208 results about "Olfactory perception" patented technology

The invention discloses a generative odor real-time synthesis method and system based on cross-modal potential space mapping, and belongs to the technical field of artificial intelligence and olfaction calculation. The method comprises the following steps: acquiring a multi-modal input stream of a current scene, and extracting an emotion semantic feature vector by using a deep neural network; mapping the semantic features into target odor chemical feature vectors by using nonlinear projection through a pre-constructed vision-smell joint embedding space; constructing a convex optimization model based on olfactory perception, and calculating a basic liquid optimal mixing proportionality coefficient matrix capable of fitting the target vector; the matrix is converted into a micro-fluidic driving signal, and the target smell is synthesized in situ in the micro-fluidic chip. The invention further discloses a self-adaptive cleaning logic and olfactory fatigue compensation mechanism based on scene mutation detection. The method solves the problems that in the prior art, label matching is dependent, new smell cannot be synthesized, and dynamic transition is lacked, and olfactory replicating and real-time generation of abstract semantic scenes are achieved.

The invention relates to the technical field of power equipment monitoring, in particular to a multi-mode sensor power equipment state monitoring system based on AI smell. The data acquisition module is used for acquiring multi-dimensional sensing data around the electrical equipment; the AI olfaction processing module is used for converting original sensor data into standardized odor feature fingerprints by performing spatial-temporal feature extraction and multi-modal feature fusion on the multi-dimensional perception data; the overheating state analysis module is used for generating an overheating comprehensive index and an equipment state evaluation result based on the smell characteristic fingerprints; the multi-stage early warning and response module is used for carrying out early warning grade judgment based on the overheating comprehensive index and the equipment state evaluation result and generating graded early warning information; and the storage module is used for storing historical monitoring data and early warning event records. According to the invention, through system integration of the multi-mode sensor array of the bionic olfaction mechanism, AI feature fusion processing and intelligent analysis decision, active sensing and accurate identification of the overheating state of the power equipment are realized.

The invention discloses a multi-mode perception collaboration and real-time synchronization system, which breaks through the limitation of vision / hearing in the prior art, covers vision, hearing, smell and movement, and realizes more accurate cooperation through a perception layer, a control layer and an execution layer. According to the invention, an immersive experience space full of shock and reality can be created, synchronous output of visual, auditory, tactile and olfactory signals is realized by means of high-precision equipment, and a series of cross-sensory signal superposition schemes are designed on the basis of response characteristics of human physiology and psychology to various sensory stimuli. Therefore, the overall perception of the experiencer to the space atmosphere is enhanced. Meanwhile, through weight distribution and conflict resolution, the system can flexibly adjust the sensing mode according to the environment and the user state. The multi-device cooperation error can be controlled at millisecond level and millimeter level, and the natural fusion of virtuality and reality is realized.

The invention belongs to the technical field of intelligent fragrance control, and discloses an intelligent fragrance control system and method based on olfaction perception self-adaption, multi-dimensional data such as exhaled gas fragrance residue and skin electroreaction are captured in real time through a multi-mode olfaction fatigue monitoring unit, and 1-5 olfaction fatigue levels are accurately judged in combination with an LSTM-attention model; and then the dynamic release control unit is matched with a layering strategy, for example, short-time pulse stimulation is started in light fatigue, fragrant cross-modulation switching and concentration zeroing are triggered in heavy fatigue, and local high-concentration pseudo fatigue is avoided synchronously through a distributed space probe. By means of the design, fragrance release is always matched with the real-time olfaction state of a user, the problem that the fragrance cannot be effectively perceived after continuous exposure is thoroughly solved, it is ensured that the user can stably perceive the fragrance in different use periods, and the use experience is remarkably improved; and a complete logic chain with multi-mode monitoring, double-target sensing and cooperative control is constructed.

The invention discloses a wearable digital olfaction experience device, system and method. The core purpose of the wearable digital olfaction experience device, system and method is to determine that olfaction is a brand-new and high-fidelity digital information medium. The device is positioned as a purely "olfactory display" that includes a nose wearing structure, an olfactory stimulus generating unit, a wireless communication module, and a processing circuit. The core of the olfactory stimulus control device is that the processing circuit adopts pure open-loop control logic and is configured to receive timestamps and parameters defined in an external digital control instruction sequence and drive the olfactory stimulus generation unit to perform high-fidelity micro-dose release strictly according to the timestamps and parameters. An accurate and synchronous olfactory dimension is provided for immersive experience such as VR / AR, a brand-new and private information expression mode is opened up, and a complete technical link from content creation to sharing is constructed around the device.

