5156results about "Optical detection" patented technology

A method and system for early prediction and warning of mine disasters through on-site monitoring is provided. [Solution] The method involves installing sensors at the mine site to monitor surface water, groundwater data and underground rock data in real time, so that mine safety management personnel can obtain timely and comprehensive data to better understand the state of the mine environment. The predictive analysis module uses deep drilling and computational learning technology to analyze the surface water, groundwater data and underground rock data to predict the risk assessment index Fpzs, which is helpful in predicting potential disaster risks, and comprehensively takes into account various factors such as the number of past disasters Lzs, the water level fluctuation coefficient Sbxs, and the rock stability coefficient Ywxs, which is helpful in quantifying the risk level, providing a more accurate disaster risk assessment, and reducing the casualties caused by mine disasters.

The invention discloses a surface mine disaster detection method based on an unmanned aerial vehicle, and belongs to the technical field of mine disaster detection, and the method comprises the steps: evaluating terrain complexity and geological stability, obtaining known disaster risk area information, and generating a risk area distribution map based on the known disaster risk area information; a high-risk area is obtained based on terrain complexity, geological stability and the risk area distribution map, and an unmanned aerial vehicle flight path avoiding the high-risk area is generated based on the high-risk area; acquiring high-resolution image data in real time through the unmanned aerial vehicle according to the flight path of the unmanned aerial vehicle to obtain a panoramic image map; detecting the panoramic image by using a deep learning algorithm to obtain attribute information of a suspected collapse area; in combination with known mine collapse feature data, the authenticity of the collapse area is judged by using a similarity matching algorithm, and a detection result is obtained; and uploading a detection result to a management platform, and carrying out real-time display and dynamic updating. According to the invention, the efficiency and accuracy of mine disaster monitoring are improved.

The invention provides a room obstacle detection optimization method and system based on a cross-modal attention mechanism. Wherein a dynamic compensation coefficient is calculated by acquiring motion track data of the mobile equipment, and a stable visual coordinate system is constructed. Visible light and near-infrared wave band acquisition of the multispectral sensor is synchronously triggered, the visible light captures geometric deformation characteristics of a floor projection surface, and the near-infrared detects a local heat radiation abnormal area. And extracting a thermal feature connected domain conforming to periodic biological motion as a living obstacle, and marking a collision risk boundary of a static obstacle. And based on a living body motion law and a collision boundary deviation trend, synchronously optimizing the dual-band exposure parameters and updating the trajectory prediction model, and forming a closed-loop feedback link of sensing and planning. According to the technical scheme provided by the invention, the living body and the static obstacle are accurately distinguished in a dynamic environment, and the sensor parameters are adaptively adjusted to improve the real-time obstacle avoidance response capability.

The invention relates to the technical field of coal gangue classification and recognition, in particular to a coal gangue recognition method and system based on hyperspectral imaging and laser ranging, and the method comprises the steps: mapping hyperspectral image data to a three-dimensional point cloud of laser ranging data, and obtaining a mapping result; adopting the trained network model to extract multi-scale spatial features and multi-scale spectral features from the mapping result; the extracted features are fused, and then candidate target areas are generated based on the fused features; classifying the candidate target areas to obtain a classification result of the coal gangue; constructing a three-dimensional model of the coal surface based on laser ranging data; generating a triangular mesh model for the three-dimensional model of the coal surface; smoothing the triangular mesh model to obtain a reconstructed model; determining the granularity of the coal briquettes based on the reconstruction model; and based on the spectral data, identifying the lithofacies characteristics of the coal, and distinguishing different types of coal. And the coal gangue sorting accuracy and efficiency are improved.

The purpose of the present invention is to provide a snow cover amount estimation system and a snow cover amount estimation method which enable accurate, economical, and remote measurement of snow cover amount.　A snow cover amount estimation system 301 according to the present invention is provided with: an optical fiber 50 which receives vibration from the surface of the snow at a given point; a vibration measuring instrument 11 for measuring the vibration received by the optical fiber 50 as a distribution in the longitudinal direction of the optical fiber 50; and an analysis processing unit 12 that has, as accumulation data, the relationship between snow cover amount and the vibration received by the optical fiber 50, compares the distribution measured by the vibration measuring instrument 11, as measurement data, with the accumulation data, and estimates the snow cover amount at the given point.

