179 results about "Digital Archives" patented technology

The invention relates to the technical field of digital management, in particular to an offshore platform component processing full life cycle quality tracing system which comprises a component unique identification code generation module, a multi-source processing data acquisition module, a quality judgment and tracing code association module, a holographic digital archive construction module and a three-dimensional visual tracing module. Wherein the component unique identification code generation module is used for generating a unique identification code; the multi-source processing data acquisition module is used for acquiring processing process data associated with the unique identification code of the component in real time; the quality judgment and traceability code association module is used for generating a quality judgment result based on a preset quality rule base; and the holographic digital archive construction module is used for generating a full-life-cycle data chain of the component. According to the method, the whole life cycle data chain with the unique traceability code as the index is constructed and mapped to the BIM model, and structural management and space-time visual traceability of the quality information of the offshore platform component are achieved.

The invention discloses an archive digitization full-life-cycle encryption integrity verification method and system, relates to the field of digital archive safety management, and is used for solving the problem of integrity and safety guarantee in archive digitization management. Logic units are divided through a semantic analysis engine, non-uniform blocks are generated based on sensitivity dynamic partitioning, local hash values are calculated, and a multi-level verification tree is constructed to generate root hash and a hash path mapping table; acquiring visitor identities, terminal environments and timestamps in each stage of an archive life cycle, generating state snapshots in combination with a hash path, and constructing a life cycle state snapshot chain; reconstructing a target logic unit verification path according to the access request, analyzing the structural difference between a current path and a historical snapshot chain through a path reconstruction type difference verification algorithm, and identifying structural offset, node tampering or path loss; and response control is triggered for abnormal verification, including session key updating and permission freezing, so that the security integrity guarantee of the digital archive in the full life cycle is improved.

The invention relates to the technical field of bridge engineering construction, in particular to a bridge deck concrete flatness detection and correction method, which comprises the following steps: synchronously acquiring bridge deck point cloud, elevation and crack data through a three-dimensional laser scanner, a laser profiler and an ultrasonic sensor, and fusing to generate a three-dimensional digital model; defects such as local protrusions and wave deformation are recognized based on an intelligent analysis algorithm, causes are analyzed, and correction process parameters such as milling, cladding, grouting or ultrathin layer pouring are generated in a targeted mode; operation is executed through equipment such as a finish milling machine, closed-loop control is realized by combining real-time monitoring of a laser profiler, and finally, a traceable digital file is formed through laser detection, inspection and acceptance of an unmanned aerial vehicle and data archiving. By means of the method, the pass percent of the flatness of the bridge floor can be increased to 94% or above, the maximum height difference is controlled within 3 mm, the maintenance period of the bridge is prolonged, and the maintenance cost is reduced.

The invention relates to the technical field of cold-chain commodity transportation, in particular to a temperature monitoring and control method in a cold-chain commodity transportation process, which comprises the following steps: acquiring real-time temperature data, and generating a thermal response digital file of a cold-chain commodity according to the real-time temperature data and a cold-chain commodity category database; real-time positions and external air temperature data of the cold chain commodities are collected, and a temperature threshold value of the next time period is predicted according to the heat capacity characteristic parameters reflected by the thermal response digital archive; a three-dimensional temperature field distribution diagram is constructed based on the temperature threshold value of the next time period and the vibration data of the compartment where the cold-chain commodities are located; generating a control instruction according to the coordinates of the temperature anomaly region in the three-dimensional temperature field distribution diagram; after the control weight coefficient is calculated according to the control instruction and the preset energy consumption optimization objective function, the temperature control operation is executed according to the control weight coefficient and the control instruction, and balance temperature monitoring and control and energy consumption optimization are effectively achieved.

The invention discloses a digital archive online management system based on big data. The digital archive online management system comprises a digital acquisition layer which is used for carrying out semantic perception and structured extraction on heterogeneous archives; and the intelligent classification layer is used for mapping the collected archive entities, attributes and relationships to a dynamically expanded domain knowledge graph based on a knowledge graph construction technology and a graph neural network, realizing association mining and dynamic classification of cross-modal archives through node embedding and link prediction, adapting to evolution requirements of archive themes in combination with a weak supervised learning mechanism, and realizing dynamic classification of the cross-modal archives. A classification system with causal interpretation is formed; the storage retrieval layer is used for encoding the generation time, the space trajectory and the event causal chain of the archive into space-time causal metadata; the archive utilization layer is used for actively pushing associated archives and generating a personalized analysis report by analyzing user behavior preferences and scene requirements; and the backup layer is used for dynamically sensing the threat type and calling an evolutionary algorithm to adjust the backup frequency, the storage position and the recovery path.

