The following is an apparatus and a method that enables the automated collection and identification of airborne particulate matter comprising dust, pollen grains, mold spores, bacterial cells, and soot from a gaseous medium comprising the ambient air. Once ambient air is inducted into the apparatus, aerosol particulates are acquired and imaged under a novel lighting environment that is used to highlight diagnostic features of the acquired airborne particulate matter. Identity determinations of acquired airborne particulate matter are made based on captured images. Abundance quantifications can be made using identity classifications. Raw and summary information are communicated across a data network for review or further analysis by a user. Other than routine maintenance or subsequent analyses, the basic operations of the apparatus may use, but do not require the active participation of a human operator.

A method for operating a sensor device for measuring a concentration of a gas species in a gas is disclosed. In an embodiment, the method includes recording a set of data points by performing a plurality of measurements of a temperature sensor element reading, wherein each of the measurements is performed with a different heater setting of the first pellistor element and each of the measurements results in a data point of the set of data points, performing a curve fit of an evaluation function to the set of data points, wherein the evaluation function comprises a first function and a second function, wherein the first function is based on an ideal behavior of the first pellistor element, and wherein the second function is a temperature-dependent steadily rising or steadily falling function and determining the concentration of the gas species in the gas from the curve fit.

The present disclosure discloses a method for inverting aerosol components using a LiDAR ratio and a depolarization ratio, including: S1. identifying sand dust, a spherical aerosol and a mixture of the sand dust and the spherical aerosol based on a depolarization ratio; S2. calculating a proportion of the sand dust in the mixture of the sand dust and the spherical aerosol; and S3. identifying soot and a water-soluble aerosol in the spherical aerosol based on a LiDAR ratio. In the present disclosure, only a wavelength with a polarization channel is needed, to identify the aerosol components, achieving high accuracy with low detection costs.

A substance sensor includes sensitive membranes to react with substances included in the odors of a gas in correspondence with the substances, and is configured to detect the reaction values of the sensitive membranes. An odor specifier specifies the odors of the gas on the basis of the reaction values of the sensitive membranes. A reaction value calculator calculates reaction values corresponding to the odors specified by the odor specifier on the basis of the reaction values of the sensitive membranes. A percentage calculator calculates the percentages of the reaction values corresponding to the odors specified by the odor specifier to the total of the reaction values corresponding to the odors. A display displays the percentages of the reaction values corresponding to the odors, calculated by the percentage calculator, so that comparison of the percentages is enabled between the odors specified by the odor specifier.

Provided is a method for multi-information fusion of gas sensitivity and chromatography and on-site detection and analysis of flavor substances using an electronic nose instrument. The electronic nose instrument includes a gas sensor array module (I), a capillary gas chromatographic column module (II), an automatic headspace sampling module (III), a computer control and data analysis module (IV), an automatic lifter (V) for headspace sampling, a large-volume headspace vapor generation device (VI) and two auxiliary gas sources (VII-1, VII-2). The electronic nose instrument detects a large number of odorous samples to establish a big odor data. On this basis, the normalization fusion preprocessing is done, and the cascade machine learning model realizes both an on-site recognition of many foods, condiments, fragrances and flavors, and petroleum waxes and a real-time quantitative prediction of their odor quality grades and many key component concentrations.

A processing system may collect sensor data for a first zone via sensor devices deployed in the first zone in communication with the processing system, the sensor devices including at least one of a camera or a microphone, and where the sensor data is collected over a period of time, may identify that a first disposition is associated with the first zone based upon the sensor data, by applying at least one detection model configured to output at least one disposition based upon the sensor data as input data, where the at least one disposition comprises the first disposition, where the sensor data comprises a plurality of inputs to the at least one detection model, and where the identifying comprises aggregating a plurality of outputs of the at least one detection model from the plurality of inputs, and may report that the first disposition is associated with the first zone.

Described herein is a chemical sensing system that can be deployed in an environment and automatically monitor the environment. The chemical sensing system includes one or more chemical sensing units with sensing elements that sense chemicals in the environment. The chemical sensing system analyzes measured values output by the sensing elements to identify patterns indicative of events. After identifying an event, the chemical sensing system may generate an inference about the environment using measured values output by the sensing elements during the event.

Chalcogenide waveguides with high width-to-height aspect ratios and a smooth exposed surfaces can serve as mid-infrared evanescent-absorption-based sensors for detecting and identifying volatile organic compounds and/or determining their concentration, optionally in real-time. The waveguide sensors may be manufactured using a modified sputtering process in which the sputtering target and waveguide substrate are titled and/or laterally offset relative to each other and the substrate is continuously rotated.

The biological information measurement system of the present invention includes a test subject-side device provided in a toilet installation room, and a server communicable with the test subject-side device, the test subject-side device includes a sulfur-containing gas sensor sensitive to sulfur-containing gas and outputting detection data, a transmitter-receiver transmitting measurement data including detection data of the sulfur-containing gas detected by the sulfur-containing gas sensor to the server, and the server includes a database in which measurement data including detection data of sulfur-containing gas detected by the sulfur-containing gas sensor is accumulated and recorded with dates and times of defecation acts by being associated with test subject identification information, and server-side data analyzer that analyzes physical condition of a test subject on the basis of a time-dependent variation tendency of the measurement data accumulated and recorded in the database.

As described herein, a method for measuring air quality comprises operating a real-time air quality sensor to continually measure a parameter of environmental air quality; automatically determining if the parameter indicates that a select environmental condition has been reached and providing an output signal responsive thereto; communicating the output signal to an air-quality sampling system; automatically operating the air-quality sampling system responsive to the output signal to collect an air sample for a pre-determined time; and providing laboratory analysis of the collected air sample.