520 results about "Detailed data" patented technology

The invention belongs to the technical field of computer data protection, and particularly relates to a computer data hierarchical protection method and a dynamic protection system. According to the method, the to-be-protected data is graded and scored, dynamic adjustment of the data protection grade is realized in combination with the dynamic risk of the computer network environment, and more detailed data grading is performed in combination with the semantic risk value by identifying sensitive information in the to-be-protected data, so that the pertinence and effectiveness of data protection are ensured, and the data protection efficiency is improved. Meanwhile, multiple risk parameters of the computer network environment are comprehensively considered, the security state of the network environment is reflected in real time through calculation of the dynamic risk score value, the data protection grade is intelligently adjusted according to the grading score and the dynamic risk score value, and dynamic optimization of the data protection strategy is achieved; and through fusion of historical behavior records and current session contexts of operators, fine management of access permissions is realized, and the security of data access is further enhanced.

The invention relates to the technical field of meteorological disaster early warning, in particular to a lightning disaster early warning system and method based on multi-source data, and the system comprises an atmospheric electric field monitoring module, an early warning strategy customization module, a risk area recognition module and a real-time early warning release module. According to the invention, through multi-source data integration and analysis and in combination with the regional electric field intensity and lightning frequency, the lightning activity intensity is accurately evaluated, the monitoring sensitivity and accuracy are significantly improved, and detailed data support is provided for intensity change, so that a more targeted early warning strategy is formulated; the safety level and the response requirement are optimized through frequency and intensity analysis, resource allocation is more reasonable, response time is more efficient, potential risk areas are further identified through path analysis, thunder and lightning conduction paths are refined, the risk areas are accurately calibrated, the early warning level is dynamically adjusted, it is ensured that early warning information has timeliness and space adaptability, and the early warning efficiency is improved. Powerful support is provided for power grid safety and lightning protection management, and the intelligent disaster prevention level is comprehensively improved.

The invention provides a food information tracing method and system based on Internet data, and relates to the technical field of industrial Internet, and the method comprises the following steps: generating an initial batch identifier of a to-be-produced product according to a product production plan, obtaining real-time external data of an associated region, and storing the real-time external data in a database; when it is judged that a batch adjustment event occurs in the production process of the to-be-produced product, based on real-time state data and real-time external data of a production line, dynamic batch decision is carried out to generate at least two sub-batch identifiers, and a tree-shaped association relationship is established between the sub-batch identifiers and the initial batch identifier; and receiving sub-batch detailed data of each sub-batch identifier, uploading the sub-batch detailed data to a block chain network, storing the batch topological relation in a block chain main chain, storing the sub-batch detailed data in a corresponding sub-chain node, responding to a tracing request of a user terminal, and according to the tree-shaped association relation, tracing the sub-batch data of each sub-batch identifier. And retrieving the full life cycle data of the corresponding target batch in the block chain network. The method overcomes the problem of tracing information splitting caused by batch splitting.

The invention relates to the technical field of laser calibration, in particular to a laser optical axis calibration device and method, and the device comprises an optical axis offset detection module, a calibration parameter calculation module, a dynamic adjustment implementation module and a calibration effect evaluation module. According to the invention, the response speed and precision are enhanced by monitoring the output of the laser emitter in real time, evaluating the instant deviation of the optical axis and dynamically calibrating the optical axis, the deviation trend of the optical axis is predicted by using a data analysis technology, the future deviation path is effectively controlled, and non-critical calibration is reduced, so that the long-term performance and stability of equipment are improved; dynamic adjustment measures are adopted, the positions of an angle adjuster and an optical element are finely adjusted, so that high calibration precision is ensured, energy loss and equipment abrasion are reduced, calibration effect evaluation of a vibration sensor provides immediate feedback for operation, transparency of the calibration process is improved, an operator can make a more accurate decision based on detailed data, and the operation efficiency is improved. Therefore, the reliability and the operation efficiency of the calibration task are enhanced.

The invention relates to the technical field of bridge maintenance, in particular to a beam bridge dynamic anti-seismic performance evaluation method and system, and the method comprises the steps: model preparation, model establishment, boundary condition and load application, analysis and calculation, and result analysis and evaluation. According to the method, through detailed data collection and model preparation, a detailed finite element model of the bridge is accurately constructed, actual characteristics of a main beam, a pier, a support and other key components are fully considered, boundary conditions are reasonably set, seismic loads are applied, calculation is performed by adopting a proper anti-seismic analysis method, and the seismic response of the bridge is effectively calculated; the method has the advantages that the method is simple, the anti-seismic performance of the bridge under the earthquake action is evaluated, potential weak parts of the bridge under the earthquake action are accurately identified, reliable basis is provided for formulating targeted anti-seismic reinforcement measures, and the efficiency and reliability of anti-seismic analysis and performance evaluation of the bridge structure are remarkably improved.

