17results about How to "Solve information silos" patented technology

The invention relates to a technical method for automatically checking converted product names, which belongs to the technical field of automatic processing of data in the manufacturing industry and comprises the following operation steps of: 1, receiving an original product name and a target product name input by a user; 2, automatically calculating and identifying a difference item between the original product name and the target product name based on a natural language processing technology and a feature word extraction rule; and a third step of obtaining related batch data and quality standard data from the BIP system according to the identified difference item code. And 4, automatically checking and analyzing the acquired data by utilizing an automatic checking engine. And 5, generating a checking report containing batch information which does not meet the requirement, and displaying a checking result through a visual interface. The system has the characteristics of automation, intellectualization, integration and precision. The problems that manual operation efficiency is low, errors are prone to occurring, checking items are omitted, and batch information is misread in the traditional transferred product name checking process are solved.

This invention relates to the field of terminology database technology in the construction engineering field, and discloses a method and system for constructing and applying a terminology database in the construction engineering field. The method includes preprocessing unstructured data to obtain structured construction engineering text data; extracting structured construction engineering text data based on a joint extraction architecture to obtain structured terminology data and construction engineering triple information; establishing a standard database and a terminology database; constructing a terminology-standard two-layer knowledge graph based on the inherent relationship between the standard database and the terminology database and the construction engineering triple information; and responding to user queries by using a hybrid decision-making mechanism based on rule-based reasoning and graph neural network learning to call the standard database, terminology database, and terminology-standard two-layer knowledge graph to obtain query results. This invention realizes an intelligent closed loop for the entire lifecycle of construction engineering terminology from extraction and management to application, solving the problems of difficult acquisition, complex management, and inefficient application of industry terminology knowledge.

The present application relates to the technical field of vehicle identity authentication, and discloses a vehicle distributed identity authentication method and system based on biological characteristics, which comprises the following steps: a user completes initial biological characteristic registration on a source vehicle, and biological characteristics are bound with random keys by a fuzzy binding algorithm to generate a binding factor and a biological characteristic hash value and store them in association; when the user uses a target vehicle, the target vehicle locates the source vehicle according to the user identity and requests verification. The source vehicle sends the binding factor and the biological characteristic hash value to the target vehicle; the target vehicle collects the current biological characteristics of the user, recovers the candidate key by decoding operation using the binding factor, and generates a temporary biological characteristic hash value; and the authentication is completed by comparing the temporary biological characteristic hash value with the received biological characteristic hash value. The method uses a decentralized hash transmission and fuzzy binding verification mechanism to realize efficient, safe and non-repeated cross-vehicle identity authentication on the premise of protecting the privacy of biological characteristics.

The invention discloses a cross-platform information acquisition and public opinion processing optimization method and system. The method comprises the following steps: collecting network public opinion data from a plurality of independent public opinion monitoring subsystems; performing standardized preprocessing on the collected data from different subsystems to generate standard public opinion data in a unified format; performing public opinion analysis on the standard public opinion data based on a multi-dimensional analysis model, and generating an analysis result containing propagation popularity and risk assessment; and generating a public opinion monitoring report and early warning information according to an analysis result. The system comprises corresponding function modules. According to the method, multi-source data are integrated through a unified framework, deep analysis is performed by using a multi-dimensional model, accurate monitoring, intelligent early warning and resource optimization of whole-network public opinions are realized, and the automation level and decision support capability of public opinion processing are effectively improved.

This application relates to a drone-nested power distribution application system and method based on power grid drone inspection, comprising an automatic drone nesting unit, a drone swarm, an edge computing unit, a collaborative scheduling unit, and an intelligent application unit. Each unit is connected to the dedicated power grid via a dual-link redundant transmission through a 5G network. The automatic drone nesting unit provides the drone swarm with automatic take-off and landing, intelligent power replenishment, and environmental adaptive protection. The drone swarm is equipped with multimodal sensors to collect images of distribution network equipment and environmental data. The edge computing unit, integrated within the drone nesting unit, performs multimodal data fusion, defect identification, and online incremental algorithm updates. The collaborative scheduling unit, based on a digital twin model of the distribution network, achieves unified scheduling, spatiotemporal isolation, and emergency response for multiple drones and tasks. The intelligent application unit seamlessly integrates with the power grid management platform to achieve task distribution and closed-loop processing of work orders. This application significantly improves inspection efficiency and defect identification accuracy while reducing operation and maintenance costs.

This invention discloses a multi-agent cooperative control method for cross-domain unmanned swarms across land, sea, air, and space, comprising the following steps: S1: Constructing a decoupling model to separate the complexity of cooperative control along three dimensions: hierarchical, frequency-based, and domain-based; S2: Based on the decoupling model, designing a unified cooperative strategy, which generates personalized control objectives adapted to the dynamics and roles of agents in different dimensions according to a dynamically updated cross-domain cooperative situation map; S3: Introducing an event-triggered distributed reinforcement learning mechanism for each agent, ensuring that the agent triggers only when preset triggering conditions are met. This invention, through a hierarchical-frequency-domain triple decoupling model, separates the extreme complexity of cross-domain cooperation along three orthogonal dimensions: task level, control frequency, and physical space, and defines a standard interface to encapsulate the dynamics of heterogeneous platforms, reducing the complexity of system design and analysis.

