1577 results about "Data accuracy" patented technology

The invention relates to the technical field of pile foundation monitoring, and discloses a pile foundation state real-time monitoring and diagnosis system based on a digital twinborn technology. The system comprises a multi-source data acquisition module, a data confidence evaluation module and an acoustic emission monitoring decision module. The multi-source data acquisition module comprises a plurality of sensor groups deployed at different depths of a pile foundation, each group comprises a strain sensor, an acceleration sensor, an acoustic emission sensor and a temperature sensor, and pile foundation data can be acquired in multiple dimensions; the data confidence evaluation module receives original data, generates a correction data sequence through time sequence noise separation and reconstruction, and calculates data confidence according to correction data distribution dispersion; the acoustic emission monitoring decision module judges whether acoustic emission monitoring is started or not according to the data confidence coefficient, and controls the acoustic emission sensor array at the top of the pile foundation to collect acoustic emission signals during starting. The system can comprehensively obtain pile foundation data, improve data accuracy, achieve early damage recognition and guarantee pile foundation safety.

The invention discloses a natural resource engineering monitoring method and system based on cloud computing, and relates to the technical field of engineering monitoring. A cloud access layer is constructed, a standardized monitoring data set is formed, a monitoring quality abnormity label set is established, and an engineering state vector set is generated based on a space-time alignment monitoring data set; according to the method, standardization and unified management of multi-source monitoring data are achieved through cloud access, the data accuracy is guaranteed in combination with time synchronization, space mapping and a quality label mechanism, the method constructs an engineering state profile and generates consistent snapshots, and the method has the advantages of being simple in structure, convenient to operate and high in practicability. Historical comparison and tracing are supported, a risk event set and a risk evidence chain are generated through causal atlas inference, risk full-chain tracing is achieved, a scheduling instruction is further generated and combined with an execution receipt to form closed-loop management, differential evaluation and dynamic adjustment are supported, and therefore linkage and continuous optimization of monitoring, risk identification and engineering scheduling are achieved.

The invention discloses an indoor water tank sediment starting speed measurement system and method, and aims to solve the technical problem that data accuracy is affected due to the fact that a sensor disturbs a flow field in an existing measurement method. The core of the technical scheme is that the non-contact measurement characteristic of the PIV technology is applied to the whole process from flow field construction to data acquisition. The device is mainly composed of an imaging unit, a laser lighting unit, a movable sliding frame, a water flow adjusting unit and a buffer plate. Optical measurement is carried out through the imaging unit and the laser illumination unit, a physical sensor does not need to be arranged in a flow field, and interference of a measuring instrument on a water flow structure and a sediment starting process is fundamentally avoided. The movable sliding frame which is integrally designed integrates the functions of sediment laying, particle throwing and measuring, so that a test area can be quickly positioned; and the buffer plate and the water inlet and drainage adjusting unit are combined, so that a gradually-changed flow field from weak to strong can be accurately and stably simulated.

The invention relates to the technical field of data processing, and discloses a knowledge graph incremental updating and consistency checking method and system. The method and the device are used for solving the problem of low incremental updating and consistency checking efficiency of a large-scale knowledge graph. The method comprises the following steps: collecting a to-be-updated data source, sorting and separately storing data, and marking priority labels; performing change detection on the marked data source, identifying change items by comparing entities and relationships, and generating a log; incremental updating is executed based on the log, and nodes and edges are processed in a hierarchical fusion mode; preliminary consistency verification is carried out, and attribute uniqueness and relation directivity are checked; expanding a verification range, traversing an association path through cascade check, and recording problems; and optimizing storage according to the record, merging the update area, updating the index and cleaning the log. The method solves the problem of low efficiency of incremental updating and consistency verification of the large-scale knowledge graph, improves the response speed and the data accuracy of the system, and is suitable for a high-frequency dynamic data environment.

The invention relates to the technical field of artificial intelligence, in particular to a government work report generation system and method based on multi-path retrieval and a large model, and the system comprises a data engineering module, a database system module, a multi-path retrieval module, a cue word engineering module and a report generation system module. The system has the beneficial effects that database management and work report generation capabilities are considered, a user not only can store, manage and check own government affair data, but also can be linked to a report generation module to generate a government work report based on a knowledge base constructed by a client, and the data accuracy and personalization of report content are greatly improved.