The invention discloses a digital archive supervision system based on a block chain, and relates to the field of digital archive supervision. The system comprises an archive collection module, a block chain pre-processing module, a dynamic consensus module, an intelligent contract module and a supervision module. The archive collection module preprocesses heterogeneous data through a CRNN algorithm to generate a standard data set; the pre-processing module adopts the combination of SM4 and homomorphic encryption to protect data; the dynamic consensus module dynamically adjusts the right based on the node credit score, the main chain uses a PBFT method enhanced by a threshold signature to ensure the safety of core operation, and the side chain uses DPoS-RAFT to process high-frequency business; the intelligent contract module constructs a Merkle tree through block hash, and performs automatic hash verification and triggers exception handling during access; the supervision module realizes layered examination and approval of the unfreezing application by using a decision tree algorithm; according to the system, through cooperation of multiple modules, full-process block chaining of archives from collection, encryption, consensus to supervision is achieved, and the system is suitable for credible storage and supervision scenes of digital archives.

The invention discloses a digital archive multi-protection-based data security transmission method, and relates to the field of data security transmission, and the method comprises the steps: generating a random seed in real time based on a quantum state, carrying out the iterative blocking of the quantum seed through combining with Logistic chaotic mapping, outputting variable-length secret key fragmentation, carrying out the symmetric encryption of archive data through employing a lightweight SM4 algorithm, and carrying out the encryption of the archive data. Obtaining encrypted data of the fragments; a behavior anomaly probability is calculated through a hidden Markov model, a risk score is calculated through a safety interval, and when a score value exceeds a safety threshold value, a grading response is triggered; key fragments are generated by adopting n nodes, at least k fragments can reconstruct signatures to monitor the node state of the block chain, and when the node anomaly rate exceeds a node threshold value, a three-layer architecture is automatically switched. The method has the advantages that an active multi-protection system is constructed through a quantum dynamic key, risk-driven hierarchical response and block chain disaster recovery switching, and quantum attack resistance and dynamic adaptation to transmission of network risks are realized.

The invention relates to a digital archive intelligent processing method, a storage medium and a system, which are suitable for multi-source heterogeneous archive management scenes such as colleges and universities. The method comprises the following steps of: classifying structured and unstructured data such as paper archive scanning pieces and database views, and extracting metadata and entity information by adopting a scanning and OCR (Optical Character Recognition) technology; a complex table and document content are analyzed through a model, semantic analysis (entity recognition, relation extraction and event abstract) is achieved in combination with a language model of a Transform architecture, and a structured report containing a data abstract, an entity relation graph and abnormal annotations is generated. The system is internally provided with a parameter template automatic generation module, supports cross-page content continuous restoration and sensitive data encryption desensitization, and realizes safe sharing through an API interface. The method solves the problems of low efficiency, difficulty in multi-source data fusion and the like of traditional archive processing, improves the automation level and data value mining capability of archive management, and is suitable for intelligent upgrading of complex archive scenes.

The invention discloses a traditional Chinese medicine decoction piece production data management method and system based on quality tracing, and relates to the technical field of production data management. According to the invention, a unique tracing identification code is generated for warehousing traditional Chinese medicine raw materials, and information is bound to create a digital file; in the production process, data and quality data of all procedures are collected in real time by scanning the identification codes, and a dynamic production digital file is formed; an improved TCN neural network is trained to construct a quality prediction model, and the model can accurately predict product quality by introducing optimization such as a process perception attention mechanism and parallel branches; performing real-time quality evaluation and process adjustment by using the model in production; key process data is stored through a block chain, and a traceability code is provided on a finished product package for visual query; data communication and credible tracing of a whole production chain are achieved, quality control is converted into active prediction and intervention from passive inspection, and the quality stability and management efficiency of the traditional Chinese medicine decoction pieces are remarkably improved.

