71results about How to "Make up for limitations" patented technology

The invention relates to the technical field of marine environment numerical simulation, in particular to a near-shore typhoon wave refined simulation method based on terrain adaptive grids and parameter dynamic correction, and the method comprises the steps: obtaining basic data and simulation parameters of a target sea area, constructing a computational domain and an initial grid, and constructing a target sea area; the initial grid is an unstructured grid fused with multiple physical constraint factors; performing optimization processing on the initial grid based on a numerical stability criterion to obtain a final calculation grid meeting a calculation convergence requirement; establishing a bidirectional coupling model, and applying the final computational grid to the bidirectional coupling model; carrying out localization iteration calibration on key physical parameters of the bidirectional coupling model to obtain an optimal parameter set; and carrying out typhoon wave process simulation calculation and constructing a typhoon wave feature database by utilizing the final calculation grid and the optimal parameter set, and realizing high-precision simulation and prediction of the typhoon wave process by constructing an adaptive optimization grid, a bidirectional coupling model and a parameter localization calibration mechanism.

The application discloses a vehicle seat occupancy detection method and system and a storage medium, and relates to the technical field of vehicle intelligent detection. The method comprises the following steps: in response to an opening operation of a target vehicle door, camera sensing data in a preset time period is acquired, wherein the camera sensing data is used to represent vital sign object information sensed by a surround-view camera of a target vehicle within a preset range of the target vehicle door; and based on the camera sensing data and seat pressure sensor data, the occupancy of a vehicle seat corresponding to the target vehicle door is determined, wherein the seat pressure sensor data is used to represent force information of the vehicle seat sensed by a seat pressure sensor of the target vehicle. The application solves the technical problem that the accuracy of vehicle seat occupancy detection in the related art is low, and thus the vehicle safety reminder function cannot be effectively triggered to ensure passenger safety.

This invention discloses a method and system for managing chat logs based on a storage network, relating to the field of log management technology. The method includes the following steps: S1, constructing an interaction matrix; S2, constructing an association matrix; S3, calculating participation; S4, outputting summary text; and S5, assessing risk coefficients. This invention effectively divides different chat logs by constructing an interaction matrix and marks chat logs within the same conversation segment. After the initial construction of the interaction matrix, to further conserve storage resources, the position values ​​in the matrix are optimized: if the logical correlation between two chat logs is weak, the value at the corresponding matrix position is reset to zero, thus avoiding redundant storage; while for strongly correlated log pairs, their position value is retained as 1. This design quantifies the connection strength between chat logs, thereby reflecting the closeness of the relationship between users.

This invention relates to the field of electronic digital data processing, and more particularly to a method and system for identifying the status of ventilation equipment in a smart laboratory. The method includes: real-time acquisition of the original vibration signals of each ventilation branch pipe of the ventilation equipment; denoising the original vibration signals to obtain the optimal reconstructed signal for each ventilation branch pipe; calculating the outlier value of the ventilation branch pipe using the optimal reconstructed signal; if the outlier value is greater than or equal to a preset threshold, the corresponding ventilation branch pipe is identified as abnormal; otherwise, it is identified as normal. This invention enables the obtained optimal reconstructed signal after denoising to be both clean and complete, improving the reliability and anti-interference capability of the overall status identification method.

The utility model discloses a three-dimensional coil structure which is applied to a multi-layer circuit board and comprises a three-dimensional coil unit, the three-dimensional coil unit is arranged on the side edge of a target device on the circuit board in a surrounding mode, the three-dimensional coil unit comprises horizontal wiring units and vertical through hole units, the horizontal wiring units are arranged on the top layer and the bottom layer of the circuit board, and the vertical through hole units are arranged on the top layer and the bottom layer of the circuit board. The horizontal wiring unit is used for forming a horizontal edge of the three-dimensional coil, and the vertical through hole unit penetrates through the circuit board, is connected with the horizontal wiring unit and is used for forming a vertical edge of the three-dimensional coil. The three-dimensional coil unit is arranged around the side edge of the target device, and the horizontal wiring unit and the vertical through hole unit are combined to form the three-dimensional coil structure, so that the coverage area of a magnetic field in the side edge area of the device is enlarged, and the limitation of a traditional planar coil structure is made up; the three-dimensional coil unit can form a complete magnetic field and a good filtering effect on the side edge of the device, and a planar coil magnetic field structure does not need to be reinforced by additionally adding components and a complex circuit structure.

