303 results about "Service Interface for Real Time Information" patented technology

Systems and methods for dynamic knowledge integration in LLM systems including receiving multimodal input data comprising text, image, audio, video, and / or code data, extracting information by processing the multimodal input data through a document processor, storing the extracted information in a dynamic knowledge base, receiving a user query at a query processor, identifying knowledge domains related to the user query using domain-specific agents, retrieving real-time information from the dynamic knowledge base responsive to the identified knowledge domains, integrating the real-time information into the processing of an LLM by a dynamic knowledge integrator, and generating a response using the LLM with the real-time information.

The invention relates to the technical field of water conservancy management, and discloses a water conservancy dynamic decision-making method and system based on digital twinning and multi-source heterogeneous data, and the method comprises the steps: carrying out the real-time information capturing of a target water conservancy system, and generating a system operation information scheduling matrix based on a grid geographic model and a time dislocation mark; performing hierarchical slicing on the system operation information scheduling matrix according to a multi-scale time window to form a multi-channel flow framework of regional hydrological dynamic behaviors; analyzing the evolution trends of the water level, the flow and the water quality by using a multi-channel flowing framework and a dynamic fusion analysis operator; dividing a river reach, a reservoir and a regulation and control facility corresponding to the potential risk event as candidate scheduling areas; and based on the local risk coupling network, dynamically optimizing a scheduling strategy, a pump gate operation sequence and a data acquisition frequency, and generating a real-time scheduling and emergency response scheme of the candidate region. The method has the advantage of improving flood early warning accuracy and water supply scheduling efficiency.

The invention provides a data physical node isolation scheduling method and system, and belongs to the technical field of distributed storage and cloud computing. The method comprises the steps of collecting attribute information of tenants and establishing a tenant demand model; monitoring in real time and predicting the resource load of the physical node by using machine learning, and generating a resource evaluation report; formulating differentiated isolation strategies according to the data security levels of the tenants, adopting physical isolation for the tenants with high security levels, and distributing independent physical nodes for the tenants; the scheduling priority is allocated based on the business emergency degree and the resource demand of the tenant, the node load condition is combined, the high-priority tenant is preferentially scheduled to the node with the load lower than the preset threshold value, and meanwhile, the strategy is dynamically adjusted according to real-time information. The corresponding system comprises a tenant management module, a resource monitoring module, an isolation control module and a scheduling decision module. Unification of data security isolation and efficient and dynamic resource scheduling in a multi-tenant environment is achieved, data security and service quality are effectively guaranteed, and the resource utilization rate is increased.

The invention proposes a robot path planning algorithm based on a particle swarm optimization algorithm and a dynamic window method, and relates to the field of control theories and electronic information, and the method comprises the steps: introducing an inertia weight updating strategy based on a state factor, setting adaptive parameters and crossover and mutation operators to improve the global search capability, increase the population diversity, and improve the robot path planning precision. On-line self-adaptive updating of inertia weight and learning factors is realized on line in combination with Q-learning, gene combination modes are enriched through crossover operators, convergence and exploratory performance of the algorithm are improved, an obstacle avoidance strategy of a traditional DWA algorithm is improved, weight parameters of a dynamic window evaluation function are dynamically adjusted according to real-time information of a target and an obstacle, and an obstacle avoidance algorithm is established. According to the method, the global planning is adopted, the path points generated through global planning are adopted as temporary targets, fusion of MOQLCOPSO and the improved DWA algorithm is achieved, local optimum is effectively avoided, the planning efficiency and path safety are improved, and the method is suitable for mobile robot navigation under the complex three-dimensional terrain.