A system and method for polarization detection of a target in a strong background are provided. The system includes: an image signal acquisition module configured for image information acquisition and signal conversion of a plurality of channels; a YoLoV3 neutral network-based feature extraction module configured to increase a number of network layers, obtain a fused feature map combined with intensity information and polarization information, and extract a feature difference between an intensity modality and a polarized light modality; a Darknet53 neutral network-based feature extraction module configured to extract a feature value of a high dynamic range image; a residual network-based feature fusion module configured to learn weights of different modalities, obtain a fused feature map of intensity modality information and polarization modality information, and select and optimize the fused feature map by attention mechanism processing; and an image printing module configured to filter background information.

The invention discloses an air-ground collaborative dam termite trace detection method and device and electronic equipment. The method comprises the steps that an unmanned aerial vehicle is used for cruising and scanning the surface of a dam to obtain image information; constructing a three-dimensional map of the dam by using the image information; extracting termite activity trace characteristics on the image information; according to the image information, a detection and recognition model is constructed, and the detection and recognition model is that an efficient detector for a small target is introduced on the basis of yov8; deploying the detection and recognition model on a ground tracked robot, and performing initial detection and recognition on the termite activity trace characteristics by the unmanned aerial vehicle by using the detection and recognition model; the termite traces recognized through initial detection are determined as suspected features, and the position points of the suspected features are determined and calibrated on a map; and the ground tracked robot plans a one-way planning route map to a position point according to the position point calibrated on the three-dimensional map, then navigates to the position point with the suspected feature, and carries out detection confirmation, so that air-ground collaborative integrated dam termite earth surface exposure feature detection is comprehensively realized.

The invention provides a visual detection method and related system for a complex assembly structural member, and the method comprises the steps: determining a target multi-scale decomposition algorithm corresponding to a preset detection type and a first algorithm control parameter corresponding to the target multi-scale decomposition algorithm when the target detection type is the preset detection type; performing multi-scale decomposition on the target area according to a target multi-scale decomposition algorithm and the first algorithm control parameter to obtain a low-frequency component part and n high-frequency component parts; determining a second feature extraction algorithm corresponding to the preset detection type and a second algorithm control parameter of the second feature extraction algorithm; performing feature extraction on the m high-frequency component parts according to a second feature extraction algorithm, a second algorithm control parameter and m feature type labels to obtain m second feature sets; and determining a target detection result according to the m second feature sets and a target detection verification standard.

The invention discloses a distributed polarization detection system and method based on position regulation and control target reconstruction, and belongs to the field of distributed polarization cooperative detection and photoelectronic imaging. The distributed polarization detection system comprises a lighting device, a multi-parameter auxiliary detection objective table and a long-wave infrared polarization detection device; the long-wave infrared polarization detection device is provided with three sub-polarization detection devices, the method is implemented based on a distributed polarization detection system, and polarization information in three different directions can be collected at the same time through the distributed polarization detection system based on position regulation and control target reconstruction. The identification capability of the disguised / similar target at a single angle is improved; and errors caused by time delay are avoided. Polarization information obtained by reasonably distributing detection positions is mutually supplemented, polarization images are mutually fused, target signals are effectively extracted from scattered light to analyze the polarization characteristic difference between interference light and target reflected light, and the resolution, contrast and detection distance of polarization imaging can be improved.

The invention discloses a human body existence sensing method based on millimeter wave radar and infrared pyroelectric sensor double-source collaborative fusion, and the method comprises the steps: processing original data collected by a millimeter wave radar sensor receiving end, and obtaining a high-quality distance-speed dimension data matrix; carrying out SVD decomposition, and reconstructing two new data matrixes which are respectively corresponding to a strong target signal and a weak target signal; a human body existence sensing output result of the millimeter wave radar sensor is obtained through the track features and the breathing features; processing a signal of the infrared pyroelectric sensor to obtain a human body existence sensing output result of the infrared pyroelectric sensor; and constructing a heterogenous data matrix according to output results of the two sensors, and performing fusion algorithm processing on the heterogenous data matrix to obtain a fusion result. And finally, the fusion result is stored in a delay memory matrix, and the aging degree is calculated according to the aging factors corresponding to different delay units, so that a final human body existence sensing result is obtained.

The invention discloses iron core feeding detection equipment which comprises a workbench, a first linear module used for horizontal movement is installed on the upper surface of the workbench, and a jacking rotating assembly used for adjusting the vertical height of an iron core is installed on the first linear module in a sliding mode. The upper surface of the workbench is further provided with a height detection assembly used for detecting the vertical height of an iron core through an installed fixing frame, and further comprises a second linear module used for horizontal movement. The second linear module is slidably provided with a camera adjusting part used for detecting a key groove in an iron core and a transverse moving clamping assembly used for clamping the detected iron core to a tray to be conveyed. And before a series of subsequent processing production of the iron core, the iron core is detected, so that the production quality is ensured.

