156 results about "Device Sensor" patented technology

The embodiment of the invention provides a form generation method, device and system based on AI enhancement and a storage medium, and relates to the technical field of form generation. The method comprises the steps of generating form structure metadata according to a natural language processing technology, a reinforcement learning algorithm and / or a type security verification rule; according to the form structure metadata, the equipment sensor data and / or the user visual behavior data, the rendering priority of each field is determined; and generating a target form according to the rendering priority and the equipment parameters. By generating the form structure metadata which is reasonable in structure and conforms to the type safety specification, the automation degree and reliability of form design are improved. By fusing form structure metadata, device sensor data and user visual behavior data, a rendering strategy can reflect device characteristics and user attention distribution. The target form is generated by combining the rendering priority with the equipment parameters, so that the form layout is adaptively matched with the terminal equipment, and the loading performance and the interaction experience of the form are improved.

The invention relates to the technical field of power communication network security, in particular to a power communication network risk assessment method based on risk genes and a space-time large model. According to the technical scheme, the power communication network risk assessment method based on the risk gene and the space-time large model comprises the following steps that equipment sensor data, meteorological grid data and service topology data of a power communication transmission network are obtained in real time through a multi-source data acquisition module, and space-time alignment and feature coding are executed; a risk gene map is constructed, the risk gene map comprises a three-layer map structure of an equipment vulnerability gene, an environment threat gene and a business dependence gene, and a cross-space-time risk propagation rule is defined; a multi-modal space-time large model is trained, and a framework combining Transform and a space-time diagram convolutional network is adopted. A biological gene concept is introduced into power communication network risk assessment, gene-level fault traceability is achieved, and risk factors have combinability and interpretability.

The invention relates to the technical field of Beidou inspection data processing, and discloses an automatic inspection data acquisition and space-time association method under Beidou space-time reference. The method comprises the following steps: acquiring historical working condition data of inspection equipment based on nanosecond-level time synchronization and centimeter-level space positioning information of a Beidou system, and constructing a space-time dynamic prediction model; acquiring an equipment sensor measurement value, a moving track point set and a timestamp sequence in real time, and outputting a theoretical inspection value through a model; performing space-time multi-dimensional comparison on the theoretical value and the actual value, analyzing a time accumulation error, a space deviation degree and data flow form consistency, and generating a difference feature tensor; inputting the tensor into a geocoding topological reasoning network, simulating anomaly diffusion and generating an anomaly probability cloud picture in combination with topographic map node attributes and equipment distribution, and delineating an anomaly range; polling parameters are dynamically configured according to the cloud atlas, enhanced collection is started for a high-probability abnormal area, and data credibility inspection is executed on peripheral equipment.

The invention provides a business processing method of a smart factory platform based on a Beidou grid code, and the method comprises the steps: carrying out the multi-stage grid subdivision of a factory physical space through the Beidou grid code, and generating a unique grid code; the grid coding adopts an integer format to represent position information; equipment sensor data, personnel positioning data and business logic data are bound with the grid codes, and a space-time joint index table is constructed; performing real-time deviation correction on the positioning data through a grid neighborhood topological relation and personnel moving speed constraint to generate a high-precision positioning track; and mapping the service logic to the grid codes through a rule engine, and triggering automatic operation according to grid attributes. Traditional floating point latitude and longitude coordinates are replaced by integer coding, data calculation efficiency is optimized through bit operation, cross-level business association and fast path planning are supported, and business response efficiency is improved.

The invention discloses a port logistics carbon emission monitoring system based on the Internet of Things and a computer, and the system comprises a multi-modal data collection and transmission module which carries out the full-amount collection of the multi-dimensional data of equipment, sensors and environment in a port area through a hierarchical heterogeneous communication network; the edge intelligent processing and resource scheduling module is deployed at the local of a port, performs priority dynamic allocation and real-time processing on the acquired data, and uploads aggregated data; the anomaly detection and carbon flow modeling module is used for carrying out anomaly detection based on a space-time diagram neural network and constructing an operation chain carbon flow model integrated with a port production operation system; the digital twinning driven monitoring network optimization module is used for constructing and operating a communication-environment digital twinning model and dynamically optimizing the layout of the monitoring network; the accounting decision and intelligent optimization module is used for performing carbon footprint tracing based on a task-level accounting unit and generating a low-carbon optimization strategy; and the visualization and user interaction module is used for providing a visualization display and decision support interface of the carbon emission data.