This invention provides an enclosure experimental device and method for measuring carbon sequestration in shellfish and algae, comprising: a stabilizing component, an enclosure component, a collection component, and a collection device; the stabilizing component is fixed on a marine aquaculture area, and multiple enclosure components are arranged inside the stabilizing component, each enclosure component containing a collection component for collecting shed material from aquaculture organisms; the collection device is mounted on the stabilizing component, with its lower end positioned above the collection component, and its upper end connected to a monitoring instrument via an air tube, the monitoring instrument being configured to measure the CO2 content of the air above the collection device. This invention can simulate a real marine aquaculture environment, enabling better collection of biological shed material and gas data, and improving the accuracy and scientific rigor of carbon sequestration measurement.

The invention discloses a high-precision GNSS slope displacement monitoring system and method suitable for loess collapsibility characteristics, and the system comprises a GNSS monitoring module which comprises at least one monitoring point and a reference point; the monitoring point is welded and fixed on an existing protective steel pipe on site through the L-shaped mounting base; the data acquisition and transmission module is integrated in a waterproof box and comprises a data acquisition instrument, an MEMS sensor, a communication module and a power supply system which are electrically connected with the monitoring points; the cloud platform early warning center is used for receiving the data transmitted by the communication module and carrying out data fusion calculation and graded early warning; according to the invention, through data fusion of the GNSS and the MEMS sensor, limitation of a single technology is made up, and high-precision and continuous displacement monitoring under all-weather and all-working conditions is realized.

The invention discloses a reinforcement learning intelligent traffic signal control method and system based on state-driven retrieval enhancement. The method comprises the steps of collecting real-time traffic flow state information of a traffic environment and constructing a global traffic state vector, retrieving a knowledge base to obtain related knowledge fragments and performing weighted aggregation to obtain a comprehensive knowledge representation vector, and constructing a fusion decision model fusing retrieval enhancement and a Markov decision mechanism, training convergence of the strategy network is completed after the enhanced state vector is generated, traffic signal control is achieved based on the converged strategy network, the generalization adaptation capacity, the anti-interference capacity and the operation stability of the signal control strategy to various traffic scenes are improved, random fluctuation of traffic flow and sudden traffic conditions can be effectively coped with, and the traffic signal control method is suitable for being popularized and applied. Through knowledge retrieval and prior knowledge fusion, traceability and interpretability of a control decision are realized, the efficiency of traffic signal control is effectively improved, the occurrence rate of intersection traffic delay and congestion is reduced, and reliable support is provided for intelligent collaborative management and control of a road network.

The application discloses a kind of education resource sequence recommendation method, device and equipment based on three-view structure distillation and storage medium, the method includes: based on student-course interaction log, the learning sequence of time sequence course index is constructed, three types of view hypergraph are constructed according to semantic, path, concept structure multidimensional feature, three-view course representation matrix is generated by structure coding fusion, and the recommended list is output by inputting education resource recommendation model;Education resource recommendation model generates student state vector by the coding of Transformer, and the total course score is obtained by fusing three-view branch score and predicted;The present application predicts the education resource recommendation by three-view collaborative scoring from multiple perspectives, accurately captures course representation, effectively depicts learning path high-order law, improves the accuracy, explainability and generalization ability of education resource recommendation in sparse interaction and cold start scene.

The invention provides a tumor identification method based on multi-modal information cooperation, and relates to the technical field of tumor identification. The method comprises the following steps: firstly, constructing a multi-modal cooperative characterization unit, synchronously receiving medical image and electrical impedance time sequence data, cooperatively mining macroscopic morphological association features and microscopic difference features of a tumor by using a multi-domain coupling characterization space technology, and outputting a multi-modal cooperative feature vector; then, an electrical impedance time sequence analysis unit is built, electrical impedance signal deep correlation features are extracted through time sequence feature multi-order analysis, and electrical impedance deep feature vectors are output; then designing a dynamic feature adaptation fusion unit, performing adaptive fusion and dimension recombination on the multi-modal collaborative feature vector and the electrical impedance deep feature vector based on a feature responsivity adaptation technology, and outputting a stabilized fusion feature vector; and finally, constructing a feature correlation judgment engine, quantifying the feature contribution degree based on a structural causal model and a multi-layer correlation verification technology, and outputting a tumor diagnosis result. The problems of insufficient multi-modal feature collaboration and explanatory deviation caused by black box mapping in the prior art are effectively solved, and the accuracy and logic robustness of tumor recognition are improved.