The invention discloses a wind profile radar radial speed quality control and horizontal wind field inversion method. According to the method, through the steps of multi-mode detection splicing, signal-to-noise ratio threshold value quality control, beam consistency inspection, horizontal wind component inversion, space and time continuity inspection and the like, the quality control process of the wind field data is optimized, the precision of the horizontal wind field data is remarkably improved, and particularly, the root-mean-square error and deviation in high-level data are remarkably reduced. The core innovation comprises a mode splicing strategy based on sounding data comparison, dynamic signal-to-noise ratio threshold calculation, threshold setting of beam consistency check and a wind component compensation algorithm when a vertical beam is missing. Through experimental verification, compared with a traditional wind profile radar data processing method, the wind profile radar data processing method has remarkable advantages in data accuracy and stability.

The invention relates to the technical field of environment assessment, in particular to a coastal zone culture area multi-dimensional environment assessment method and a cloud platform. The method comprises the following steps: continuously recording dissolved oxygen concentration, pH value, centigrade temperature, salinity unit, turbidity scattering unit, chlorophyll fluorescence intensity, ammonia nitrogen milligram per liter and nitrite milligram per liter, synchronously calling multi-source remote sensing images covering a culture area and an adjacent water area, extracting remote sensing reflectivity data through image correction and atmospheric correction, and calculating to obtain water color parameters. According to the method, the water quality sensor array is deployed at the key point of the culture area, continuous multi-parameter environmental data acquisition is carried out, multi-source remote sensing images are synchronously integrated, water color information is extracted in real time, and the timeliness and data accuracy of culture water area environmental monitoring are improved; trend decomposition and dynamic baseline construction are carried out based on the data sequence, so that the environmental fluctuation evaluation of the breeding area is more objective and accurate.

The invention discloses a water conservancy facility monitoring method and system based on digital twinning, and relates to the technical field of water conservancy monitoring. Historical operation data of a water conservancy facility are obtained based on a digital twinning model for analogue simulation, and full life cycle data of the water conservancy facility are obtained; and importing the standard operation data into the digital twin model, carrying out data comparison and data compensation on the standard operation data and the full life cycle data, verifying the accuracy of the standard operation data, and generating output verification data after comparison is completed. The verification data is generated by comparing the operation data with the data simulated by the digital twin model and combining cross verification of multiple operation data in the same area, so that data accuracy confirmation and data compensation can be carried out on the data distortion problem caused by abnormal data acquisition of the water conservancy facility operation data acquisition equipment; the reliability of the collected operation data is ensured, and the accuracy of evaluation and decision-making of the subsequent water conservancy facility monitoring operation state is guaranteed.

The invention provides a field NL2SQL data automatic synthesis method and system based on a large language model, and the method comprises the steps: building an SQL template library through collecting a public data set and real business query data, carrying out the grading according to the SQL complexity, and forming an SQL template set covering different difficulties; specific SQL queries are generated based on an SQL template library and a large language model, verification is carried out through multiple mechanisms such as grammar check, execution verification and result dimension consistency check, and correctness and performability of the SQL queries are ensured. Generating a plurality of candidate natural language questions according to the verified SQL query and the large language model, calculating a semantic consistency score of each candidate question and the SQL query through a cross consistency evaluation mechanism, screening out the question with the most consistent semantics as a final question-answer pair sample, and meanwhile, eliminating low-quality samples by setting a consistency threshold value, so as to obtain a final question-answer pair sample; and the data accuracy and consistency are further improved.

The invention discloses a liquid cooling charging module health state prediction system, and relates to the technical field of electrochemical detection, and the system comprises a multi-parameter collection unit which collects the pressure and flow data of a cooling liquid, and is provided with an independent collection node at each branch of a double-gun charging system, and provides basic data for monitoring; the dynamic calibration unit communicates with the acquisition unit, compensates data drift based on a temperature-vibration interference model of machine learning training, executes baseline calibration by using an idle period to update a reference value, and guarantees data accuracy; the leakage detection unit is used for calculating a data change rate after compensation, outputting an early warning according to a preset condition and positioning a leakage branch; and the health state evaluation unit fuses the early warning signal and the historical operation data to generate a prediction result. The problems that tiny leakage detection is difficult and a sensor is prone to interference can be solved, manual inspection is reduced, the maintenance cost is reduced, and the requirement of a high-power charging scene is met.

