3683 results about "Real time display" patented technology

The invention relates to a steel logistics full-process real-time dynamic management method and device, and belongs to the technical field of steel logistics control methods and devices. According to the technical scheme of the invention, data acquisition and monitoring are carried out, and transport vehicle and cargo states are tracked; demand prediction and inventory dynamic adjustment are carried out, and high-frequency cargo response emergency orders are allocated according to shipment frequency; visual management of the supply chain is carried out, shared data of all links of the supply chain is established, a 3D logistics map is constructed, and inventory, transportation states and bottleneck nodes are displayed in real time; and risk control management: quickly starting the alternative scheme when the early warning is triggered. The method has the advantages that efficiency is optimized, limitation of a traditional single transportation mode is reduced, rolling updating and emergency response of demand prediction are achieved, data transparency and credibility are improved, rapid risk response is achieved, and logistics full-life-cycle management is achieved.

The invention belongs to the technical field of data processing, and provides a multi-source data fused building settlement trend prediction method, device and medium, and the method comprises the steps: firstly collecting multi-source monitoring data of a target building, then carrying out the preprocessing and fusion, obtaining fusion feature data, inputting the fusion feature data into an AI prediction model, and obtaining a target building settlement trend prediction result; and finally, combining the real-time settlement amount, the settlement rate and the settlement trend prediction result in the fused feature data, comparing with a preset early warning threshold value, and judging whether an early warning instruction is triggered or not. If the early warning instruction is triggered, a corresponding alarm is given out, and the real-time settlement amount, the settlement rate and the settlement trend prediction result are displayed in real time. Through cooperation of multi-source data fusion and the scene adaptive AI model, accurate prediction and timely early warning of the settlement trend of the building are realized, the core is to break through the limitation of single data and a fixed model, and the precision of settlement prediction and the timeliness of risk response in a complex scene are remarkably improved.

An AI-driven centralized orchestration system (100) with MCP protocol for real-time compliance and risk data management, including: a. a centralized integration and orchestration platform configured to connect heterogeneous enterprise IT systems through standardized API connections and execute automated workflows; b. a variety of domain-specific artificial intelligence (AI) agents that interface with IT service management (ITSM), vulnerability management, and endpoint and asset management platforms for data collection, analysis, and assessment; c. a Multi-Agent Communication Protocol (MCP) layer that enables structured communication, negotiation and coordination between AI agents in real time; d. a data consolidation module configured to aggregate, standardise and align heterogeneous data into a unified repository using machine learning models; e. a compliance reporting module for dynamically generating and distributing audit-ready compliance reports based on AI-analyzed data and triggered workflows; f. an alerting module configured to deliver context-dependent predictive notifications of compliance violations or risk anomalies through various communication channels; g. a predictive dashboard module capable of displaying compliance status, risk metrics, and proactive insights in real time via AI-driven visualization tools; i.e., where the orchestration platform, AI agents, and MCP layer together enable automated, scalable, and proactive compliance and risk actions.

The invention relates to the technical field of display control, in particular to an LED screen display control method and system and an LED screen. The method comprises the following steps: acquiring multi-modal stage sensing data and LED screen real-time display data, and performing stage performance environment perception according to the multi-modal stage sensing data and the LED screen real-time display data to obtain stage environment perception data; performing flow scene coding prediction based on the stage environment perception data to obtain renderable scene factors; obtaining display content data of the LED screen, and analyzing a pre-output picture of the LED screen to obtain visual pre-output data of the LED screen; performing multi-modal stage dynamic characteristic reasoning according to the LED screen visual pre-output data and the renderable scene factors to obtain a stage visual dynamic output structure diagram; and performing real-time heterogeneous driving rendering on the stage visual dynamic output structure diagram to obtain a millisecond LED rendering diagram block data set. According to the invention, the display response precision and the picture adaptation capability of the LED screen can be improved.