Systems and methods for decentralized group audio communication may include a secondary device which receives a first periodic signal broadcast from a primary device, which information for participation in a group communication session. The secondary device may detect a signal from an on-device sensor indicative of speech input at the secondary device, transmit a slot allocation request to the primary device in response to detecting the signal indicative of speech input, receive a second periodic signal assigning a communication slot to the secondary device for broadcasting information to the device group, and broadcast, during the assigned communication slot, audio signals representative of speech captured at the secondary device, for receipt by other devices within the device group.

Systems, methods, and devices for monitoring sanitation events in a medical environment are described herein. A method includes receiving, at a monitoring device, a first signal indicative of the presence of a user device; receiving, at the monitoring device, a second signal generated by a sensor configured to detect activation of a sanitation device; using both information from the first signal and information from the second signal as inputs to a model; and calculating, based on an output of the model, an infection risk score.

The application discloses a kind of respiratory support equipment sensor self-calibration method, comprising the following steps: S1, first sensor obtains first oxygen concentration N1, second sensor obtains second oxygen concentration N2;S2, the difference of first oxygen concentration N1 and second oxygen concentration N2 is calculated, and it is judged: if |N1-N2|<K, then execute step S3, if |N1-N2|>K, then execute step S4, K value is set threshold value;S3, obtain initial average concentration and the initial average concentration N0 as output concentration;S4, obtain several oxygen concentrations N1, N2, N3......Ni corresponding to several sensors, and carry out data fitting to it, obtain concentration optimal solution Ny, and the concentration optimal solution Ny is used as output concentration;S5, select the two sensors of measured oxygen concentration closest to optimal solution Ny as working sensor.The application solves the problem of low parameter accuracy caused by the error of sensor measured data or the error of sensor itself.

The invention discloses an industrial equipment full life cycle fault prediction and health management method and system, and the method comprises the steps: constructing an end-to-end unified network architecture, and achieving the direct interconnection of equipment, a sensor and a platform. And building an equipment full-information dimension digital mapping model, and completing real-time synchronization of the physical equipment and the digital model. The process, state and quality data of equipment operation are comprehensively collected, and high-quality feature information for health assessment is generated through storage, exception elimination, standardization, noise reduction and feature extraction processing. A physical mechanism and a data driving method are fused to construct a health assessment model, and feature information and working condition parameters are input to calculate a health index. And pre-judging the remaining service life by adopting a time sequence prediction model, setting a multi-stage early warning threshold value, triggering early warning, and pushing early warning information. And matching an optimal operation and maintenance scheme, recording maintenance data, updating the model and the database, constructing a cross-scene fault knowledge system, and iteratively optimizing, evaluating and predicting the model. The equipment reliability is improved, and the operation and maintenance cost is reduced.

The invention discloses an inspection method, device and equipment for an oil and gas exploitation system and a storage medium, and belongs to the technical field of oil and gas exploitation. The method comprises the steps that basic information associated with an inspection point is acquired, the inspection point comprises a to-be-inspected equipment assembly in the oil and gas exploitation system, and the basic information represents the association relationship between the inspection point and inspection equipment; generating first inspection information by using the basic information and the inspection task of the inspection point; performing conflict detection on the first inspection information, and optimizing the first inspection information based on a conflict detection result to obtain second inspection information; routing inspection is conducted on the routing inspection point based on the second routing inspection information, first routing inspection data and second routing inspection data are obtained, the first routing inspection data comprise routing inspection images collected by the image collection device, and the second routing inspection data comprise information collected by the device sensor; and generating an inspection result based on the first inspection data and the second inspection data. The method can improve the inspection accuracy and inspection efficiency of the oil and gas exploitation equipment in the oil and gas exploitation system.

The purpose of the present invention is to provide a technique for diagnosing, early, efficiently, and with minimal false alarms, an abnormality caused by aging deterioration of a device in a semiconductor manufacturing apparatus, on the basis of a change in a feature quantity trend obtained from a signal waveform acquired by a sensor mounted on the device.　To this end, a diagnostic apparatus for a semiconductor manufacturing apparatus according to the present invention comprises: a feature quantity computation unit that computes feature quantity from sensor waveform data corresponding to a process ID associated with a sensor item indicating a state of a device to produce a feature quantity trend in a time series; a trend type classification unit that classifies the feature quantity trend by trend type; a trend change amount computation unit that classifies a change in the feature quantity trend by trend change type, applies a trend change amount computation method corresponding to the trend change type on the basis of the trend type, and calculates a trend change amount; and a trend change abnormality diagnosis unit that determines an abnormality of the feature quantity trend in diagnosis from the feature quantity trend in diagnosis and the feature quantity trend in normal condition.

