A gas sensing device includes chemo-resistive gas sensors, wherein each of the gas sensors generates signals corresponding to concentrations of gases in a mixture of gases; a heating arrangement for heating gas sensors according to a periodic temperature profile; a preprocessing processor for receiving the signals from each of the gas sensors and for preprocessing the received signals to generate a preprocessed signal sample for each of the gas sensors for each period of the periodic temperature profile; a feature extraction processor configured for receiving the preprocessed signal samples and for extracting for each of the periods a set of feature values from the preprocessed signal samples received for the respective period; and a gas concentration processor for receiving sets of feature values.

Disclosed is a method and a system for efficiently and accurately processing air particulate datasets when facing a high number of air particulate datasets from multiple locations to generate an artificial intelligence model having one or more computer-based rules that determines eligibility of a user to avail a health-related service based on air particulate records associated with current and past locations of the user.

A system and method for creating a scent database is described. An electronic sensing unit is used to receive an odorant sample and generate an electronic signature characterizing the sample received therein via a guiding unit that guides a first portion of the sample into an electronic sampling unit and a second portion of the sample towards an outlet. A control unit is used to receive data indicative of the signature generated by the sensing unit and data from user(s) indicative of olfactive descriptors characterizing the sample to which the users are exposed, enabling creation of a data record including first and second data corresponding to the same sample. The database includes data, each associated with a specific odorant sample, which may be used to characterise/formulate/create, a desired scent based on comparison of an electric signature generated for the scent and data records which signatures comply with best compliance criterion.

A method for characterizing compounds of interest, introduced into a measuring chamber of an electronic nose, includes injecting a first gas sample formed from a carrier gas without the compounds of interest forming a second gas sample from the carrier gas with the compounds of interest; determining a measurement signal (S.sub.k(t.sub.i)); measuring values φ1, φ2 of the relative humidity; determining corrective parameter ({tilde over (S)}.sub.k.sup.ref|.sub.φ2; ΔS.sub.k.sup.ref|.sub.Δφ); and determining a useful signal (Su.sub.k(t.sub.iϵP2)) by correcting the measurement signal associated with the second gas sample using the determined corrective parameter, and characterizing the compounds of interest based on the useful signal.

A gas leak detection system that combines sensor units having an array of sensors that detect natural gas and the volatile organic compounds and variable atmospheric conditions that confound existing gas leak detection methods, a specially designed sensor housing that limits the variability of those atmospheric conditions, and a machine learning-enabled process that uses the wide array of sensor data to differentiate between natural gas leaks and other confounding factors. Multiple low-cost sensor units can be used to monitor gas concentrations at multiple locations across a site (e.g., a well pad or other oil or natural gas facility), enabling the gas leak detection system to model gas leak emission rates in two- or three-dimensional space to reveal the most likely origin of the gas leak.

A gas leak detection system that combines sensor units having an array of sensors that detect natural gas and the volatile organic compounds and variable atmospheric conditions that confound existing gas leak detection methods, a specially designed sensor housing that limits the variability of those atmospheric conditions, and a machine learning-enabled process that uses the wide array of sensor data to differentiate between natural gas leaks and other confounding factors. Multiple low-cost sensor units can be used to monitor gas concentrations at multiple locations across a site (e.g., a well pad or other oil or natural gas facility), enabling the gas leak detection system to model gas leak emission rates in two- or three-dimensional space to reveal the most likely origin of the gas leak.

Provided is a novel analysis method which, when a chemical sensor is used to perform a measurement, makes it possible to identify a sample without controlling or monitoring a change in the time the sample is introduced. According to the present invention, a sample can be identified without knowing a change in the time the sample is introduced, by using a chemical sensor having a plurality of channels each having different characteristics to perform a measurement, and performing an analysis on the basis of responses obtained from each channel.

A method for preparing original data of an odor image includes a measurement result acquiring step of acquiring each measurement result measured with respect to the odor substance included in the sample in each of a plurality of sensor elements of an odor sensor, and a data processing step of generating the original data for representing the odor of the sample in the image by processing each of the acquired measurement results. Each of the sensor elements has different detection properties with respect to the odor substance. In a case where each of the original data items is represented in a small image, the odor of the sample is represented in an odor image in a predetermined display mode in which small images are assembled, and each of the small images is varied in accordance with the magnitude of the value of each original data item.

An air quality management system comprises a plurality of air quality sensors to sense air quality within a building, a plurality of air cleaning devices, and a computer system in communication with the plurality of air quality sensors and the plurality of air cleaning devices. The plurality of air quality sensors is located at a particular location within the building. The computer system determines a correlational model of air quality for the building that indicates a correlational relationship between the sensed air quality, a spatial parameter, a temporal parameter, and operation of the air cleaning devices. The computer system controls the plurality of air cleaning devices to implement an air quality control policy based on one or more air quality management parameters.

A method, apparatus and storage medium for forecasting air pollutant concentration, including: constructing a training set, a validation set and a test set based on a data set; the data set is obtained by collecting pollutant concentration data and meteorological data in a predetermined length of time in a target area; constructing an adjacent matrix A of a graph structure based on the spatial distribution of monitoring stations in the target area; establishing a neural network model F(x;Θ|A), where x is the input data of it, including pollutant concentration data and meteorological data within predetermined time period, training the neural network model using the data of the training set, adjusting the parameters Θ of the neural network model using the data of the validation set and the data of the test set, and obtaining the modified neural network model; using the modified neural network model for air pollutant concentration forecasting.