The invention relates to the technical field of display, and particularly discloses a dynamic ambient light adaptive OLED display optimization method and system, and the method comprises the steps: obtaining an ambient light time sequence data set of an environment where an OLED display screen is located, and synchronously obtaining real-time display parameters and historical brightness adjustment data of the display screen; acquiring ambient light sensing features according to the ambient light time sequence data set; obtaining photo-thermal structure coverage area data of the OLED display screen according to the real-time display parameters; and acquiring preliminary optimization parameters according to the ambient light sensing characteristics and the photo-thermal structure coverage area data. According to the invention, illumination intensity, spectrum drift and contrast change are captured in real time in combination with ambient light perception characteristics, the one-sidedness of adjustment only according to brightness traditionally is solved, reflection can be reduced through photothermal structure deformation under strong light, brightness can be improved to offset interference, and human visual characteristics can be matched under weak light. And the display definition and the visual comfort in different environments are effectively improved.

The invention relates to the technical field of obstacle detection, and discloses an unmanned subway obstacle intelligent detection system based on a multi-mode AI sensor, and the system comprises the multi-mode AI sensor, a preprocessing unit, a data processing unit, and a communication unit. According to the method, in data preprocessing, point cloud filtering denoising, down-sampling burden reduction, image graying contour highlighting and Gaussian filtering denoising all improve the processing efficiency and the detection precision. Efficient data fusion establishes a multi-coordinate system conversion relation, blind area misjudgment is avoided, and the complex environment adaptability is enhanced. A comprehensive obstacle detection strategy covers laser radar multi-link processing and Canny algorithm application of visual images, mutual verification is carried out, and the reliability is improved. When obstacles are detected, real-time display and graded alarm can be achieved, early warning and scheduling control can be achieved by means of network transmission information, braking or avoiding can be achieved according to conditions, operation safety is guaranteed, and the system is reasonable in structure, has adaptability and expandability and assists technology development.

The invention provides an AR intelligent shopping guide interaction method and system applied to store management, and the method comprises the steps: firstly obtaining an interaction data set of a user in a store, covering a user position movement track, a commodity attention action sequence and voice consultation content, carrying out the user intention analysis of the interaction data set, and carrying out the user intention analysis of the interaction data set; the method comprises the steps of obtaining commodity demand characteristics and interaction preference characteristics, generating AR shopping guide interaction content, including commodity three-dimensional display information and an interaction guide instruction, adaptive to a user based on the commodity demand characteristics and the interaction preference characteristics, aligning and fusing the AR shopping guide interaction content with a store physical scene space, generating an AR shopping guide interaction scene capable of being displayed in real time, and displaying the AR shopping guide interaction scene in real time. And finally, responding to user interaction operation in the AR shopping guide interaction scene, generating feedback information and updating the interaction data set to trigger interactive process iterative optimization, thereby providing personalized and immersive shopping guide experience, and improving store operation efficiency and customer satisfaction.

The invention relates to the technical field of industrial equipment fault diagnosis, and provides an industrial equipment real-time fault diagnosis method and system based on a generative model, and the method comprises the following steps: collecting the original operation data of industrial equipment in real time through a plurality of sensors, carrying out the preprocessing of the original operation data, obtaining the real-time operation data, and carrying out the calculation of the real-time operation data; the preprocessing comprises abnormal value detection and standardization; constructing a generative model based on the real-time operation data, generating a normal data sample of the industrial equipment in a normal state through the generative model, and integrating the real-time operation data and the normal data sample to obtain a multi-dimensional data sample; performing feature extraction on the multi-dimensional data sample by using a deep learning model to obtain a fault diagnosis vector; performing fault mode identification on the fault diagnosis vector through a classification model to obtain a fault diagnosis result, and performing state judgment on the fault diagnosis result according to a preset threshold to obtain an industrial equipment state; and the state and the fault diagnosis result of the industrial equipment are displayed in real time through a dynamic monitoring interface. According to the method, the real-time performance and the overall efficiency of fault diagnosis are improved, and the loss caused by equipment faults can be effectively reduced.

