925 results about "Data application" patented technology

The invention relates to the technical field of data security, in particular to a data security sharing method and system. The method comprises the following steps: acquiring original shared data, carrying out reverse mapping and block marking, generating block marking data, carrying out inter-block random arrangement on the block marking data, carrying out differential disturbance simulation based on a random sequence, forming disturbance block data, and encrypting the disturbance block data by applying a progressive encryption technology. The method comprises the following steps: carrying out fragmentation storage, generating storage shared data, carrying out access monitoring on the storage shared data, collecting shared access data, and constructing an evidence chain and generating an access traceability data chain according to the data, thereby realizing the security and traceability of data sharing. According to the invention, a safer and more credible data security sharing method is realized.

The invention relates to the technical field of data processing and privacy protection, in particular to a data desensitization and integrity verification method and system based on a differential privacy algorithm, and aims to realize collaborative optimization of data privacy protection and integrity guarantee. Determining a total privacy budget by calculating global sensitivity, a data leakage risk coefficient and independent and joint data privacy information amount, dynamically allocating the privacy budget for a single-task or multi-task scene, and injecting noise based on an allocation result to realize differential privacy desensitization; meanwhile, a verification voucher is generated by using a hash function, a digital signature and an alliance chain, and the data integrity is ensured through signature verification, data consistency verification and block chain verification. The system comprises a data application processing module, a global sensitivity calculation module, a desensitization core processing module, a verification voucher generation module and an integrity verification module, is suitable for government affairs, enterprises and other scenes with high requirements for data privacy and integrity, and effectively improves the safety and reliability of data processing.

The invention relates to the technical field of power grids, in particular to a metering box remote monitoring method, system and device based on artificial intelligence and a medium. Acquiring electrical parameter data and environmental data of the metering box; performing time domain and frequency domain feature extraction on the data to obtain key features; inputting the processed data into a preset abnormal state detection model; identifying an abnormal state of the metering box based on a model output result; and when the abnormity is identified, alarm information is generated and sent to a monitoring terminal through a remote communication network. Multi-dimensional monitoring data are collected in real time through multiple sensors, feature extraction and anomaly detection are performed by applying an artificial intelligence technology, a model is continuously optimized in combination with an online learning mechanism, and comprehensive sensing of the running state of the metering box and accurate recognition of the abnormal state are achieved. Compared with a traditional monitoring system, the method improves the detection accuracy, reduces the false alarm rate and the missing report rate, improves the fault processing efficiency through the automatic generation of the maintenance suggestions, and provides a powerful guarantee for the operation of a power system.

The invention relates to the technical field of natural language processing, and discloses a knowledge base question and answer platform construction method based on a large language model, which comprises a knowledge acquisition module, a data preprocessing module, a text processing module, a vectorization module, a question understanding module, a mixed retrieval module, a prompt generation module, an answer generation module and an answer quality analysis module. A secondary inquiry processing module and a feedback learning module; according to the method, a semantic segmentation algorithm is combined with semantic retrieval and keyword retrieval, so that the flexibility is high; normalized prompts are constructed, input is performed according to correlation sorting, and the accuracy of answers is improved; multi-dimensional confidence evaluation is introduced, strict multi-layer security and compliance filtering is set, and the reliability of the system is ensured; the relevance of multiple rounds of dialogues is judged and complemented, so that interaction is more natural and efficient; knowledge is collected and updated in real time, a knowledge base and a retrieval strategy are continuously optimized, and a closed loop of data-application-feedback-tracing-optimization is formed.

The invention discloses an intelligent data management system and method based on multi-source data collection, and relates to the technical field of data processing. Multi-source data from multiple data sources are obtained, an original data set with credibility marks is generated, data records in the original data set are classified according to data types, and for time series data, data records in the original data set are classified according to credibility marks. Extracting trend features by applying a segmented multi-model time sequence feature extraction framework; for the data of the unstructured data, extraction of unstructured features is carried out through a feature extraction model based on a multi-layer perceptron; for structured data, a knowledge graph technology is adopted to establish an adaptive association relationship, association relationship data is generated, trend features, unstructured features and the association relationship data are used as input of a data value evaluation model, and data asset performance evaluation of dynamic weight is generated; and intelligent management and value evaluation of the multi-source heterogeneous data are realized.

