Gas sensing device and method for operating a gas sensing device

A method for operating a gas sensing device for sensing one or more gases in a mixture of gases;

• the gas sensing device comprising one or more chemo-resistive gas sensors, wherein the method comprises:
• using each of the gas sensors for generating signal samples corresponding to a concentration of one of the one or more gases in the mixture of gases, wherein the one or more gas sensors are alternately operated in recovery phases and in sense phases, wherein at least some of the signal samples of each of the gas sensors represent one of the recovery phases and one of the sense phases;
• using one or more heat sources for heating the gas sensors according to one or more first temperature profiles during the recovery phases and according to one or more second temperature profiles during the sense phases, wherein for each of the gas sensors a maximum temperature of the respective first temperature profile is higher than a maximum temperature of the respective second temperature profile;
• using a preprocessing processor for receiving the signal samples from each of the gas sensors and for preprocessing the received signal samples in order to generate preprocessed signal samples for each of the gas sensors;
• using a feature extraction processor for receiving the preprocessed signal samples and for extracting one or more feature values from the received preprocessed signal samples of each of the gas sensors based on characteristics of the received preprocessed signal samples of the respective gas sensor;
• using a humidity processor for receiving a first group of the feature values and for estimating a humidity value of the mixture of gases, wherein the humidity processor comprises a first trained model based algorithm processor and a first trained model for the first trained model based algorithm processor, wherein the first group of feature values is fed to inputs of the first trained model based algorithm processor, and wherein the humidity value is based on an output of the first machine learning algorithm processor;
• and
• using a gas concentration processor for receiving a second group of the feature values and the humidity value, and creating for each of the gas sensors sensing results, wherein the gas concentration processor comprises a second trained model based algorithm processor and a second trained model for the second trained model based algorithm processor, wherein the second group of feature values is fed to inputs of the second trained model based algorithm processor, wherein the sensing results are based on output values at one or more outputs of the second machine learning algorithm processor, and wherein the sensing results depend on the humidity value.