Healthcare workers rely on face masks and other personal protective equipment (PPE) to safeguard their health. The COVID-19 pandemic has shown that PPE alone cannot protect workers, because fatigue, activity, even exposure to people impact the health and ability of the worker. The goal of this project is to develop smart PPE, which includes the design of small, low cost, and smart batteryless sensor devices that can be attached to masks. The masks will provide useful information for workers to self-manage health without the need for recharging or maintenance at reduced size and cost, unobtrusively protecting the worker.

The research tasks center on building an energy harvesting and battery-free hardware and software platform that conducts continuous inference and notification on in-mask sensor data despite intermittent power failures stemming from dynamic energy input. Three research tasks are pursued (1) prototyping a hardware platform for intermittently powered human sensing, (2) developing a task-based adaptive checkpointing system for memory-constrained intermittent systems that perform on-device inference, (3) exploring adaptive mechanisms for continuous inference which modulates estimated accuracy of prediction to reduce power failures. Finally, the research products are integrated into a single platform and sensing applications are developed for smart PPE.

This research will enable the computational means for low cost, active protection of healthcare workers in the COVID-19 pandemic and future health crises using smart PPE. By leaving batteries behind, these devices can function maintenance-free, without recharging, at a reduced size and cost. These devices will provide actionable data and notifications to workers and hospitals for controlling the spread of infectious diseases and maintaining a ready, healthy workforce. The research informs ultra constrained computing system design and could be applied to protect other essential workers and the general population.

The developed systems, including software, hardware, documentation, and detailed assembly instructions will be made available to the community. All research products will be made available at the following website http://kamoamoa.com/projects/smart-ppe/. The site will remain accessible for at least a year after the completion of the work.

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.

Agency
National Science Foundation (NSF)
Institute
Division of Computer and Network Systems (CNS)
Type
Standard Grant (Standard)
Application #
2032408
Program Officer
Matt Mutka
Project Start
Project End
Budget Start
2020-06-01
Budget End
2021-05-31
Support Year
Fiscal Year
2020
Total Cost
$200,000
Indirect Cost
Name
Northwestern University at Chicago
Department
Type
DUNS #
City
Chicago
State
IL
Country
United States
Zip Code
60611