The invention relates to the technical field of track foreign matter real-time detection, and particularly discloses a track foreign matter real-time detection method based on YOLOv5 improvement. Comprising the steps of video vibration synchronous acquisition, space offset compensation parameter generation, dynamic feature enhancement processing, feature weight thermodynamic diagram generation, hierarchical perception feature aggregation, cross-scale target verification, foreign matter positioning instruction packaging and multistage early warning execution control. Image distortion caused by mechanical vibration and illumination fluctuation is effectively overcome by synchronously acquiring track video and vibration time sequence signals, constructing a spatial offset compensation parameter set and combining with a dynamic feature enhancement template to correct video frames, a feature weight thermodynamic diagram is generated through visual saliency detection, features are aggregated through a layered perception model, and the visual saliency detection accuracy is improved. Early warning levels are dynamically matched according to the sizes and the positions of the foreign matters, and a sound-light alarm and braking system is linked; according to the invention, the reliability of data transmission is ensured, the operation and maintenance cost is greatly reduced, and the safety requirement of millisecond response of modern rail transit is met.

The embodiment of the invention provides a half-coal rock roadway surrounding rock loose circle dynamic detection device based on three-dimensional laser scanning, and belongs to the technical field of optical measurement. According to the dynamic detection device for the loose circle of the surrounding rock of the half-coal-rock roadway based on three-dimensional laser scanning, three-dimensional point cloud data of surface characteristics of the surrounding rock of the roadway are obtained by performing three-dimensional laser scanning on the surrounding rock of the half-coal-rock roadway, and a three-dimensional surrounding rock model of the surrounding rock of the roadway is newly built based on the preprocessed three-dimensional point cloud data; and performing surrounding rock surface characteristic comparison based on the three-dimensional surrounding rock model and the surrounding rock reference model, and determining a loosening circle area where the roadway surrounding rock is loosened. And finally, a monitoring report is generated based on the newly built three-dimensional surrounding rock model of the roadway surrounding rock, and the surrounding rock surface characteristics of the three-dimensional surrounding rock model are displayed in real time, so that the spatial distribution and change conditions of the loose circle of the roadway surrounding rock can be accurately obtained in real time, dynamic monitoring can be performed, and the safety of mine engineering is ensured.

The invention relates to the technical field of robot reconnaissance, and discloses a tracked robot intelligent reconnaissance system based on panoramic vision and multispectral analysis, which comprises the following steps: dynamically adjusting sensor parameters based on environmental spectral characteristics to adapt to different light conditions, and collecting high-quality panoramic vision and multispectral data; performing panoramic vision fusion processing on the acquired data to compensate light change in a complex environment and enhance image quality; performing multispectral data analysis according to the fused data, and classifying target materials based on an analysis result to improve reconnaissance accuracy; and a relevance optimization algorithm of visual data and spectral information is combined to filter interference in multi-target reconnaissance and feed back and correct path planning of the robot in real time. Target materials are classified according to a multispectral data analysis result to solve the problem of insufficient target recognition accuracy in the reconnaissance process, and the success rate and high efficiency of a reconnaissance task are ensured by combining machine learning with a prediction algorithm.

The invention provides a mosquito detection and cooperative killing system and method.The mosquito detection and cooperative killing system comprises a bionic multi-mode sensor array and a dynamic feedback killing device, and the bionic multi-mode sensor array comprises an infrared sensing module used for simulating human skin radiation characteristics; the CO2 concentration gradient sensor is used for detecting the change of the concentration of carbon dioxide and activating the directional scanning of the infrared sensing module; the odor molecule release device is used for triggering a mosquito approaching behavior; the dynamic feedback killing device is used for starting the laser mosquito killing module and killing mosquitoes through infrared positioning coordinates. According to the technical scheme, the mosquito killing effect is improved.