The invention discloses a panoramic imaging method and device, equipment and a medium, and relates to the technical field of automatic driving, and the method comprises the steps: carrying out the projection transformation of an original image collected by a vehicle camera, and generating an aerial view; determining the size of an adaptive target window according to the distance from each pixel to a central pixel in the aerial view, and performing optical flow estimation on each pixel in two adjacent frames of aerial views in the size of the target window based on vehicle motion information measured by an inertial measurement unit to obtain a dense optical flow field; extracting inner points from the dense optical flow field by using a preset improved RANSAC algorithm, and estimating global motion parameters based on an extracted inner point set; fusing the global motion parameters and motion parameters measured by the inertial measurement unit and the positioning system by using a Kalman filtering method to obtain fused motion parameters; and projecting the historical panoramic image to an aerial view coordinate system by using a homography matrix calculated based on fusion motion parameters, and splicing the historical panoramic image with the current aerial view to generate a new panoramic image.

The invention discloses a bridge floor deformation prediction method under temperature influence of a highway-railway dual-purpose multi-tower cable-stayed bridge, which comprises the following steps of: based on a temperature gradient model of a bridge tower, establishing a longitudinal deformation model of the bridge tower at the most unfavorable temperature, and establishing a main beam deformation prediction model caused by deformation of the bridge tower; based on the temperature gradient model of the main beam, establishing a main beam deformation prediction model of the main beam at the most unfavorable temperature; establishing a main beam deformation prediction model of the stay cable at the most unfavorable temperature based on the most unfavorable temperature difference model among the stay cable, the tower and the beam; performing weighted combination on the three girder deformation prediction models according to the combination coefficient to obtain a bridge floor overall deformation prediction model; according to the scheme, the method for establishing the deformation of the bridge floor through the deformation of the main beam caused by the bridge tower, the deformation of the main beam and the deformation of the main beam caused by the stay cable is systematically provided, and reference is provided for simplifying and calculating the temperature effect borne by the same type of bridge structures.

The application relates to a bar code recognition method and device based on multi-engine fusion, which comprises the following steps: determining the priority order of multiple recognition engines according to the image features of a target image, wherein different recognition engines have different performances in recognizing bar codes, and the priority order matches the image features; performing bar code recognition on the target image according to the first recognition engine in the priority order; if the recognition result is a recognition failure, performing bar code recognition according to a preset multi-level retry strategy and the priority order until the bar code in the target image is recognized, wherein the multi-level retry strategy is used for progressively enhancing the image quality and switching the recognition engine to ensure that the bar code is recognized. The application improves the bar code recognition accuracy.

The application discloses a kind of multi-dimension feature extraction and fusion identification method and system for railway DAS signal, belong to railway safety monitoring technical field, including: synchronous acquisition railway along DAS data, train operation state data and environmental data and preprocessing;From time domain, frequency domain, time-frequency domain and time-space correlation domain extract multi-dimensional fault feature, form multi-dimensional feature set;Build multi-train history database, establish normal feature benchmark based on historical data and extract evolution trend characteristic parameter;Calculate the difference feature of real-time feature and normal feature benchmark, combine spatial correlation to filter abnormal features;Abnormal features are fused using a weighted fusion strategy, and a trained fault identification model is used to diagnose fault type, damage level and early risk index.The application improves the accuracy and robustness of fault identification through multi-dimensional feature fusion and multi-round verification, enabling early fault warning.

The present application belongs to the technical field of metallurgy and mineral processing suspension fluidization roasting, and particularly relates to a system and process for producing nickel by coal-based roasting reduction electric furnace smelting of laterite nickel ore. The system comprises a feeding drying unit, a preheating drying and crushing unit, a heat supply heating unit, a coal-based pre-reduction unit, an electric furnace smelting waste heat recovery unit, a dust removal, powder conveying and desulfurization unit, and the laterite nickel ore is processed by the "dry powder crushing, coal suspension roasting, coal-based pre-reduction, and ore-smelting electric furnace" technology. The present application has strong adaptability to raw materials, can produce high-value products from cheap resources, and adopts multiple energy-saving technologies in the new process to greatly reduce energy consumption and realize efficient use of energy. The present application makes up for the limitations and deficiencies of the traditional RKEF process, can reduce process energy consumption, improve resource recovery rate, provides a new innovative breakthrough direction for efficient utilization of laterite nickel ore resources for smelting nickel-iron alloy, and can greatly improve the economic value of the development and utilization of such resources.