This utility model discloses a sensor detection device. The sensor detection device includes: a clock generation module, the power supply terminal of which is connected to a power source, and the clock generation module is used to periodically output clock pulse signals through a clock output terminal; a self-locking module, the power supply terminal of which is connected to the power source, and the self-locking control terminal of which is connected to the clock output terminal of the clock generation module to control the self-locking module to open or close; a control module and a detection module, the power supply terminal of which is connected to the power output terminal of the self-locking module; the control terminal of which is connected to the detection module to control the operation of the detection module; and the status feedback terminal of which is connected to the self-locking control terminal of the self-locking module to control the self-locking module to open or close. This utility model reduces the energy consumption of the sensor detection device.

The utility model provides a kind of photoelectric sensor particle detection device and equipment based on double channel detection, it is related to optical particle detection technical field.The device sensor sampling circuit output end is connected with sampling signal distribution circuit input end;Sampling signal distribution circuit first output end is connected with first signal gain circuit input end, and second output end is connected with second signal gain circuit input end;First signal gain circuit output end is connected with first analog-digital conversion circuit input end;Second signal gain circuit output end is connected with second analog-digital conversion circuit input end;The gain coefficient of first signal gain circuit is greater than second signal gain circuit;The output end of first analog-digital conversion circuit and second analog-digital conversion circuit is connected with digital signal processing circuit.The utility model can make signal pass through different gain amplifier, double ADC sampling, make one way channel satisfy small particle measurement, another way satisfies large particle measurement, and the electrical signal of larger particle and smaller particle can be considered.

Sensor and / or sound detection device with: a sensing device (10) with a sensitive surface (12) which is designed such that a change in at least one physical quantity and / or at least one chemical concentration at the sensitive surface (12) causes a change in a sensor signal output by or tapped from the sensing device (10); wherein at least one access channel (18) in the sensor and / or sound detection device is designed such that, at least as long as the at least one access channel (18) is open, air and / or at least one gas can be transferred through the at least one access channel (18) between a spatial environment of the sensor and / or sound detection device and the sensitive surface (12); characterized by at least one at least partially water-impermeable membrane (20) with an inner membrane surface (20a) oriented towards the at least one associated access channel (18), wherein at least one contact surface (22) of the respective membrane (20) located on the respective inner membrane surface (20a) is pressed against at least one associated membrane contact surface (24) on the at least one associated access channel (18) by deformation of the respective membrane (20) when a membrane outer surface (20b) of the respective membrane (20) or a cover layer (40) located on the respective membrane outer surface (20b) is wetted with at least a minimum quantity of liquid, such that the at least one associated access channel (18) is sealed liquid-tight, wherein the at least one membrane (20) is designed such that, if the respective membrane outer surface (20b) or cover layer (40) is not wetted,the respective membrane (20) is in its initial position and the at least one associated access channel (18) is kept open via at least one open intermediate gap between the at least one contact surface (22) of the respective membrane (20) in its initial position and the at least one associated membrane contact surface (24) on the at least one associated access channel (18).

A positioning fingerprint data generation method and apparatus, a device, a medium, and a program product. The method comprises: acquiring device sensor data collected by two or more collection devices and used for positioning, and trajectory data of a moving carrier (S101); acquiring a positioning position of a target indoor area on the basis of the trajectory data of the moving carrier and pre-measured mounting parameters of the collection devices on the moving carrier (S102); and generating positioning fingerprint data of the target indoor area on the basis of the device sensor data and the positioning position of the target indoor area (S103). The method can improve the generation efficiency of positioning fingerprint data, and reduce costs.

The present disclosure is directed towards systems and method for determining whether a scannable code displayed on a client device has been scanned. In particular, the systems and methods described herein involve activating one or more on-board sensors of the client device to capture output signals. Based on the output signals, the systems and methods include identifying discrete signals that indicate whether the scannable code has been scanned by a scanning device. Further, based on an analysis of the identified discrete signals, the systems and methods include determining whether the scannable code has been scanned by the scanning device.

A golf club system includes a golf club, a detection unit, and a smart tag. The golf club has a golf club head, a shaft, and a grip. The detection unit is standing on or raised above the ground plane. The smart tag is a computer-readable marking on the golf club. The smart tag is detected by the detection unit when the golf club is positioned within a detection zone associated with a sensor of the detection unit. The detection unit collects data associated with a user swinging the golf club for transmission to a computing device. The sensor defines the detection zone as a volume extending to an extent of a radius R about a reference axis that is perpendicular to the ground plane and extending vertically along the reference axis above the ground plane.

