Preliminary Characterization of Bio-inspired Dog-Nose Sampler for Aerosol Detection
Yahya Naveed, Julia Gersey, Pei Zhang
TL;DR
The paper introduces a dog-nose-inspired aerosol sampler that decouples inhalation and exhalation flows to enhance VOC capture at distance in open environments. It details a pyramid-shaped airflow chamber and PWM-driven motor control implemented on an ESP32, enabling programmable breathing-like patterns. Experimental comparisons against passive and inhalation-only sampling show improved VOC detection, with performance influenced by inhalation speed, orientation, and breathing schemes; limitations include post-inhalation VOC peaking and material-related baseline shifts. The work advances small, bio-inspired sampling nodes and provides design guidance for extending sampling reach and robustness in real-world aerosol sensing applications.
Abstract
Before aerosols can be sensed, sampling technologies must capture the particulate matter of interest. To that end, for systems deployed in open environments where the location of the aerosol is unknown, extending the reach of the sampler could lessen the precision required in sensor placement or reduce the number of sensors required for full spatial coverage. Inspired by the sensitivity of the canine olfactory system, this paper presents a rudimentary sampler that mimics the air flow of a dog's nose. The design consists of speed-controlled inhalation jets, as well as exhalation jets that are angled down and to the side. We tested this design on volatile organic compounds (VOC) in a small number of scenarios to validate the concept and understand how the system behaves. We show that in preliminary testing this dog-nose setup provides improvements over passive and solely inhalation sensing.