The invention discloses a network topology and equipment resource information display method and device, equipment, a medium and a product, and relates to the field of network topology monitoring, and the method comprises the steps: employing a data collection module to collect network data; the network data comprises network topology information and resource information; carrying out optimization processing on the network data by utilizing a data processing module, and determining optimized network data; dynamically generating a network topology view according to the optimized network data by using a generation module of a display screen interface on the basis of the equipment operation state and the site connection relationship; based on a user interaction module, the link information of each link, the basic information of each network node and the resource state information in the network topology are displayed in a graded mode according to the network topology view, the information display effect in a large-scale network environment is optimized, and the resource state can be displayed in real time.

The invention relates to an edge fusion method and system of an XR immersion type LED display screen. The method comprises the following steps: carrying out feature extraction on image data of an XR immersive LED display screen to obtain an RGB three-channel spatial domain feature matrix and a frequency domain edge feature matrix; performing feature processing to obtain a multi-core context feature map; performing coding processing to obtain a position-brightness comprehensive coding feature matrix; performing multi-scale decomposition to obtain a multi-scale detail feature map; carrying out pixel clustering on the edge region of the XR immersive LED display screen to obtain an edge topological structure diagram and a brightness transition function; and performing dynamic matching on the display frame rate through a PID controller, and performing brightness compensation and color correction on the edge region to obtain edge fusion data. The method has the multi-scale feature extraction capability, the edge fusion problem under different scenes can be adaptively processed, and it is ensured that processing delay meets the real-time display requirement, so that the overall performance of an XR immersive display system is improved.

The invention relates to an intelligent winding control method of a lithium battery automatic cutting and winding machine in the field of winding machines, which aims at the inertia effect of a material in a high-speed winding process, establishes a material dynamic model, comprehensively considers the quality, rigidity and damping parameters of the material, predicts the dynamic response characteristics of the material in the winding process, and controls the winding speed of the material. A feed-forward compensation mechanism is introduced into a control system, and control instruction correction is performed on an execution mechanism according to a prediction result of a material dynamic model, so that the influence of a material inertia effect on position control precision is inhibited; in a man-machine interaction interface of the winding machine, information display and operation guide functions are provided, key parameters and equipment state information in the winding process are displayed in real time, monitoring and management by operators are facilitated, a perfect data recording and tracing system is established, production process data of each roll of battery cells are completely recorded and stored, and the production efficiency of the battery cells is improved. A traceable quality management chain is formed, and data support is provided for product quality analysis and improvement.

The invention discloses an intelligent interactive Agent system based on Langchain and an implementation method, and relates to the technical field of natural language processing and artificial intelligence. Comprising the steps of 1, establishing an intelligent interactive Agent system by using an interface and an integrated tool provided by a Langchain framework, 2, managing calling of various tool modules and services through a central scheduling module, and dynamically registering and unbinding the tool modules by using the interface provided by the Langchain framework, and 3, processing user input by using a large language model through a process management module, and establishing an intelligent interactive Agent system. 4, a series of tool modules are integrated through the integrated tool management module, the tool modules comprise a text search tool, a weather query tool and a video information acquisition tool, each tool module works independently or is in linkage with other tool modules, and the tool modules are connected with the integrated tool management module. And 5, managing a user interaction interface through a front-end management module, supporting a user to query and control in a natural language, displaying a processing progress and a processing result in real time, and providing feedback and help information.

