119 results about "Radiometric data" patented technology

The invention discloses an intelligent earth surface solar radiation forecasting method based on satellite remote sensing, and belongs to the field of information technology and meteorological technology. The method comprises the following steps: S1, acquiring geostationary satellite observation data, satellite inversion earth surface solar radiation data and terrain factor data, and executing Z-score standardization processing; s2, performing dimensionality reduction on the standardized input sequence and the target data by using a pre-training auto-encoder to obtain latent variables of a historical sequence and a future cloud picture observation sequence; s3, inputting the dimension-reduced historical sequence into a conditional potential space diffusion model, modeling the historical satellite cloud picture sequence, and predicting a probabilistic potential variable of a cloud picture at a future moment; converting the solar radiation prediction result into a corresponding earth surface solar radiation prediction result through an inversion model; and S4, the self-encoder is adopted to perform dimension raising to obtain a final prediction result. According to the method, based on a frequency domain and space domain multi-modal feature adaptive fusion mechanism, while a complex cloud-radiation relation is modeled, predicted structural consistency and physical rationality of radiation intensity are kept.

The invention provides a multi-scale photovoltaic power prediction method and system fusing numerical weather forecast and a physical information neural network, relates to the technical field of photovoltaic power prediction, and realizes rolling prediction of future meteorological parameters and horizontal radiation intensity through numerical weather forecast. The authenticity and the stability of the meteorological data are effectively improved by combining quantile mapping and cascade correction of the time sequence mode attention neural network; and through combined modeling of a physical information neural network and a time sequence characteristic network, meteorological and radiation data subjected to multi-level correction and conversion are deeply fused with a photovoltaic system physical law, and high-precision prediction of photovoltaic power is realized. The whole prediction process has automatic anomaly elimination and deletion complementation capabilities, the prediction robustness under complex meteorological conditions and extreme environments is enhanced, and the sequential response and physical consistency of photovoltaic power are optimized, so that the engineering applicability and intelligent level of the system are greatly improved.

The invention provides a base station electromagnetic radiation visual monitoring method and device, and the method comprises the steps: determining a three-dimensional topographic map of a monitoring region, carrying out the electromagnetic radiation measurement of an actual geographic position corresponding to a preset collection point on the three-dimensional topographic map, and obtaining the actual measurement data; obtaining beam characteristic parameters of each base station and space coordinate data of the actual geographic position, and calculating predicted electromagnetic radiation data of the actual geographic position according to the electromagnetic radiation prediction model; correcting the model, and calculating electromagnetic radiation data of a target area on the three-dimensional topographic map based on actually measured electromagnetic radiation data and the corrected electromagnetic radiation prediction model; and visually displaying the actually measured electromagnetic radiation data of the preset acquisition point and the electromagnetic radiation data of the target area. Therefore, accurate monitoring and visual display of the electromagnetic radiation of the base station are realized, so that the accuracy and reliability of electromagnetic radiation evaluation are improved, and the overall change rule of the electromagnetic radiation value of each position in the whole monitoring area can be visually observed.

The invention discloses a broadband oscillation characterization platform of a multi-chip power module and a near-field characteristic evaluation method, and belongs to the technical field of power electronics. The continuous operation condition of the power converter is decoupled into a series of discrete switching points, transient near-field radiation data of a to-be-tested power module under the discrete switching points are obtained through a double-pulse test, and near-magnetic field radiation signals are reconstructed; performing time-frequency analysis on the reconstructed near magnetic field radiation signal to generate a two-dimensional time-frequency matrix; and calculating a radiation energy entropy value based on the two-dimensional time-frequency matrix, fusing the radiation energy entropy value with the peak amplitude in the two-dimensional time-frequency matrix to generate a comprehensive EMI index for evaluating the broadband oscillation electromagnetic interference risk, and triggering EMI risk early warning when the comprehensive EMI index exceeds a threshold value. According to the method, the spectrum complexity is quantified through the radiation energy entropy, the multi-dimensional EMI risk assessment is carried out by fusing the peak amplitude of the time-frequency matrix, and the broadband oscillation in the multi-chip parallel power module can be accurately and efficiently represented.