A monitoring system can generate compressed storage system monitoring data segments using monitoring data obtained from a storage system. The monitoring system can obtain storage system monitoring data and generate a segment by applying the storage system monitoring data to a machine learning model trained to segment the storage system monitoring data. The monitoring system can generate a compressed segment by applying a specified compression technique to the segment. In response to user query, the user query specifying a portion of the storage system monitoring data; the monitoring system can perform at least one of: reconstructing and providing the portion using the compressed segment; or providing the compressed segment for reconstruction of the portion.

The invention provides a coal preparation plant production data full-process management system and method, and the method comprises the steps: a data collection subsystem collects equipment data and production data of different data sources of each plant through a preset data collection interface; the data transmission subsystem encrypts and transmits equipment data and production data acquired by the data acquisition subsystem to the data cleaning subsystem for cleaning, and the data storage subsystem stores the data cleaned by the data cleaning subsystem to a plurality of databases of different types in a mixed storage mode. And the data application subsystem obtains the target data from the data storage subsystem and performs production plan optimization, equipment fault early warning and quality control and optimization based on the target data and preset data. By the adoption of the method, efficient processing and deep application of the whole process of production data of the coal preparation plant are achieved, powerful support is provided for intelligent and refined production management of the coal preparation plant, and the overall operation level and economic benefits of the coal preparation plant can be effectively improved.

The invention discloses a vehicle electromagnetic compatibility test method and device based on a big data platform, and relates to the technical field of vehicle testing, and the method comprises the steps: creating a vehicle electromagnetic compatibility detection item in a cloud platform, and generating a detection task; detecting equipment and a to-be-detected piece are connected to the cloud platform through the Internet of Things technology, and standardized parameters and a hardware connection template of a detection task are configured; physical connection of the detection system is completed based on the hardware connection template; calling an automatic test module to execute a standardized test process, and collecting test data in real time; performing multi-dimensional analysis and intelligent evaluation on the test data to generate a detection report and authentication data; synchronizing the detection report and the authentication data to a service platform for secondary data application; visualization and collaborative management of the test process are carried out through the remote monitoring module.

The application provides a pumped storage power station data fusion intelligent analysis platform, comprising: a data source comprising a plurality of original data; the data center is configured to collect original data and convert the original data to obtain unified data; the data application comprises an algorithm middle table module, and the algorithm middle table module is configured to construct an operator library, associate corresponding measurement attributes with measurement point identifiers of unified data and form a matching table; obtaining an algorithm construction instruction; according to the algorithm construction instruction, the operator library and the measurement attributes, performing algorithm modeling through a drag-and-drop operation process to obtain a power station data analysis algorithm; instantiating the power station data analysis algorithm to obtain an instantiated algorithm; and processing the corresponding unified data according to the instantiation algorithm and the matching table to generate an analysis result data set. The pumped storage power station data fusion intelligent analysis platform provided by the invention can realize multi-source heterogeneous data integration and analysis, and is high in efficiency, low in cost and good in real-time performance and accuracy.

Disclosed herein are systems, methods, and media for emissions data analysis. The disclosed embodiments include accessing emissions activity data from at least one emissions activity data source. The emissions activity data may correspond to an entity and the at least one emissions activity data source corresponds to an activity region. The disclosed embodiments include extracting structured emissions data from the emissions activity data by applying the emissions activity data to a machine learning model configured to standardize data. The machine learning model may be trained with emissions training data. The disclosed embodiments include accessing an emissions factor database containing a plurality of emissions factors. The disclosed embodiments include selecting, from the emissions factor database, at least one emissions factor corresponding to the activity region. The disclosed embodiments include generating an emissions line item based on the structured emissions data and the at least one selected emissions factor.