The invention relates to the technical field of vehicles, and discloses an engine intelligent layered thermal management system and method based on multivariable predictive control, and the system comprises a thermal management execution module, an information sensing module and an intelligent control module; the information sensing module is used for collecting real-time information and sending the real-time information to the intelligent control module; the information sensing module comprises a plurality of sensors and a communication interface, the plurality of sensors at least cover a temperature sensor, a pressure sensor and a flow sensor, and the communication interface is used for obtaining engine torque, rotating speed, fuel injection amount, boost pressure and vehicle speed information; the intelligent control module receives the real-time information sent by the information sensing module, performs thermal load prediction and multi-target optimization calculation to obtain an optimal control sequence, and sends the optimal control sequence to the thermal management execution module; and the thermal management execution module receives the optimal control sequence and calls an execution element to execute a thermal management action.

The invention relates to the technical field of scenic spot route planning, and provides a scenic spot global collaborative touring planning method and system, and the method comprises the steps: constructing a scenic spot environment depth model, and deploying an ant colony algorithm on the constructed scenic spot environment depth model through key parameter initialization and tabu table initialization; path selection is carried out by executing ant colony movement, and real-time information updating and ant colony collaborative obstacle avoidance are carried out in the movement process; constructing a pheromone updating rule to update global pheromones, and judging and outputting an optimal path through iterative convergence; and performing multi-dimensional verification on the output optimal path, and generating a personalized touring scheme according to the path passing the verification. According to the invention, collaborative planning and dynamic optimization of the scenic spot sightseeing path are realized, the sightseeing efficiency of tourists is effectively improved, the queuing time is reduced, the information interaction comprehensiveness is enhanced, and the overall operation efficiency and tourist experience of the scenic spot are remarkably improved.

The invention discloses an intelligent fire-fighting resource dynamic scheduling method based on the Internet of Things, and relates to the technical field of fire-fighting emergency intelligent scheduling, and the method comprises the steps: collecting fire-fighting global situation awareness data, synchronizing the data to a central database through an encryption protocol, and constructing a fire-fighting real-time commanding combat information system; based on a combat information system of fire-fighting real-time commanding, a combat guarantee scheme is formulated, meanwhile, fire-fighting power information, geographical and meteorological information and field real-time information are collected, and a dynamic dispatching instruction is generated; dynamically mapping the dynamic scheduling instruction to a fire-fighting resource state, generating a resource state mapping table, optimizing resource allocation through a resource priority scoring function and a linear programming model, and generating a resource scheduling scheme; performing Bayesian verification and rating processing on professional pointing information in execution of the resource scheduling scheme to generate a targeted action instruction; according to the method, the continuous evolution capability of the scheduling model is realized through a multi-agent voxel learning parameter adjustment framework of the empirical rule base.

The invention relates to the field of railway shunting management and control, and provides a field intelligent shunting management and control method and device.The method comprises the steps that field real-time information is obtained, and the field real-time information comprises a vehicle license plate picture, laser ranging information and an original signal collected by a track circuit; the field section real-time information is recognized, modeling information is obtained, and the modeling information comprises vehicle identity information, vehicle position coordinates and real-time station track occupancy states; establishing a digital twinborn model according to the modeling information; performing dynamic planning algorithm processing according to the digital twinborn model in combination with preset vehicle target distribution, station track capacity limitation and locomotive performance parameters to obtain a shunting coupler plan; the turnout position is adjusted to the preset angle according to the shunting coupler plan, the overall efficiency of shunting operation and the accuracy of the plan can be remarkably improved, and the safety and reliability of the operation process are effectively enhanced.

A method for using contextual searching, such as intelligent search engines, to search for specialized machine learning models, such as customized LLMs (LLMs) tailored to individuals, organizations, and entities, to provide users with access to real-time data, static data, and advanced search capabilities. Therefore, methods and systems are described herein for ensuring precise and efficient information retrieval by identifying relevant artificial intelligence models, such as custom large-language models.

