A Fuzzy Inference System for the Identification

TL;DR

This paper presents an automated odor identification system combining an electronic nose with a fuzzy inference system, demonstrating acceptable precision in detecting organic vapors for various industrial applications.

Contribution

The paper introduces a novel integration of a fuzzy inference system with an electronic nose prototype for odor identification, enhancing automation and accuracy.

Findings

Electronic nose prototype detects organic vapors effectively.

Fuzzy system provides acceptable odor identification precision.

System demonstrates potential for industrial odor detection applications.

Abstract

Odor identification is an important area in a wide range of industries like cosmetics, food, beverages and medical diagnosis among others. Odor detection could be done through an array of gas sensors conformed as an electronic nose where a data acquisition module converts sensor signals to a standard output to be analyzed. To facilitate odors detection a system is required for the identification. This paper presents the results of an automated odor identification process implemented by a fuzzy system and an electronic nose. First, an electronic nose prototype is manufactured to detect organic compounds vapor using an array of five tin dioxide gas sensors, an arduino uno board is used as a data acquisition section. Second, an intelligent module with a fuzzy system is considered for the identification of the signals received by the electronic nose. This solution proposes a system to identify odors by using a personal computer. Results show an acceptable precision.