This application relates to the field of intelligent healthcare, specifically to a method, device, and program product for predicting the risk of bladder cancer muscle invasion based on three-dimensional reconstruction. The method includes: S1, acquiring tumor imaging data from a cancer patient; S2, performing three-dimensional reconstruction using the tumor imaging data to obtain a three-dimensional tumor model; S3, identifying the absolute maximum distance between any two points on the three-dimensional tumor model in a three-dimensional coordinate system as the major axis; generating a major axis plane from the major axis, and calculating the maximum minor axis perpendicular to the major axis plane to obtain the minor axis; S4, calculating the ratio of the major axis to the minor axis to obtain the tumor's major-minor axis ratio; S5, predicting the risk of muscle invasion using the tumor's major-minor axis ratio to obtain the prediction result. This application predicts intermuscular invasion from multiple dimensions and has significant clinical value.

The invention relates to the technical field of leakage detection, in particular to a natural gas pipeline leakage detection method based on multi-modal data fusion, and the method comprises the steps: constructing a pipeline leakage simulation experiment platform, and obtaining a pipeline leakage image and text; splicing the image and the text to construct a data set; training an ELM-LPP model by using the data set, constructing a basic ELM model, optimizing an ELM model objective function by using an LPP algorithm, and introducing an adaptive feature weighting matrix, a combined graph regularization item and an F norm regularization item; and optimizing a hidden layer neuron weight vector and a hyper-parameter of the ELM model by taking minimization of an objective function as an objective. According to the invention, the problem of insufficient precision in detection of multi-modal data in the prior art is solved.

The present application relates to the technical field of nano-catalytic materials, and particularly relates to an amide platinum complex, a preparation method and application thereof. Compared with conventional precursors, the amide platinum complex provided by the present application has stable structure and unique coordination environment, the amide ligand can play a space steric hindrance effect and electronic induction effect to promote the reaction to proceed smoothly and effectively inhibit the platinum particle aggregation, the hydroxyl and iodine ligand can be used in coordination to realize mild pyrolysis, there is no impurity residue, and high specific surface area and high purity platinum dioxide can be prepared by only one step, which better makes up for the limitations of the existing precursors, and has extremely high industrialization and application value.

The invention provides a landslide area extraction method and device, electronic equipment and a storage medium, and belongs to the technical field of image data processing. The method comprises the following steps: respectively inputting a first remote sensing image of a time phase before occurrence of a landslide, a second remote sensing image of a time phase after occurrence of the landslide and a slope map into a first feature extraction network, a second feature extraction network and a third feature extraction network of a landslide extraction depth model, a first feature map, a second feature map and a third feature map which are correspondingly output are obtained; inputting the first feature map, the second feature map and the third feature map into a feature fusion module of a landslide extraction depth model to obtain a fused feature map output by the feature fusion module; and inputting the fused feature map into a decoder of the landslide extraction depth model to obtain a landslide extraction result output by the decoder. According to the method, the accuracy, robustness and efficiency of landslide automatic detection and mapping are improved, the slope map is introduced as a supplement of topographic information, and the identification capability of the model for the potential landslide area is enhanced.

This invention discloses a method for predicting the maneuvering motions of hydrogen fuel cell-powered ships based on multi-source data fusion, relating to the field of intelligent ship navigation. The method collects geodetic coordinate system position and heading data from the BeiDou Navigation Satellite System and ship hull coordinate system acceleration data from the Inertial Measurement Unit (IMU). After differential and integral preprocessing, a neural network model is built. A fusion-type loss function is constructed based on the transformation relationship between the ship hull coordinate system and the geodetic coordinate system. The model is trained using a backpropagation algorithm and can also be extended to fuse data from multiple sensors such as GPS. This invention fully leverages the complementary advantages of multiple sensor sources, effectively compensating for the inherent deficiencies of single-sensor data, significantly improving the accuracy and robustness of ship maneuvering motion prediction, and providing reliable technical support for intelligent navigation decision-making and safety assurance of hydrogen fuel cell-powered ships.