The invention discloses an odor knowledge base construction method and system based on molecular modeling and deep learning, and belongs to the technical field of artificial intelligence and digital odor. According to the method, firstly, smell molecules are subjected to standardization treatment, and smell perception labels of the smell molecules are extracted to construct a smell knowledge base; expressing the odor molecules as a molecular graph structure, introducing molecular position coding to model a three-dimensional geometric configuration, and learning high-dimensional feature expression through a first graph neural network; then selecting odor molecules from the knowledge base and generating mixture candidates based on the similarity so as to form a mixture molecular map; and finally, processing the molecular map of the mixture by using a label prediction model, predicting an olfactory perception label of the mixture, and expanding a result to a knowledge base. According to the method, unified characterization of the single molecule and the mixture is realized, the technical vacancy of mixture olfaction prediction is filled, the dimensionality and expansibility of the knowledge base are improved, and the method can be widely applied to the fields of digital blending, smell recommendation and the like.

A system is provided.SOLUTION: A system comprising: means for a user to create and log into an account; means for a terminal to send a request for olfactory data; means for a server to generate, encode and deliver olfactory data; means for the terminal to decode received olfactory data and send control signals to an olfactory device; and means for the olfactory device to generate and provide a specified scent to the user.SELECTED DRAWING: Figure 1

Embodiments of the present application provide a method, device, medium, equipment and product for classifying wine samples, relating to the technical field of artificial intelligence. The method comprises: contacting odor molecules of a wine sample with at least one recombinant cell expressing an olfactory receptor and a reporter protein, the reporter protein generating a detectable signal after the receptor binds to the odor molecules; obtaining time series data of the signal, calculating the maximum value and baseline value thereof, and determining a response characteristic value of each olfactory receptor according to the same; and inputting the characteristic value into a trained machine learning model to obtain a wine sample classification result. The present method accurately extracts a stable characteristic value of the response of an olfactory receptor to a wine sample, thereby eliminating interference caused by initial value fluctuations and improving the accuracy of model classification.

The application discloses a sensor with a bionic olfactory positioning function, comprising a gate electrode, a dielectric layer and an electrode; the dielectric layer is arranged between the gate electrode and the electrode; and the dielectric layer comprises a porous structure zwitterionic polymer film. Through the combination of the high sensitivity of the sensor to dimethyl carbonate (DMC) and the application method, accurate positioning of a DMC leakage position is realized, and meanwhile, the sensor has the characteristics of high sensitivity, durability and excellent intelligent bionic positioning, and overcomes the positioning function that traditional sensors do not have.

The invention discloses a method for analyzing aroma components of cooking wine based on molecular docking and an odor activity value and application. According to the method, cooking wine aroma is taken as a research object, volatile substances are detected by gas chromatography-mass spectrometry (GC-MS) and headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS), and by combining with odor activity value (OAV) analysis, the combining capacity of aroma molecules and olfactory receptors is simulated through molecular docking, characteristic aroma compounds are screened, and the aroma of the cooking wine is detected. And finally, constructing a recombinant aroma model according to the characteristic aroma compounds, carrying out sensory evaluation, and evaluating the aroma similarity of the recombinant aroma model and the natural cooking wine sample to determine the characteristic aroma components of the cooking wine. The method can be used for analyzing aroma substances of cooking wine and performing standardized flavor management.

This invention discloses an olfactory electrostimulation model for automatically generating current stimulation signals for an artificial nose, relating to the technical field of olfactory stimulation signal generation using biomimetic neural networks. The implementation steps include: First, constructing a biomimetic neural network framework. Based on the neuronal anatomical structure of the olfactory epithelium and olfactory bulb system, extracting the main neuron types, and organizing them according to their connection methods in biological systems; Second, using the Hindmarsh-Rose neuron model to model various neurons in the constructed network and simulate their dynamic firing behavior; Subsequently, setting the connection weights between neurons and the interlayer transmission current to realize the computational model of the entire biomimetic neural network; Finally, in the odor encoding and stimulation signal generation stage, the odor detection curve of the electronic nose is used as an external stimulus input to the biomimetic neural network. The network calculates and generates a series of peak signals, which are output as current stimulation signals to the olfactory bulb for stimulation, thereby realizing the olfactory induction function of the artificial nose.