The invention discloses a power distribution network fault identification method and device based on artificial intelligence, and the method comprises the steps: obtaining the multi-source fault characterization information of a power distribution network, and the multi-source fault characterization information comprises telemetering data and telecommand data; performing expert database-based normalization processing on the multi-source fault representation information to generate a standardized fault data sample; matching and checking the standardized fault data sample to generate checked fault data; performing graph data conversion processing on the checked fault data according to a power distribution network graph model to generate fault graph data; and based on the fault graph data, reasoning the fault of the power distribution network through the fault reasoning model to obtain the speculated fault of the power distribution network. The multi-source information is obtained, the limitation of a single channel is broken, data differences are eliminated through expert database normalization, data accuracy is guaranteed through matching checking, graph data conversion is associated with topology, artificial intelligence reasoning gets rid of manual dependence, and efficiency and accuracy are improved.

The present invention relates to the technical field of energy meter electrical parameter measurement. Disclosed is an intelligent anti-interference system for a power line carrier energy meter. The system comprises: collecting voltage and current signals of a power line, and constructing a sample database; performing time-frequency feature classification by means of a preset model, and establishing feature and scenario mapping by synchronizing scenario recognition results; building a scenario interference recognition network on the basis of the mapping result; collecting real-time data of N communication channels of a power line carrier energy meter, and performing channel coordination decision and anti-interference enhancement; performing communication data evaluation on the basis of a comprehensive scoring function; and performing anti-interference management on the basis of channel access decision, anti-interference enhancement, and a parallel access result. The present invention solves the technical problem of poor accuracy and reliability of metering data of existing power line carrier energy meters caused by interference signals and noise when the power line carrier energy meters are in complex electromagnetic environments, and achieves the technical effect of improving the anti-interference capability and the reliability of the power line carrier energy meters.

An integrated document portfolio management and governance system and method are disclosed. The system includes a computing unit having an application interface adapted to present and / or formulate at least one input query. The system further includes aa central controller having a backend server communicably connected to the application interface of the computing unit. The backend server includes a data receiving component adapted to receive document dataset, each comprising a plurality of data elements, from a plurality of data sources in one or more formats. The backend server further includes a data ingestion module adapted to detect, normalize, and aggregate the plurality of data elements of the document dataset and subsequently store them within a central data repository. Furthermore, the backend server includes an ontology generator module adapted to create and maintain a dynamic ontology for the ingested datasets in real-time, wherein the plurality of data elements is categorized and contextualized in accordance with the dynamic ontology. Additionally, the backend server includes a governance module adapted to enforce & monitor data compliance policies and a data analysis module adapted to analyze the ingested data and generate actionable insights, wherein the actionable insights include one or more predictive analysis, data accuracy status, governance status, operational inefficiency, risk indicators, compliance gaps, and risk lineage and integrity. In operation, a user formulates an input query towards the central controller which in response is configured to automatically manage, govern & monitor the received data and subsequently visualize one or more actionable insights and / or compliance gaps onto the application interface of the computing unit.

The invention relates to an intelligent water affair remote monitoring and control system based on the Internet of Things, in particular to the field of intelligent water affair remote monitoring and control, and the system comprises the steps: firstly, pre-training a long and short-term memory network model through a cloud, and generating a lightweight edge prediction model to reduce calculation and transmission loads; the data transmission module effectively reduces the occupation of transmission bandwidth based on a dynamic quantization threshold value of a residual error and a differential coding technology, meanwhile, the high precision of the data is kept, the verification feedback module monitors the accuracy of the transmission data in real time through confidence coefficient detection, and triggers model re-calibration when the confidence coefficient is reduced, so that the long-term stability of the system is ensured, and the reliability of the system is improved. The sampling optimization module dynamically adjusts the sampling frequency according to the confidence coefficient and the residual fluctuation characteristics, balance is achieved between bandwidth occupation and reconstruction precision by using the Lyapunov optimization theory, the real-time performance and accuracy of water affair monitoring are improved, and meanwhile bandwidth consumption and energy consumption are effectively reduced.

The invention provides a heterogeneous data stream real-time automatic cleaning and correcting method based on a dynamic rule engine, and relates to the technical field of data processing, and the method comprises the steps: accessing a multi-source heterogeneous data stream; loading a predefined dynamic cleaning rule set to a rule engine; monitoring an input data stream in real time, analyzing data content in parallel through a rule engine, and triggering a cleaning action; dynamically generating a correction operation instruction according to a rule matching result; a data credibility weight factor and a correction utility attenuation coefficient are introduced, and a cleaning strategy is dynamically adjusted; and outputting the cleaned standardized data stream and recording a correction log. Through the dynamic rule engine and the intelligent algorithm, flexible adjustment and real-time processing of the heterogeneous data stream cleaning rule are realized, the efficiency and accuracy of data cleaning are improved, and the problems of insufficient rule flexibility, low processing efficiency and difficulty in ensuring data accuracy in the prior art are solved.