The invention discloses an earth surface downlink short-wave radiation space downscaling method based on a super-resolution reconstruction technology, belongs to the technical field of meteorological data analysis, and solves the problems of insufficient solar radiation data space resolution and weak earth surface heterogeneity characterization capability in the prior art. Carrying out super-resolution reconstruction on the radiation data set by adopting a super-resolution combination model, and carrying out weighted fusion on a reconstructed data set output by the super-resolution combination model; according to the method, the output results of the multiple models are subjected to weighted fusion, weight optimization of the super-resolution sub-models is performed in combination with the high-resolution terrain factors, spatial downscaling from 5km to 1km resolution is finally realized, the spatial precision of the solar radiation data is remarkably improved on the basis of keeping the hour-level time resolution of the original data, and the accuracy of the solar radiation data is improved. And more earth surface heterogeneity information can be captured, and meanwhile, the high-time-resolution application requirement is met.

The invention discloses a multi-target path planning method and device, equipment and a storage medium, and relates to the technical field of traffic path planning, and the method comprises the steps: obtaining solar radiation data and original map data, carrying out the multi-source data fusion based on the solar radiation data and the original map data, and obtaining the radiation road network data; based on the radiation road network data, a total cost function of the path length is constructed through an accumulated cost function of the path length and a heuristic function of the estimated cost, and candidate paths are generated according to the total cost function; on the basis of the radiation road network data, calculating the path average radiation intensity of the candidate path, and further obtaining the energy recovery amount of the candidate path; constructing a dual-target cost function based on the total cost function and the energy recovery amount, adjusting node priorities and screening and updating a non-dominated solution set according to the dual-target cost function, and generating a target candidate path set according to the non-dominated solution set; and determining an optimal balance path in the target candidate path set through multi-dimensional index quantitative evaluation and balance coefficient sorting.

The invention discloses an electric power intelligent monitoring system based on multi-device cooperative linkage and an operation and maintenance method, and belongs to the technical field of electric power intelligent monitoring and operation and maintenance. Radiation data and historical decay records are collected through a sensor, a linear regression algorithm is adopted to fit and establish an energy spectrum purity attenuation model, and the dose loss proportion is calculated in real time; carrying out dynamic compensation on beam intensity and irradiation time based on the proportion, fusing real-time dose monitoring data by utilizing a Kalman filtering algorithm, and optimizing a beam intensity value to suppress noise interference; the irradiation time is further adjusted according to whether the dose loss exceeds a threshold value or not, and a dynamic compensation combination is formed; the effectiveness of the combination in each stage of the source life cycle is verified through the simulation module, and the verified compensation parameters are updated to the control system in real time, so that closed-loop regulation and control are realized. According to the invention, the whole process of dose output in the irradiation process is accurately and stably controlled, and the consistency and reliability of the irradiation process are remarkably improved.

Lowest cost usage scheduling of an energy system during a time interval of interest is achieved by utilizing two components of learning and optimization. First, several learning methods are used to forecast energy production and if needed energy consumption of a given group of energy components as a function of historical production data, weather, and solar irradiance data collected from weather and geo reports. A classification approach is used to select the learning model. A classification approach is used to select the learning model and approach. Then, an optimization problem is formulated and solved to create the optimal schedule of energy usage during time intervals of interests for the given group of energy components subject to scheduling and equipment constraints. Accordingly, integrated iterative methods, programs, and systems are described aiming at minimizing the cost of energy consumption for the given group of energy components within time intervals of interest.

The invention relates to the technical field of quality control detection, in particular to a radiotherapy radiation amount detection device and method based on multi-sensor fusion, and the device comprises a data obtaining module which obtains the state information of the connection between a functional plug-in and a detection base, and a data processing module which obtains the state information of the connection between the functional plug-in and the detection base and obtains the state information of the connection between the functional plug-in and the detection base, determining first space attitude information of each functional plug-in relative to the detection base; the global space attitude determination module is used for determining global space attitude information of each functional plug-in in a radiotherapy coordinate system based on the first space attitude information and second space attitude information of the detection base; the multi-dimensional radiation data detection module is used for synchronously acquiring multi-dimensional radiation detection data from each functional plug-in based on global space attitude information in the process of executing radiotherapy irradiation; according to the invention, through combined sensing formed by the micro displacement sensor and the inertial measurement unit, real-time accurate measurement and dynamic compensation of the spatial attitude of each functional plug-in are realized.

