# Sniffing Like a Wine Taster: Multiple Overlapping Sniffs (MOSS) Strategy Enhances Electronic Nose Odor Recognition Capability

## TL;DR

A new strategy called MOSS, inspired by wine tasters, improves electronic noses' ability to detect and recognize odors with high accuracy.

## Contribution

The MOSS strategy introduces a novel sniffing method that enhances odor recognition using overlapping sensor signals.

## Key findings

- The MOSS strategy achieved over 95% accuracy in recognizing gaseous alkanes and liquors.
- Rapid and overlapping sniffs generate feature-rich temporal signals for better odor detection.
- The strategy works effectively with a limited number of sensors, making it practical for real-world applications.

## Abstract

As highly promising devices for odor recognition, current electronic noses are still not comparable to human olfaction due to the significant disparity in the number of gas sensors versus human olfactory receptors. Inspired by the sniffing skills of wine tasters to achieve better odor perception, a multiple overlapping sniffs (MOSS) strategy is proposed in this study. The MOSS strategy involves rapid and continuous inhalation of odorants to stimulate the sensor array to generate feature‐rich temporal signals. Computational fluid dynamics simulations are performed to reveal the mechanism of complex dynamic flows affecting transient responses. The proposed strategy shows over 95% accuracy in the recognition experiments of three gaseous alkanes and six liquors. Results demonstrate that the MOSS strategy can accurately and easily recognize odors with a limited sensor number. The proposed strategy has potential applications in various odor recognition scenarios, such as medical diagnosis, food quality assessment, and environmental surveillance.

Inspired by expert wine tasters, a multiple overlapping sniffs (MOSS) strategy is presented to enhance electronic noses' odor detection. By employing rapid, successive inhalations of odorants, this strategy elicits rich temporal signals from sensor arrays. MOSS strategy achieves over 95% accuracy in recognizing gaseous alkanes and liquors, holding promise for odor recognition in medical, food, and environmental applications.