The application relates to the field of infrared thermal imaging denoising, in particular to an infrared thermal imaging denoising and imaging optimization method based on deep learning, which comprises the following steps: acquiring an infrared image in real time; determining a first noise coefficient for quantifying fixed pattern noise by analyzing the statistical characteristics and spatial fitting difference of an image block; determining a second noise coefficient for quantifying stripe noise by combining the polar coordinate energy spectrum distribution and the directional peak value trend; determining a dynamic noise index for quantifying random noise by combining the smooth difference and residual anomaly of noise coefficients between adjacent frames; determining a noise weight based on the three indexes, and optimizing a loss function to train a denoising model. The application solves the problem of insufficient denoising or excessive smoothing caused by unified processing of coupled noise, improves the precision of filtering complex coupled noise, and highly preserves infrared weak details.

The present application provides a kind of ghost imaging monitoring method and system based on environmental coupling simulation and image enhancement, the method comprises: setting initial light source, the initial light source is handled with splitter matrix model to obtain probe light path light source and reference light path light source, based on the probe light path light source and reference light path light source, respectively construct probe light path and reference light path;In probe light path, lens, object to be measured and bucket detector are set in sequence, and surface detector is set in reference light path, high gauss blur is introduced in probe light path to simulate heavy fog environment, and random phase screen based on Perlin noise is introduced to simulate turbulent environment.The present application builds ghost imaging system through Python, uses Gaussian simulation to simulate heavy fog environment and turbulent environment, and combines the concept of histogram equalization in digital image processing, the imaging quality of ghost imaging is optimized by non-linear mapping gray scale chart, and the imaging quality of ghost imaging system under long-distance condition can be improved.

The application discloses application of a GABAA alpha 6 receptor knockout substance and a combination drug thereof in preparation of a bladder cancer treatment product. The application provides application of a substance for knocking out a GABAA alpha 6 receptor gene and a macrophage inhibiting drug in preparation of a tumor treatment product. The application also provides application of the substance for knocking out the GABAA alpha 6 receptor gene and the macrophage inhibiting drug in preparation of a product for inhibiting tumor progression. The application explores the regulation of CD8+ T cell function by knocking out the GABAA alpha 6 receptor gene, verifies the application value of the GABAA alpha 6 receptor gene in bladder cancer treatment, and provides a new strategy for clinical treatment.

This invention discloses a method for identifying ecosystem function impairment based on soil moisture use efficiency, relating to the fields of ecological remote sensing monitoring and geographic information processing. The method includes: acquiring total primary productivity (TPP) data and soil moisture data; calculating the TPP of each spatial unit; determining the maximum TPP and defining the corresponding soil moisture content as the soil moisture threshold for ecosystem function impairment; using this threshold to divide samples from normal years and drought years; establishing a linear regression model and further extending it to identify data points below the soil moisture threshold in drought years; and estimating the decrease in TPP based on non-drought years when functional impairment is determined. This invention can effectively identify the critical conditions for the transition of an ecosystem from a normal state to a functionally impaired state, and achieve quantitative identification of ecosystem function impairment caused by extreme drought and estimation of TPP loss.

The application relates to the field of image acquisition, in particular to an image acquisition device suitable for urban drainage environment, which comprises an image acquisition module (1), a light supplement lamp (2), a body (3) and a support (4), the body (1) is internally fixedly installed with the image acquisition module (1) on one side, and a plurality of light supplement lamps (2) are arranged in a circular array with the image acquisition module (1) as the center, the end of the body (1) is fixedly installed with a sealing plate (5), and the sealing plate (5) is installed with a lens (6) capable of covering the projection range of the light supplement lamp (2) and the image acquisition module (1) in the middle. The image acquisition device can acquire image data at regular time intervals, transmit the collected data to a cloud platform in real time, can intuitively judge the real-time discharge condition of sewage, and make up for the limitation of the monitoring range of a traditional water quality sensor.