The invention discloses a BIM-based building construction monitoring method, and the method comprises the steps: arranging a data collection device at a construction site, and obtaining multi-source data, such as structural members, construction machinery, spatial positions of operators, construction states, safety indexes and environmental parameters; automatically mapping multi-source data to a BIM three-dimensional model through an adaptive coordinate transformation and semantic recognition algorithm, matching the multi-source data with construction plan nodes, and generating a BIM construction state model reflecting a field state in real time; the system automatically compares the model with a construction plan model, identifies a state and calculates deviations such as progress, position, size, quality and safety; the method comprises the following steps: displaying deviation parts and potential safety hazards in a BIM interface in a highlight manner, superposing rectification suggestions, issuing a construction adjustment instruction confirmed by a manager to a field terminal, and storing monitoring, comparison, early warning and processing records in a database according to a time sequence to form a digital file; and real-time intelligent monitoring and visual management of construction progress, quality and safety are realized.

The invention relates to the technical field of irrigation water, and discloses an irrigation district water optimization method and system based on dynamic data management, and the method comprises the steps: collecting the basic data of an irrigation district project and a monitoring station, the data of the irrigation district monitoring station, the monitoring data of the water volume of each branch water port in an access irrigation district, and the geographic information topological data of an integrated channel system and a land parcel; constructing a digital archive library; obtaining a water demand forecast and a recommended water distribution scheme according to the data in the digital archive, and making an actual water consumption scheme by referring to the water distribution scheme; calculating a canal system utilization coefficient and an irrigation water utilization coefficient based on the canal head water diversion amount, the water consumption data of each tail end water diversion port and the actual water consumption data of the field plot, and evaluating the water utilization efficiency; and when optimization is determined, optimizing water consumption of the irrigation area according to the canal environment data, the canal system utilization coefficient and the irrigation water utilization coefficient. According to the invention, by establishing a total-factor digital mapping relation, accurate metering and dynamic optimization of irrigation water are realized, and dynamic planning of water saving of an irrigation area is realized.

The application discloses an intelligent geometric reasoning and semantic understanding method based on a three-dimensional large language model, which collects point cloud data of building components through a three-dimensional scanning device and associates text information, constructs a multi-modal three-dimensional large language model comprising a geometric perception coding module, a context semantic understanding module and a parameter efficient fine-tuning module; model training adopts a cross-modal contrast loss and a task instruction fine-tuning strategy, and finally outputs semantic recognition, attribute completion and historical background analysis results of the building components. The application is suitable for digital protection of building heritage, intelligent construction process monitoring and three-dimensional digital archive management, can improve component function recognition accuracy and cultural semantic mining capability in a complex scene, and supports real-time semantic updating and interactive response of a dynamic construction environment.

The invention discloses an intelligent computer archive classifying and filing method. The method relates to the technical field of archive digital management, and comprises the following steps: step 1, acquiring an image of an archive to be archived, and preprocessing the image of the archive; 2, identifying the preprocessed archive image based on OCR image identification software to obtain an initial identification result of archive characters; 3, constructing a semantic analysis model, carrying out semantic analysis on the file character initial recognition result, and outputting a high-precision character recognition result, and 4, based on the high-precision character recognition result, searching a preset target identification character, and carrying out matching classification; step 5, generating hierarchical directory information based on a matching classification result; and step 6, completing archiving storage in combination with a matching classification result and directory information. According to the method, character context semantic association and global sequence logic can be effectively captured, file semantic accurate analysis is realized, and low-confidence character and terminology errors in OCR initial recognition are greatly corrected.

The invention discloses an archive full-life-cycle tracing management method and system based on a block chain, and relates to the technical field of data processing, and the method comprises the steps: creating a digital archive, generating a unique archive identifier, and storing the unique archive identifier in the block chain; obtaining event related data of the archive; calling a block chain smart contract, associating event-related data with the archive identifier, and recording the event-related data as newly-added block data into a block chain; in response to the tracing request, retrieving and extracting all associated on-chain records from the block chain according to the target archive identifier; the method is based on chain records. Constructing and outputting at least one of the following traceability views: a circulation track and a state transition history of an archive entity, an association relationship graph between the archive and other associated archives, all operators related to the archive in a life cycle and operation records thereof, and change history and version comparison information of archive content or metadata; and based on the output tracing view, verifying the archive and triggering a predefined disposal rule or alarm.

