A @jhumeche #DesignDay team is developing an affordable, fully automated pollen detection device that will provide accurate, time sensitive data—and help allergy suffers prepare for hyperlocal conditions. 

The device collects an air sample from the surrounding environment via a DC brushless fan, pulling it through custom 3D printed tubing. A video of the sample is recorded using a digital holographic imaging system, consisting of a 4.5 mW, 405 nm wavelength laser opposite a CMOS camera sensor. This raw video is then wirelessly transmitted to an external computer, where it is processed and filtered; the new filtered videos are then analyzed by a computer vision model that detects particles and returns count and size distribution data.

Read more in the Design Project Gallery.

Team Members: Zachary Alligood, Sean Enright & Olivia Perry

Faculty Mentor: Rich Bauernschub & Steve Belkoff

Project Sponsor: StarX Technology