Monitoring and Detection of Fruits and Vegetables Spoilage in the Refrigerator using Electronic Nose Based on Principal Component Analysis

The study focuses on monitoring freshness and determining food spoilage inside the refrigerator. The objective is to design an electronic nose system that will be sensitive to the gases emitted by spoiled food samples namely banana, pechay, carrots and grapes operating in low level temperature particularly the refrigerator and then determine food spoilage using Principal Component Analysis - K Nearest Neighbors, however, it will not take any corrective actions. The system will gather readings from MQ gas sensors and will be subjected to PCA and KNN. PCA is implemented to minimize data and for feature projection represented in form of graphs. Whereas, KNN is applied for clusters formed by the PCA transformation to classify the grouping of the food. The results from the combined approach produced an overall accuracy rate of 92%, thus, the electronic nose system is capable of sensing food gases and accurately determine spoilage inside the refrigerator.