The invention discloses an intelligent optimization system based on a self-adaptive control hydraulic cylinder, and relates to the technical field of hydraulic cylinder control, and the system comprises a monitoring data collection module which collects data of a flow field, a temperature field and a stress field in real time by means of various sensors arranged at different parts of the hydraulic cylinder, synchronously carries out the preprocessing and coding of the collected data, and transmits the data to a data processing module; the data is transmitted to the data processing and analyzing module in real time; detailed data of the hydraulic cylinder in different physical fields are acquired in real time through the monitoring data acquisition module, and the coupling coefficient is accurately calculated by using the multi-physical field coupling model, so that the system can deeply understand the specific influence of each physical field on the performance of the hydraulic cylinder; according to the method, the system can construct a more accurate hydraulic cylinder dynamic model in the model prediction control module, so that the future state of the hydraulic cylinder is accurately predicted, further, the system can obtain an optimal control input sequence through an objective function optimization algorithm, and the pertinence and effectiveness of a control strategy are remarkably improved.

The invention particularly relates to a data analysis method and system. The method comprises the steps of extracting original data corresponding to a target service from a target data source according to a pre-configured data extraction strategy of the target service, loading the original data to an operation data storage layer of a data warehouse, and storing the original data; operating a data storage layer to output the original data to a detail data layer; the detailed data layer performs data preprocessing on the original data to obtain basic data and outputs the basic data to the summarized data layer; the summarizing data layer performs aggregation processing on the basic data according to a current data processing task corresponding to the target business, obtains structured data corresponding to the target business, and outputs the structured data to the application data service layer; and the application data service layer performs data analysis on the structured data according to the service configuration information corresponding to the current data processing task, and outputs a corresponding data analysis result. According to the scheme, efficient and accurate data management and analysis can be realized.

The invention relates to the technical field of optic nerve detection, in particular to a plastic particle quality detection method and system based on optic nerves, and the method comprises the following steps: capturing a plastic particle image through an industrial camera, carrying out the balance processing of the image contrast, extracting the brightness and color features of the image, and removing the noise interference; and adjusting the image brightness and optimizing the particle edge to obtain a particle optimization image. According to the invention, the accuracy and automation level of plastic particle quality detection are greatly enhanced by using the visual neural network and the image processing technology, and the edge and shape features of the particles can be accurately extracted from a complex background by automatically adjusting the image contrast and brightness and applying an advanced edge detection algorithm. According to the method, the visual quality of the image is optimized, tiny flaws such as cracks and bubbles of the particles can be effectively recognized and analyzed, and more detailed data support can be provided compared with a traditional method by accurately calculating the surface roughness and texture uniformity of the particles.

The invention relates to the technical field of industrial park intelligent monitoring, and particularly discloses a data acquisition and monitoring control method based on an intelligent industrial park, which comprises the following steps: acquiring key state data of equipment in real time, including operation time, operation temperature and operation power; an advanced signal processing algorithm is used for calculating an operation temperature abnormal index and an operation power abnormal index, the system can comprehensively evaluate the state of equipment and accurately judge whether slight or serious abnormal conditions exist or not based on detailed data analysis results, and the system can not only give out instant early warning notifications but also give out alarm information according to the serious abnormal conditions. According to the method, a machine learning model is adopted to predict the future operation state of the equipment, the equipment state abnormal coefficient in each future monitoring period is predicted based on the equipment state data in the current period, and classification and dynamic regulation and control of the equipment state are carried out according to a preset threshold value.