The invention relates to the technical field of food quality safety, and discloses a food quality safety traceability method based on big data, which comprises the following steps: step 1, binding a unique batch identification code for each food batch, and deploying Internet of Things sensing equipment to collect environmental parameters and geographical location information, after the environment parameters and the geographical location information are associated with the batch identification codes, a data packet with an identity label is formed; and 2, the cloud big data platform receives and gathers the data packets with the identity labels, integrates preset static basic data and node event data, and constructs a dynamic digital file for recording a complete life cycle process by taking batch identification codes as main keys. According to the technical scheme of binding unique identification codes for food batches and deploying Internet of Things sensing equipment to automatically collect and associate uploaded data to a cloud platform for convergence and fusion, automatic and integrated management of whole-course data of a supply chain is realized.

The invention relates to the technical field of video processing and artificial intelligence, and discloses an AI video integrated device and a processing method thereof, and the device comprises the following steps: a video collection module obtains a real-time video stream; the event pre-classification module performs analysis to generate an event probability vector; the dynamic strategy scheduling module distributes a control instruction according to the vector. The deep analysis module loads an artificial intelligence model after receiving the instruction and extracts structured metadata; the archive packaging and anchoring module integrates the video stream and metadata, constructs a digital archive package, and carries out encrypted hash calculation, trusted timestamp anchoring and encrypted packaging; and the storage and output module transmits the encrypted file package to an external file management system. An event-driven dynamic strategy scheduling mechanism is introduced, low-power-consumption operation is kept in a conventional state, when the lightweight event pre-classification module recognizes a key event, a high-performance processing mode is switched to, deep analysis resources are mobilized, and the resource utilization efficiency of the device is improved.

The invention discloses an intelligent archive digital processing method and system, and the method comprises the steps: carrying out the synchronous scanning of a paper archive through a multi-spectral linear array scanner, and collecting the archive image data of a visible light wave band and a near-infrared wave band; performing non-uniform illumination correction and perspective distortion correction on the archive image data to generate a geometric and color standardized dual-channel fusion archive image; based on the dual-channel fusion file image, outputting structured layout description information including a text area, a table area, a signature area and an illustration area; generating a preliminary archive information atlas according to the structured layout description information; and based on the archive information atlas and a preset archive metadata specification, finally outputting a fully structured digital archive object conforming to an archive standard. According to the embodiment of the invention, the fully-structured digital archive object can be automatically generated in a high-fidelity manner, and the accuracy, integrity and knowledge degree of digital processing are improved.

The invention relates to a method for detecting microcracks on the inner wall of a wall enclosure superheater of a boiler. The method comprises the following steps: macroscopically identifying and preliminarily screening a high-risk area; creating an endoscope channel based on the primary suspicious area list and performing primary peeping on the inner wall; carrying out detection surface preparation and acoustic coupling optimization; data acquisition is carried out through accurate arrangement of the small-sound-velocity self-coupling phased array ultrasonic probe; extracting defect signal features and carrying out three-dimensional digital modeling; performing crack depth accurate quantization based on a time of flight diffraction mode; carrying out comprehensive data analysis and evaluating a security level; and integrating detection results, and generating a digital file based on the results. According to the invention, standardization of the detection process and systematization of data management can be realized, the detection efficiency and accuracy are greatly improved, a scientific basis is provided for equipment life prediction and maintenance decision, and the safe operation level of the boiler is effectively improved.

The invention relates to the technical field of archive classification, in particular to an electric power customer digital archive classification method and device, electronic equipment and a storage medium, and the method comprises the steps that classification features of to-be-classified pictures are extracted, and the classification features comprise textbox positions, sizes and text information of the to-be-classified pictures; and inputting the classification features of the to-be-classified pictures to the classifier set, and obtaining corresponding classification results and labels in combination with the classification rules. According to the method, field matching and image matching are introduced, a classification rule for three-level confidence calculation is set, and an optimal classification result is preferentially output, so that the problem that classification and recognition errors are easily caused when keyword features are unstable in an existing power customer digital archive classification method is solved; the automatic power customer digital archive classification and label generation capability is provided, manual intervention is reduced, the archive classification capability is improved, and the archive classification accuracy is ensured.

The invention relates to the technical field of digital archive management and information retrieval, and discloses a digital archive multi-modal data semantic enhancement fusion retrieval method and system.The method comprises the steps that a policy cycle time axis and a policy term evolution graph are constructed, tense logical reasoning is conducted on archive seals, and permission effectiveness evolution is derived; the temporal permission feature vector and the content semantic vector are fused to generate a multi-modal representation vector, and cross-policy-cycle semantic enhancement retrieval is realized by combining query expansion and temporal permission filtering, so that the problems of missing detection and misjudgment of policy and regulation archives in seal permission historical evolution and term cross-cycle retrieval are solved.

