# Development Trend of Electronic Nose Technology in Closed Cabins Gas Detection: A Review
## 4 Application of Electronic Nose in Gas Detection of Closed Cabins  
As a rapid detection technology, electronic nose devices can make a significant contribution to the field involving gas detection in enclosed cabins. This section focuses on the application of electronic noses in the field of enclosed cabins, mainly in automobiles, space  
Figure 3: Electronic nose structure.  
stations, and aircraft, where the immediate purpose of these applications is to improve the safety of enclosed cabin operations. Table 2 summarizes and describes the gas detection in closed cabins found in the literature. The current technical application of the electronic nose is mainly focused on the detection of hazardous and warning gases in closed cabins.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Sample** & **Sensor** & **Application** & **Analysis Method** & **References** \\ \hline Five types of polyurethane materials for automotive interiors & MOS sensor & Comparing the ability of three sensors to discriminate between materials & PCA, MDA & [16] \\ Three production stages of leather for automobiles & MOS sensor & To leather material quality classification & PCA & [6] \\ Seven different vehicle seat materials & MOS sensor & Differentiate different materials and connect with sensory analysis & PCA & [20] \\ Preparation of CO, NO\({}_{2}\), SO\({}_{2}\) gases with different concentrations in the vehicle & MOS sensor & Different evaluations gas heat sensitivity & PCA & [18] \\ Auto interior polyurethane (PU) leather and polyvinyl chloride (PVC) leather & (MEMS) Chip Sensors & Design of electronic nose chamber to improve electronic nose response sensitivity & PCA, SVM & [17] \\ Vehicle manufacturing & Chemiresistive & Analyze part odor characteristics & PCA, CA & [21] \\ Eight sample materials & Polymer Sensors & classify and identify & & \\ Two polypropylene materials & MOS sensor & Differentiate between two materials using a deep learning algorithm & Deep Learning & [22] \\ Cigarette smoke, fast food smells, feces, and biological agents with vehicles & MOS sensor & Assess the air quality level in the vehicle & Custom AQL sensory evaluation algorithm & [23] \\ Automotive interior polyvinylane (PU) leather, polyethylene (PVC) leather, rubber strips, foam, seat, and floor mats & MOS type sensor & Design a classifier to distinguish between odor types and classes & KNN, SVM & [19] \\ Volunte air in the vehicle & WCD alcohol sensor & Detection of drunk and fatigued driving in the vehicle & & [36] \\ Volunte gas in vehicle & MOS sensor & Identify the alcohol content in the vehicle & Deep learning, KNN & [37] \\ In-vehicle ethanol, tetrahydrofuran, turpentine, paint thinner, and gasoline & MOS sensor & Monitors 5 highly flammable liquids & BP-ANN & [38] \\ Experimental data of a two-aisle aircraft & MOS sensor & Optimal monitoring location for a single sensor determined & CDF & [26] \\ cocktail model & & Study the influence of factors such as the passenger cabin & & \\ Four-row model of a two-aisle passenger cabin & MOS sensor & passenger location of the location and number of sensors & CDF & [27] \\  & & Developed a 3D mounting point model for the sensor & CDF & [28] \\ \hline \hline \end{tabular}
\end{table}
Table 2: Application of electronic nose in gas detection in closed cabins.