The present disclosure provides, method, a system, and apparatus for identifying odorants. For example, the apparatus performs sensing an odorant using an olfactory sensor, encoding the sensed odorant to an electrical signal using an input processor, determining an identity representation of the odorant based on the encoded electrical signal, and determining odorant information using a time-dependent hash code based on the identity representation of the odorant.

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 computer-implemented method and device includes obtaining a first electrical signal on a basis of an interaction between one or more odor substances in a gas and at least one first odor sensor, filtering at least one predetermined odor group out of the gas and obtaining a filtered gas, wherein the odor group comprises at least one odor substance that is to be filtered out, obtaining a second electrical signal on the basis of an interaction between one or more odor substances in the filtered gas and the first odor sensor and/or at least one second odor sensor, determining a difference between the first and second electrical signals, and assigning this difference to the odor group.

The present disclosure relates to an apparatus (100) for quantitative assessment of olfactory dysfunctions and neurocognitive deficits, the apparatus includes first filters (104-1) adapted to sterilize air received from an air pump, a second filter (106) filter odor molecules from the air, a manifold (108) adapted to split the sterilized air into a plurality of channels, at least one channel carries the sterilized air to a first MFC (110) and adjacent channels carry sterilized air to second MFCs (112). Each container in a reservoir (114) filled with an odorant different from adjacent containers, and a nozzle (118) adapted to receive the odorized air from the reservoir that is inhaled by a subject through an odor delivery unit (124), based on degree of variation in volumetric concentration of the odorants, quantitative assessment of olfactory dysfunction is determined.

Described is an apparatus (1) for measuring odours comprising: a measuring chamber (2); an intake duct (4) having two ends, an inlet end (4a) in communication with the outside environment and an outlet end (4b) in connection with the measuring chamber; at least one sensor (3), positioned inside the measuring chamber (2) and designed for measuring the olfactory properties of a gas; a control unit (6) designed for processing signals coming from the at least one sensor (3) and providing a parameter representing the odours measured in the gas to be analysed; a suction device (5), positioned inside the intake duct (4) and designed to circulate the gas inside the apparatus (1); a cleaning device designed for restoring the characteristics of the at least one sensor (3) following a measurement, wherein the cleaning device is designed for generating ozone inside the apparatus (1).

A system and method for concurrently measuring odorant concentration and also compensating for changes in relative air density when measuring odor intensity levels may be used to provide more accurate and reliable readings from an odorometer. Odorometers typically measure the concentration of a given target gas in a gas-air mixture. Because changes in air density make it difficult to accurately determine how much air is in the gas-air mixture sample, a method of compensating for changes in the air density is able to produce a more accurate concentration reading. By measuring the relative temperature and pressure of the air at calibration and when a particular reading is taken, the final reading can be corrected to account for changes in the air density. By correlating the odor intensity readings with odorant concentration readings a wide array of advantages may be realized.

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.

Electronic sensing systems and methods are disclosed. The electronic sensing system (ESS) receive an olfactory product and one or more smell characteristics of the olfactory product are detected and extracted by identifying a headspace of the olfactory product. A comparison of the extracted smell characteristics with one or more smell characteristics associated with a historic training data stored in a database is performed and a match between the extracted smell characteristics and the one or more smell characteristics associated with the historic training data is determined using machine learning technique(s). Further, the ESS generates a report for the olfactory product comprising at least one of type of the consumable, name of the olfactory product, a status of the olfactory product, an age of the olfactory product, and a decaying index, and classifies the olfactory product into one or more categories based on the report and/or the historic training data.

Vapor wake detection is a highly advantageous method and system for detecting explosives and other illicit substances. With vapor wake detection, a canine and a handler are used; however, unlike other detection schemes, the canine leads the handler. After the handler positions the canine in a desired location, the canine detects scents in the air that come to the canine. When the canine detects a trained scent, the canine leads the handler to or follows behind the carrier of the item with the scent. Once the carrier is identified by the handler, the proper personnel are contacted. To implement vapor wake detection effectively, specific rigorous training is utilized.

A system that screens for particularly identified odors, such as those associated with explosive and other bomb-making materials, weapons and illegal drugs, includes an odor delivery unit with one or more fans that force air across the object being screened, such as a person. The airflow from the odor delivery unit passes over and across the object being screened creating an odor stream that passes through a partition that allows the odor stream to flow freely through it and simultaneously obscures a canine positioned on the other side of the partition from view by the person or object being screened.