The invention provides an urban low-altitude unmanned aerial vehicle instant distribution scheduling and path planning method considering demand prediction. The method comprises the following steps: establishing a three-dimensional environment map of an unmanned aerial vehicle distribution system by adopting a grid-topology hybrid modeling strategy based on three-dimensional urban environment map data; according to the three-dimensional environment map of the unmanned aerial vehicle distribution system, the starting point and the target point of the unmanned aerial vehicle, the optimal flight path of the unmanned aerial vehicle, the time required by the optimal path and the transportation cost are obtained by using an unmanned aerial vehicle path planning algorithm of space-time improvement A *; and according to the order data, the unmanned aerial vehicle performance parameters, the optimal flight path of the unmanned aerial vehicle, the time required by the optimal path and the transportation cost, using the CNN-LSTM-Attention order prediction model and the task allocation model to output a task allocation scheme including a virtual order and an actual order. Accurate spatial data support is provided for path planning of the unmanned aerial vehicle, the reasonability of low-altitude logistics distribution path planning is improved, and finer data support is provided for urban airspace management.

The invention relates to the technical field of self-adaptive starting, and discloses a self-adaptive starting method and system based on voltage and current monitoring, and the method comprises the steps that an MCU (Microprogrammed Control Unit) triggers an auxiliary silicon controlled rectifier and a main silicon controlled rectifier through preset starting logic to start a motor, and carries out the high-frequency sampling of current and voltage data in real time; once starting failure is detected, short-time voltage sequences and short-time current sequences before and after a failure occurrence point can be automatically captured and stored. Then, key features are extracted from the sequences, and failure causes are determined through decision tree model analysis. And based on the analysis result and the current retry times, the MCU outputs a corresponding retry strategy to ensure that the motor can be successfully started or enter a safety mode. Thus, the reliability of motor starting is improved, subsequent fault diagnosis is supported through detailed data recording, and the maintainability and safety of the system are greatly improved.

The invention discloses a motor control method and system for underwater decontamination operation of an intelligent robot, and particularly relates to the field of underwater operation, comprising sensor deployment, data preprocessing, model analysis and motor control. According to the method, the key parameters of the underwater decontamination operation of the intelligent robot are comprehensively collected, fine data preprocessing and model analysis are carried out, accurate evaluation of the motor state is achieved, meanwhile, based on the evaluation result, the motor control instruction can be flexibly adjusted in real time, motor faults are effectively avoided, and the motor control efficiency is improved. In addition, the underwater sewage disposal system further provides detailed data recording and analyzing functions, powerful support is provided for subsequent system maintenance and optimization, and the efficiency and reliability of the underwater sewage disposal operation of the intelligent robot are remarkably improved.

The invention provides a medical aid decision-making method and device, relates to the field of intelligent medical treatment, and adopts three models with different capabilities to cover different plates of a whole inquiry process, thereby effectively reducing common illusion problems of a large model. The triage route is responsible for a special medical logic reasoning model, and it is ensured that the patient is accurately guided to the needed medical service. The multi-modal model is responsible for collecting the complaint information of the patient through an efficient voice interaction technology, meanwhile, effective communication and recording are carried out, and detailed data support is provided for follow-up diagnosis. The medical expert model realizes semantic alignment on medical data through special training, can deeply understand slight differences in expression of patients, and further improves the accuracy and efficiency of diagnosis and treatment.

The invention relates to the technical field of geographic information data, in particular to an ecological remote sensing data processing system which comprises a remote sensing layer acquisition module, a boundary position checking module, a region coding integration module, a spatial change splicing module and an ecological trend drawing module. According to the method, by accurately matching the geographic identification information and the spatial boundary value, the coverage range and the positioning precision of the ground feature pattern spots are remarkably improved, the time information and the spatial information are effectively integrated, the continuity and the accuracy of the data are enhanced, the boundary resetting technology effectively reduces the errors of the geographic information, and the time-space continuity of the data is improved; the processing efficiency is greatly improved by constructing a continuous layer structure and optimizing a data retrieval process, the fine boundary splicing technology also allows fine tracking of ecological changes, more detailed data support is provided for ecological monitoring, the ability of ecological trend analysis is enhanced, and thus the overall effect and application value of ecological monitoring are improved.

The invention relates to the technical field of dust monitoring, and discloses a dynamic monitoring system and method for dust distribution and diffusion, and the method comprises the steps: determining a monitoring region through a site positioning module, and configuring a ground monitoring site; the data acquisition module is used for acquiring numerical data of a ground monitoring station and integrating data of different dimensions; the data display module processes and displays the obtained numerical data and displays a trend curve of the analog data; the safety early warning module analyzes the numerical data, judges the standard exceeding condition of the numerical data, triggers early warning and extracts and displays radar data and meteorological data of the ground monitoring station when the numerical data of the ground monitoring station exceeds the standard, so that the response time to potential pollution events is shortened; detailed data of related monitoring stations are extracted in real time to assist in decision making; and the control execution module generates a spraying strategy according to the standard exceeding condition of the numerical data, and controls the spraying group to execute the spraying strategy. According to the invention, the resource use is optimized, and the purification efficiency is improved.