The invention relates to the technical field of hydraulic valves, and discloses a digital hydraulic valve intelligent diagnosis system which comprises a data acquisition module, a data preprocessing and label generation module, a feature fusion module, a classification diagnosis and decision fusion module and a service life prediction and suggestion generation module. Data such as pressure, vibration, displacement, flow and pollution degree of the valve are comprehensively captured through deployment of a multi-source sensor array at key positions of the digital hydraulic valve and a self-adaptive acquisition strategy, early fault feature omission is avoided, then through preprocessing means such as soft-hard hybrid wavelet threshold denoising and multi-sensor time alignment, the data precision is effectively improved, and the accuracy of the data is improved. Then, through dynamic-static layered feature fusion and an attention weighting mechanism based on GRU, different feature advantages under steady-state and fault working conditions are fully combined, the fault feature distinction degree is greatly enhanced, and the problem that similar faults are likely to be confused is solved.

The invention discloses a geological archive structure integrity guarantee method and system based on map dynamic maintenance, and the method comprises the steps: obtaining an archive circulation path which is directly and indirectly connected with an archive for peripheral associated data marked as an undeletable archive, analyzing a potential breaking point in the path, and obtaining a risk region which may cause a data isolation problem; performing deep scanning on archive data in the risk area to obtain content features and historical circulation records of archives, judging whether the content features and the historical circulation records meet data accuracy standards or not, and determining a non-key archive list needing to be deleted; according to the non-key file list, analyzing the operation influence range of each file to be deleted, obtaining potential impact on the stability of the whole system after the file is deleted, and if it is judged that the information network integrity is damaged due to deletion, moving the file out of the deletion list; and for the finally determined deletion list, acquiring backup data and a flow path log of the archive, and updating the archive connection atlas through a dynamic maintenance mechanism to obtain a new information network structure.

The invention relates to the technical field of air compressor optimization, and discloses an intelligent air compressor optimization control method and system based on an IOE control system.The intelligent air compressor optimization control system comprises a collection unit, a preprocessing unit, an analysis unit and an optimization unit, rich operation data such as air inlet pressure, flow, exhaust pressure and temperature are comprehensively collected in real time, denoising is conducted through a moving average method, and data accuracy is ensured; normal, overload and abnormal fluctuation modes are clearly divided, accurate judgment is performed by means of a preset interval and reasonable calculation, and powerful support is provided for control decision making; in a normal mode, intelligent regulation is performed according to a parameter average value, and operation efficiency and stability are improved; the valve opening degree is adjusted according to the deviation degree in the overload mode, the load is effectively reduced, and equipment is protected; in the abnormal fluctuation mode, a PID control algorithm is used, the opening degree, the cooling amount and the like of the valve are flexibly adjusted according to deviation and the change rate, and parameters are rapidly recovered to be stable. The fault rate and the maintenance cost can be greatly reduced, and the working efficiency is remarkably improved.

The invention specifically relates to a forest stock dynamic exploration system and method based on unmanned aerial vehicle multispectral fusion, and relates to the technical field of forest resource monitoring. A data preprocessing module; a feature extraction module; a model construction and estimation module; and a result output and visualization module. According to the method, a multi-dimensional data fusion and dynamic calibration mechanism changes the limitation of a traditional fixed soil regulation coefficient; when the soil regulation coefficient is obtained, four core factors of soil type, terrain illumination, soil humidity and texture partition distance are comprehensively considered; interference of different soil backgrounds, terrain illumination and humidity changes on vegetation index calculation is effectively eliminated, the enhanced vegetation index can reflect the coverage and health condition of forest vegetation more truly, a high-precision data basis is provided for subsequent forest stock estimation based on the vegetation index, and compared with a traditional method, the method has the advantage that the method is more accurate. And the data accuracy and reliability are improved.

The invention discloses a tunnel lining construction full-process intelligent monitoring and early warning platform, which relates to the technical field of tunnel construction intelligent monitoring and comprises a field sensing unit, an edge computing unit and a central management center. According to the invention, the field sensing unit synchronously acquires multi-source data template stress, template deformation, template displacement, surrounding rock and environment parameters and personnel and equipment positioning, and displacement sensors are alternately arranged to realize temperature drift correction, so that the data precision is improved; through fusion of a dual-spectrum camera and an ultra-wideband label, sub-meter personnel positioning precision and safety protection article identification are realized in a low-illumination environment, a full-dimension sensing network covering physical states, environments and behaviors is formed, and an edge computing unit adopts an embedded chip to provide computing power. And multi-modal feature fusion and physical consistency constraint deep learning reasoning are executed, an online change point detection mechanism is introduced to dynamically adjust an early warning threshold value, and different geological conditions and construction stages are adapted.