This invention provides an emergency bionic robot collaborative method and multimodal rescue system with task and state collaborative perception, relating to the field of emergency bionic robot technology. It acquires environmental perception data streams through multi-source sensing acquisition devices deployed on each robot body in an emergency bionic robot cluster, covering panoramic vision, terrain stiffness distribution, gas composition concentration, and sound wave spectrum data. Each type of data stream is processed to obtain feature segments, and then visual and tactile, olfactory and auditory related segments are spatially superimposed to generate a collaborative scene map. The collaborative scene map undergoes physical field state interference deduction and cross-map temporal correlation fusion to generate a global collaborative perception situational deduction map. Based on this global collaborative perception situational deduction map, the coordinates of the disaster spread source, the leading edge of the spread path, and the robot's pose and state information are determined, generating a distributed rescue collaborative instruction set to achieve efficient robot collaborative rescue.

The invention belongs to the technical field of sulfur hexafluoride leakage detection, and relates to a biological detection method for sulfur hexafluoride leakage based on odorous dogs and GIS space positioning. Comprising the following steps: step 1, selecting dogs and performing special training; selecting dogs with high olfactory sensitivity, taking SF6 gas or equipment operation gas as a target smell source, establishing conditioned reflex through smell-reward training, and inhibiting interference on oil smell and dust; step 2, preparation before field detection; a ventilation system is closed to stabilize the smell, an anti-puncture sheath is arranged for the dog, and a tractor wears high-voltage protective clothing to ensure that the equipment is grounded; step 3, grading detection and accurate positioning; a dog census GIS equipment in a zigzag path, marks a suspicious area through warning, then sniffs key points such as a flange and an insulator in a close range, and remeasures and confirms a leakage point in combination with a portable leak detector. According to the invention, by using the advantages of sensitive smell and strong maneuverability of the odorous dog, the SF6 gas leakage of the GIS / GIL equipment can be quickly, efficiently and accurately positioned.

The invention discloses a flavor modifier, atomized essence and an aerosol generating device, and relates to the technical field of essence. According to the technical scheme, the flavor modifier comprises an active agent, a compound containing a phenolic hydroxyl group and-O-beta-D-glucosidic bond or a compound containing an alcoholic hydroxyl group and-O-beta-D-glucosidic bond is selected as the active agent, and the flavor modifier can be weakly combined with a Piezo channel in a trigeminal nerve to directly modulate a trigeminal nerve mechanoreceptor, so that the flavor of the trigeminal nerve is improved. The activity of the Piezo channel is inhibited, so that the sensitivity of the Piezo channel to mechanical friction of aerosol particles is reduced, and the nasal cavity roughness is reduced. Meanwhile, the flavor modifier disclosed by the invention can also cooperate with olfactory signals transmitted by other components in the atomized essence to jointly improve the smoothness, the fineness and the overall moist feeling of the fragrance.

The invention belongs to the technical field of agricultural product quality nondestructive testing, and relates to a food freshness intelligent monitoring device and method based on olfactory visualization. The device takes an olfaction visualization technology as a core, combines a deep learning algorithm and an Internet of Things technology, and mainly comprises portable detection equipment and an intelligent management cloud platform based on the Internet of Things; wherein the portable detection equipment adopts a main control-edge computing-sensing terminal three-stage heterogeneous framework, and a separated sample reaction chamber is designed, so that real-time acquisition of images of the olfactory sensor is realized. In the monitoring process, firstly, images before and after reaction of a sample and an olfactory sensor are collected, color difference extraction is carried out on the original images, an olfactory sensor data set is established, and a FousNet model is trained by utilizing the data set; and finally, accurately predicting the content of physicochemical indexes of the freshness of the food by utilizing a FousNet model, monitoring and evaluating the freshness of the food in real time, and providing technical support for intelligent management of the freshness of the food.

1. The name of the design product: game props (olfactory perception). 2. The use of the design product: a game prop for entertainment. 3. The design features of the design product: in shape. 4. The picture or photo that best indicates the design features: perspective drawing.

The application relates to a multi-modal sensory self-adaptive adjustment method and device based on physiological characteristic feedback, a computer device and a storage medium. The method comprises the following steps: determining a target physiological index to be adjusted, defining a sensory parameter space composed of multi-modal sensory control parameters and a control parameter vector; generating an initial control parameter vector based on a preset sampling strategy and converting the initial control parameter vector into a physical control instruction for execution, collecting corresponding physiological signals to generate a physiological characteristic vector; constructing a training set by combining the control parameter vector and the physiological characteristic vector into a data pair, establishing a probability agent model; performing parameter optimization iteration based on the model and the training set, selecting a target characteristic vector from a non-dominant physiological characteristic vector set and executing a physical control instruction corresponding to the target characteristic vector, and calculating an average physiological characteristic vector in a sliding time window to perform real-time monitoring and dynamically adjusting the physical control instruction. The application can realize personalized real-time adjustment of multi-modal environmental stimuli such as vision, hearing and olfaction, and effectively improve the user state.

