High sensitivity and compact thermally-adsorption/desorption-controlled odor sensing system

Abstract

In this study, we have developed a highly sensitive and compact thermally controlled artificial olfactory system (TC-OSS) consisting of 16 sensitive membranes (PCM) with excellent heat resistance and a microheater. Five reference VOCs with odor intensity of 2 were measured using TC-OSS. A machine learning model was constructed based on the feature values (height, slope, etc.) calculated from the shape of time series data (5 classes×40 data). The accuracy of the learning model was evaluated by cross-validation (number of repetitions＝100), and it was successfully discriminated with a high accuracy rate of 95.8±2.7%.