Optimizing the Spectral Properties of the Chemical Sensor to Detect Concentrations of Gas Mixtures

Abstract

Monitoring aromatic hydrocarbons is environmentally important because these chemical pollutants are ubiquitous. While waiting for powerful sensors capable of detecting hydrocarbons at extremely low levels, the current study demonstrates how each of the pure gas mixtures can be quickly and accurately identified. A noise removal unit was created for the chemical sensor data and then processed on the basis of the proposed algorithms in order to achieve matching and calibration. This method can be extended to other important aromatic hydrocarbon pollutants.