Secure blockchain (BC)-based tokens are issued and linked to payment cards and / or devices of customers. Custom conditions associated with the tokens are stored in smart contracts on a BC. The tokens are stored in a cloud-based key vault and / or in the BC. Validation of a token for access a smart contract on the BC can only be made by a financial institution (FI) to the key vault. Real-time information for a transaction device, for transaction information, and / or for the customer is provided as input data to the smart contract for evaluation of the conditions. After the token is authenticated by the key vault, the real-time information is gathered and passed to the corresponding smart contract on the BC for evaluation. The FI receives transaction authorization or transaction denial based on the smart contract's evaluation of the conditions.

The invention relates to the technical field of automatic feeding and discharging, in particular to an intelligent control system for automatic feeding and discharging of wood-working machinery, which comprises the following modules: a multi-sensor real-time sensing module used for collecting real-time information of plates and a field environment and generating plate state information; the intelligent scheduling and optimizing module is used for generating a grabbing and placing action plan of the feeding and discharging manipulator according to the plate state information, the machining rhythm of the cutting machine, the plate specification and the stacking area state, and sending an action instruction to the feeding and discharging manipulator; and a multi-device coordinated scheduling module. According to the method, the plate state information, the processing rhythm and the stacking area state are received, the grabbing priority, the placing position and the action path are calculated, meanwhile, path and sequence optimization is conducted by combining the current position, the motion constraint and the time relation of all equipment, and a coordinated action sequence is generated and issued for execution; the system can dynamically adjust the action sequence and path of equipment to avoid idling of the manipulator or congestion of a stacking area.

A robot fleet platform for preparing a job request includes one or more processors configured to execute instructions. The instructions include a job request ingestion system configured to receive job content relating to at least one of picking, packing, moving, storing, warehousing, transporting or delivering of items in a supply chain. The job content includes an electronic job request and related data. The instructions include a job content parsing system configured to apply filters to the received job content to identify candidate portions thereof for robot automation. The instructions include a fleet intelligence layer that activates a set of intelligence services to process terms in the candidate portions of the job content and receive therefrom at least one recommended robot task and associated contextual information. The instructions include a demand intelligence layer that provides real time information relating to a parameter of demand for the items in the supply chain.

A knowledge graph-based nuclear power plant fault diagnosis and display method and system, an electronic device, and a storage medium. The method comprises the following steps: monitoring, in real time, a key device to be monitored, and acquiring real-time information of said key device (S101); on the basis of the real-time information, determining whether there is an anomaly early-warning for said key device (S102); if there is an anomaly early-warning, identifying a fault data feature of said key device (S103); acquiring a related knowledge graph model in a knowledge base and calling the knowledge graph model (S104); performing complex knowledge decomposition and reasoning on the basis of the related knowledge graph model and the fault data feature to obtain a fault diagnosis result (S105); and displaying the fault diagnosis result (S106).

The application belongs to the field of evaluation assistance, and particularly relates to an interactive teaching evaluation assistance system and device based on multi-modal fusion. The system collects multi-dimensional information through a portrait module, combines multi-modal feature extraction and a knowledge graph algorithm to construct a user training action portrait library. A strategy recommendation module generates an optimal guidance scheme from a portrait library, real-time information and a teaching guidance strategy library through a correction scheme matching model. An auxiliary adjustment module collects training action images in real time, uses a space-time feature extraction model and an evaluation algorithm to obtain a continuous correction action sequence and a standard score after guidance. A traceability feedback module combines an action standard knowledge base, obtains a horizontal and vertical space-time change chain of non-standard actions through a forward reasoning model, and feeds back to the instructor to adjust the scheme in real time until the action meets the standard. The application realizes precise evaluation and personalized scheme matching of multi-modal data fusion, and effectively improves the scientificity and interactivity of evaluation assistance.

The invention relates to the technical field of artificial intelligence and multi-agent cooperative control, in particular to an agent autonomous cooperation method and system based on group hierarchical cooperation, and the method comprises the steps: responding to a natural language task request input by a user; generating a preliminary task execution plan based on the task description data, selecting expert agents matched with sub-tasks in the task execution plan from the group, and generating a task allocation instruction to perform task cooperation; and each expert agent receives the task allocation instruction to execute the corresponding sub-task, writes an execution state, a stage result and intermediate data into a group memory space in real time in an execution process, and performs semantic integration and induction after all the sub-tasks are executed to generate a unified task output result. Under the unified command of the super agent, each expert agent can realize autonomous cooperation and real-time information sharing based on the group memory space, and realize adaptive dynamic re-planning when the task is abnormal or the environment is changed.