The application discloses a campus safety risk identification method and system based on multi-algorithm nested cooperation and a medium, relates to the technical field of campus risk identification, and constructs a dynamic rule library, matches all dynamic rule graphs corresponding to initial event signals from the dynamic rule library, and creates dynamic rule graph instances; each node is activated according to a topological order and an activation condition, the comprehensive confidence and the quasi-truth degree of a potential risk hypothesis are calculated at a convergence node based on DS evidence theory to perform risk early warning; multi-dimensional information is deeply associated and comprehensively judged, and the problems of information silos and low-level misjudgment are solved; a school calendar rhythm is converted into a time weight factor and embedded into a DS evidence fusion process, time background can be perceived, the contribution degree of different types of evidence and the sensitivity of risk decision-making can be automatically adjusted, false positives caused by neglecting context are reduced, and early and accurate early warning can be ensured in a high-risk period.

The present application relates to the field of biological sample collection device, in particular to a biological sample collection information tracing device, comprising: a tube body for storing biological samples; a sealing tube cover detachably installed at the opening of the tube body; a trigger component arranged between the tube body and the sealing tube cover; a clock chip cooperating with the trigger component to determine the opening time of the sealing tube cover; a memory for storing the opening time detected by the trigger component; a near field communication module for transmitting the opening time stored in the memory to a reading device; a microcontroller for processing the state of the trigger component to determine whether the sealing tube cover is opened and transmitting the information of the opening time to the memory; a circuit board for connecting the trigger component, the clock chip, the memory, the near field communication module and the microcontroller. The present application realizes the digitization and objective tracing state of the biological sample as soon as it is collected from the outside.

The present application relates to the technical field of metering informationization and intelligent management system, in particular to a kind of inspection and calibration system and device of intelligent inspection platform;Including: customer inspection digital acceptance module, sample intelligent receiving tracking module, detection execution automation integrated module, report automatic generation management module, provincial measurement resource sharing analysis module;The present application realizes inspection whole-process digitization, automation and intelligent management by constructing wisdom measurement inspection and calibration platform, significantly improves customer handling efficiency, reduces communication cost, eliminates sample confusion loss risk, improves detection data accuracy and task completion rate, shortens report issuing cycle and enhances standardization and anti-fake ability, simultaneously creates new mode of centralized sharing of provincial measurement resources, breaks information silos, provides strong support for administrative supervision, agency optimization and customer traceability, overall reduces inspection cost, improves service quality, promotes high-quality development of measurement industry.

The application provides a kind of city traffic operation management system and method based on big data, by obtaining initial traffic data of city traffic from each database, and the initial traffic data is standardized and integrated, and multidimensional traffic data is obtained, the integration of various data sources is realized, the content of traffic data is enriched, the problem of information island is solved, by based on the multidimensional traffic data, combined with management requirements, build multiple city traffic management models, establish various management models, realize the arrangement of each type of traffic data, provide effective data information for subsequent decision-making, by visualizing the city traffic management model, it is convenient for decision-makers to intuitively understand the traffic operation, according to traffic demand, based on visual display data, combined with artificial intelligence, get traffic decision, realize the precise acquisition of traffic decision, promote green traffic construction and industry governance.

The utility model discloses an aluminum electrolysis cell shell temperature monitoring system, which comprises a monitoring client, a cell shell temperature monitoring cloud platform and a plurality of local acquisition and control units, and each local acquisition and control unit comprises a plurality of temperature sensors and a plurality of heat dissipation modules; and each on-site acquisition and control unit acquires temperature data of key point positions of the electrolytic cell shell in real time through the temperature sensor, accurately controls the work of the heat dissipation module according to a preset temperature threshold value, and monitors the state of the heat dissipation module. According to the scheme, the problems of exception handling lag and information isolated island of traditional aluminum electrolysis cell shell temperature monitoring can be solved. Automatic temperature adjustment can be achieved, production risks caused by manual delay are avoided, data are integrated, barriers are broken, enterprises are helped to optimize the process, energy is saved, efficiency is improved, the electrolytic aluminum efficiency is effectively improved, intelligent transformation of the industry is promoted, and competitiveness is improved.