According to the efficiency adaptation method applied to the solar communication unmanned aerial vehicle in the stratosphere, collaborative optimization of energy management and communication service of the solar unmanned aerial vehicle in the stratosphere environment is achieved by constructing a dynamic solar radiation database, predicting communication load and setting a dynamic threshold value and a multi-objective optimization mechanism. The method has the capability of responding to solar radiation fluctuation and communication load change in real time, effectively avoids the problems of misalignment of electric quantity management and interruption of a communication link, and remarkably improves the cruising ability and task reliability of the unmanned aerial vehicle. Meanwhile, according to the method, through a data-driven closed-loop optimization mechanism, the energy utilization efficiency and the communication quality are both considered, and the method has good practicability and popularization value.

The invention discloses a super-surface sub-terahertz inversion imaging method and system, and relates to the field of multi-dimensional electromagnetic imaging. The problems of view field mismatching, output delay, large-size imaging and the like existing in a directional aperture sharing TR framework of an existing APCI based on the metasurface are solved, synchronous extraction of sub-terahertz frequency band active scattering and passive radiation data is achieved through spatial staggered layout and related average processing technologies, and the system has the advantages that the system is simple in structure and convenient to operate, and the system is easy to popularize and use. And a solution is provided for single-region information decoupling and multi-target fusion imaging. The highly integrated and high-throughput sub-terahertz APCI technology promotes the development of the detection system towards the direction of miniaturized deployment and real-time data reading. Besides, a non-imaging security check scheme is also introduced, non-interactive autonomous identification and hidden monitoring of hidden objects in public scenes are realized, and the method is also suitable for the application fields of aircraft navigation positioning, abnormity monitoring, non-interactive hidden security check and the like.

Methods and computing apparatus for implementing a radiation dosimetry process. An example process may include exposing a first radiation sensitive film to a series of known doses of radiation, measuring a first set of radiation data with a measurement device, and determining a calibration curve. The calibration curve may be determined by selecting Raman spectral ranges based on the first set of radiation data, determining a plurality of band area ratios, and generating the calibration curve based on plotting the band areas and ratios compared to known dose. The radiation dosimetry process then exposes a second radiation sensitive film to an unknown dose of radiation, measures a second set of radiation data for the second radiation sensitive film with the measurement device, and determines a dose exposure level for the second radiation sensitive film by comparing the second set of radiation data with the calibration curve.

The invention discloses an offshore salt mist aerosol monitoring system and method based on a drifting buoy, and relates to the technical field of marine atmospheric environment monitoring, and the method comprises the steps: transmitting the position and time information received by a GNSS receiver to a main control module, and carrying out the resolving of the main control module, and obtaining a preliminary direction; transmitting the data of the attitude measuring instrument to the main control module; the main control module corrects the initial azimuth angle and the elevation angle according to the attitude data, and adjusts the accurate direction of the sun photometer according to the correction result; calculating the optical thickness of the aerosol according to radiation data measured by the sun photometer; the aerosol particle spectrum distribution is inversed according to the aerosol optical thickness; and the main control module performs information interaction on the inverted aerosol particle spectrum distribution and the land through the wireless communication module. The defects of a traditional mode are effectively overcome, and the optical parameters and the dynamic change process of the salt mist aerosol are captured more accurately.

The application discloses a kind of based on agent model's air bag template ice shell building weatherability optimization design method, it is related to building design technical field.The problems that existing technology lacks the quantitative evaluation index of ice shell building weatherability and lacks the construction of universal agent model are solved, including: S1 stage is established microclimate response agent model, through orthogonal experimental design to generate ice shell case set, extract morphological characteristics and spatial characteristics, obtain wind snow distribution label by combining CFD simulation, construct neural network agent model;S2 stage is fused multiple tools to realize performance optimization, utilize Grasshopper parametric modeling to extract features, call agent model to predict surface snow wind distribution, obtain radiation data jointly by Ladybug, combine sublimation rate to calculate initial and later strain energy and weatherability index, finally, morphological parameters are multi-objective optimized by NSGA-II algorithm, it has application prospect in the field of ice shell building structure optimization.

