A system including one or more gas sensor assemblies having one or more gas sensors. The gas sensor is for sensing a preselected gas. The gas sensor assembly includes a housing with a cavity therein, and the sensor is mounted on the housing so that the sensor is able to detect the preselected gas in the cavity. The gas sensor assembly includes a sensor control module in communication with the gas sensor, and also in communication with a central controller. Via the central controller, the sensor may be tested using a purge gas, and the sensor may be zeroed if necessary. Also, via the central controller, the sensor may be calibrated using a calibration gas mixture having the preselected gas in a known concentration. The central controller is configured for manual or automatic testing and calibration. Accordingly, the testing and calibration, whether manual or automatic, is done remotely.

The invention relates to a method and a device for determining particulate emissions in the driving operation of a vehicle, in particular of a motor vehicle. According to the invention, provision is made that the device has a sensor system and a control unit and that in driving operation the sensor system and the control unit jointly undertake the function of particulate matter sensors. Here, the sensor system senses driving operation values on the vehicle. From the sensed driving operation values and by means of correlations of driving operation values with particulate matter values determined and stored in advance in the control unit, the control unit estimates the particulate emissions from tyre abrasion of the vehicle. Finally, the invention relates to a vehicle with the device according to the invention.

The disclosure discloses a wide-concentration multi-component hazardous gas detector and an implementation method thereof, solving the problems of the existing technology that false negative results, ultra-limit concentration and sensor poisoning often occur in a gas detector used in fire fighting forces. The wide-concentration multi-component hazardous gas detector includes a gas diluting and sampling connector, a sensor integrated module, electrochemical sensors, ADC (analog to digital converter) circuits, MCU (microprogrammed control unit) single chip microcomputers, acousto-optic alarms, a 4-button keyboard module, an LED (light-emitting diode) display module, an SD card data memory module, a power supply control and electric quantity display module, a high-performance lithium battery pack, a small evacuation pump, 433M signal transmission modules and a remote command platform signal collection terminal.

The present invention relates to a method for characterising, by means of an electronic nose, the release kinetics of odorous compounds from a sample, comprising the following series of steps: (a) supplying a sample; (b) at a time t1, exposing the sensor array of the electronic nose to some of the gaseous medium comprising the odorous compounds released from the sample, and processing the response emitted by the sensor array of the electronic nose, after said exposure, in the form of a signal; and (c) repeating step (b) at least once, at a time t2 different from the time t1, whereby an olfactory kinetic signature characterising the sample is obtained. The present invention also relates to the use of this method for anti-counterfeiting and/or quality control purposes and for generating a data bank or database of temporal olfactory signatures. The present invention finally relates to certain devices used when implementing such methods.

A material screening process of generating input features for each material of a subset of materials to be screened, generating target properties for each material of the subset of materials, inputting screening conditions, the input features, and the target properties into a material screening artificial intelligence model and training the material screening artificial intelligence model based on the inputs. Once the model is trained, inputting a dataset of materials to be screened into the trained material screening artificial intelligence model, the dataset of materials includes the subset of materials used to train the model, screening the dataset of materials on the trained material screening artificial intelligence model using the screening conditions and ranking the materials of the dataset based on predicted target properties obtained from the screening.

A system is provided that detects the odor of air exhaled from a subject. Based on affection information and the odor, the system indicates features of the exhaled air related to a disease based on measurement information in which the affection information indicates affection or non-affection. The system also detects the odor in the air from a medical examinee. Based on the measurement information and the features, the system determines the possibility that the medical examinee will be affected with a disease.

A concentration sensor assembly can include a vaporization chamber having a compound. The concentration sensor assembly may include a first flow path coupled to the vaporization chamber. The first flow path may direct a first gas to the vaporization chamber. A second flow path can direct a second gas out of the vaporization chamber. The second gas can include the compound and the first gas. A first sensor is disposed along the first flow path. The first sensor measures first data indicative of a first mass flow rate of the first gas. A second sensor is disposed along the second flow path. The second sensor measure second data indicative of a second mass flow rate of the second gas. A computing device may determine a concentration of the vaporizable substance within the second gas based on the first data and the second data.

An air detection system is provided and includes an intelligent device and an internet of things processing device. The intelligent device includes an inlet, an outlet, a gas-flowing channel, a control module and a gas detection module. The gas-flowing channel is disposed between the inlet and the outlet. The control module is disposed in the intelligent device and includes a processor and a transmission unit. The gas detection module is disposed in the gas-flowing channel and electrically connected to the control module. The gas detection module includes a piezoelectric actuator and at least one sensor. The piezoelectric actuator inhales gas into the gas-flowing channel through the inlet and discharges the gas through the outlet. The sensor detects the introduced gas to obtain gas information and transmits the gas information to the control module. The internet of things processing device is connected to the transmission unit of the intelligent device for receiving the gas information.

A mobile monitoring device for monitoring controlled contamination areas may include a motorized mobile structure, a sampling unit, and a central management and control unit. The motorized mobile structure is configured to move within an area to be monitored. The sampling unit is positioned on said mobile structure, and configured to perform sampling operations of air and/or surfaces of said area and obtain sampling data. The central management and control unit is operatively connected to the mobile structure and to said sampling unit. The mobile structure may be controlled by the central unit to reach predefined points of the area to be monitored. The sampling unit may be selectively activated and/or deactivated by said central unit in correspondence with said predefined starting points of said sampling operations.

A method includes applying heat to a metal oxide sensing element of a gas sensor, varying the heat applied to the metal oxide sensing element for at least a time interval, and measuring an electrical resistance of the metal oxide sensing element versus variation of the heat for a time interval. The measurement of electrical resistance of the metal oxide sensing element versus variation of the heat applied to the metal oxide sensing element is compared to a set of corresponding reference measurements associated with a plurality of different target gases. A further sensor parameter versus the variation of electrical resistance and variation of the heat applied is measured to obtain a three-dimensional trajectory corresponding to variation of the sensor resistance, the variation of said heat and the variation of the further sensor parameter. This comparing includes comparing the trajectory in three dimensions to a set of reference three-dimensional objects.