The invention discloses an element plugging test system based on visual perception and a control method and device.The system comprises a visual perception module, a grabbing device, a conveying device and an upper computer, and the visual perception module is used for conducting visual recognition on jacks of elements to be tested and comprises a 2D camera and a 3D camera; the 2D camera has a first field of view, the 3D camera has a second field of view, the first field of view comprises the second field of view, and the first field of view range is larger than the second field of view range; the grabbing device comprises a clamping end, and the clamping end is used for clamping the plug to plug and unplug the jack; the visual perception module is mounted at the clamping end so as to move along with the clamping end; the conveying device is used for conveying to-be-tested elements; the upper computer is in communication connection with the visual perception module, the grabbing device and the conveying device. The visual perception module can be compatible with large-deviation incoming materials, so that multi-degree-of-freedom position and posture adjustment is realized; therefore, the application range of the system is greatly expanded, and the system has excellent flexibility, compatibility and accuracy.

The invention provides a surveying device and method for an internal structure of a coating, and relates to the technical field of surveying. The surveying device comprises an acquisition system used for acquiring coordinate information of muons, and the coordinate information comprises intersection point coordinates of the muons and the acquisition system; the positioning time service system is connected with the acquisition system and is used for recording the position information of the acquisition system; the control system is respectively connected with the acquisition system and the positioning time service system, and is used for obtaining a structure image of the internal structure of the to-be-detected coating according to the coordinate information and the position information, and judging the condition of the internal structure of the to-be-detected coating according to the structure image; wherein the to-be-detected coating is located at the upper part of the underground space; and the mobile carrier can move in the underground space, and the acquisition system, the positioning time service system and the control system are fixed on the mobile carrier. The surveying device can efficiently detect the condition of the internal structure of the to-be-detected coating in real time in a non-invasive mode, and the safety of the operation period and the construction period of the underground space is guaranteed.

A system includes sensors, memory, and a processor. The sensors are configured to capture images of a workspace, and the memory is configured to store the images and a model of machinery located within the workspace. The processor is configured to generate a spatial representation of the workspace based on the captured images. The processor is also configured to identify non-machinery entities within the workspace and, for each of the identified entities, generate an object that specifies a spatial extent of the respective entity and a protective separation distance for the entity. Further, the processor is configured to recognize an interaction between the entities and merge the corresponding objects into a merged object specifying a protective separation distance therefor. Moreover, the processor is configured to control operation of the machinery in accordance with a safety protocol and the protective separation distance for the merged object.

The invention discloses a railway tunnel foreign matter detection method based on radar point cloud and RGB image fusion. The method comprises the following steps: acquiring a laser radar point cloud and an RGB image in a railway tunnel; obtaining an RGB image by using an adversarial network model GAN to judge the abnormal occurrence state of the foreign matter in the railway tunnel, and if the abnormal state of the foreign matter occurs, projecting the obtained laser radar point cloud to an image plane to obtain a dense depth map; processing through a sliding window to obtain data slices which are approximately square; and carrying out data feature extraction, fusion and foreign object target detection on the data slices of the RGB image and the dense depth map by using a fusion target detection network based on the OfficientNet-FPN, and outputting a foreign object target information detection result containing a target category, a position, a confidence coefficient and a distance. According to the railway tunnel foreign matter detection method based on radar point cloud and RGB image fusion, high precision, high efficiency and high reliability of railway tunnel foreign matter detection are realized.

The invention provides an underground structure boundary identification method and system based on distributed optical fiber sensing, and relates to the technical field of underground structure detection and boundary identification. The method comprises the following steps: firstly, arranging a sensing array in a to-be-detected area, establishing a channel corresponding to a space coordinate, and collecting a non-excitation base line; medium and noise are estimated through low-energy probe, excitation frequency band, energy and repetition rate are optimized, and the signals are emitted by an adaptive seismic source; reflection and transmission responses are synchronously collected under the unified time reference; performing wavelet denoising, temperature and dispersion compensation and time alignment on the data, and extracting amplitude, phase and frequency characteristics; gradient is calculated on the feature field, non-maximum suppression is carried out, and stable boundary points are obtained by adopting self-adaptive double thresholds based on local statistics and combining time continuity and space connectivity constraints; a two-dimensional section is obtained through spline fitting, a three-dimensional model is reconstructed under the constraint of multi-section consistency, a section map and the three-dimensional model are output, and high-precision, real-time and visual detection of small-size boundaries is achieved.

The invention relates to the technical field of laser heat treatment, and provides a calibration method of a full-automatic circuit board cutting machine. The method comprises the following steps: acquiring physical coordinates of a circuit board of a cutting device through an intelligent sensor, and constructing a reference coordinate system matrix based on the physical coordinates; determining vibration parameters of the cutting device according to coordinates of laser spots emitted by a laser and the reference coordinate system matrix, and generating a nonlinear error component according to the vibration parameters and power information of the laser; generating an error function based on an error matrix formed by the error components, and determining a calibration coefficient vector by solving the error function; closed-loop control is conducted on the laser path of the cutting device through the calibration coefficient vector, the adaptability of the cutting device to complex working conditions is improved by integrating multi-source error factors and establishing a nonlinear mapping relation, and the cutting precision and stability are ensured.