The invention discloses an agricultural ecological water utilization potential mining method and system based on a block chain, and belongs to the technical field of agricultural information. The method comprises the following steps: collecting agricultural water data through the Internet of Things, and ensuring credibility through blockchain evidence storage; on the basis of on-chain data, dynamically accounting the gridding ecological water utilization potential by using a model fusing a physical mechanism and deep learning; a water right transfer and ecological compensation protocol is automatically generated and executed through an intelligent contract, and ownership transfer and payment automation are achieved; and constructing an incentive and on-chain governance mechanism based on contribution proof, distributing tokens according to data quality, water saving amount and governance participation, and updating system parameters through right proof voting. The system correspondingly comprises a data storage module, a potential accounting module, an intelligent contract module and an incentive management module. According to the method, credible evaluation, efficient conversion and sustainable operation of the agricultural water-saving potential are realized.

The invention relates to the technical field of power system analysis and data processing, discloses a combined extraction method of a power grid topological structure and electrical parameters, and aims to solve the problems of fragmentation and inconsistency of topology and parameter information caused by data source splitting in traditional power grid design data processing. The method comprises the following steps: constructing a multi-modal analysis framework, and synchronously processing a wiring diagram, an equipment inventory, a specification and a nameplate image; extracting a power grid topological structure based on a graph neural network, identifying equipment symbols and reasoning complex connection logic; extracting electrical parameters such as voltage class and rated capacity from the text by using a named entity recognition and relation extraction technology; performing joint alignment and consistency verification on topology and parameters through cross-modal matching and power grid design specification constraint; and finally, a structured power grid digital model conforming to the IEC 61970 CIM standard is output, synchronous and high-precision combined extraction of the topological connection relation and the electrical attributes is realized, and high-quality data support is provided for power grid intelligent review and risk early warning.

The invention discloses a vehicle intelligent management method and system based on multi-dimensional data perception and dynamic analysis, and aims to solve the problems of lag distortion of vehicle management data, stiffness of an assessment mechanism, passive safety management and information isolated island of an existing aluminum processing enterprise. The system comprises a vehicle-mounted intelligent terminal, a cloud management platform and a user interaction terminal, a vehicle management system is constructed through an integrated scheme of hardware sensing, a software platform and an intelligent algorithm, and the management method comprises dynamic profit assessment, intelligent salary commission, predictive maintenance, dynamic fuel consumption standard management, active safety management and cargo loading intelligent check. Real-time data acquisition and automatic analysis are realized, management is upgraded from experience driving to data and algorithm driving, post-processing is converted into beforehand early warning and in-process intervention, multi-system data flow is broken through, accurate transportation cost management and control, transportation safety beforehand prevention and transportation capacity resource optimization configuration are realized, and the transportation efficiency is improved. And the management efficiency and the decision scientificity are obviously improved.

The application discloses a kind of coal mine multi-source data gathering management method and platform, it is related to coal mine data processing technical field, platform uses five progressive type architecture of sensing layer-edge layer-transmission layer-platform layer-application layer, method covers multi-source heterogeneous data acquisition and edge integrated processing, double-ring redundant low-delay transmission, data depth management, Kafka priority subscription distribution, whole-service collaborative control feedback whole process, by multi-protocol adaptation, 3 sigma criterion+linear interpolation data cleaning, hierarchical fusion intelligent labeling, hierarchical directional distribution and closed-loop feedback etc. Technology, solve coal mine multi-protocol access adaptation, data efficient flow, high-quality management and whole-service collaborative control industry problem.The application greatly improves data acquisition, flow, management efficiency and reliability, realizes coal mine whole-service data intercommunication and collaborative control, reduces the incidence of safety accidents, improves production and operation efficiency.

This disclosure relates to the field of core network technology, and in particular to a signaling processing method, apparatus, device, medium, and product for inter-network roaming. The method includes: receiving signaling sent by a user terminal; identifying whether the signaling is an inter-network roaming service according to a pre-configured roaming mapping table; in response to the signaling being an inter-network roaming service, obtaining a preset shared key between the home operator network and the visited operator network, and generating a security verification code based on the shared key and the content of the signaling; adding roaming relay information to the extended header field of the signaling according to the roaming mapping table to obtain complete signaling; and sending the complete signaling to the second operator network. Generating a security verification code through the preset shared key between the home operator network and the visited operator network and the signaling content ensures the integrity of the signaling. Attackers who do not know the shared key cannot forge the correct security verification code, preventing signaling tampering and ensuring the security of signaling transmission.

The application provides a small and medium-sized factory digital transformation system and method based on multi-agent cooperation, taking a central coordination agent as a total control core, deploying professional AI agents such as safety monitoring, factory monitoring, project management and multi-field development, and each agent undertakes intelligent responsibilities of factory safety, production, equipment, quality and development. The system greatly reduces the digital technology use threshold through natural language interaction mode, realizes encrypted communication and efficient cooperation among multi-agents based on the sessions_send message queue built in OpenClaw, and has the abilities of agent autonomous optimization, abnormal autonomous intervention and full-link security protection, which can significantly reduce the deployment cost and technical threshold of small and medium-sized factory digital transformation, break the information silos of various business systems, realize the leap from passive monitoring to active early warning and autonomous intervention, and greatly accelerate the digital transformation landing process of small and medium-sized manufacturing enterprises.