835 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 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.

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 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.

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.

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 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.

The invention provides a data asset management system and method based on a data asset catalogue, and the system comprises a data classification and structure management module which is used for dividing data into examples, examples and cases, and carrying out the standardized definition, index establishment and retrieval support of the storage forms of all kinds of data through a metadata management module; the data asset life cycle management module is used for recording and controlling the state of the data assets in each stage in the life cycle from development to commercialization in the process of converting the data into the data assets, and describing process information of various artificial products generated by the data assets in the life cycle and mutual relations of the process information through the metadata management module; and the data asset blood relationship management module is used for recording dependency relationships between data sources and data applications and between the data applications through a hierarchical management strategy and a data asset reference model between different management levels so as to form a traceable chain between the data assets.

The invention discloses an indoor and outdoor fine three-dimensional modeling method based on multi-modal data fusion. The method comprises the steps that unmanned aerial vehicle close-range photography, airborne laser scanning and ground supplementary photography are carried out on a building in a low-altitude area, and a first outdoor photo data set, a first laser point cloud data set and a POS data set of the building are obtained; continuously collecting at an indoor entrance through a laser SLAM mobile scanning system and a panorama camera according to a pre-planned route to obtain a second indoor photo data set and a second laser point cloud data set of the building; aerial triangulation adjustment calculation of a multi-source data set is carried out under the assistance of a POS data set, and an indoor and outdoor integrated fine surface three-dimensional model is automatically constructed. According to the method, the indoor and outdoor integrated surface three-dimensional model of the large building can be duplicated, the element cosmic space base scene is realized, and data application is provided for the industries of element cosmic scenes, indoor navigation, surveying and mapping and the like.

The invention discloses an intelligent agricultural big data system, and belongs to the field of agricultural big data, and the system comprises an environment monitoring module, a sensing layer deploys a sensor to collect original data, and a transmission layer is provided with an edge gateway which is connected with the sensor and carries out the transmission of the original data; the equipment layer is used for regulating and controlling irrigation, ventilation and light supplement schemes, and the control layer is used for optimizing MQTT message middleware to control the agricultural Internet of Things system; according to the data management module, a data collection layer obtains original data, a data processing layer processes the original data according to a three-layer data cleaning mechanism, and a data storage layer stores the processed data; according to the system management module, the data application layer constructs an interface covering Web, a mobile terminal and AR equipment, the data display layer generates a soil moisture thermodynamic diagram, a crop growth distribution diagram and an equipment operation state diagram, and intelligent management of agricultural production is ensured. The advanced Internet of Things technology is adopted, and the accuracy and the real-time performance of data acquisition are improved.

The invention discloses a server health examination method and device, equipment and a medium. The method comprises the following steps: acquiring hardware layer data, system layer data, application layer data and physical environment layer data of a target server through a data acquisition component; determining a current value and a predicted change range of each health index regularly, and determining a current health level and a predicted health level range of the target server according to the current value and the predicted change range of each health index; when the current health level belongs to an abnormal level, executing a self-healing operation corresponding to the current health level; and when the predicted health level range contains an abnormal level, executing an early warning operation. According to the embodiment of the invention, real-time quantitative evaluation, abnormity prediction, early warning and automatic repair of the health state of the server can be realized, health evaluation and health pre-judgment can be comprehensively and accurately carried out on the server, and the operation stability of the server is improved.

The embodiment of the invention discloses an OCR (Optical Character Recognition)-based customer and merchant data generation method and device and a medium, and relates to the technical field of data processing, and the method comprises the steps: obtaining original customer and merchant image data corresponding to a target customer and merchant, carrying out the key field recognition of the original customer and merchant image data through an OCR recognition technology, and determining an OCR recognition result; calling a preset third-party data service interface, acquiring enterprise industrial and commercial information of the target customer service provider, performing dual-channel data verification according to the enterprise industrial and commercial information and the OCR recognition result, and determining customer service provider verification result data, the customer service provider verification result data including verification results of multiple pieces of customer service provider data; performing graded approval on the plurality of pieces of customer and merchant data through the customer and merchant verification result data and a preset business processing rule, and determining approval graded data of the customer and merchant data; and according to the approval grading data of the customer and merchant data, determining the data flow direction of the customer and merchant data, and based on the data flow direction of the customer and merchant data, generating a customer and merchant main data application form.

The invention belongs to the technical field of sensor measurement and recognition, and particularly relates to a human body motion recognition system based on LSTM (Long Short Term Memory), which comprises a data acquisition module, a data calculation module and a data application module, and utilizes a neural network model and a wearable electronic sensor to detect a human body walking state. A new long short term memory (LSTM) recurrent neural network model, namely an LSTM-STRM model, is established, the model combines multi-task learning, an attention mechanism and spatio-temporal feature fusion to accurately classify the walking state of the human body, and the walking state is compared with the original LSTM model. The result shows that the LSTM-STRM model can be used for classifying the time sequence data collected by the measuring unit, the states of the five targets can be classified with high precision, and the recognition accuracy is higher than that of an original LSTM model. The method improves the recognition precision, is high in adaptability, is suitable for the fields of medical treatment, human-computer interaction, exercise training and the like, and has a wide application prospect.

The application provides a security management system and method applied to a smart education platform, wherein the system comprises: a platform application security management module, which is used for performing security management on a data application layer of the smart education platform; a data security management module, which is used for performing security management on a data storage layer of the smart education platform; and a big data component security management module, which is used for performing security management on a big data basic component layer of the smart education platform. The security management system applied to the smart education platform of the application performs security management on the data application layer, the data storage layer and the big data basic component layer of the smart education platform through the platform application security management module, the data security management module and the big data component security management module, so that the security of the big data platform is ensured.