The utility model relates to a sensor testing system and semiconductor process equipment. The sensor testing system comprises a low-voltage testing unit, a high-voltage testing unit, a negative-voltage testing unit and a temperature testing unit. The testing device has the advantages that by arranging the low-pressure testing unit and the high-pressure testing unit, a low-pressure pressure sensor and an ultrahigh-pressure pressure sensor can be tested, so that pressure performance parameters of the sensors are tested, and diversity of testing varieties of the sensors is realized; the negative pressure test unit is communicated with the low pressure test unit and the high pressure test unit, so that a negative pressure condition can be provided for the test of the pressure sensor, and the test diversity is improved; by arranging the temperature testing unit, the temperature testing unit can enable the constant-temperature medium to pass through the sensor to be tested so as to simulate the actual use condition, so that the temperature performance parameters of the sensor are tested.

Implantable devices and / or sensors can be wirelessly powered by controlling and propagating electromagnetic waves in a patient's tissue. Such implantable devices / sensors can be implanted at target locations in a patient, to stimulate areas such as the heart, brain, spinal cord, or muscle tissue, and / or to sense biological, physiological, chemical attributes of the blood, tissue, and other patient parameters. The propagating electromagnetic waves can be generated with sub-wavelength structures configured to manipulate evanescent fields outside of tissue to generate the propagating waves inside the tissue. Methods of use are also described.

An input / output device includes a first sensor electrode and a second sensor electrode. In addition, the input / output device includes a first electrode and a second electrode which are electrodes for a display element, and a substrate sandwiched between the first sensor electrode and the second sensor electrode. The second sensor electrode is formed concurrently with the first electrode using the same material. The input / output device sensors a change in capacitance of a capacitor formed between the first sensor electrode and the second sensor electrode. Furthermore, a third sensor electrode to which a floating potential is applied may be provided to overlap with the first electrode. In the input / output device, either a liquid crystal element or a light-emitting element may be used, or both the liquid crystal element and the light-emitting element may be used.

Various implementations disclosed herein include devices, systems, and methods that determine a rate and volume of liquid being consumed by a user based on user attributes determined from wearable device sensor data. For example, a process may obtain sensor data from at least one sensor on a wearable device. The sensor data may correspond to activities of a user wearing the wearable device while consuming a liquid during a liquid consumption event. Based on the sensor data, the process may further determine a liquid consumption type associated with the activity of the user. Based on the sensor data and the liquid consumption type, the process may further determine a consumption rate and a consumption volume associated with the activity. Optionally, feedback may be provided to the user based on the determined consumption rate and consumption volume.

The invention belongs to the technical field of wind power equipment operation and maintenance, and discloses a wind power equipment fault early warning method based on edge calculation. The method comprises the following steps: acquiring vibration, temperature and current parameter operation data through a wind power equipment sensor, generating an original data sequence, and preprocessing to obtain a preliminary feature set; the time sequence gradient of each parameter is analyzed and calculated through a time sequence, and a parameter change rate sequence is obtained through optimization of a gradient descent algorithm. When the sequence exceeds a threshold value, a stable change trend is obtained through sliding window smoothing, and anomaly classification and risk grading are completed in combination with a historical working condition database and a support vector machine. And starting deep analysis according to an edge node resource state, constructing a fine prediction model to generate an early warning signal containing a fault probability and occurrence time, matching a risk level to activate a local response, and outputting an alarm. According to the invention, through edge localization processing and multi-algorithm cooperation, accurate pre-judgment of faults is realized, and the operation and maintenance response efficiency and early warning accuracy of wind power equipment are improved.

A system and method for generating floor plans using a mobile device, comprising a memory and a processor in communication with the memory. The processor captures a plurality of walls in a room using one or more sensors of the mobile device. The processor then captures one or more openings in the room. The processor then generates a floor plan based on the walls and the openings.

The invention provides an elevator flat layer detection method, which comprises the following steps of: acquiring images of elevator floor gate scenes of marks A and B through a robot image acquisition module by utilizing a mark A and a mark B which are respectively marked on an elevator car inner vertical surface or a car door vertical surface and an elevator floor door vertical surface, and detecting angular point coordinates; the actual height difference between the mark A and the mark B is calculated, and whether the actual height difference is smaller than a preset threshold value or not is judged, so that flat layers of the top face of the lift car floor and the top face of the floor door floor are detected; real-time and non-contact detection of the leveling state of the elevator without the door or with the door is achieved, the installation and maintenance cost of an equipment sensor is greatly reduced, and it is guaranteed that the robot safely and efficiently operates in a multi-layer station.