The invention discloses a ceramic glaze detection method and system based on image processing and a hierarchical classifier, and relates to the technical field of data processing and analysis. The method comprises the following steps: S1, scanning the surface of the ceramic glaze line by line through a color linear array CCD sensor, and collecting high-resolution RGB image data; s2, preprocessing the image data acquired in the step S1, and identifying a potential defect area; s3, performing preliminary classification on the potential flaw areas identified in the S2, and screening suspected flaw areas; s4, performing fine classification on the suspected flaw areas output in the step S3; s5, according to a classification result, performing real-time marking on the flaw area through an automatic marking device; s6, the detection result is transmitted to an upper computer through the Ethernet to be displayed and recorded in real time; by adopting the ceramic glaze detection method and system based on image processing and the grading classifier, the ceramic production quality and the working efficiency and precision in production process control can be improved.

The invention relates to the technical field of information, in particular to an omni-channel order management system based on a block chain. Comprising an order management and digital twinning module, an inventory management and cloud network cooperation module, a payment and intelligent contract module, a logistics and edge computing module, a customer service and after-sales management module, an authority management and security module, a data analysis and prediction module and a compliance and audit module. The order management and digital twinning module creates a digital model for an order through a digital twinning technology, and displays the change of an order state in real time; and the inventory management and cloud network cooperation module synchronizes inventory information of each channel in real time and dynamically allocates resources by using a cloud network fusion technology. Through digital twinning, an enterprise can dynamically monitor each link of an order in real time, when a complex supply chain is processed, problems can be predicted in advance, delay or order loss is avoided, and more efficient and more transparent order fulfillment is realized.

The invention relates to a batch rectification system based on intelligent control, and relates to the technical field of batch rectification. A data acquisition module; the data acquisition module is used for acquiring temperature, pressure, flow and material concentration data in real time; the control module is used for receiving various data of the data acquisition module; a model prediction control algorithm is built in the control module; according to the model prediction control algorithm, a rectification process dynamic model is established, a current system state and a set control target are combined, an optimal control strategy is obtained through rolling optimization calculation, and a control instruction is sent by an execution mechanism based on the optimal control strategy; an execution mechanism; the touch display screen is connected with the control module; the operation parameters of the rectification system are displayed in real time.

The invention discloses a low-cost dual-drive self-calibration dust concentration on-line monitoring system and a monitoring method. According to the system, a dust concentration monitoring assembly comprises an oscillating balance dust continuous tester and a plurality of low-cost dust monitors; the coal mine information processing center is respectively connected with the oscillating balance dust continuous tester and the low-cost dust monitor; the visual client is connected with the central processor through a third communication module. The method comprises the following steps: carrying out on-line monitoring operation by utilizing multiple groups of dust concentration monitoring assemblies; performing self-calibration on dust concentration data of the low-cost dust monitor by using a physically-driven prediction model; performing secondary real-time calibration on the dust concentration data of the low-cost dust monitor by using a data-driven machine learning calibration model; and generating a mine whole area dust distribution cloud picture by using the mine whole area dust distribution cloud picture unit, and sending the mine whole area dust distribution cloud picture to the visual client for real-time display. According to the system and the method, high-precision monitoring of the dust concentration can be realized on the basis of greatly reducing the monitoring cost.

The invention provides a stroke patient gait walking analysis method and device. The stroke patient gait walking analysis method comprises the steps that pressure data and inertial data generated in the gait walking process of a patient are collected based on a plantar pressure sensing module and an inertial measurement module; performing data preprocessing on the pressure data and the inertial data; constructing a double-flow neural network to respectively extract pressure features and inertial features of the pressure data and the inertial data, performing feature fusion, and calculating step length, stride frequency, gait asymmetry index and gait stability index key indexes based on the fused features so as to realize gait evaluation; an evaluation result is transmitted to the flexible OLED touch screen, and gait parameters, rehabilitation progress, abnormal early warning and training guidance information are displayed in real time through the flexible OLED touch screen. According to the method, the end-to-end process from original sensor data to clinical application is realized, manual monitoring is avoided, the accuracy and clinical practicability of evaluation are improved, and the method is particularly suitable for family rehabilitation monitoring of stroke patients and precise rehabilitation evaluation of medical institutions.