1. The name of the design product: electronic device energy storage battery real-time information viewing graphical user interface. 2. The use of the design product: for an electronic device. 3. The design points of the design product: in the graphical user interface. 4. The picture or photo that best indicates the design points: design 2 front view. 5. Design 2 is designated as the basic design. 6. The use of the graphical user interface: for viewing energy storage battery real-time information. 7. The change state description of the graphical user interface: double-click "real-time information" in design 1 front view to enter design 1 change state diagram; double-click "real-time information" in design 2 front view to enter design 2 change state diagram; double-click "real-time information" in design 3 front view to enter design 3 change state diagram; double-click "real-time information" in design 4 front view to enter design 4 change state diagram. 8. Other circumstances that need to be explained: X is the text content.

The invention relates to the field of enterprise group portrait design, in particular to a design method for constructing a high-tech enterprise group portrait based on enterprise data, and realizes real-time information tracing and accurate information confirmation of high-tech enterprise production data information through analysis and design of the enterprise data. The design method comprises the following steps: step 1, capturing basic information and production industry data of each enterprise from an enterprise database; 2, inputting the production industry data into a preset production-creation evaluation model for analysis, and obtaining an innovation ability score; step 3, layering each enterprise according to the innovation ability score, taking a layering result as a label, performing feature clustering in combination with enterprise process parameters and productivity utilization rate, and establishing an enterprise group portrait; and 4, performing performance evaluation on the constructed enterprise group portrait, and optimizing and adjusting a parameter interval of the enterprise group portrait according to a performance evaluation result.

The technical scheme of the invention discloses a multi-source data fusion and intelligent processing method for vehicle network interaction. According to the invention, a multi-source data fusion and intelligent processing architecture oriented to vehicle network interaction is constructed, and technologies of multi-source heterogeneous data access, standardized modeling, distributed data processing, machine learning prediction, optimization scheduling and the like are comprehensively applied; real-time information interaction and collaborative optimization control among multiple subjects such as an electric vehicle, a charging facility and a power grid dispatching system are realized. Compared with the prior art, the scheme disclosed by the invention has the advantages that the data processing capability, the prediction precision, the response speed and the system adaptability are remarkably improved, and the requirements of vehicle network interaction large-scale application can be better met.

Systems, methods, and computer readable medium are disclosed for performance of network connection operations. Performance of network connection operations includes accessing a cloud service via a client device, the cloud service containing real-time network information including at least two of a real-time server load for a plurality of servers, real-time server capacity, a customer preference, or geolocation IP; receiving from the cloud service, identities of a plurality of candidate servers from the servers, wherein, based on the real time information, the candidate servers meet criteria for potential establishment of a connection with the client device; transmitting probe packets from the client device to at least some of the candidate servers; receiving responses to the probe packets; determining from the responses, communication characteristics for at least some of the probe packets; selecting a server based on the communication characteristics; and establishing a connection between the client device and the selected server.

Aspects related to a prognostic compliance model using real-time information taxonomy are provided. A modeling platform may access regulation information associated with an event processing request. The platform may generate a prediction summary using a prognostic model. The prediction summary may include a predicted event processing request and information of one or more potential conflicts. The platform may generate, using the prognostic model and based on the prediction summary, a conflict alert. The conflict alert may correspond to the event processing request or predicted event processing request. The platform may output the conflict alert to a user device. The platform may receive feedback information corresponding to the conflict alert. The platform may update the prognostic model based on the feedback information.