The invention relates to the technical field of environmental psychology, exercise rehabilitation and intelligent environment regulation and control, and discloses a time lag effect analysis method and system for night running multi-mode sensory stimulation, and the method comprises the steps: building a night running test environment, collecting visual, auditory and olfactory multi-mode sensory stimulation data and physiological and psychological indexes of participants, and analyzing the time lag effect of night running multi-mode sensory stimulation. After preprocessing, constructing a single sensory stimulation time lag model, and analyzing peak time and lag characteristics of each stimulus; the sensory interaction is explored through a coupling model, and a co-stimulation combination and a key influence time period are identified; and finally, formulating sensory regulation and control strategies of different periods and different road sections. According to the method, the time dynamic rule of nighttime multi-sensory stimulation is determined for the first time, the nighttime environment restoration research blank is filled, urban nighttime space design can be directly guided, and the method has good application prospects.

The application discloses a molecular property prediction method based on spectral position coding and bionic side inhibition gating, and relates to the field of olfactory perception. The method comprises the following steps: constructing a molecular structured input comprising atomic types, a Coulomb matrix and graph Laplacian eigenvector; fusing atomic chemical attributes and spectral domain topological positions through a feature extraction module to generate initial atomic features; using a multi-scale aggregation module, hierarchical neighborhood aggregation is carried out based on preset scale constraints to extract multi-level structure features covering chemical bonds, functional groups and molecular skeletons; with the help of a global interaction module of bionic side inhibition gating, local features are dynamically modulated by a global query signal to realize adaptive denoising and semantic sharpening; finally, through mask pooling and a decoupled multi-label prediction head, the scores of each odor attribute of the molecule are output. The application significantly improves the accuracy, structure perception ability and cross-task generalization performance of molecular property prediction.

To realize an olfactory adjustment device that can instantly change the intensity of odors. [Solution] The olfactory adjustment device (20) comprises a first electrode and a second electrode (21) positioned such that the nasal cavity (12) is located between the first electrode (21) and the second electrode (22), and a current supply unit (23) that changes the odor intensity of the sense of smell by supplying current between the first electrode and the second electrode.

This invention provides an electronic nose. [Solution] An electronic nose is provided, comprising a substrate containing a carbon precursor and a gas-active substance precursor, and an olfactory sensor array including a plurality of olfactory sensors formed by irradiating the substrate with lasers of different parameters, wherein each olfactory sensor includes a laser-induced graphene layer formed from the carbon precursor by laser irradiation of one parameter, and gas-active particles formed from the gas-active substance precursor and embedded in the laser-induced graphene layer, and the plurality of olfactory sensors react to different types of gaseous substances.

The system according to this embodiment aims to reproduce the sense of smell in a digital space and improve the user experience. [Solution] The system according to the embodiment comprises a generation unit, a supply unit, and a collection unit. The generation unit generates olfactory sensations. The supply unit provides the olfactory sensations generated by the generation unit to the user. The collection unit collects the user's response to the olfactory sensations provided by the supply unit.

OLFACTORY TRAINING KIT AND ASSOCIATED METHOD The invention relates to an electronic system comprising software and / or hardware means for implementing the following steps: the selection of an identifier associated with a receptacle (10) containing an olfactory sample; the display, on a display (22), based on the selected identifier, of a group of labels (23); the selection, by the user, of at least one label (23) from among the plurality of labels. Figure for the abstract: Fig. 3

The invention relates to the technical field of mosquito repelling equipment, in particular to an outdoor self-adaptive mosquito repelling sound wave playing system and method, and the system comprises a plurality of sound wave generating units, a frequency adjusting module, a smell releasing device, a solar power supply module and a supporting frame. The sound wave generating unit outputs signals of different frequency bands through the central control unit, the smell releasing device can controllably release flower fragrance substances, and the sound wave generating unit and the smell releasing device work cooperatively to meet environmental requirements. The system supports indoor, outdoor and water area modes, adopts frequency-band-divided sound wave playing and smell release amount accurate adjustment, and combines solar power supply and intelligent management to realize dynamic adaptation. The mosquito wing vibration frequency and olfactory sensitivity can be accurately matched, the mosquito repelling effect is improved, long-term stable operation is ensured, and diversified scene requirements are met.