This invention relates to the field of printing defect detection technology, specifically a method for detecting printing defects in environmentally friendly art paper based on image recognition. The method includes: acquiring multispectral printing images of the environmentally friendly art paper sample to be tested, including images from three spectral channels: visible light, infrared reflection, and ultraviolet excitation; separating the printing area from the background substrate, extracting effective pixel regions, and constructing a benchmark library of printing defect features spanning the three spectral types; inputting the effective pixel regions into a pre-trained deep convolutional defect recognition network, performing multi-level feature matching with the benchmark library to generate preliminary defect recognition results; performing cross-spectral verification on the preliminary results, and confirming the final defects by combining the abnormal features of the three spectral types; marking the defect areas and generating a detection report. This method can improve the accuracy and comprehensiveness of printing defect detection on environmentally friendly art paper and is suitable for environmentally friendly art paper printing quality inspection scenarios.

This invention discloses a three-dimensional stereoscopic audio-visual composite detection system, device, and computer storage medium. The system includes a three-dimensional stereoscopic microphone array, a rotatable camera unit, a multi-channel signal acquisition and processing unit, and a multimodal data fusion processing module. The three-dimensional stereoscopic microphone array consists of six arms, with four horizontal arms arranged radially in a cross shape in the horizontal plane, and two vertical arms arranged side by side in the central vertical direction; each arm contains 48 microphones, forming a three-dimensional sampling grid, with an overall footprint of 213cm × 213cm and a height of 111cm. The rotatable camera unit is mounted at the top of the vertical arm and has a 360° horizontal and pitch-adjustable rotation capability. The multimodal data fusion processing module detects and identifies targets based on intelligent algorithms, and uses the Time Difference of Arrival (TDOA) algorithm to calculate the three-dimensional coordinates of the sound source, guiding the camera unit to perform visual verification, and realizing the fusion output of the target's three-dimensional coordinates and image information. This invention can achieve audio-visual composite detection of low-altitude targets, with high positioning accuracy, strong anti-interference ability, and good real-time performance, and is suitable for fields such as UAV detection, key area defense, and border monitoring.

The invention discloses a pharmaceutical composition for enhancing the killing power of CIK cells to tumor cells and application, and belongs to the technical field of biological medicine. The pharmaceutical composition is composed of a PD-1 monoclonal antibody and a protein phosphatase PP2A inhibitor, the PD-1 monoclonal antibody is Pembrolizumab, the protein phosphatase PP2A inhibitor is LB100, and the mass ratio of the PD-1 monoclonal antibody to the protein phosphatase PP2A inhibitor is (100-10): 1. Through combined use of the PD-1 monoclonal antibody and the protein phosphatase PP2A inhibitor LB100, by adjusting related signal channels in the CIK cells, immunosuppression of tumor cells on the CIK cells is relieved, the killing activity of the CIK cells on the tumor cells is remarkably improved, more powerful immune cell support is provided for tumor treatment, and good clinical application prospects are achieved.

The invention discloses a blood vessel structure and function coupling analysis method and system based on multi-mode MRI, and belongs to the field of medical image analysis and computational physiology. According to the method, 4D Flow MRI hemodynamic data and blood vessel spatial configuration features are fused, and the problem that in the prior art, structure and function analysis is split, and the coupling relation between the structure and the function cannot be revealed is solved. The method comprises the core steps of blood vessel image acquisition and preprocessing, structural feature extraction, functional parameter calculation, coupling analysis and result output, and the system correspondingly comprises functional modules. According to the method, automatic registration and collaborative analysis of structural-functional data are realized, comprehensive support can be provided for diagnosis of diseases such as liver cirrhosis and portal hypertension and TIPS surgical planning, and clinical prediction accuracy and diagnosis and treatment efficiency are improved.

The invention relates to an intelligent patrol method and system for a subway protection district, and the method comprises the steps: carrying out the preprocessing of a real-time image collected by an unmanned plane, carrying out the target detection of each frame of aerial photo in the preprocessed real-time image, and obtaining all target detection results; constructing an environment field corresponding to the moving target based on the bounding box of each moving target, performing environment feature extraction on the environment field, performing self feature extraction on each moving target, and combining the obtained self features with the target environment to generate final detection features; and matching the final detection features with known detection features in a database, carrying out duplicate removal on a target detection result according to a matching result, carrying out track prediction on the moving target, and generating alarm information according to an obtained track prediction result to give an alarm. Therefore, accurate duplicate removal and dynamic tracking of the moving target are realized, the accuracy and efficiency of patrol of the subway protection area are improved, and the safety of the subway protection area is improved.