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护理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呼吸器口罩短缺导致紧急建造各种净化系统，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，但当新口罩在可能的COVID 19卷土重来期间短缺时，去污可以作为紧急备用。 除确保灭活有害水平的二聚体外，任何去污都必须防止对面罩过滤性能的损害。 湿热是一种易于部署的去污方法。 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去污风险。 然而，为每个面罩布线温度和湿度传感器是麻烦的、耗时的并且难以按比例放大。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。 对手可以使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，低温室可能会导致储存的标本意外解冻。因此，该研究项目进一步研究如何保护大量温度和湿度传感器免受具有信号注入能力的对手可访问的高威胁环境中的恶意干扰。更广泛的影响包括对www.example.com的贡献，这是一个由来自世界各地的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口罩去污。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通过帮助保护全球医疗保健工作者而产生更广泛的影响。 此外，委员会认为，值得信赖的传感器技术的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具有已知不均匀加热风险的烘箱中进行面罩去污过程所需的条件，（2）通过使用无线供电的计算RFID标签，快速鼓励部署高度可扩展和可信赖的传感器网络技术，用于监测和验证个体面罩去污，（3）通过防止恶意干扰违反基于传感器的系统的完整性、可用性，和传感器数据的机密性。 该方法的关键是设计和部署基于英特尔WISP和UMass Moo的无线供电计算RFID标签，并配备传感器来测量湿热净化过程。通过移除电线和电池，该方法能够更快速地部署监测，而无需对去污系统进行重大修改。 该研究特别有利于小型诊所、农村设施和发展中国家，这些国家缺乏方便的专用N95口罩去污系统。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。

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.