A change rate of in-vehicle carbon dioxide concentration at an optional time point when the vehicle is in a parked state is estimated on the basis of detection signals of a CO.sub.2 concentration sensor at two different time points when in the parked state; and on the basis of a detection signal of the CO.sub.2 concentration sensor at the optional time point, a preset time constant of concentration change of the in-vehicle carbon dioxide concentration, and the estimated change rate, the in-vehicle carbon dioxide concentration at a time point when a predetermined time according to the time constant has elapsed since the optional time point is estimated (steps S4 to S7). A detection target organism is determined to be present in the vehicle when the estimated in-vehicle carbon dioxide concentration is equal to or more than a threshold value set according to the detection target organism (steps S8 and S9).

A method is provided for operating a gas concentration monitoring system as well as a gas-measuring device, a central unit, a gas concentration monitoring system as well as computer program product. The safety of persons or the safety of a situation is determined with respect to at least one hazardous gas. The concentration of the gas is provided to a memory and analysis device. A measured value rating number is determined for a preset period of use. A number of instances, of the measured concentration values exceeding of a preset gas concentration limit value is input. A safety code is determined from at least one of: the measured concentration values, the measured value rating numbers and from the a total number of instances in which a gas concentration limit value was exceeded.

The invention relates to a sensor device (1) for detecting a gas (G), particularly a permanent gas such as H.sub.2, CO, CO.sub.2, CH.sub.4, comprising: an adsorption filter (30) comprising a body (2) consisting of a molecular sieve material, a sensing element (10) for detecting said gas (G), and a carrier (4) for carrying the sensing element (10), wherein the carrier (4) comprises an opening (50) via which said gas (G) to be detected can reach the sensing element (10), and wherein the adsorption filter (30) is connected, particularly glued, to the carrier (4) and closes said opening (50) so that said gas (G) to be detected can diffuse through said body (2) towards the sensing element (10).

Provided is a carbon dioxide concentration prediction system including a prediction unit configured to predict, based on a current carbon dioxide concentration of an internal space in a prediction target and environment information in the prediction target, a carbon dioxide concentration of the internal space, and a provision unit configured to provide the carbon dioxide concentration predicted by the prediction unit. The prediction unit may further predict a change over time of the carbon dioxide concentration in the prediction target from the current carbon dioxide concentration to the carbon dioxide concentration predicted based on the current carbon dioxide concentration and the environment information, and the provision unit may further provide the change over time of the carbon dioxide concentration.

Systems and method for automatically determining offset correction values in a differential measurement system, and for correcting measurement offsets between two measurement devices in the differential measurement system. A method for determining real-time offset corrections in a gas analysis system having first and second gas analyzers includes for each of a plurality of gas concentrations within a range of gas concentrations: a) supplying the concentration of gas to the first and second gas analyzers through first and second gas flow lines, respectively; b) measuring a first gas concentration value using the first gas analyzer; and c) measuring a second gas concentration value using the second gas analyzer. The method may also include determining an offset value between each corresponding first and second gas concentration value, and determining a functional relationship between the offset values and gas concentration measurements of the first gas analyzer.

A wearable CO.sub.2 monitor and stale air dosimeter comprising a power supply with rechargeable battery and battery charger, an accurate CO.sub.2 sensor, a fast-reacting CO.sub.2 sensor, programmable control circuitry, and a user interface for presenting results and indications. The accurate CO.sub.2 sensor provides CO.sub.2 levels which are used to compute staleness levels and further accumulated as a staleness dose. The fast-reacting CO.sub.2 sensor alerts the user to changes in CO.sub.2 levels and allows the accurate CO.sub.2 sensor to be powered down during periods when CO.sub.2 levels are stable.

A gas sensor includes: a first thermistor having a resistance value that changes according to a concentration of a first gas with a first sensitivity and changes according to a concentration of a second gas with a second sensitivity; a second thermistor connected in series to the first thermistor, the second thermistor having a resistance value that changes according to a concentration of the first gas with a third sensitivity that is lower than the first sensitivity and changes according to a concentration of the second gas with a fourth sensitivity that is different from the second sensitivity; and a correction resistor connected in parallel with the first or second thermistor.

A method for monitoring air quality is described. The method includes measuring ethane and methane using a mobile sensor platform to provide sensor data. The sensor data includes methane data and ethane data captured at a nonzero mobile sensor platform speed. Methane and ethane peak(s) are identified in the sensor data. Correlation(s) between the methane and ethane peak(s) and/or between the methane peak(s) and at least one amount of .sup.13C are determined. A source for the methane is determined based on the correlation.

Methods of the disclosed subject matter provide compensation for sensor drift in a hazard detection device having a plurality of sensors coupled to a processor to determine that a carbon monoxide sensor is drifting and to compensate for the drift by calculating a corrected carbon monoxide measurement value based on the ambient environmental conditions.

Computing device and method using machine learning to optimize operations of a processing chain of a food factory. The computing device collects data representative of characteristics of a product processed by the processing chain. At least some of the collected data are received from one or more sensor monitoring operations of the processing chain. The computing device determines at least one product characteristic value based on the collected data. The computing device executes the machine learning inference engine, which uses a predictive model for inferring command(s) for controlling processing appliance(s) of the processing chain based on inputs. The inputs comprise the at least one product characteristic value. The computing device transmits the command(s) to the processing appliance(s) of the processing chain. Examples of product characteristic values comprise: a product temperature, a product humidity level, a product geometric characteristic, a product weight, and a product defect measurement.