A sensing device for sensing a target gas includes a measurement module for providing measurement information about a measurement of the concentration. The sensing device further includes a signal calibration module for using a machine learning model for determining, on the basis of the measurement information, a calibrated measurement value of the concentration. The signal calibration module determines a feedback feature using the calibrated measurement value. The signal calibration module uses the machine learning model for determining a subsequent calibrated measurement value on the basis of subsequent measurement information about a subsequent measurement of the concentration and on the basis of the feedback feature.

A combustible gas sensor module and a combustible gas sensing device. The combustible gas sensor module includes an enclosure including a first end and a second end opposite to each other; a plug connector disposed at the first end of the enclosure for connecting to a sensing device body of a combustible gas sensing device; a sensor unit disposed at the second end of the enclosure for sensing combustible gas; and a circuit board disposed in the enclosure and respectively connected to the plug connector and the sensor unit, with a microcontroller provided thereon.

Embodiments of the present specification provide methods and systems for maintaining accuracy and precision of calibration for a detector. The methods and systems include reducing the humidity of an internal calibration assembly by directing flow path of dry air periodically through the internal calibration assembly.

One variation of a method includes, during a calibration period: triggering collection of an initial bioaerosol sample by an air sampler located in an environment; and triggering dispensation of a tracer test load by a dispenser located in the environment; accessing a detected barcode level of a barcode detected in the initial bioaerosol sample; accessing a true barcode level of the barcode contained in the tracer test load; and deriving a calibration factor for the environment based on a difference between the detected barcode level and the true barcode level. The method further includes, during a live period succeeding the calibration period: triggering collection of a first bioaerosol sample by the air sampler; accessing a detected pathogen level of a pathogen detected in the first bioaerosol sample; and interpreting a predicted pathogen level of the pathogen in the environment based on the detected pathogen level and the calibration factor.

A method of detecting gas includes determining and storing, by a controller, a zero level of a photoionization detector using ambient air inflow when an ultraviolet lamp is in a turned OFF state, wherein the stored zero level is based on an ambient temperature; sampling, by the controller, an output of a detector electrode of the photoionization detector when the ultraviolet lamp is in a turned ON state; and comparing the sampled output of the detector electrode to the stored zero level to determine if a threshold concentration of a gas is present.

In an illustrative configuration, a method for monitoring air quality is disclosed. The method includes accepting analyte gas into a cell and reflecting light rays into the analyte gas repeatedly across the cell into at least one sensor. The light scattered by particulate matter in the analyte gas and amount of spectra-absorption due to presence of a gaseous chemical is then measured. Based on the determined amount of spectra-absorption and the measured scattered light the gaseous chemical is then measured.

An integrated carrier for a calibration gas storage cylinder is provided. The integrated carrier may comprise a carrier base, a carrier cap, and carrier beams. Each of the carrier beams may comprise a cap-end and a base-end. A cap-end bolt may be threaded into the cap-end and a base-end bolt may be threaded into the base-end. The carrier cap may comprise a laterally-oriented keyhole access opening that may be configured to mate with the cap-end of the carrier beams and the carrier base may comprise an axially-oriented bolt passage that may be configured to pass the base-end bolt of the carrier beams. The carrier base, the carrier cap, and the carrier beams may collectively define a cylindrical receiving space that may include the calibration gas storage cylinder and may define a longitudinal containment height. The carrier base may comprise a regulator-receiving depression and a detector-receiving depression that may each comprise open sides facing the carrier cap.

Systems and methods for detecting a composition of a binary gas mixture are provided. Such methods and systems include, with a species-dependent mass flow meter, sensing a mass flow rate of a binary gas mixture comprising gases of differing gas correction factors and, with a species-independent pressure sensor, sensing a total pressure of the binary gas mixture. An output representative of a relative concentration of one gas of the binary gas mixture is provided. The relative concentration is determined as a function of the sensed mass flow rate and the sensed total pressure.

Devices and methods are provided for breath gas analysis when determining the difference in the concentrations of at least one gas in the exhaled breathing air on the one hand and in the ambient air on the other hand. The device may include at least one gas sensor, by means of which the concentration of a gas can be determined, and a line system, through whose lines the exhaled air to be examined, the ambient air and a calibrating gas can be selectively pumped to the gas sensor. The method may include feeding ambient air; feeding calibrating gas to the gas sensor; feeding exhaled air to the gas sensor; feeding calibrating gas to the gas sensor again; and feeding exhaled air to the gas sensor again.

A gas sensing device includes chemo-resistive gas sensors; heating elements for heating each of the gas sensors; an information extraction block for receiving signal samples and for generating representations for the received signal samples; and a decision making block configured for receiving the representations, wherein the decision making block comprises a weighting block and a trained model based algorithm stage, wherein the weighting block receives feature samples of the representations and applies time-variant weighting functions to the feature samples of the respective representation in order to calculate a weighted representation including weighted feature samples.