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 testing and overhauling, in particular to a rotating machine equipment overhauling method and system based on the digital twinning technology, and the method comprises the steps: constructing a transformer substation three-dimensional virtual model which comprises a physical space, a virtual space and a digital service space; acquiring sensor data of a to-be-modeled object through a sensor assembly, processing the data, constructing a three-dimensional model, and filling the three-dimensional model into the virtual space; the physical space and the virtual space are mapped to the digital service space, the equipment operation state and fault positioning information are displayed in real time through the digital service space, overhaul suggestions are provided, the overhaul device is controlled by generating an overhaul instruction to overhaul the rotating machine equipment, and efficient monitoring and maintenance of the transformer substation equipment are achieved.

The invention provides an AR-assisted acupoint dynamic positioning method and system based on biological characteristics, and relates to the technical field of medical assistance, and the method comprises the steps: building a three-dimensional body model based on the body shape point cloud data, collected in real time, of a current user, and calculating the theoretical coordinates of acupoints in combination with a traditional Chinese medicine acupoint positioning rule; dynamically calibrating the theoretical coordinates on the basis of synchronously acquired body surface conductivity change characteristics and body surface temperature distribution characteristics of the to-be-acupunctured body area of the current user, and generating acupuncture point coordinates and corresponding needle inserting parameters; the acupuncture point coordinates are mapped to the body part of the current user, visual acupuncture point marks are displayed in real time through AR equipment, and operation guidance related to the needle inserting parameters is synchronously provided; when it is detected that the body position change of the user exceeds the preset threshold value, the above steps are executed again, and the acupoint coordinates and the operation guidance are updated, and through multi-modal biological feature fusion, dynamic calibration and AR visualization interaction, acupoint positioning is precise, dynamic and visualized.

The utility model relates to the technical field of belt conveyors, in particular to a movable high-precision intelligent belt constant feeder which comprises a conveying support, a conveying belt and a weighing assembly, the conveying belt is rotationally arranged on the conveying support, and the weighing assembly comprises a weighing roller, a weighing sensor, a speed sensor, a controller and a digital display dial plate. The weighing roller is arranged in the conveying belt and abuts against the conveying belt, the weighing sensor is connected with the weighing roller and the conveying support and used for outputting weight signals, the speed sensor is arranged in the conveying belt and used for outputting speed signals, and the controller is electrically connected with the weighing sensor, the speed sensor and the digital display dial plate. The controller responds to the weight signal and the speed signal and is used for controlling the digital display dial plate to display the weight value in real time. The bulk cargo transfer weight measuring device has the effect that the bulk cargo transfer weight can be accurately measured in the conveying process of the conveying belt.

The invention discloses an optical cable icing galloping online monitoring system based on a BOTDR, and belongs to the technical field of distributed optical fiber sensing. The system comprises an optical module, a signal processing module and a data processing module, the optical module is used for generating a detection light signal and interacting with a sensing optical fiber to obtain a Brillouin scattering signal, and then the Brillouin scattering signal is converted into an electric signal; the signal processing module is used for performing frequency down-conversion, signal filtering and digital acquisition on the electric signal to obtain multiple groups of Brillouin scattering signal data; the data processing module is used for processing the multiple groups of Brillouin scattering signal data and extracting a Brillouin frequency shift center frequency; temperature and strain distribution along the optical cable is obtained according to the frequency shift, and temperature and strain states are transmitted to a QT upper computer through PCIE for real-time display. According to the invention, high-precision and long-distance optical cable icing galloping monitoring can be realized, reliable early warning and safety guarantee are provided, and technical support is provided for maintenance and management of an electric power system.