The invention discloses a multi-sensory stimulation senior cognitive training box, and relates to the technical field of cognitive training, the multi-sensory stimulation senior cognitive training box comprises a base, the top of the base is provided with a training box body, and the training box body is sequentially provided with a first storage groove, a second storage groove and a third storage groove from top to bottom; the first functional module box is installed in the first storage groove in a sliding mode, a visual module is arranged in the first functional module box and used for training the vision of the old, the second functional module box is installed in the second storage groove in a sliding mode, and an auditory module is arranged in the second functional module box and used for training the auditory sense of the old; according to the multi-sensory stimulation senile cognition training box, the visual module (the first functional module box), the auditory module (the second functional module box), the olfactory module (the third functional module box) and the tactile module (the fourth functional module box) are integrated in the unified training box body, and the problems that an existing product is single in function and isolated from one another are solved.

This invention provides a computer implementation method for providing a real-time biocompatible stimulating environment with audio, visual, and olfactory components to enhance psychedelic therapy. [Solution] The method provides a virtual biocompatible environment for the user's experience, receives sensor data associated with the user, analyzes the sensor data using at least one machine learning model to determine changes in the user's state, determines modifications to be made to the virtual biocompatible environment based at least partially on the analyzed sensor data, and provides the modified virtual biocompatible environment to the user.

The present application belongs to the technical field of fruit fly prevention and control, and discloses a disorienting agent, a preparation method and application thereof. The disorienting agent contains rosemary extract and orange peel essential oil. The rosemary extract and orange peel essential oil contain terpenes and other compounds (such as 1,8-cineole in rosemary), which can compete with natural signal molecules to bind to odor binding proteins or olfactory receptors, which can cause fruit flies to fail to activate the correct nerve signal or directly block the signal transduction pathway. The orange peel essential oil in the disorienting agent has a strong smell, which can strongly cover or mask the weak smell signal emitted by the fruit, forming an "olfactory masking" effect, so that the fruit fly cannot find the fruit. Moreover, compared with sex pheromones as disorienting agents, which can only act on male fruit flies, the disorienting agent of the present application can interfere with the olfactory receptors of adult fruit flies to make them unable to find the target, so that they cannot accurately locate the oviposition site and harm the fruit. The disorienting agent is effective for both female and male fruit flies.

The invention discloses an animal olfactory behavior training experiment device, relates to the technical field of animal behavioristics experiment devices, can be cooperatively used with an external nerve recording system and a behavior detection analysis system, and aims to explore a correlation mechanism among smell stimulation, behavior response and nerve activity. The device adopts a radial single-starting-point and multi-terminal-point space structure, and is combined with a multi-odor channel system with physical isolation, so that approaching or avoiding behaviors of animals can be accurately induced. The system is integrated with an intelligent closed-loop control module based on an STM32 single-chip microcomputer, and a graded gas path cleaning mechanism is designed and comprises the functions of countercurrent purging, ultraviolet photolysis, electronic nose cleaning verification and the like, so that the purity of odor stimulation and the reliability of the experimental process are ensured. Meanwhile, the device supports TTL synchronization signal output with millisecond-level precision, can be seamlessly connected with commercially available electrophysiology and behavioristics equipment, and is suitable for multi-mode animal behavior training, recording and regulation scenes.

The invention belongs to the technical field of quality evaluation of traditional Chinese medicinal materials, and provides a poria cocos medicinal material quality evaluation method based on an intelligent sensory technology, which comprises the following steps: S1, data acquisition: respectively acquiring tactile, visual, olfactory and gustation data of different poria cocos samples by using a texture analyzer, a color photometer, an electronic nose and an electronic tongue; s2, model establishment: carrying out data fusion on the tactile, visual, olfactory and taste data of the different poria cocos samples, and establishing a production place identification model or an authenticity identification model or a grade discrimination model by adopting PLS-DA; s3, sample detection: inputting tactile, visual, olfactory and taste data of a to-be-detected poria cocos sample into the production place identification model, the authenticity identification model or the grade identification model, and judging the type, authenticity or grade of the production place according to a model prediction result. The method can distinguish poria cocos from different producing areas, and provides a scientific basis for quality control and producing area identification of poria cocos.