The invention discloses a PDF file structured data extraction system and method, and belongs to the technical field of electronic data processing. According to the system, the PDF is analyzed through PyMuPDF, tables are extracted through camera, titles are regularly positioned, paragraphs are segmented, and finally the paragraphs are serialized into JSON, so that the problem that structured file information cannot be accurately obtained in the prior art is solved, and the system is used for rapid digital archiving and subsequent data utilization.

The invention provides a sensitive information leakage prediction method and system based on digital archives, and relates to the field of digital archive management.The method comprises the steps that pointing entities are determined from a preset digital archive library, and a relation edge set is constructed according to the entities, entity relations and the pointing entities; determining an initialization weight of the entity according to the co-occurrence frequency of the entity and the pointing entity, the number of connecting edges of the entity, the number of connecting edges of the pointing entity and the cosine similarity; determining the current weight corresponding to the entity according to the initialization weight of the entity, the time attenuation factor and the context correlation degree, and determining the current content sensitivity corresponding to the current digital file, and inputting the current content sensitivity, the propagation path risk value and the carrier vulnerability value corresponding to the current digital file to a preset sensitive information leakage prediction model to obtain a sensitive information leakage risk degree. The method can dynamically adapt to archive security level changes and semantic association scenes, and the real-time performance and accuracy of prediction are improved.

The invention discloses a digital archive management system based on a block chain, and relates to the technical field of archive management, and the system comprises an extraction module which is used for extracting a state set according to behavior statistical information in the digital archive management system; the risk analysis module is used for positioning a text position according to a normal set in the state set, predicting a semantic layer exception risk and an authority risk, constructing a control flow graph to evaluate a structural layer exception risk, and summarizing to generate a risk signal; the association analysis module is used for analyzing the operation threat condition of the Solidiity contract in the digital archive management system on the basis of the risk analysis module, and judging the starting of a Solidiity contract correction mechanism; the influence module is used for starting a Solidinity contract correction mechanism and analyzing the influence of an abnormal condition on Solidinity contract operation; the waiting setting module is used for setting a time lock waiting period.

The invention discloses a digital archive management vulnerability assessment method and system based on multi-dimensional influence factors, and relates to the technical field of digital information management, and the method comprises the steps: collecting an internal data integrity verification result, external file format support data and an associated source flow record of a digital object; calculating a format outdated risk index, a data integrity attenuation degree index and a source flow chain vulnerability index; calculating the weighted sum of the format outdated risk index, the data integrity attenuation index and the source flow chain vulnerability index to generate a comprehensive vulnerability index; and comparing the comprehensive vulnerability index with a preset vulnerability response threshold value, and triggering a disposal process according to a comparison result. According to the method, accurate and prospective measurement of the vulnerability of the digital archives is realized through a multi-dimensional and dynamically quantitative evaluation model, and a key decision basis is provided for an automatic and verifiable long-term storage strategy in combination with a strategy-driven adaptive weight, so that the scientificity and initiative of risk management are remarkably improved.

The invention provides an auxiliary filing method based on offshore wind power data, which depends on a digital filing auxiliary platform of a B / S (Browser / Server) architecture, and realizes structured storage of offshore wind power industry specifications and associated logic by constructing a dual-core knowledge base; adopting metadata capture to complete batch processing of multi-format documents; through intelligent identification and classification, automatic paper composition and association relation solidification, an archiving catalog and a unique archive number which accord with industry specifications are generated; and automatically generating multi-dimensional indexes such as technical process, equipment full life cycle, hierarchical classification and the like, and finally outputting a standardized data packet imported by an adaptive offline archiving and digital system in combination with a man-machine interaction verification optimization result. According to the method, the archiving efficiency and normalization are greatly improved, accurate retrieval of data is realized, dependence on professional experience is reduced, and meanwhile, high-quality data support is provided for digital delivery and intelligent operation and maintenance of offshore wind power projects.