This invention relates to the fields of nuclear detection electronics and radiation signal processing technology, specifically to an intelligent analysis system and method for nuclear radiation data. The system includes: acquiring a discrete voltage sequence output by the detector; marking pulse signals as clean pulses and calculating the real-time decay constant; calculating the net signal amplitude using a digital twin state-space recursive model; determining the real-time count rate based on the net signal amplitude and calculating the dynamic time window width based on the real-time count rate; discretely accumulating the net signal amplitude based on the dynamic time window width to generate a single-particle physical energy value; determining the measured peak position based on the single-particle physical energy value and generating a gain adjustment coefficient by combining the measured peak position with the real-time decay constant; and outputting a gain control signal based on the gain adjustment coefficient. This invention ensures precise synchronization between the subsequent calculation model and the current physical state of the detector, thereby significantly improving the physical authenticity and accuracy of energy spectrum analysis under varying temperature conditions.

The application belongs to the field of cold region track engineering and subgrade engineering, and specifically discloses a high-speed rail ballastless track-subgrade freezing characteristic simulation test device based on meteorological conditions in cold regions, which comprises a programmable high-low temperature test box for controlling the alternating change of environmental temperature, a rainfall simulation device for adjusting according to different rainfall in cold regions, a solar radiation simulation device for adjusting according to different illumination in cold regions, a ballastless track structure composed of unit block type structure, a subgrade structure composed of three-layer structure, and a data acquisition and monitoring module for monitoring and collecting deformation displacement, temperature, moisture and radiation data in real time. Through the device, real-time monitoring of relevant parameters such as the temperature of the high-speed rail ballastless track, deformation, the temperature of the subgrade, moisture and deformation in cold regions can be realized, the freezing depth of the subgrade and the contribution of each soil layer in frost heaving deformation can be determined, and the influence of the ballastless track on the freezing characteristics of the subgrade can be further analyzed.

This invention relates to the field of radiation leakage detection technology, and discloses a radiation leakage detection method and apparatus based on a target sensor. The method includes: determining the current state of a radiation device, and acquiring a first set of radiation data of the radiation device in the current state based on the target sensor corresponding to the radiation device and according to the acquisition mode corresponding to the current state; determining whether the radiation device has experienced radiation leakage based on the first set of radiation data and a preset radiation threshold; when radiation leakage occurs, determining the radiation leakage level, and triggering a radiation leakage alarm based on the radiation leakage level. Therefore, this invention can achieve real-time leakage monitoring of radiation devices, adapt to the detection needs of different working states, accurately identify radiation leakage risks and quickly trigger alarm measures, effectively improve the active safety protection capability of radiation devices, and promptly ensure the radiation safety of operators and surrounding personnel, thereby improving the safety and stability of radiation device use.

The application discloses an ionizing radiation field simulation calibration system based on artificial intelligence and particularly relates to the field of simulation calibration, comprising a multi-source radiation data acquisition module, a data preprocessing module, an AI simulation calculation module, a real-time radiation field calibration execution module, and a multi-dimensional calibration result AI verification module; the application generates a standardized data set by collecting original radiation field data and performing outlier rejection, normalization and enhancement processing; a radiation field dynamic simulation model is constructed based on a deep learning model, and a three-dimensional space dose distribution simulation result is output in real time; a calibration parameter optimization model is constructed based on reinforcement learning, a calibration instruction is generated, and an execution mechanism is driven to perform real-time calibration; a multi-dimensional verification index system is constructed, a deep learning classification model based on an attention mechanism is used to intelligently verify the calibration result, and the calibration result is divided into three grades, namely, qualified, to-be-optimized and unqualified; for the result that does not pass the verification, an error traceability algorithm is started, and a correction suggestion is generated.

The application provides a surface crack temperature field determination method and system and electronic equipment, relates to the ground crack monitoring technical field, constructs a crack surface three-dimensional geometric model; according to the crack wind speed, determines the crack heat convection coefficient; according to the rock-soil conduction data and the rock-soil physics data, determines the rock-soil heat conduction amount; according to the solar radiation data, determines the solar radiation intensity; according to the crack surface three-dimensional geometric model, the crack heat convection coefficient, the rock-soil heat conduction amount and the solar radiation intensity, constructs a surface crack temperature field calculation model; according to the surface crack temperature field calculation model, determines the surface crack temperature field data in the target mining area. The application can complete the monitoring of the surface crack temperature field data in the target mining area by constructing the surface crack temperature field calculation model, provides data support for the unmanned aerial vehicle infrared monitoring equipment, and provides a basis for the surface crack evolution.

