Wireless E-Nose Sensors to Detect Volatile Organic Gases through Multivariate Analysis.

Saifur Rahman,Muhammad Awais,Mohsin Raza,Muhammed Irfan,Abdullah S Alwadie,Rabia Nawaz,Ehtasham Javed

doi:10.3390/mi11060597

Abstract

Gas sensors are critical components when adhering to health safety and environmental policies in various manufacturing industries, such as the petroleum and oil industry; scent and makeup production; food and beverage manufacturing; chemical engineering; pollution monitoring. In recent times, gas sensors have been introduced to medical diagnostics, bioprocesses, and plant disease diagnosis processes. There could be an adverse impact on human health due to the mixture of various gases (e.g., acetone (A), ethanol (E), propane (P)) that vent out from industrial areas. Therefore, it is important to accurately detect and differentiate such gases. Towards this goal, this paper presents a novel electronic nose (e-nose) detection method to classify various explosive gases. To detect explosive gases, metal oxide semiconductor (MOS) sensors are used as reliable tools to detect such volatile gases. The data received from MOS sensors are processed through a multivariate analysis technique to classify different categories of gases. Multivariate analysis was done using three variants—differential, relative, and fractional analyses—in principal components analysis (PCA). The MOS sensors also have three different designs: loading design, notch design, and Bi design. The proposed MOS sensor-based e-nose accurately detects and classifies three different gases, which indicates the reliability and practicality of the developed system. The developed system enables discrimination of these gases from the mixture. Based on the results from the proposed system, authorities can take preventive measures to deal with these gases to avoid their potential adverse impacts on employee health.

Highlights

In present times, industries have seen the importance of sensory olfactory systems, in that they can help in detecting the adverse effects of gases on human health
The e-nose developed using various metal oxide semiconductor (MOS) sensors has become a widespread practice in different fields
The proposed system assessed organic gas quality, where a metal oxide sensor was used to collect the data. This was further analyzed using principal component analysis (PCA)-based multivariate classification methods to discriminate against various odors because of volatile organic compounds (VOCs)

Summary

Introduction

Industries have seen the importance of sensory olfactory systems, in that they can help in detecting the adverse effects of gases on human health. In the gas detection area, a comprehensive review was conducted by Hodgkinson and Tatam [9], which compared methods like photoacoustic spectroscopy, spectrophotometry, tunable diode laser spectroscopy, and non-dispersive infrared They did not consider any multivariate techniques, such as PCA, to detect and classify a mixture of gases. This study further aims to develop a novel MOS-nose sensor-based detection system to classify such volatile gases from a mixture of gases and further classify them using PCA based on a multivariate analysis technique. To probe and differentiate commonly produced gases from mixtures (acetone, ethanol, and propane) in manufacturing industries using a high performance PCA-based multivariate analysis technique. In Bi design, both variables and observations are made together

Theory of Principal Component Analysis

PPP132

Conclusions

Findings

Limitations