This application relates to the field of vehicle control technology and discloses a predictive control method and system based on road surface adhesion coefficient. In this method, a cloud server acquires real-time information uploaded by vehicles on the road. The cloud server can combine the real-time information with historical information from each grid to form a road surface adhesion coefficient matrix. The cloud server sends the road surface adhesion coefficient matrix to the vehicle. Based on the road surface adhesion coefficient matrix, the vehicle's current position, and navigation path, the vehicle determines the predicted road surface adhesion coefficient value in its current direction of travel. Based on the predicted road surface adhesion coefficient value, the vehicle calculates the upper limit of its regenerative braking capacity and / or the upper limit of its driving torque, and then controls the vehicle accordingly. The beneficial effect is improved vehicle control efficiency on low-adhesion roads.

An object of a system according to an embodiment is to provide an optimal tour plan according to a situation of an individual or a group.SOLUTION: A system according to an embodiment includes a generation AI, AR technology, a customization unit, a real-time information provision unit, and a feedback collection unit. The generation AI analyzes a user's interest, a past visit history, and a current situation and generates an optimal tour plan. AR technology enhances the experience in the field. The customization unit customizes the tour plan in accordance with a situation of an individual or an organization. The real-time information providing unit provides information in real time. The feedback collection unit collects feedback from the user.SELECTED DRAWING: Figure 1

The invention discloses a rail transit monitoring and decision-making method and device based on image recognition and artificial intelligence. The rail transit monitoring and decision-making method based on image recognition and artificial intelligence comprises the following steps: acquiring an ATS interface frame image with a timestamp acquired by an external camera device or a video acquisition card; performing information extraction on the ATS interface frame image to obtain a structured real-time information set; obtaining abnormal event detail information according to the obtained structured real-time information set; generating suggested operation instruction information according to the abnormal event detail information; and displaying the suggested operation instruction information and carrying out multi-channel pushing. The ATS interface image is acquired through the external camera or the video acquisition card, direct data interaction with software and hardware of the ATS system is avoided, interference on the SIL (security integrity level) of the ATS system is avoided, the ATS interface image acquisition device can adapt to the ATS systems of different manufacturers and different versions, and compatibility risks and potential safety hazards caused by traditional intrusive interface modification are solved.

The invention discloses a power distribution network map-oriented real-time primitive display method and system, and the method comprises the steps: triggering the real-time primitive display of a power distribution network map when the power distribution network map is initialized or the visual field of the power distribution network changes; obtaining power distribution network type geographic element information according to the power distribution network map view field; drawing a to-be-displayed static primitive to a cache, and obtaining primitive file information from a server through a primitive file name in the geographic element information; the power distribution network map request mode is used for drawing a real-time primitive, sending a power distribution network object identifier needing to be drawn to a power distribution network real-time information primitive subscription service, and pushing real-time information corresponding to a power distribution network object to a map through a pushing service; the power distribution network map pushing mode is used for drawing real-time primitives, and in the drawn primitives, the primitive information with changed real-time information is incrementally pushed for the power distribution network map to refresh the primitives; technical support can be provided for stable operation and efficient decision making of the dispatching automation system.

The application relates to the technical field of maintenance planning, and particularly discloses a landscape greening maintenance planning method and system based on big data, which comprises the following steps: constructing a maintenance area model, updating the maintenance area model based on a photographed image; performing rasterization processing on the maintenance area model to determine greening parameters in each grid area; clustering the grid areas based on the greening parameters, synchronously determining the demand accuracy of each type of grid area, obtaining real-time information of each grid area, feeding back the real-time information to a management end, and receiving a maintenance scheme containing a maintenance target fed back by the management end. The application constructs a landscape model based on a BIM model, updates the landscape model based on a large amount of image data, the real-time performance of the landscape model is extremely high, software analysis is performed on the landscape model, the maintenance target can be determined, more targeted maintenance tasks can be generated, and the manpower workload is greatly reduced while the maintenance effect is almost unchanged.