Described are methods, platforms, systems, and media, for enhancing well-being by using methodology including receiving media comprising an unstructured user-generated narrative; applying one or more algorithms to the unstructured user-generated narrative to extract semi-structured user context data; applying a first machine learning model to classify one or more of sentiment, intent, habits, patterns, beliefs, and motivations from at least the user context data, wherein the first machine learning model comprises an unsupervised machine learning model; applying a second machine learning model to identify one or more recommended next actions from at least the user context data, wherein the second machine learning model comprises a supervised machine learning model; and generating one or more well-being-related insights for the user based at least on the user context data, and one or more of the sentiment, intent, habits, patterns, beliefs, motivations, and one or more recommended next actions to encourage a healthy lifestyle.

The invention discloses a petroleum industry personnel behavior safety video monitoring system based on artificial intelligence, and the system comprises a front-end equipment layer which is used for collecting physical environment data; the edge computing layer is deployed on a local server of a factory and is used for preprocessing and preliminarily analyzing the data acquired by the front-end equipment layer; the cloud analysis layer is used for carrying out deep analysis on the data uploaded by the edge calculation layer by utilizing deep learning and natural language processing technologies; the cloud analysis layer can integrate data from the front-end equipment layer, the edge computing layer and the cloud analysis layer; and the application service layer is used for presenting the result of the cloud analysis layer to a user in a user-friendly manner. According to the method, video spatio-temporal features are extracted through the CNN-BiLSTM fusion model, risk behaviors such as no helmet wearing and illegal operation are accurately identified, and the false alarm rate is reduced; the NLP analyzes the work order to construct the knowledge graph, the knowledge graph is matched with the video behavior event in a space-time manner, the risk score is dynamically evaluated, and the comprehensive early warning accuracy is improved.

The invention relates to the technical field of big data intelligent decision making, and provides a household appliance commodity dynamic pricing system and method based on multi-source data fusion, and the system comprises a data collection server, a feature extraction engine, a model training cluster, and a strategy execution terminal. The feature extraction engine comprises a time sequence feature constructor used for generating sliding window statistics; the semantic analysis unit is used for analyzing a commodity detail page text description to generate a brand premium coefficient; and the image recognition module is used for predicting the willingness to pay by the user through the commodity main image quality score. Through collaborative design of the feature extraction engine and the model training cluster, the dynamic response capability and the data application depth which are deficient in a traditional pricing mechanism are realized, traditional household appliance merchants are assisted to adapt to market changes, the customer satisfaction and the market share are improved, and the survival and development of the merchants are guaranteed.

The invention belongs to the technical field of data processing, and particularly relates to a medical big data processing method, device and equipment based on lake and warehouse integration and a medium, the method comprises the following steps: collecting original medical data, and uniformly accessing the original medical data to a data access layer of a lake and warehouse integrated architecture in an original format and full-amount information to form a source pasting library; preprocessing the original medical data in the source library, performing unified coding and format conversion according to the medical data standard set, generating a standardized data set, and storing the standardized data set in a normalization library; on the basis of data in the normalization library and the source pasting library, multi-modal medical data are associated and integrated through cross-source federated query and computational flow technologies according to business scene requirements of clinical diagnosis and treatment, scientific research analysis or management decision, a special topic library oriented to a specific business topic is constructed, and a special topic library view is generated; and providing a query interface and an analysis service for the data application platform through the thematic database. The data processing speed and efficiency are improved, delay is reduced, and the data throughput efficiency is ensured.