The invention discloses a handover content generation method and device for nursing work and computer equipment. The method comprises the steps that initial medical information of a target object is acquired, and the initial medical information is generated by splicing multiple pieces of statement information; target medical information is determined in the initial medical information, and the target medical information is information in the initial medical information, and the relevancy between the target medical information and target handover content used for nursing work exceeds a preset threshold value; and based on the target medical information, predicting and generating target handover content corresponding to the target object. The technical problem that the processing efficiency and the data accuracy are affected due to the fact that manual content filling is still needed in an existing SBAR handover method is solved.

The invention relates to the field of data processing, and discloses a neurosurgery operation data processing method for precision medical treatment, which is used for solving the problem that mark points cannot be captured due to the fact that a navigation camera is shielded when intraoperative data is collected. The method comprises the following steps: acquiring preoperative image data, intra-operative navigation image data and spatial information of an intra-operative reference mark point, constructing a preoperative three-dimensional navigation model through the preoperative image data, obtaining a navigation coordinate system, obtaining an intra-operative image frame sequence through the intra-operative navigation image data, carrying out spatial registration, extracting intra-operative navigation information, and obtaining an intra-operative image frame sequence. The method comprises the following steps: acquiring intraoperative navigation information, judging whether occlusion occurs in an operation or not according to the intraoperative navigation information, if yes, generating missing image frame data during occlusion through a dynamic trajectory prediction model, and effectively judging the missing image frame data according to a newest instrument space pose, thereby effectively improving data integrity and coherence, improving operation data accuracy and improving operation accuracy. The operation risk is reduced.

The invention discloses a single-hole cluster test method, device and equipment for cave depot water curtain holes and a storage medium, and relates to the technical field of underground engineering and water sealing.The method comprises the steps that a test instruction input by a user is received; when the test instruction is a single-hole water injection fallback test instruction, sending a single-hole water injection fallback test control signal to a programmable logic controller of the target water curtain hole through an OPC server so as to perform a single-hole water injection fallback test and collect first test data; when the test instruction is a water curtain effectiveness test instruction, water curtain effectiveness test control signals are sent to programmable logic controllers of all the water curtain holes through the OPC server, so that water curtain effectiveness tests are carried out on all the water curtain holes, and second test data are collected; and obtaining a test result according to the first test data and the second test data. According to the application, remote data acquisition and test control of the water curtain hole cluster can be realized without entering the cave depot by field personnel, and meanwhile, the test efficiency and the data accuracy are improved.

The invention relates to the technical field of electronic lock manufacturing, in particular to electronic lock full-automatic detection equipment and a detection method thereof. Comprising a feeding module, a detection carrier, a code scanning mechanism, an aging test station, an on-load test station, a CCD detection station, an output force detection station, an airtightness detection station, a code printing module, a discharging module, two four-axis robots and an electric signal detection mechanism. The two four-axis robots transfer electronic locks to be detected among the feeding module, the discharging module and the detection carriers in all the stations. The electric signal detection mechanism stretches into the electronic lock on the corresponding detection carrier to carry out electric driving and signal detection, so that one-stop full-automatic high-precision detection of the electronic lock from code scanning, aging, on-load testing, visual size detection, output force detection, air tightness detection to code printing and blanking is realized; the detection efficiency, the data accuracy and the process reliability are remarkably improved, and meanwhile the manual intervention cost and the equipment complexity are reduced.

The invention discloses a question and answer-based report generation method and device and a storage medium, and the method comprises the steps: obtaining question information inputted by a user, calling an intelligent answer model to answer the question information, and obtaining answer information; based on an answer layout style associated with the question information, performing visual rendering on the answer information to obtain an initial answer rendering result; receiving an editing operation executed by the user for the initial answer rendering result, and modifying the initial answer rendering result based on the editing operation to obtain a target answer rendering result; and in response to a report generation operation executed by the user, based on the report layout style associated with each piece of question information, performing combination and visual rendering on the target answer rendering result corresponding to each piece of question information to obtain a report file. According to the method, it can be ensured that the finally generated report file conforms to user expectation, the layout reasonability and data accuracy of the report file are improved, and the report generation efficiency is improved.

