Intelligent sensing devices for automatized non-invasive breath-based diagnosis

There is a permanent demand for technological advances in the automotive sector that allow the timely detection of drivers under the influence of alcohol. Although there are technologies to estimate alcohol in blood such as breathalyzers with a mouthpiece, the suspect individual needs to breathe through the mouthpiece as enough to reach the sensor threshold. This is inconvenient for people. Tools to reliably assess the state of sobriety of the individual behind the wheel and timely identify alcoholized ones are still missing. This project aims to build the prototype hardware of a digital multisensory system for automated non-invasive analysis of exhaled breath to detect volatile organic compounds (VOC) signature of alcoholized person. The prototype will be based on an array of commercial volatile sensors. The prototype hardware developed in the project will be integrated with intelligent data processing software developed by AntiSense to build the intelligent breath analyzer. The intelligent breath analyzer is designed to predict alcoholized state of the person trained on data generated from the multisensory array. As use case, the technology is intended to enable cars to sense by smell when a driver is under influence of alcohol.

Intern: 
Shibam Debbarma
Faculty Supervisor: 
Sharmistha Bhadra
Province: 
Quebec
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