The invention relates to the technical field of control systems, and discloses a self-adaptive control system and method for a five-axis numerical control machine tool, machining data and a machining program are controlled through a simulation interaction module, and the state and the machining data of the machine tool are displayed in real time through an interaction display strategy; the sensing monitoring module obtains machining data in the machining process in real time and transmits the machining data to the path judgment module and the simulation interaction module through a data transmission strategy. The path judgment module judges the machining path of the five-axis numerical control machine tool according to the machining data through a path generation strategy, so that the machining efficiency and quality are improved; the motion control module generates a motion control instruction of the five-axis numerical control machine tool according to the machining program and the machining path of the five-axis numerical control machine tool through an instruction generation strategy, accurately drives the five-axis numerical control machine tool to move, and ensures the machining precision; the safety monitoring module monitors the state of the machine tool in real time, and if the five-axis numerical control machine tool is abnormal, an abnormity processing strategy is executed.

The invention discloses a bridge disease detection system based on an unmanned aerial vehicle and a detection method thereof. The system comprises an unmanned aerial vehicle system and a ground station. The unmanned aerial vehicle system comprises a rotor power unit, a navigation control unit, a communication unit and an intelligent detection unit. The rotor power unit provides flight power, and the navigation control unit is responsible for environment sensing, positioning and three-dimensional point cloud model generation and guides the unmanned aerial vehicle system to stably fly along a preset route. The communication unit guarantees the real-time transmission of flight state information, environment information and video images between the unmanned aerial vehicle system and the ground station. The intelligent detection unit captures images of a bridge through a camera and a holder, and analyzes and recognizes the type, size and position of a disease in real time. And the ground station displays the flight state, environment information and route execution of the unmanned aerial vehicle system in real time, supports route planning and displays a disease identification result. The problem of how to inspect when the unmanned aerial vehicle is difficult to obtain effective GPS positioning information is solved.

The invention relates to the technical field of intelligent operation and maintenance management of an energy storage power station, and provides an energy storage power station efficient operation and maintenance management system fusing AI and the Internet of Things, and the system comprises an Internet of Things data collection module which is used for obtaining multi-source heterogeneous data of a battery pack, an inverter and an environment sensor in the energy storage power station in real time; the AI analysis module comprises an anomaly detection unit, a performance prediction unit and a scheduling decision unit which are respectively used for anomaly probability calculation, equipment performance degradation trend prediction and optimal charging and discharging strategy generation; the dynamic optimization control module receives an instruction of the scheduling decision-making unit and adjusts operation parameters of the energy storage power station through a dynamic load adjustment algorithm; and the visual interaction module integrates an equipment state three-dimensional mapping interface and an alarm pushing unit, and displays the decision result of the AI analysis module and the equipment health degree score in real time. The operation and maintenance management efficiency can be improved, the reliability and safety of equipment operation are enhanced, the operation and maintenance cost is reduced, and the service life of equipment is prolonged.

The invention discloses a fire extinguishing system and method for accurate positioning of thermal runaway of a container type energy storage power station. The fire extinguishing system is composed of an energy storage power station, battery packs distributed in an array mode and a fire extinguishing system body. Each battery pack is provided with a ventilation safety valve and a fire extinguishing device, a hydrogen sensor array covering the whole area is arranged on the plane of the energy storage power station, the ventilation safety valves guide out hydrogen generated in the initial stage of thermal runaway, and the sensor array monitors the concentration of the whole area in real time. The industrial personal computer receives sensor data, constructs a gas concentration distribution diagram by combining pre-stored battery pack space distribution information, and displays a thermal runaway area on the display screen in real time. The positioning program analyzes a hydrogen concentration field based on gas diffusion characteristics, and after the position of a fault battery pack is accurately recognized, the industrial personal computer immediately triggers the fire extinguishing device in the corresponding pack to implement fixed-point fire extinguishing, so that an early fire extinguishing closed loop is formed. According to the system, through multi-sensor data fusion and gas distribution mapping technologies, rapid positioning and accurate suppression of a thermal runaway source are achieved, and the safety protection level of an energy storage power station is effectively improved.