The application discloses a multi-target path planning method and device, equipment and a storage medium, and relates to the technical field of traffic path planning. The method comprises the following steps: acquiring solar radiation data and original map data, performing multi-source data fusion based on the solar radiation data and the original map data, and obtaining radiation road network data; constructing a total cost function of path length by using a cumulative cost function of path length and a heuristic function of estimated cost based on the radiation road network data, generating a candidate path according to the total cost function; calculating the average radiation intensity of the candidate path based on the radiation road network data, and then obtaining the energy recovery amount of the candidate path; constructing a double-target cost function based on the total cost function and the energy recovery amount, adjusting the node priority and screening and updating a non-dominated solution set according to the double-target cost function, generating a target candidate path set according to the non-dominated solution set; and determining an optimal balance path in the target candidate path set by using a multi-dimensional index quantitative evaluation and a balance coefficient sorting.

The utility model belongs to the technical field of meteorological monitoring, and relates to a solar radiation meteorological monitoring device, which comprises a support body; the sensor assembly is installed on the supporting body and used for detecting meteorological information of an area where the device is located, and the meteorological information comprises wind speed, wind direction, temperature, humidity, air pressure, noise, rainfall, illumination, air quality and sunlight irradiance; the first PLC is connected with the sensor assembly and used for storing meteorological information detected by the sensor assembly; the communication module is connected with the first PLC and an upper computer, and the first PLC transmits the meteorological information to the upper computer through the communication module; and the power supply module supplies power to the sensor assembly, the first PLC and the communication module. According to the utility model, basic indexes such as temperature, atmospheric pressure, humidity, wind and rainfall can be collected, solar radiation data can also be collected, and completeness and accuracy of meteorological information are improved.

A system includes at least one processor, and a memory that includes computer program code. The memory and the computer program code are configured to, with the at least one processor, cause the at least one processor to monitor a radio frequency (RF) spectrum within an area to detect RF emissions from RF emitters, acquire emission data of the detected RF emissions, process the acquired emission data to determine approximate locations of the RF emitters, and compile the determined approximate locations and acquired emission data into an RF landscape map of the area.

The application provides an industrial equipment electromagnetic radiation data prediction method and system, and relates to the technical field of equipment management. The method comprises the following steps: historical working condition data and radiation influence data of an industrial equipment are used to construct a preliminary prediction model, and the second prediction model is obtained by correcting the model according to the spatial relationship, electromagnetic compatibility and environmental data of adjacent equipment. According to the model, the electromagnetic radiation intensity of the equipment in the next cycle is predicted, and the corresponding processing strategy is executed according to the prediction result to ensure that the equipment operates within a safe range. The application aims to improve the problems of time and labor consumption and poor prediction of the existing method.

The invention discloses an environmental radiation data acquisition terminal, and relates to the technical field of environmental radiation monitoring, a core control board is independently designed based on an embedded system main control chip, the redundancy function of a traditional industrial personal computer is abandoned, data acquisition and uploading core tasks are focused, and the stability of an operation system is improved. Terminal software adopts a mode of'modular design + protocol library expansion ', in the application process of the environmental radiation data acquisition terminal, corresponding data acquisition modules can be configured for hardware interfaces according to actual needs, and corresponding data monitoring equipment models and communication protocols are configured for the data acquisition modules, so that flexible application under standardization is realized, and the data acquisition efficiency is improved. The production, debugging and maintenance cost is reduced; when the data monitoring equipment is newly added or replaced, compatibility can be realized only by upgrading the corresponding data acquisition module or updating the communication protocol library, the whole software architecture does not need to be modified, and the compatibility, the stability and the universality of the environmental radiation data acquisition terminal are improved.

A remote-sensing-based temporal net exchange estimation method of a farmland ecological system is provided. The remote-sensing-based temporal net exchange estimation method includes: obtaining low-resolution LAI remote-sensing images and high-resolution NDVI remote-sensing images during the transit of same day in a growth period of crops and constructing, associating and generating multi-temporal LAI data; in combination with daily temperature and surface solar radiation data, obtaining an LAI temporal result by simulation; comparing model simulation with remote-sensing data result and performing parameter sensitivity analysis and model uncertainty analysis to determine localized model parameters; inputting these localized parameters into the model, assimilating the high-resolution LAI result and outputting a spatial distribution temporal result of the net exchange of the farmland ecological system.