The invention discloses an agricultural insurance data acquisition and management system based on satellite remote sensing. The system comprises a data acquisition module, a preprocessing module, a verification module and a management module. The data acquisition module covers basic, universal and vector data acquisition according to data types; the preprocessing module improves the quality of collected data; the verification module verifies a cultivated land vector and insured user information, and data accuracy and reliability are enhanced; the management module builds two libraries, and constructs an agricultural insurance data large model by utilizing knowledge graph modeling. In the technical application, on the basis of satellite remote sensing and A I, large-user plot data is collected by means of an image segmentation algorithm, and the cost is reduced. A full-coverage model is constructed through abstract materialization, and business application is supported. Technical means such as satellite remote sensing, weight dispatch data superposition and AI image recognition are used for verifying data, manual operation is reduced, verification accuracy is guaranteed, data value is mined, and the agricultural insurance data management level is improved.

The invention belongs to the technical field of data transmission processing, and discloses a control system and method for intelligent agriculture multilayer soil temperature and humidity sampling. The system comprises a land data acquisition module, an updated data acquisition module, a data set preprocessing module, a soil humidity prediction module, a decision report generation module and a report transmission module, and is characterized in that a land data set is acquired, an updated data set is acquired, the land data set and the updated data set are preprocessed to obtain comprehensive feature data, and the comprehensive feature data are transmitted to the decision report generation module; analyzing the land data set, the update data set and the comprehensive feature data set to obtain a predicted humidity reference value, analyzing the predicted humidity reference value to obtain a soil decision report, processing the soil decision report, and outputting the processed soil decision report to a terminal. The method has the remarkable advantages of high accuracy of sampled soil data, strong auxiliary decision-making capability and good use economic effect.

The present application relates to the technical field of parallel processing, and provides a parallel processing method and system for batch write-off tasks. The method comprises: extracting a plurality of pieces of query data of a preset write-off window, comprising external write-off codes and write-off services; performing file import on the basis of the data, and generating transaction files with unique identifiers; when file name identifiers are verified, parsing the external write-off codes, and generating fund files; generating pending write-off files by means of procurement-settlement mapping authentication; identifying request time identifiers to identify write-off conflicts, and generating conflicting file clusters; updating the configuration of a parallel processing module on the basis of the conflict condition; and utilizing the updated module to process the conflicting file clusters in parallel. The present application solves the technical problems of data conflict, irrational resource allocation and low processing efficiency caused by improper parallel processing in batch write-off tasks, and realizes real-time extraction, verification, parsing and authentication of write-off data, thereby ensuring the data accuracy and consistency.

The invention relates to the technical field of the Internet of Things, in particular to a real-time monitoring system for oil fume emission of an oil fume purifier based on the Internet of Things technology, and the real-time monitoring system is characterized in that oil fume concentration original data, environmental parameter data and historical oil fume data are acquired through a data acquisition module; the weighted filtering module dynamically distributes filtering weights based on the environmental parameter data, performs weighted fusion on the original data of the oil smoke concentration, and effectively inhibits environmental interference; the weighting correction module calls historical oil smoke data to establish a reference mode and distributes correction weights, secondary optimization is carried out on filtered data, and the data rationality is improved; the state evaluation and decision-making module calculates a comprehensive operation efficiency index based on the timeliness of the correction data, and generates graded early warning in combination with a concentration threshold value; according to the process, the data accuracy is optimized step by step, the problem of misjudgment caused by unreliability of single data is solved, and accurate early warning is achieved.

According to the clinical nursing patient information monitoring and inputting method and system, the data accuracy, the data inputting efficiency and the privacy protection safety are improved; the method comprises the following steps: firstly, collecting and preprocessing vital sign data of a patient in real time through various physiological sensors; then, acquiring a nursing record image, acquiring nursing record data through an OCR model, acquiring nursing information voice, transwriting the nursing record data and the nursing information voice into nursing information data through a medical scene voice transwriting model, and performing unified standardization processing on the three groups of data to generate patient information data; and finally, when patient information data is input, symmetric encryption is carried out by adopting a national cryptographic SM4 algorithm, encrypted data is obtained, a dynamic encryption key is generated through an ECDH key distribution technology, and the dynamic encryption key can be called to carry out decryption operation after authentication of a dual protection mechanism of Hash value pre-verification and identity authentication is passed.