A vehicle includes an on-hoard satellite navigation device, a telematics control unit, a non-transitory computer readable medium, and a processor. The on-board satellite navigation device is in communication with a global positioning system unit to acquire real-time information regarding conditions near the vehicle's vicinity. The telematics control unit is in wireless communications to a cloud services or a vehicle network to upload and receive crowdsourced information regarding conditions near the vehicle's vicinity. The non-transitory computer readable medium stores predetermined information regarding conditions near the vehicle vicinity. The processor is programmed to output one or more complexity values related to the vehicle's vicinity during vehicle travel based on one or more of the real-time information, the crowdsourced information and the predetermined information.

The present application relates to a kind of methods for realizing network content risk analysis based on key points driving, comprising the following steps: depth semantic analysis is carried out to original text, and risk key points are identified and extracted;According to the preset confidence threshold filtering low reliability key points, calling big model intelligent screening risk key points;Multi-source evidence online retrieval is carried out, and multi-source search results are integrated and risk tendency determination;Multi-dimensional risk research and judgment is carried out.The method for realizing network content risk analysis based on key points driving, device, processor and computer readable storage medium thereof of the present application are adopted, by reconstructing analysis process with risk key points as core, and comprehensively deciding by depth fusion local semantic knowledge and external real-time information, surpassing existing technology in precision, explainability and flexibility etc.Dimensions, provide solid technical foundation for constructing next-generation intelligent, efficient, reliable network content risk prevention and control system, and have important practical value and innovation.

The application discloses a novel anti-fake traceability system and method, relates to the technical field of anti-fake traceability, and comprises a data acquisition unit, an abnormality tracing unit and a determination output unit. The data acquisition unit is used for acquiring a product identification code, acquiring business data of a current link through preset data acquisition points of each circulation link, updating and generating a dynamic product unique identification code, determining real-time information data of the product based on a scanning code reading result of the dynamic product unique identification code, synchronously writing the business data of the current link, comparing the real-time information data of the product according to preset scanning code standard data, determining a circulation state of the product, and correspondingly generating abnormal early warning information in the abnormal circulation state of the product. The application can ensure the reliability and timeliness of a tracing result, and also improves the accuracy of abnormal determination of goods diversion.

The application discloses a micro-grid self-adjusting energy management system and method combined with AI and an intelligent terminal, and relates to the technical field of power system automation. The system comprises: a real-time information acquisition module for acquiring real-time operation state information of a target micro-grid and corresponding charging station information; an expected load prediction module for generating expected load prediction information of the target micro-grid within a future preset management window based on the real-time operation state information and the charging station information, in combination with a pre-constructed expected load prediction model; an adjustment margin optimization module for maximizing the adjustment capacity margin of the target micro-grid within a future preset period as a target, establishing an optimization task and solving it, and outputting a power limit value corresponding to each charging interface; and a charging load control module for distributing and managing the charging load of the target micro-grid according to the power limit value. The application effectively improves the load prediction accuracy and enhances the operation stability of the micro-grid self-adjustment.

The invention discloses an mrk image three-dimensional visualization and plotting method based on digital twinning, and relates to the technical field of GIS and three-dimensional visualization, by establishing a digital twinning body of an mrk image in a deduction system, the mrk image generated according to a combat scenario in the real world can be conveniently mapped to a virtual space, and the real-time performance of the mrk image is improved. Therefore, deduction simulation, optimal route planning, formation of combat scheme suggestions and conversion into mrk graphs can be carried out by utilizing marine environment information, real-time situation data and underwater sound field calculation, full interaction between virtuality and reality is realized, optimal decision is carried out by utilizing simulation deduction, and the real-time situation data and the underwater sound field calculation can be realized. The method overcomes the defects that an mrk graph is stiff and is difficult to formulate an optimization scheme in combination with complex conditions such as marine environment information and a friend or foe situation, and fully utilizes the capabilities of flexible trend distribution, real-time information access, marine environment information support and efficient dynamic optimization of a deduction system.