Hi!
Our company is preliminary researching the opportunity to use BME688 for recognition of cigarette smoke and perfume (two classes: Smoke and Perfume). We made recordings of signals for classification task in laboratory using the Bosch BME688 Gas Sensor Developer Kit and BME688 Software, exported the trained AI configuration data and performed the classification AI training validation using Adafruit ESP32-S3 TFT Feather and Adafruit BME688. During validation in laboratory we found that in time fading perfume switches the classification result (100%) from Perfume to Smoke and vice versa resulting in large count of False Positives (far from 5%) for both classes.
What we could do in order to improve the classification task accuracy?