The invention provides a wheel tread derailment detection method and system for a railway vehicle. According to the method, jacking driving devices with jacking rotating wheels are symmetrically arranged on the two longitudinal sides of a track, a pressure sensing unit is arranged between the two jacking rotating wheels, optical detection units with orthogonal optical paths are installed on the outer sides, and displacement measurement units are integrated on the jacking rotating wheels, so that a three-dimensional detection network is formed. During detection, a top rotating wheel lifts a wheel step by step, a blocking signal, tread pressure and a vertical displacement parameter are synchronously collected, and a space mapping relation between a pressure decreasing path and a displacement abnormal point is established; converting the blocking signal into a blocking release rate, and calculating a displacement accumulated value in combination with a space mapping relation; and when the displacement accumulated value is continuously increased and the blocking release rate exceeds a threshold value, wheel-rail separation is judged, and jacking is controlled to be stopped. Through cooperative detection and analysis of multiple sensors, accurate judgment and self-adaptive jacking control of the wheel-rail separation state are achieved, and the problem of wheel diameter adaptability of a traditional fixed jacking mode is effectively solved.

The invention belongs to the technical field of automation equipment, and discloses high-voltage connection unit assembly and detection equipment, which comprises a bedplate, and a turntable A and a turntable B which are mounted on the bedplate at an interval, a plurality of product fixing units A are mounted on the turntable A; a shell feeding unit, a shielding piece mounting unit, a lining feeding unit and a lining press-fitting unit are sequentially arranged in the rotation direction of the rotary disc A; the product fixing unit A is used for positioning the shell and is provided with a first supporting surface perpendicular to the rotation axis of the rotary table A and an elastic telescopic pin inserted into the first supporting surface; the elastic telescopic pin is provided with a first cylindrical section which is matched with a hole for mounting the bushing on the shell and a second cylindrical section which is matched with a bushing hole; the second cylindrical section is positioned above the first cylindrical section; a plurality of product fixing units B are mounted on the turntable B; a sealing ring assembling unit and a discharging mechanical arm used for transferring the assembled high-pressure connecting unit to the outside of the rotating disc B are sequentially arranged in the rotating direction of the rotating disc B.

The invention discloses an illumination adaptability rock crack identification and calibration method based on an image identification algorithm, and relates to the technical field of geotechnical engineering intelligent image identification, and the method comprises the following steps: collecting an illumination incident angle, a polarization state and an illumination gradient corresponding to an image frame, building an illumination time sequence observation layer, and obtaining an illumination time sequence observation layer; forming an illumination feature baseline for crack boundary tracking; and performing coherent phase decomposition on the image sequence based on the illumination feature baseline, stripping mirror reflection and enhancing diffuse reflection texture, and generating a crack drift suspicion image. Through construction of an illumination time sequence observation layer and coherent phase decomposition, illumination interference stripping in a crack image is realized, false drift is eliminated by combining anti-fact playback and time reconstruction, and a dynamic threshold control mechanism is constructed by introducing an anti-illumination mask and an anti-phase pattern and linking a polarized light diaphragm and a shading array. And high robustness of crack identification and closed-loop regulation and control of false early warning are realized.

The invention relates to the technical field of power-on devices, and discloses a rapid power-on and power-off device for assembly line automation, the rapid power-on and power-off device comprises a transportation track, a transportation plate and a power-on butt joint device, the power-on butt joint device is arranged on one side of the transportation track, and a butt joint base and a butt joint socket are arranged on the transportation plate; the power-on butt joint device and the butt joint socket transmit power to the motor through a contact type conductive structure, the power-on butt joint device is composed of a butt joint plug, the butt joint plug is a cylindrical connector in a vertical array, the butt joint base is in a groove shape, the butt joint socket is arranged in the butt joint base, and the butt joint base is in flexible connection with the inner wall of the butt joint socket. The back face of the butt-joint socket is provided with a wire interface connected with a power supply wire, the front face of the butt-joint socket is provided with an interface matched with the butt-joint plug, a positioning column is arranged in the conveying rail on one side of the power-on butt-joint device and can position the position of the conveying plate, and an air bag is arranged on the outer ring of the interface on the front face of the butt-joint socket and can control the amount of gas contained in the butt-joint socket.

