条件；(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，通过使用无线供电的计算RFID标签来监测和验证个人口罩消毒。(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，提高对基于传感器的系统安全的认识和理解。该方法的关键是基于英特尔WISP和UMass Moo的无线供电计算RFID标签的设计和部署，该标签带有测量湿热净化过程的传感器。通过去除电线和电池，该方法可以更快地部署监测，而无需对净化系统进行重大修改。这项研究对小型诊所、农村设施和发展中国家特别有益，因为这些国家无法方便地获得专用的N95口罩去污系统。该奖项反映了美国国家科学基金会的法定使命，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。

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.