The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Apr. 30, 2024

Filed:

Jun. 29, 2021
Applicant:

Infineon Technologies Ag, Neubiberg, DE;

Inventors:

Cecilia Carbonelli, Munich, DE;

Manuel Carro Dominguez, Munich, DE;

Andrea Heinz, Munich, DE;

Sebastian Schober, Munich, DE;

Jianyu Zhao, Munich, DE;

Assignee:

INFINEON TECHNOLOGIES AG, Neubiberg, DE;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G01N 33/00 (2006.01);
U.S. Cl.
CPC ...
G01N 33/0034 (2013.01); G01N 33/0063 (2013.01); G01N 2033/0068 (2013.01);
Abstract

A gas sensing device includes one or more chemo-resistive gas sensors; one or more heat sources, wherein the gas sensors are heated 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; a preprocessing processor for generating preprocessed signal samples; a feature extraction processor for extracting one or more feature values from the received preprocessed signal samples; and a gas concentration processor for creating a sensing result, wherein the gas concentration processor includes a classification processor for outputting a class decision value, wherein the classification processor is configured for outputting a confidence value, wherein the classification processor includes a first trained model based algorithm processor, wherein the gas concentration processor comprises a quantification processor for creating an estimation value, and wherein the quantification processor comprises a second trained model based algorithm processor.


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