Electronics and Telecommunications Research Institute

YongWon Jang

Seunghwan Kim

Kwang Hyo Chung

Jae Hun Choi

Hyung Wook Noh

Hwin Dol Park

Do Hyeun Kim

Chang-Geun Ahn

Chang-geun Ahn

Disclosed are a device and a method for anomaly detection of a gas sensor. The device includes a measuring unit that extracts a characteristic of a gas supplied from the outside, generates data based on the extracted characteristic, and outputs the data, and a data processing unit that receives the data, determines whether an error occurs in the data, and outputs an anomaly detection result based on a result of determining whether the error occurs in the data. The measuring unit performs a calibration operation or an environment adjusting operation before extracting the characteristic, and the data processing unit determines whether the error occurs in the data, based on machine learning.

Device and method for anomaly detection of gas sensor

Disclosed are a gas detection intelligence training system and an operating method thereof. The gas detection intelligence training system includes a mixing gas measuring device that collects an environmental gas from a surrounding environment, generates a mixing gas based on the collected environmental gas and a target gas, senses the mixing gas by using a first sensor array and a second sensor array under a first sensing condition and a second sensing condition, respectively, and generates measurement data based on the sensed results of the first sensor array and the second sensor array, and a detection intelligence training device including a processor that generates an ensemble prediction model based on the measurement data.

Gas detection intelligence training system and operating method thereof

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Daejeon, South Korea

YongWon Jang