The invention discloses an intelligent pressure maintaining control method for a thin-wall product of an injection molding machine based on mold pressing feedback. The intelligent pressure maintaining control method comprises the following steps: (1) constructing a hardware layer; (2) configuring a software layer; (3) a mold cavity pressure acquisition module acquires original pressure data in the injection mold cavity in real time through a pressure sensor; (4) the data preprocessing module carries out filtering processing on pressure signals generated by the pressure data, and (5) the dynamic pressure maintaining control module dynamically adjusts pressure parameters and pressure maintaining time by receiving the real-time pressure data, product wall thickness parameters, mold structure parameters and injection molding process parameters, generates a pressure maintaining control instruction and sends the pressure maintaining control instruction to an injection molding machine control system; driving the injection molding machine to execute pressure maintaining action; (6) the dynamic pressure maintaining control module associates and stores the pressure change curve and the parameter adjustment record in the pressure maintaining process in a feedback learning module, and optimization calculation is carried out; and (7) the man-machine interaction interface displays the pressure change curve, the pressure maintaining control parameters and the forming state of the injection mold cavity in real time.

The invention discloses an underwater micropterus salmoides body length and mass measurement method, and relates to the technical field of aquaculture. Comprising the following steps: 1) target detection and key point detection: performing target detection and key point detection on underwater largemouth bass by using a YOLOv8 model to obtain key point coordinate information of a fish head and a fish tail; and 2) obtaining depth information: obtaining the depth information of the underwater image through a monocular depth estimation algorithm, and calculating the body length of the largemouth bass in combination with a key point detection result. And 3) mass estimation: based on the body length information, estimating the mass of the micropterus salmoides through a power function regression model. And 4) model deployment: deploying the model in a recirculating aquaculture monitoring system, and displaying and recording the body length and quality information of the micropterus salmoides in real time. According to the method, the body length and the body weight of the largemouth bass can be obtained in real time in a non-contact mode, the method is suitable for a factory-like circulating water culture mode, data support can be provided for culture management, and the practical value and the popularization prospect are high.

The invention discloses a new energy vehicle endurance display method and system based on a power battery SOH, electronic equipment and a vehicle. The method comprises the steps that a vehicle, a vehicle control unit, a battery management system and a display module are triggered to be started through a KL15 signal wake-up signal, and power-on initialization and self-inspection are executed; after the self-inspection is completed, reading the stored current state-of-health initial value SOH0 of the power battery and the stored current state-of-charge initial value SOC0 of the power battery from the EEPROM; performing dynamic correction on the read SOC value, performing fixed value locking on the SOH value, and sending the corrected SOC value and the locked SOH value to a CAN bus of the whole vehicle; based on the SOH0 and the SOC1 sent by the battery management system, the remaining endurance mileage S is calculated in combination with the total delivery mileage L of the new vehicle; and the instrument and large-screen display module is used for displaying the current remaining endurance mileage in real time. According to the method, the problem of display deviation caused by neglecting battery aging in a traditional method is solved, and the user driving experience and the battery management efficiency are improved.

The invention discloses a dust concentration online monitoring method and system based on individual movement trajectory tracking. The method comprises the following steps: collecting movement track data and environmental dust concentration data of an individual through a wearable device; moving track data and environment dust concentration real-time monitoring data are transmitted to a central processing system; analyzing and processing the moving track data and the environmental dust concentration data by using a central processing system, calculating the dust receiving amount of the individual in real time, predicting the dust receiving amount of the current ith individual at the nth space position corresponding to the nth target time node in the future, and outputting the dust receiving amount as a calculation result; a calculation result is transmitted to an online monitoring platform, and the individual dust receiving amount is displayed in real time; and when the individual dust receiving amount exceeds a preset threshold value, an early warning alarm processing operation is triggered. According to the monitoring method, the accuracy of occupational health protection and the foreseeability of exposure risk assessment early warning are improved, dual monitoring management measures of independent monitoring of workers and centralized and efficient management of employers are realized, and the intelligent level of dust hazard protection is improved.