The invention relates to the technical field of electric power fault detection, and discloses a fault monitoring system and method based on an electric power acquisition terminal, and the method comprises the steps: constructing a non-linear relation between the power consumption and the temperature through analyzing the historical power consumption data of a user and the weather temperature; the method comprises the following steps: dividing a user electricity consumption day into a plurality of time periods, and setting a time interval threshold value; and in each time period, data are acquired through the electric power and temperature acquisition devices, an electric quantity and temperature scatter diagram is constructed, and nonlinear data fitting is carried out. Thirdly, the similarity between the temperature nonlinear relational expressions of different time periods is calculated, the time periods are divided into sets, and a temperature retrieval set is established; and searching a corresponding electric quantity relation set by matching the temperature nonlinear relational expression of the user in the current time period, and judging whether electric power fluctuation and fault exist or not according to the priority ranking and the relation similarity.

The invention discloses an edge detection filter based on a structure tensor and a softsign function, and aims at processing and interpretation analysis of a gravity gradient tensor, and edge detection filtering is carried out based on a three-dimensional structure tensor and the softsign function. The method can quickly determine the horizontal distribution range of the target, and effectively reduces the problems of divergence, fuzziness, deformation and the like. The boundary of the deep anomalous body can be clearly and accurately delineated under the condition of less prior information, and false boundaries between positive and negative anomalous bodies are avoided; the method can adapt to abnormal data of different targets or scales, human intervention is reduced, the screening process is simplified, and meanwhile the reliability of screening results in quality and quantity is ensured.

The invention discloses medicine package quality detection equipment, and relates to the technical field of medicine package detection, the medicine package quality detection equipment comprises a rack and adjusting assemblies, the rack is internally provided with a conveyor belt conveyor, the upper part of the rack is provided with a visual detection camera, the adjusting assemblies are arranged on two sides of the rack, and each adjusting assembly comprises a servo motor, a servo motor is arranged on the rack, and a servo motor is arranged on the servo motor. A double-output-shaft speed reducer is arranged at the end of the servo motor, lead screws are symmetrically arranged on the two sides of the double-output-shaft speed reducer, and thread lines on the outer sides of the two lead screws are opposite. When a conveyor belt conveyor conveys a medicine bottle to the position below a visual detection camera, the bottle opening of the medicine bottle can be shot and detected, at the moment, a servo motor is started, lead screws at the two ends can be driven to rotate through a double-output-shaft speed reducer, a sliding base slides in the length direction of a polished rod, and then the bottle opening of the medicine bottle is detected. At the moment, the lifting seat, the positioning spring and the rotating seat drive the roller seat to cling to the medicine bottle, so that the medicine bottle is centered and positioned and is prevented from shifting.

A visible light sensor may be configured to sense environmental characteristics of a space using an image of the space. The visible light sensor may be controlled in one or more modes, including a daylight glare sensor mode, a daylighting sensor mode, a color sensor mode, and / or an occupancy / vacancy sensor mode. In the daylight glare sensor mode, the visible light sensor may be configured to decrease or eliminate glare within a space. In the daylighting sensor mode and the color sensor mode, the visible light sensor may be configured to provide a preferred amount of light and color temperature, respectively, within the space. In the occupancy / vacancy sensor mode, the visible light sensor may be configured to detect an occupancy / vacancy condition within the space and adjust one or more control devices according to the occupation or vacancy of the space. The visible light sensor may be configured to protect the privacy of users within the space via software, a removable module, and / or a special sensor.

The embodiment of the invention discloses a multispectral recognition device and method based on a metasurface, a medium and equipment, and the device comprises a sub-aperture imaging lens group which is used for collecting the multispectral information of a target object, carrying out the sub-aperture convergence, and outputting the sub-aperture convergent light in a parallel light form; the metasurface modulation device is used for generating a preset number of metasurface atoms through the micro-nano structure metasurface, performing multispectral modulation on the aperture-divided convergent light according to the metasurface atoms, and obtaining modulated multispectral information and unmodulated spectral information; and the charge-coupled device is used for collecting the modulated multispectral information and the unmodulated spectral information to obtain a multispectral image and a full-band image. And the target detection module is used for carrying out softmax normalization processing after carrying out feature fusion on the multispectral image and the full-band image, and outputting a final target identification result. By combining the super-structure surface multispectral imaging under the deep learning method, the imaging equipment is miniaturized, and the target recognition accuracy is improved.