Tracking the rate and volume of liquid consumption is disclosed. Various implementations disclosed herein include devices, systems, and methods for determining the rate and volume of liquid consumed by a user based on user attributes determined from wearable device sensor data. For example, a process may obtain sensor data from at least one sensor on a wearable device. The sensor data may correspond to activities when a user wearing the wearable device consumes liquid during a liquid consumption event. Based on the sensor data, the process may further determine a liquid consumption type associated with the activity of the user. Based on the sensor data and the liquid consumption type, the process may further determine a consumption rate and a consumption volume associated with the activity. Optionally, feedback may be provided to the user based on the determined rate of consumption and volume of consumption.

The invention provides power device photon temperature sensing. A power device sensor includes: a semiconductor thermo-optical element; circuitry including a light emitting diode that emits photons and a photodetector that detects the photons and alters a voltage output by the circuitry; and an optical waveguide in optical communication with the light emitting diode, the semiconductor thermo-optical element, and the photodetector.

1. The name of the design product: clean running state graphical user interface for electronic equipment. 2. The use of the design product: an electronic device. 3. The design points of the design product: in the graphical user interface. 4. The picture or photo that best indicates the design points: design 1 front view. 5. Design 2 is designated as the basic design. 6. The use of the graphical user interface: (1) the interface for cleaning state display; (2) after the cleaning equipment starts, it enters the interface shown in design 1 front view, displaying an icon representing the state of the cleaning equipment; after switching, the cleaning equipment jumps from the interface shown in design 1 front view to the interface shown in design 1 change state diagram 1; after switching, the cleaning equipment jumps from the interface shown in design 1 change state diagram 1 to the interface shown in design 1 change state diagram 2; after switching, the cleaning equipment jumps from the interface shown in design 1 change state diagram 2 to the interface shown in design 1 change state diagram 3; (3) after the cleaning equipment starts, it enters the interface shown in design 2 front view, displaying an icon representing the state of the cleaning equipment; after switching, the cleaning equipment jumps from the interface shown in design 2 front view to the interface shown in design 2 change state diagram; (4) after the cleaning equipment starts, it enters the interface shown in design 3 front view, displaying an icon representing the state of the cleaning equipment; after switching, the cleaning equipment jumps from the interface shown in design 3 front view to the interface shown in design 3 change state diagram; (5) the interface shown in design 4 front view is that the cleaning equipment detects a fault in the device's clean water tank during operation, displaying an icon representing the current fault state; (6) the interface shown in design 5 front view is that the cleaning equipment detects a fault in the device's sewage tank during operation, displaying an icon representing the current fault state; (7) the interface shown in design 6 front view is that the cleaning equipment detects a fault in the device's air duct during operation, displaying an icon representing the current fault state; (8) the interface shown in design 7 front view is that the cleaning equipment detects a fault in the device's roller brush during operation, displaying an icon representing the current fault state; (9) the interface shown in design 8 front view is that the cleaning equipment detects dirt on the device's sensor during operation, displaying an icon representing the current fault state.

The invention discloses an abnormity monitoring method, device, system and equipment for landfill leachate membrane equipment and a storage medium, and the method comprises the steps: obtaining a real-time monitoring data set of the membrane equipment through a membrane equipment sensor set, and inputting the real-time monitoring data set into a pre-constructed membrane equipment operation analysis model, and outputting an operation state evaluation result of the membrane equipment, determining an abnormal level corresponding to the operation state evaluation result, and performing early warning according to the abnormal level. Therefore, the running state of the membrane equipment is monitored in real time through the sensor, the lag of manual inspection is avoided, the monitoring efficiency and the data validity are ensured, the abnormal level is analyzed according to the running data, and the situation that the membrane equipment is possibly abnormal can be known in advance, so that more time is provided for dealing with the abnormal situation; therefore, the stability and the intelligent level of leachate treatment are improved.

The present disclosure relates to a sensor device for monitoring an environment of the sensor device, comprising: a housing; one or more sensors for detecting sensor data relating to the environment; a communication interface for wirelessly communicating sensor information based on sensor data; and a control device for controlling the sensor device; wherein the sensor device has an energy storage device for operating the sensor device, the sensor device has a mounting portion on the housing, and wherein the mounting portion is designed to reversibly arrange the sensor device securely on the ground at, on and / or in an external foundation.