The invention discloses a remote sensing moisture index construction method combining surface temperature and short wave infrared information. The method comprises the following steps: step 1, collecting satellite remote sensing data in a research area; step 2, meteorological radiation data collection and spatial interpolation of a research area; 3, performing remote sensing inversion on the surface biophysical parameters; step 4, calculating surface net radiation and soil heat flux; step 5, constructing a remote sensing moisture index combined with the surface temperature and the short wave infrared information; and step 6, performing space-time reconstruction on the remote sensing moisture index. The remote sensing moisture index combining the surface temperature and the short-wave infrared information is constructed, the key defect that a traditional moisture index based on the surface temperature information is greatly influenced by albedo is overcome, and the supersaturation effect of the moisture index based on the short-wave infrared information in a high vegetation coverage area is optimized; satellite thermal infrared and short wave infrared observation information can be fully utilized, and large-range, data-area-free, complex and non-uniform underlying surface moisture index calculation is achieved.

The invention belongs to the technical field of power load prediction, and particularly discloses an urban power load prediction method and device, electronic equipment and a storage medium. The method comprises the following steps: dividing a regional map of a city to be measured into a regional map structure taking a plurality of regional nodes as a center according to a preset regional range; determining a target graph propagation matrix based on the Euclidean distance between each region node, the electrical topology information and other multi-source association information; determining target time sequence characteristic information based on power load data, meteorological and radiation data, personnel comprehensive power utilization activity information and photovoltaic power generation installed density of each region node in the recent historical time period; and inputting the target graph propagation matrix and the target time sequence feature information into a power load prediction model to obtain a power load prediction result of the to-be-detected city output by the power load prediction model. According to the invention, the precision and accuracy of urban power load prediction are greatly improved.

The present application provides a satellite remote sensing monitoring method for methane diffusion emission of eutrophic algal water bodies, obtains satellite remote sensing image data, photosynthetically active radiation data, ground temperature data and measured methane diffusion flux data of a research area; an estimation model of diffuse attenuation coefficient and chlorophyll a concentration is established by using the satellite remote sensing image data; a prediction model is established by using a random forest algorithm and precision verification is carried out by taking the combination of the diffuse attenuation coefficient, the chlorophyll a concentration, the photosynthetically active radiation data, the ground temperature data and / or different mathematical transformation forms thereof as independent variables and the measured methane diffusion flux data as a dependent variable, and the methane diffusion emission prediction model is established by selecting the independent variables with the best model precision for water body methane diffusion emission monitoring. The method of the present application can realize large-area, synchronous, accurate and continuous water body methane emission monitoring of the target water area.

The application discloses a radiation level monitoring method and system, an electronic device and a storage medium. The method comprises the following steps: collecting first radiation data through a preset radiation monitoring sensor; performing data dimension reduction processing on the first radiation data through a feature dimension reduction model to obtain second radiation data; the feature dimension reduction model comprises a boundary smoothing-based autoencoder; performing data augmentation on the second radiation data through a preset generative adversarial network model to obtain third radiation data; the preset generative adversarial network model comprises a quantum state-based generative adversarial network model; performing model training on a preset monitoring model through a federated learning architecture according to the third radiation data to obtain a target radiation monitoring model; inputting to-be-analyzed radiation data into the target radiation monitoring model for radiation level analysis to obtain a radiation level monitoring result. The embodiment of the application can effectively alleviate the data privacy risk problem and improve the accuracy of radiation level monitoring. The application can be widely applied to the technical field of monitoring.

The present application relates to a real-time monitoring method and system for radiation dose of a room where a staff member of a nuclear power plant works, comprising: after the staff member enters a control area of the nuclear power plant, a portable dosimeter acquires real-time radiation information of the staff member and real-time position information of the staff member; the portable dosimeter sends the real-time radiation information and the real-time position information to a background server; the background server receives the real-time radiation information and the real-time position information and triggers a calculation task; after triggering the calculation task, the background server calculates radiation data of the staff member in a current room according to the real-time radiation information and the real-time position information. The present application can refine the radiation condition of the staff member to a room level, provide more accurate and comprehensive dose information for radiation protection management, be more conducive to analyzing the radiation risk of the room, provide more powerful data support for formulating protection measures, and improve the safety of the staff member.