The present invention discloses a BMS battery remote monitoring and data analysis system based on a cloud platform, which relates to the technical field of remote monitoring and is used to solve the problems in the prior art that due to the lack of detailed data monitoring, it is impossible to deeply analyze the performance and loss of each part of the battery, thereby affecting the overall health assessment and management of the battery. Moreover, the battery state of the battery is usually a fixed and static value, ignoring the dynamic impact of the management frequency and power loss of different functional parts on the battery state; by combining the management frequency and power loss, the battery state of each functional part can be accurately allocated, the battery usage strategy can be optimized according to the actual situation of different modules, and unnecessary energy loss can be reduced. Unnecessary interference with the battery can be reduced. Through an automated monitoring and adjustment mechanism, manual intervention in battery management can be reduced, making battery management more intelligent and efficient.

The invention discloses a milling cutter service life management and control system based on a two-dimensional code, and relates to the technical field of machining. The cutter service life management and control center is in communication connection with a cutter service life management database, a binding end, an acquisition end, an unbinding end, a background data acquisition and analysis module, a cutter service life early warning module and a wear detection and service life correction module, and all the modules are in electric signal connection; and the tool life management database is used for storing related data of tools, including unique identification codes, initial residual life, use time, manufacturers, quantity and model data. According to the tool management system and method, the tools are managed in the whole life cycle, detailed data records are recorded in each link from warehousing, ex-warehouse, use to scrapping of the tools, enterprises can better master the use conditions of the tools, data support can be provided for purchasing, storage and the like of the tools, and the tool management process is further optimized.

The invention discloses a mine car driving state safety detection method and device, and relates to the technical field of mine car safety detection. A 3D map of a mining area is constructed, roads in the mining area are segmented, quantitative evaluation is obtained according to detailed data collection and analysis, and road state values of all road sections are obtained; by extracting key parameters in tramcar driving information and calculating a driving state value and a driving index, the driving state of the tramcar can be monitored in real time, abnormal conditions can be found in time, the driving safety of the tramcar can be evaluated more comprehensively, and data support is provided for subsequent driving path and speed optimization; a plurality of paths are generated based on a Dijkstra algorithm, the influence of the road surface condition of a road section on a mine car is reduced by calculating a congestion value, an adaptation index and a planning value, the driving safety of the mine car in a mine area is ensured, and the driving path and speed of the mine car are dynamically adjusted according to the driving index and the road state value of the mine car.

The present invention belongs to the field of wireless charging technology, and specifically relates to a vehicle-mounted wireless charging control system and method based on CAN communication. The present invention effectively solves the balance problem between charging efficiency and electromagnetic compatibility by real-time monitoring of environmental electromagnetic signals and dynamically adjusting charging frequency and other parameters. At the same time, the system periodically updates the device status and electromagnetic environment data during the charging process to ensure that the charging parameters are always in the optimal configuration. In addition, after charging is completed, the system will organize and store all relevant data to provide detailed data support for future charging optimization. These improvements not only improve charging efficiency, but also significantly enhance the system's anti-interference ability, thereby providing a safer and more efficient vehicle-mounted wireless charging experience.

The invention relates to the technical field of industrial sewage treatment, in particular to an industrial sewage treatment method and system based on big data, and the method comprises the following steps: collecting sewage samples discharged from multiple industrial sources, obtaining chemical component data, carrying out the initialization arrangement of the types and contents of recoverable resources in the samples, and forming a resource feature list. According to the method, through detailed data analysis and implementation of an optimization process, the extraction efficiency and quality of recoverable resources in industrial sewage are remarkably improved, a sewage sample is collected from an industrial source and subjected to chemical component analysis, data support is provided for a subsequent resource recovery strategy, resource classification and recovery are more accurate, and the resource recovery efficiency is improved. The recovery priority is determined by constructing an economic evaluation model, the environmental benefits and the economic benefits are effectively integrated, the intelligent degree of industrial sewage treatment is enhanced, and the resource recovery efficiency and quality are remarkably improved through a real-time adjustment mechanism.