The invention is suitable for the field of data processing, and discloses a data treatment method, terminal equipment and a storage medium. The method is applied to a data facility, the data facility comprises a data platform, a data system and a data tool, and the method comprises the steps of accessing or collecting to-be-governed data; executing a preset operation corresponding to the full life cycle stage on the to-be-treated data, wherein the full life cycle stage comprises a data production stage, a data processing stage, a data circulation stage, a data application stage, a data maintenance stage, a data display stage and a data destruction stage; multi-dimensional data assessment corresponding to the full life cycle stage is executed on the to-be-governed data, assessment results are obtained, and the assessment results comprise a data value assessment report, a data quality assessment report, a data standardization assessment report and a data safety assessment report; and constructing a matrix type responsibility system according to an evaluation result, wherein the responsibility system maps a data engineer, a data analyst, a data manager, a data security teacher and a data quality evaluator to a corresponding life cycle stage in the full life cycle stage. According to the method, the problems of full-flow fault, evaluation subjectivity, role fuzzification and facility islanding in datamation treatment are solved.

The invention discloses a geographic information data fusion system, and relates to the technical field of geographic information data processing, the system comprises the following components: a data acquisition and preprocessing unit, a deep learning semantic analysis model construction unit, a semantic level data fusion unit and a data application and visualization unit; according to the method, semantic relationship reasoning is carried out on geographic entities by using a Geo-SDNN model through the deep learning semantic analysis model building unit, the complex semantic relationship between the geographic entities can be accurately captured, and meanwhile, the semantic level data fusion unit adopts a fusion algorithm based on semantic hierarchy, so that the data fusion efficiency is improved. In addition, a multi-source data acquisition interface and a data quality evaluation module of the data acquisition and preprocessing unit effectively improve the quality of basic data, the accuracy of data fusion is further improved, the data processing flow is optimized through the overall design of the system, and the data fusion efficiency is improved. And the efficiency of geographic information data fusion is obviously improved.

The invention relates to a civil aviation data automatic classification and management method based on large model training. The method comprises the following steps: collecting navigation notification information from a plurality of official platforms; defining professional classification term dictionary interpretation according to specific use scenes and meanings in the notification information; carrying out manual annotation processing on the obtained navigation announcement data; performing large model training on the civil aviation notification information by using the marked data; deploying the trained model to a data application platform for real-time processing; the model automatically classifies the announcement into a preset professional field category according to the property of the announcement; and a manual verification system is adopted to verify and adjust the classification accuracy. The invention further relates to a corresponding device, a processor and a storage medium thereof. By adopting the civil aviation data automatic classification and management method and device based on large model training, the processor and the storage medium thereof, the efficiency of aviation safety management and operation decision can be effectively improved.

The invention provides an intelligent intelligent supervision system for civil aviation VoIP communication equipment, relates to the basic field of civil aviation air traffic control equipment, and solves the limitation problems of non-centralized supervision, imperfect supervision, non-autonomous supervision and the like existing in an existing supervision mode. The system comprises a system architecture module which adopts a layered modular design to construct a double-layer system comprising a top layer management architecture and a bottom layer operation architecture; the function service module comprises an equipment state monitoring unit, a risk assessment engine and an operation and maintenance management unit; the data processing architecture forms a multi-stage processing channel by a data acquisition layer, a data transmission layer, a data storage layer, a data calculation layer and a data application layer which are connected in sequence; the technical support system comprises a micro-service component group, a continuous integration platform and a security authentication module. The intelligent supervision network architecture of the VoIP communication equipment is subjected to brand-new autonomous design, transformation from passive response to active management is completed, and the supervision efficiency and the treatment efficiency are improved.

The invention discloses a remote database synchronization system and method based on incremental data extraction and verification, and belongs to the technical field of data transmission and database synchronization. In order to improve synchronization efficiency and data consistency and adapt to a complex and changeable distributed database environment, the system comprises a variable detection module, a data application module, a data transmission module, a data verification module and an exception handling module, the variable detection module and the data application module are respectively connected with the data transmission module, the data transmission module is respectively connected with the data verification module and the exception handling module, and the exception handling module is further connected with the data verification module; the source database is connected with the variable detection module, and the target database is connected with the data application module and the data transmission module. Through incremental extraction, compression transmission and batch writing technologies, the data transmission and synchronization efficiency is greatly improved, and the method adapts to a high-frequency data change scene; and through a multi-level data verification mechanism and an exception recovery strategy, the integrity and accuracy of data synchronization are guaranteed.

