An air quality monitor carried by a smart phone and an air quality monitoring system carried by the smart phone are provided. The quality monitor carried by the smart phone includes a shell body, wherein a sensor is provided inside the shell body; a plug is provided on the shell body for being connected to the smart phone; a signal output terminal and a power input terminal of the sensor are both connected to the plug; wherein no power source or power source managing module is provided inside the shell body; no display module is provided on the shell body. Product weight and volume are greatly reduced, in such a manner that a product of the present invention is easy to carry. An air quality monitoring system carried by a smart phone includes: the smart phone, wherein the smart phone comprises a port and a signal processing system.

Systems and methods of preventing an event occurrence or mitigating effects of an event occurrence in an industrial facility are disclosed herein. In some embodiments, a first input is received from a first sensor and, based at least in part on the first input, an initial action is automatically generated. In response to the initial action, a second input is received from a second sensor and, based at least in part of the received first and second inputs, a likelihood of an event occurrence is determined. Based at least in part of the determined likelihood, a remedial action configured to prevent the occurrence of the event occurrence is automatically generated. In some embodiments, the remedial action is generated in real-time and can be directed to a process condition, environmental condition, or secondary source.

The sensitivity and/or selectivity of a chemoresistor type gas sensor is enhanced by measuring the response of the sensing material to a gas sample while the sensing material is subjected to illumination using specially-tailored pulses of ultraviolet radiation. For a given target gas to be detected there is an optimal duration of the UV pulses to achieve peak sensitivity of the sensing material.

A thermal conductivity sensor for measuring a concentration of a gas, the sensor comprising: a substrate portion; a dielectric layer comprising a dielectric membrane, wherein the dielectric membrane is provided with a heater; a first gap between the substrate portion and the dielectric membrane wherein the primary dielectric membrane is located above the first primary gap; and a micro-machined cap layer; a second gap located between the cap layer and the dielectric membrane. A method of manufacturing a thermal conductivity sensor is also described.

The present invention relates to an air quality sensor-actuator device that monitors various physicochemical variables, controls up to two external devices and regulates by means of 0-10V control any machine that has this control input, communicates to the Internet via Wi-Fi with any 2.4 GHz router and has RS485 serial connectivity for integration thereof into open source ModBus. The device measures different variables concerning the air by means of a series of sensor means, in addition to carrying out a series of calculations using processing means and, depending on the data obtained, send command and actuation signals on external devices, and it also has a human-machine interface. The sensor means that the device subject matter of the invention has are: a temperature sensor, a relative humidity sensor, a particulate matter sensor that measures particle sizes of 1 micron, 2.5 microns and 10 microns, another sensor for measuring volatile organic compounds (VOC) and a fifth sensor for measuring CO2.

Provided is a hydrogen concentration measuring device capable of measuring with high accuracy a hydrogen concentration over an extensive range by a simple configuration. The device includes: a sensor chip which detects the electric resistance of a sensing film; an optical measurement unit which detects the transmitted light intensity of the film; and a controller. The controller performs measurement processing such that a hydrogen concentration in the gas atmosphere is measured based on the detected electric resistance in a first measurement range and based on the detected transmitted light intensity in a second measurement range and is determined so as to reduce a difference between the hydrogen concentration based on the detected electric resistance and the hydrogen concentration based on the detected transmitted light intensity in the overlap of the first measurement range and the second measurement range.

The present invention relates to an electronic, integrated, nose and tongue device, which can be stationary or portable (movable) and is designed for real-time monitoring and analyzing information about liquid substances of any kind, as well as toxic, flammable, choking, radioactive and/or polluting gases present in the air or water, which is achieved by the use of artificial intelligence algorithms capable of classifying and training the system so as to recognize the different sign patterns sent by the electronic nose and the electronic tongue. Embodiments described herein can be used in outdoor conditions and complicated areas or connected to water treatment systems, such as those used in electro-coagulation, wherein such a device may be connected to the inlet piping of the treatment systems and can determine how much energy must be used by the electro-coagulators according to the contamination degree of the water.

One or more inexpensive electrochemical gas sensors are paired with a selective ozone sensor. Ozone in ambient air influences the output signals of the electrochemical gas sensors. The unwanted ozone effects are removed from the output signals of the electrochemical gas sensors by comparing them with the selective ozone sensor output signals. The selective ozone sensor signals are removed from and/or added to output signals from the electrochemical gas sensors. True indications of concentrations of the sensed gases in the ambient air result from the compensation for ozone interference.

The invention relates to a leak detector comprising a first sensor for detecting a gas component (helium) in a gas taken in. Because the sensor is susceptible to saturation or contamination, a second sensor is provided. The sensor is a thermal conductivity sensor. The thermal conductivity sensor has a lower detection sensitivity, yet, at a high concentration of the gas component, it does not risk being contaminated. The two sensors together allow for a large detection range, from extremely sensitive measurements to instances with high concentrations of the gas components as those which can occur with gross leaks.

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). In the gas sampling period of T0-300-600 s, the gas sensor array module and the gas chromatography module have different flow rates, volumes and staring sampling time points of gas sampling, but have synchronous selection and analysis time points of multiple sensitive information. The electronic nose instrument obtains a 69-dimensional combined pattern, including steady-state response peak values, corresponding peak time points as well as under-curve areas, through each on-site real-time detection to a tested sample. 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.