The invention relates to the technical field of intelligent management of construction elevators, in particular to a digital intelligent management system for construction elevators, which comprises an operation monitoring module used for collecting operation state data of each construction elevator in real time through a sensor network, detecting fault conditions and performing early warning; the intelligent scheduling module is used for intelligently distributing transportation tasks based on the passenger flow data, the material transportation demand data and the operation state data of each construction elevator; the predictive maintenance module is used for acquiring key component parameters of each construction elevator, predicting the residual life according to the key component parameters in combination with a fault model, and generating a maintenance work order in advance so as to reduce the fault rate; the authority management module is used for limiting unauthorized personnel to use the construction elevator; and the digital archive management module is used for recording the operation state, the fault history and the maintenance record of the construction elevator and generating a complete equipment life cycle archive. According to the invention, fine and informatization management of the whole life cycle of the construction elevator can be realized.

The invention provides a dynamic structure teaching demonstration method and system based on a detachable non-oil-leaving paper umbrella model, and is applied to the technical field of data processing. According to the method, 3D scanning and manual surveying and mapping are fused to obtain oil-paper umbrella component parameters and power node data, a reverse engineering algorithm is used for restoring a core structure, and a standardized digital file is generated; and converting the archive into a disassembled animation and an assembled map, subdividing a key power area by using a modular splitting algorithm, and establishing an interactive teaching model. Extracting culture and mechanical principle correlation factors to construct a dynamic matrix, and analyzing umbrella rib mechanics and power paths to obtain teaching key points; a multi-dimensional feature matrix is established by combining class scene extraction indexes and teaching grades. Finally, optimization factors are determined by comparing teaching data, a target scheme is constructed according to layered screening influence factors of students, multi-dimensional teaching support information is generated according to the scheme effect and dynamic association information, a traditional structure is accurately restored, and understanding and non-enthusiasm cognition of the students on the dynamic structure are improved.

This invention discloses an intelligent management and control method and system for communication tower maintenance, belonging to the field of communication facility maintenance and management technology. It constructs a comprehensive digital archive; achieves closed-loop management of vehicle operation trajectories and fuel consumption, calculating theoretical fuel consumption through a dynamic fuel consumption model and fitting it with actual fuel consumption for analysis; implements collaborative management of personnel work trajectories and work quality, triggering standardized work processes through geofencing, and using convolutional neural networks to identify compliance in process images; establishes material and work order associations through RFID tags, compares actual consumption with standard usage deviations, constructs a cost prediction model using a long short-term memory network, and outputs visual reports. This invention, by constructing a multi-dimensional closed-loop management and control logic, realizes the transformation of operation and maintenance resources from post-event statistics to real-time verifiable data, significantly improving cost control accuracy, work quality, and resource utilization efficiency.

The invention provides a scaffold monitoring management system and method, and the system comprises a component identification module which is used for distributing and managing a unique digital identification code for each scaffold component; the digital archive module is associated with the component identification module and used for establishing and maintaining a digital archive for each scaffold component, and the digital archive at least comprises specification information, state information and dynamically updated historical use data of the component; the circulation monitoring module is used for tracking and recording circulation states and events of each scaffold component in the links of warehousing, ex-warehouse, project erection, warehouse returning and scrapping based on the digital identification codes; and the health degree evaluation module is used for calculating the dynamic health degree of each scaffold component through a preset evaluation model based on the component historical use data and state information recorded in the digital file module. The invention aims to improve the safety, economy and refinement level of scaffold management.

The invention discloses an agricultural non-point source pollution monitoring data quality evaluation method, and relates to the field of agricultural environment monitoring, an agricultural non-point source pollution area to be monitored is divided into a plurality of grid areas to be monitored, and a fixed monitoring unit is arranged in the physical center of each grid area; and the server creates a double-track digital file for each grid area, the double-track digital file comprises a static attribute and a dynamic attribute, the double-track digital file is stored in a database and updated according to a preset period, and an updated version record is retained. According to the method, a three-dimensional multi-index comprehensive scoring and fixed mobile monitoring collaborative verification mode is adopted, the key dimension of data quality is comprehensively covered, misjudgment is reduced, and the evaluation accuracy is improved. An index calculation method, weight configuration and threshold standard are clear, the process is clear and operable, and actual popularization and application are facilitated. And targeted rectification suggestions are output, so that the quality optimization of the monitoring data can be directly guided, the reliability of the monitoring data is guaranteed, and powerful support is provided for agricultural non-point source pollution abatement decisions.