Systems, computer program products, and methods are described herein for an integrated multimodal artificial intelligence framework for automated provisioning systems. The present disclosure is configured to aggregate and process data from multiple sources, apply advanced machine learning techniques for data normalization, feature extraction, and pattern recognition, and integrate these capabilities into an automated workflow for application provisioning. The system utilizes a processing device and non-transitory storage containing instructions which, when executed, enable the handling of complex workflows, decision-making processes, and real-time error management. Incorporating voice recognition, the system allows for natural language user interactions, enhancing accessibility and efficiency. The AI-driven framework adapts to evolving operational needs, ensuring precise and resilient application deployment within dynamic environments.

The invention relates to the technical field of data processing, and discloses an Internet of Things gateway data grading processing method and system based on edge computing, and the method comprises the steps: collecting original operation data and a data traffic value received by an Internet of Things gateway; performing feature extraction and clustering grouping according to the original operation data, calculating an average influence coefficient of samples in a group in combination with a preset service weight, and determining an importance level corresponding to the group; important data is screened out for distribution immediate evaluation; performing aging characteristic analysis according to the important data, and predicting a data processing priority; analyzing resource demand allocation according to the priority sequence and the data flow value, and constructing a resource allocation proportion; according to a resource allocation proportion and an allocation proportion lower limit, identifying nodes with insufficient proportions and optimizing the priority sequence to obtain a final scheduling scheme; according to the final scheduling scheme, the processing sequence is applied to the original operation data, and data grading output is obtained. According to the method, efficient and accurate data processing is realized.

An intelligent waybill management system comprises a data access layer, a data processing layer, a data storage layer and a data service layer. Wherein the data access layer is used for the access of access data, and comprises data of a data table, a message, a socket and a file type; the data processing layer is used for carrying out different data processing according to different data types, the data storage layer is used for carrying out data storage on the processed data, and the data service layer is used for carrying out unified data operation on data application through the data service layer after the steps of data processing and data storage are completed. The intelligent waybill management system provided by the invention can generate economic benefits and social benefits in multiple aspects.

The invention discloses an intelligent management system for goat samples, and relates to the technical field of goat sample management systems. The system comprises an identification layer used for binding a unique code for a goat sample; the sensing layer is used for collecting environment and position data of goat samples in real time; the control layer is used for automatically adjusting information of a goat sample storage environment; the data storage layer is used for storing and protecting goat sample data; and the application layer is used for providing man-machine interaction and intelligent analysis. The system can realize information acquisition, environment monitoring, authority management and data interaction of goat samples.

The invention relates to a stream data sharing method and system based on bidirectional Hash chain symmetric encryption and signcryption in the technical field of data sharing. The method comprises the following steps: calculating an original beginning left key corresponding to a first encryption time unit and an original ending right key corresponding to a last encryption time unit in a maximum time interval; on the basis of the original beginning left key and the original ending right key, original encryption sub-keys corresponding to other encryption time units are calculated to generate an encryption key; performing symmetric encryption on the stream data by using the encryption key, obtaining response data of a request time period based on the application request, and performing signcryption processing on the response data to obtain signcryption data; and sending the signcryption data to the data application user, so that the data application user performs de-signcryption on the signcryption data to obtain the response data, and performs decryption processing on the response data to obtain the target data, thereby solving the problems of relatively high resource consumption and relatively low confidentiality during point-to-point data transmission of the existing stream data.

Methods and apparatus for: i) providing a user equipment (UE) access to a core network, e.g., a 3GPP 5G core network, via a wireless local area network access point (WLAN AP) (e.g., a non-integrated non-3GPP access network), without the use of a non-3GPP Interworking Function (N3IWF) or a Trusted non-3GPPP Gateway Function (TNGF) and ii) allowing the transfer of application data via the core network are described. The transfer of application data is, i.e., in both directions, e.g. UE to User Plane Function (UPF) to data network (DN) and DN to UPF to UE. The access obtained by the UE does not require the presence of a 3GPP access network, e.g., a 3GPP radio access network (RAN) such as a gNB.