The invention relates to the technical field of calibration cooperation, in particular to an intelligent service system for calibration cooperation, which comprises a judicial file analysis module, a decision optimization module, a document logic verification module and a logic defect correction module. According to the method, efficient extraction of key information in judicial documents and accurate evaluation of case complexity are realized by combining text structured processing and fuzzy logic, and the processing strategy can quickly adjust a decision support direction based on detailed data analysis, so that the decision process better meets the actual requirements of cases, and the accuracy of the decision process is improved. The application of dynamic update data optimizes decision suggestions, improves the real-time performance and pertinence of decisions, significantly reduces judicial errors, accelerates the judgment process, guarantees the accuracy of judicial documents through automatic logic verification and error correction, effectively avoids errors caused by manual omission, and improves the accuracy of the judicial documents. And the judicial processing speed and accuracy are improved.

The invention discloses an intelligent data monitoring system and method based on an ultrasonic water meter, and the method comprises the steps: determining a data grading label through the comparison between the vibration features of the vibration data of an ultrasonic sensor in a preset time period and a recent historical feature baseline; therefore, the system can intelligently identify the abnormal degree of the current running state of the water meter. Furthermore, based on the data grading label, a data transmission strategy and a data compression strategy for the original vibration signal are specified, so that the data transmission and storage efficiency is optimized to the greatest extent on the premise of ensuring that key information is not lost. The self-adaptive strategy not only solves the problem of low data transmission and storage efficiency in a traditional scheme, but also ensures that enough detailed data can be obtained at a critical moment, and resources can be efficiently utilized during conventional operation, so that the optimal balance between data integrity and accuracy and transmission and storage cost is realized.

The invention is suitable for the technical field of photovoltaic operation and maintenance, and particularly relates to a distributed photovoltaic power station operation and maintenance method and equipment, and the method comprises the steps: obtaining image data and operation data of a distributed photovoltaic power station, and providing a detailed data basis for subsequent analysis; according to the image data of the distributed photovoltaic power station, the first operation and maintenance parameter of the distributed photovoltaic power station is determined, and the physical anomaly of the photovoltaic module is identified by evaluating the abnormal condition in the image data; according to the operation data of the distributed photovoltaic power station, second operation and maintenance parameters of the distributed photovoltaic power station are determined, and the problem of electrical performance or thermal performance is detected by evaluating an abnormal mode in the operation data; based on the first operation and maintenance parameter and the second operation and maintenance parameter of the distributed photovoltaic power station, operation and maintenance management is carried out on the distributed photovoltaic power station, the operation and maintenance management level of the photovoltaic power station is improved, the operation and maintenance efficiency and accuracy are enhanced, and potential problems can be found and solved in time.

The embodiment of the invention discloses a test sample information updating method, device and equipment based on multi-dimensional data. A specific embodiment of the method comprises the following steps: obtaining a test sample detailed data list of each piece of test sample information in a test sample information list to generate a test sample detailed data list, and obtaining a test sample detailed data list set; generating a test sample information state list set according to the list access frequency set; in response to determining that the test sample information state representing the abnormal state exists in the test sample information state list set, performing abnormal operation processing on at least one piece of test sample information representing the abnormal state to generate a processed test sample information set; and updating the processed test sample information set to the test sample storage equipment. According to the embodiment, leakage of test sample information is avoided, and the integrity and safety of the test sample information are improved.

The invention relates to the technical field of wind power energy storage, and discloses a collaborative peak regulation method and system based on a wind power energy storage system, and the method comprises the steps: collecting the detail data and SCADA data of a power generation fan, carrying out the time sequence alignment, constructing a prediction error model, calculating a standardized prediction error, constructing a hybrid prediction model, and dynamically adjusting the model parameters; a time-function double-layer decomposition strategy is constructed to calculate an energy storage attenuation value, a multi-objective optimization model is constructed in combination with the energy storage attenuation value, cross-day balance is carried out, and a charging and discharging strategy is optimized; constructing a three-channel reward function, dynamically adjusting the weight coefficient of the reward function, and automatically adjusting the weight according to the real-time state of the power grid to realize multi-target dynamic balance; the method comprises the following steps: constructing a hybrid hierarchical control execution framework, optimizing an edge layer, obtaining a wind power fluctuation rate, judging whether to trigger super capacitor pre-charging, performing model prediction control MPC optimization, realizing credible synchronization of energy storage SOC data in combination with an intelligent contract, and performing health state early warning.

