Twenty winners have been selected in the first phase of the National Institute for Occupational Safety and Health (NIOSH) Respirator Fit Evaluation Challenge with a diverse range of fit-testing solutions.
Technologies such as Light Detection and Ranging (LiDAR), infrared imagery and thermal monitoring, fabric-based sensor networks, light sensing (LED), and an app that will combine AI with facial recognition have moved forward in the competition.
These technologies were incorporated into approaches that would deliver immediate evaluation and feedback to end users about the fit of filtering facepiece respirators during use.
The Respirator Fit Evaluation Challenge is a three-phase competition aimed at improving respirator fit evaluations. The competition “seeks practical solutions that deliver real-time information on filtering facepiece respirator fit.” There’s also $350,000 in awards for winners.
Phase One involved participants submitting 10-page concept papers outlining their ideas. The 20 winners were each awarded $5,000 for their concepts.
A full list of the winners and details on their concepts can be found here.
Phase Two will see these 20 winners designing prototypes based on their initial submissions. Up to 10 teams will be chosen to receive a portion of the $100,000 Phase 2 prize purse to help them build pre-production prototypes for NIOSH evaluation in Phase 3.
This challenge is a collaboration between NIOSH, Capital Consulting Corporation and the NASA Tournament Lab.