2020-AMBR-68881 | |
Agriculture Air Filtration Air Quality Algorithm Computer Technology Food Industry Imaging Industrial Safety Light Scattering Low Cost Manufacturing Mobile Apps Portable Safety | |
Researchers at Purdue University have developed a mobile phone application using OpenCV algorithms that detect dust concentration. Dust builds up in agricultural and manufacturing settings, causing health hazards to employees, and posing risk of exploding in combination with aerosols. Current technology for detecting dust levels is inconvenient because it is expensive, difficult to install in a workspace, and separates dust matter into multiple filters which must then be weighed and further manipulated for analysis. Sometimes laser scanners are used to detect dust particles, but these devices often report size distribution of particles rather than the actual quantity of particles in a large space. The mobile app created by Purdue University uses a smartphone camera to image and sense dust as well as accurately distinguish it from normal background noise. In testing, the algorithm successfully recognizes ninety-five percent of saw dust and ninety-three percent of cornstarch particulates in the air. Advantages: -High speed detection -Portable -Accurate Potential Applications: -Agriculture -Manufacturing -Particle Science | |
Ambrose, Rose Prabin Kingsly (Project leader) Niu, Zhongzhong Zhao, Yumeng | |
December 1, 2020 Utility Patent United States 11,475,552 October 18, 2022 December 1, 2020 PCT-Patent WO (None) (None) March 2, 2020 Provisional-Patent United States (None) (None) December 3, 2019 Provisional-Patent United States (None) (None) | |
Purdue Innovates Office of Technology Commercialization The Convergence Center 101 Foundry Drive, Suite 1500 West Lafayette, IN 47906 (765) 588-3475 otcip@prf.org |