A method for determining a calibrated measurement value for a concentration of the target gas comprises obtaining a measurement signal based on the concentration of the target gas. The method further comprises determining the calibrated measurement value based on the measurement signal and based on a calibration model. The calibration model is based on calibration data of a plurality of test sensor units having the same type as the sensor unit.

The odor exploration method explores an odor based on odor information generated using a plurality of sensor elements each outputting a detection signal according to the state of adsorption by indicating an adsorption reaction unique to each odor substance, and an arithmetic unit generating the odor information by quantifying each detection signal from the sensor elements. The method includes a detection step detecting a first gas containing odor substances, a generation step generating a first odor information group generated based on a detection result of the first gas, a preparation step preparing a second odor information group generated based on a detection of a second gas, and a calculation step calculating a sum of or a difference between the second odor information group and the first odor information group based on a sum of or difference between the odor information generated for the first gas and for the second gas using the same sensor element.

A sensor system in a package, comprising: a package, the package including: a sensor chip comprising sensor array comprising a plurality of sensing elements, wherein each of the plurality of sensing elements are functionalized with a deposited mixture consisting of hybrid nanostructures and a molecular formulation specifically targeting at least one of a plurality of gases, and wherein each of the plurality of sensing elements comprises a resistance and a capacitance, and wherein at least one resistance and capacitance are altered when the interacting with gaseous chemical compounds; and a mixed signal System on a Chip (SoC), comprising an analog signal conditioning and Analog-to-Digital conversion circuit configured to convert the analog signal into a digital signal, and a low-power processor circuit configured to processes the digital signal using a pattern recognition system implementing gas detection and measurement algorithms.

The present invention discloses a method and system for protecting the operation of a train under an air pollution environment. The method for protecting the operation of the train under the air pollution environment comprises: acquiring multiple groups of roof and underbody air quality detection data; solving comprehensive roof and underbody air evaluation indicator Q.sub.0 and Q.sub.1 by using the experimental data; calculating an exposure time T.sub.0 of roof components and an exposure time T.sub.1 of underbody components; training a calculation model of pollutant condition about roof component and a calculation model of pollutant condition about underbody component; detecting roof and underbody air quality detection data after the train stops; calling the trained roof and calculation model of pollutant condition about underbody components, and solving roof and underbody component pollution levels, and performing corresponding cleaning on the roof and underbody components according to the solved roof and underbody component pollution levels. The present invention evaluates the exposed status of key components of the train under the air pollution environment, and takes relevant protective measures to ensure normal service lives of the key components of the train.

A method implemented by a computer processing circuit connected to an electronic nose, for identifying a given item by an olfactory signature, the method making use of the electronic nose to obtain an olfactory signature, repeating the use of the electronic nose a first number K of times in order to acquire K olfactory signatures, making use of the computer processing circuit in order to estimate, on the basis of the K olfactory signatures, a model of the olfactory signature of the given item, acquiring, with an electronic nose of the same type, a current measurement of the olfactory signature of a current item of the same type as the given item, and comparing the current measurement to the model, in order to estimate a similarity (SIM) between the current item and the given item.

A method for generating an abnormal state detection model, that includes: receiving first and second normal state signals detected, for a predetermined time by first and second sensors, respectively; generating a normal state data set based on the first and the second normal state signals; recognizing first and second variable values; generating a first abnormal state signal by applying the first variable value to an impulse function and a second abnormal state signal by applying the second variable value to a Gaussian distribution function; generating an abnormal state data set based on the first and second abnormal state signals; generating a detection model learning set for generating an abnormal state detection model by combining the normal state data set and the abnormal state data set; and generating an abnormal state detection model based on the detection model learning set.

A monitoring and gas detection information notification system includes monitoring devices and a cloud data processing device. The monitoring devices are respectively disposed at corresponding fixed positions, each of the monitoring devices includes a monitoring module and an actuator-sensor module. The monitoring module captures an image and converts the image into an image data. The actuator-sensor module is disposed in the monitoring module and includes one or more actuators for guiding a gas into the monitoring module and includes one or more sensors for generating a gas detecting data. The cloud data processing device stores and intelligently analyzes the image data and the gas detecting data to generate a processed data, and the cloud data processing device transmits the processed data to a notification processing system so as to conduct a notification of monitoring information and gas detecting information.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for integrating a monitoring system with one or more air quality sensors. The method includes receiving data indicating a level of volatile organic compounds within an area, determining an increase in the level of volatile organic compounds within the area, receiving video data that shows the area, detecting, from the video data, a new item of furniture within the area, sending a notification that indicates an increase in the level of volatile organic compounds is likely caused by the new item of furniture.

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.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for integrating a monitoring system with one or more air quality sensors. The method includes receiving data indicating a level of volatile organic compounds within an area, determining an increase in the level of volatile organic compounds within the area, receiving video data that shows the area, detecting, from the video data, a new item of furniture within the area, sending a notification that indicates an increase in the level of volatile organic compounds is likely caused by the new item of furniture.