The invention relates to the technical field of logistics fee settlement, in particular to a fund account payment auditing method and device, equipment and a storage medium. The fund account payment auditing method comprises the following steps of obtaining a bill and verification detail data, and judging whether the bill needs to be rejected or not according to the verification detail data so as to obtain a judgment result; if the judgment result is that rejection is not needed, outputting the judgment result that rejection is not needed to obtain a payment instruction; acquiring account balance data according to the payment instruction, and verifying the account balance data according to the verification detail data to obtain a verification result; and if the verification is passed, executing a payment instruction according to a verification passing result to obtain payment success information, and generating applicable invoice information according to the payment success information. According to the fund account payment auditing method, the commission settlement efficiency of the courier can be effectively improved, and the occurrence of artificial auditing errors can be effectively reduced.

The invention provides a packaging box ink printing friction-resistant decoloring test device based on a physical sensor, and relates to the technical field of friction-resistant decoloring tests.The packaging box ink printing friction-resistant decoloring test device comprises a rack, an electric sliding rail and a limiting sliding rail are installed on the inner surface of the rack, and a sliding seat is slidably connected to the outer surface of the electric sliding rail; according to the device, friction force can be applied to an ink layer from different directions and angles through curve friction, the adhesive force between ink and a packaging box can be more comprehensively detected, meanwhile, through arrangement of a first pressure sensor, the adhesive force between the ink layer and the packaging box can be accurately detected, and the detection precision is improved. The pressure borne by the paperboard can be accurately detected, the friction resistance performance of the printing ink on the surface of the paperboard is recorded under different pressure conditions under the condition of curve friction, detailed data support is provided for studying the wear resistance effect of the printing ink in different pressure environments, and more reliable guarantee is provided for the quality and durability of products.

The invention relates to the technical field of frequency converter detection, in particular to a quality test board for frequency converter production and processing and a test method, an interface management module automatically identifies and manages interface connection, the problem of inaccurate data caused by misplug or misconnection is avoided, and the test safety is enhanced at the same time. The test execution module covers multiple aspects of performance test, protection function test, communication test, load simulation test and the like. The data acquisition module acquires key parameters in real time and provides detailed data support for subsequent analysis. And the data analysis module quickly identifies abnormal conditions and generates a test report through preprocessing, anomaly detection and performance evaluation. The fault diagnosis module can quickly identify fault types, accurately position fault positions, provide repair suggestions and shorten maintenance time. Therefore, the problem of inaccurate detection data of the frequency converter caused by misplug or misconnection when a tester repeatedly executes interface plugging operation is solved.

A communication self-inspection and emergency shutdown method for an offshore wind turbine generator comprises the following steps: acquiring heartbeat signal data between a fan main control unit and a looped network, analyzing frequency and intensity, and judging whether a signal is normal or not; if the signal intensity is low, the interference detection module is started to identify external interference or equipment faults, and a communication interruption timer is started accordingly. And once the communication interruption exceeds the preset duration, a fault is judged and a confirmation mechanism is triggered, and after the fault is confirmed, the main control unit sends an emergency shutdown instruction. And after shutdown, acquiring running state data of the fan to judge whether the fan is completely stopped, recording shutdown time and state change, generating a fault report covering fault types, interruption, shutdown time and fan state change, and uploading the fault report to a looped network monitoring system. According to the method, accurate self-inspection of the communication state of the offshore wind turbine generator is achieved, faults can be found in time, emergency shutdown measures can be taken, detailed data are provided for operation and maintenance personnel, and safe and stable operation of the wind turbine generator is guaranteed.

The invention relates to a soil state monitoring method and system based on a sensor network, and the method comprises the steps: reasonably arranging a plurality of sensor nodes in a target soil region to form a sensor network, and comprehensively and precisely collecting soil attribute data corresponding to each node in different time periods; and the original monitoring data set can reflect the soil state in all directions. According to the method, detailed data preprocessing is carried out on an original monitoring data set, abnormal data is cleaned, error information possibly interfering analysis is effectively removed, soil attribute data of different dimensions are normalized, and a uniform and accurate data basis is provided for subsequent processing. A fusion state feature set is generated through feature fusion processing, and the soil state can be deeply described from multiple dimensions. And determining a soil state category label according to the fusion state feature set, and generating an optimization strategy to be fed back to the monitoring terminal, so that the soil state can be accurately grasped, the strategy can be dynamically adjusted, and the accuracy and reliability of soil state monitoring can be improved.