Patent ID: 11971397
Assignee: INFINEON TECHNOLOGIES AG
Field: Measurement (Instruments)
Classification: CPC G | IPC G

Claim 0:
1. 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 each of the gas sensors is configured for generating signal samples corresponding to a concentration of one of the one or more gases in the mixture of gases;
one or more heat sources, wherein the one or more heat sources are controlled in such a way that the one or more chemo-resistive gas sensors are each heated according to one or more temperature profiles;
a preprocessing processor configured 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;
a feature extraction processor configured 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 each received preprocessed signal samples of the respective gas sensor; and
a gas concentration processor for creating for each of the gas sensors a sensing result,
wherein the gas concentration processor comprises a classification processor configured for receiving a first group of the one or more feature values comprising feature values for each of the gas sensors, wherein the classification processor is configured for outputting a class decision value for each of the gases, wherein each of the class decision values indicate whether the respective gas is present in the mixture of gases, wherein the classification processor is configured for outputting a confidence value for each of the class decision values, wherein each of the confidence values indicates a reliability of a respective class decision value, wherein the classification processor comprises a first trained model based algorithm processor and a first trained model for the first trained model based algorithm processor, wherein one or more feature values of the first group are fed to different inputs of the first trained model based algorithm processor, and wherein each of the class decision values and each of the confidence values are provided on different outputs of the first trained model based algorithm processor,
wherein the gas concentration processor comprises a quantification processor configured for receiving a second group of the feature values comprising feature values for each of the gas sensors and for creating for each of the gases an estimation value, wherein each of the estimation values indicates a quantitative estimation of a concentration of the respective gas, wherein the quantification processor comprises a second trained model based algorithm processor and a second trained model for the second trained model based algorithm processor, wherein the feature values of the second group are fed to different inputs of the second trained model based algorithm processor, wherein the estimation values for the gases are provided on different outputs of the second trained model based algorithm processor, and
wherein the gas concentration processor is configured in such way that the sensing result for each of the gases depends on the estimation value for the respective gas, on the class decision value for the respective gas and on the confidence value for the respective gas.