Devices, networks, systems, methods, and processes for an Augmented Reality (AR) based device management. An AR device may receive an image depicting one or more objects, from a camera. The AR device may determine position data, including a position and an orientation, of the AR device, and transmit the position data and the image to an application server. The application server may identify the one or more objects in the image and obtain status data associated with the one or more objects. The application server may generate overlay data based on the status data of the objects. The application server may transmit the overlay data to the AR device. An augmented image generated based on the overlay data may be displayed on the AR device to present the object status data. Such augmented images integrate information with real-world objects, providing instant access to object status data and enhancing user understanding.

The invention relates to the technical field of engineering data management, in particular to a method for performing engineering data management and application by using a large model knowledge base, which can perform unified data management on engineering data by combining a large model and a knowledge base and using a unified semantic modeling model URDF and a graph database Neo4J. Therefore, the requirement of modern engineering for data management can be met, and an information'island 'between the engineering is broken through. And meanwhile, data application of the unified integrated engineering data management system is realized by utilizing technologies including RAG, large model fine tuning and the like. Therefore, the user can use the natural language to apply the data, so that the data value is explored, and the value is stimulated to change. The problems that an existing method is generally only suitable for a specific field, manual intervention is needed, interaction between data and a user is not fully utilized, and implementation of the data value is limited are solved.

The invention discloses an equipment monitoring method and system based on big data, and belongs to the technical field of industrial internet and big data analysis, and the method comprises the steps: multi-source data collection: deploying sensors at key parts of tobacco equipment, collecting time sequence data, and obtaining image data through an industrial camera, synchronously recording production work orders and maintaining log text data; edge end preprocessing: an edge computing node performs abnormal point filtering on time sequence data by adopting a sliding window algorithm, and vibration signal spectrum features are extracted through Fourier transform; a YOLO algorithm is applied to the image data to detect equipment part abrasion or material blockage conditions; packaging the processed data into a feature vector in a fixed format; cloud intelligent analysis; and performing dynamic early warning and decision making. According to the method, cross-equipment and cross-time-period fault mode correlation analysis can be realized, multi-source data are fused by using big data analysis, intelligent equipment monitoring is realized, and the fault diagnosis and prediction capability is improved.

The invention discloses an audio processing method and device, a storage medium and an electronic device, and relates to the technical field of data processing, and the audio processing method comprises the steps: obtaining voice feature data and semantic feature data of original audio data; the original audio data is audio data extracted from the target audio and video data; generating segmentation position data according to the voice feature data and the semantic feature data; and generating audio paragraph data and paragraph visualization data according to the segmentation position data, and providing the paragraph visualization data to a user interaction interface. According to the technical scheme of the embodiment of the invention, the utilization rate of the audio information can be improved, the data processing cost in an application scene is remarkably reduced, and the data application efficiency and scene adaptability are improved.

The embodiment of the invention discloses an assembly type building construction management system based on BIM and GNN models, the system comprises a data collection module, a data processing module, a data application module and a data visualization module, the data collection module is used for collecting multi-source heterogeneous data of the whole period of building construction, the multi-source heterogeneous data comprises a building information model, a data processing module, a data application module and a data visualization module, and the data processing module is used for processing the multi-source heterogeneous data in the whole period of building construction. BIM (Building Information Modeling) data, sensor data, video stream data and external data; the data processing module is used for processing the multi-source heterogeneous data to obtain a data processing result which comprises a fused data set, standardized graph structure data and structured decision suggestions; the data application module is used for adjusting resource allocation according to the data processing result and generating an optimization instruction which comprises a structured instruction set and a structured scheme set; and the data visualization module is used for converting the optimization instruction and the structured decision suggestion and displaying a conversion result in a visual interface. According to the invention, the integration level, the intelligence and the cost-benefit balance degree of fabricated building construction management can be improved.