842 results about "Area network" patented technology

The invention provides an enterprise employee behavior analysis and safety risk early warning monitoring method and system, and relates to the technical field of enterprise risk management, and the method comprises the steps: collecting employee terminal operation behavior data, building an activity thermal distribution diagram based on office area grid behavior association intensity, and training a behavior evaluation model. And inputting the behavior scoring matrix into a deep neural network to extract target behavior characteristics, calculating an abnormal behavior risk weight coefficient in combination with a department security policy, performing classification and analyzing a risk diffusion probability, and generating a risk situation index to determine an early warning level. Starting a response strategy according to the early warning level, blocking high-risk early warning in real time, tracking associated accounts, establishing a risk association map, identifying potential risk propagation nodes and performing active protection, finally generating an early warning report and feeding back effective protection rules to a behavior baseline model, and realizing continuous optimization of a risk early warning mechanism. And the accuracy and effectiveness of safety risk early warning in the enterprise are improved.

A diagnostic system and method for identifying and resolving vehicle Controller Area Network (CAN) bus faults is disclosed. The system connects to a vehicle's data link connector (DLC) and automatically retrieves diagnostic trouble codes (DTCs) from multiple electronic control units (ECUs). It filters the DTCs to identify those related to CAN communication errors, groups repeated DTCs across ECUs to highlight systemic faults, and assigns repair priority based on status, scope, and criticality. A user interface displays prioritized DTCs with definitions, affected systems, possible causes, and repair guidance. Upon technician input, the system re-scans the network to confirm resolution and updates the display accordingly. The invention supports semantic and conceptual recognition of communication faults, enabling robust, language-agnostic analysis. This system reduces diagnostic time, improves repair accuracy, and supports multilingual or manufacturer-specific DTC definitions without requiring external infrastructure or advanced user expertise.

The invention discloses a method for generating an autonomous inspection orthoimage of an unmanned aerial vehicle, and relates to the technical field of unmanned aerial vehicle surveying and mapping and autonomous navigation. Global optimization of an air route is realized through a path optimization strategy fused by a genetic algorithm in combination with grid characteristics of an inspection area and image parameter constraints, and candidate waypoints are used as nodes; redundant waypoints are screened through leg smoothness factors, route complexity is reduced, a genetic algorithm takes flight height and waypoint spacing as constraints, a fitness function containing flight distance, turning times and overlapping rate is constructed, a global optimal path is found through population iteration, multi-target requirements are optimized and balanced, and it is ensured that the route meets the image acquisition precision requirement and also meets the requirement of image acquisition. The flight distance can be shortened, the turning frequency is reduced, the cruising ability of the unmanned aerial vehicle is adapted, efficient propelling of the inspection task is guaranteed, meanwhile, waypoint coordinates output through simulation directly adapt to a flight control system, and it is guaranteed that actual flight parameters are consistent with planning parameters.

The invention provides a double-pulse high-frequency switching power supply control method and system for precise electroplating, and relates to the field of electroplating, and the method comprises the steps: collecting area surface data through a three-dimensional scanner, and obtaining a three-dimensional model; extracting a high-curvature area grid according to the three-dimensional model, and calculating to obtain a surface concave-convex degree index; performing current field simulation, and calculating current density vector distribution; when the deviation of the current density vector distribution exceeds a preset deviation threshold value, pulse parameters are optimized through a genetic algorithm; selecting a pulse parameter which is most matched with the surface concave-convex degree index, and carrying out iterative calculation to obtain updated current density vector distribution; based on the difference between the updated current density vector distribution and the initial distribution, predicting a coating thickness value, and determining a preliminary evaluation index; and optimizing pulse parameters to obtain a final control scheme of uniform current distribution. According to the method, pulse parameters can be dynamically optimized according to the geometrical shape of the workpiece, and uniform current distribution and stable plating quality are realized.

The invention discloses a method and a system for processing route planning data for electric power line inspection. The method comprises the following steps: acquiring line distribution and topographic feature data; gridding the power network region, determining the patrol priority, and generating a region priority sequence; the overall patrol task is decomposed, a plurality of task subsets are generated, one task is allocated to each unmanned aerial vehicle, and each task subset comprises an initial position and a target line section; generating an initial route path based on the topographic features; comprehensively analyzing all initial paths, identifying potential airspace intersections and performing conflict prediction, and generating a conflict-free route path set by performing height hierarchical adjustment on related paths; and calculating predicted flight time and energy consumption of each unmanned aerial vehicle, redistributing boundary tasks according to a load balancing principle, and finally generating a balanced multi-unmanned aerial vehicle cooperative route scheme. According to the method, the safe and efficient multi-machine collaborative inspection route can be automatically generated through systematic task decomposition, conflict prediction and load balancing optimization.

The invention relates to the technical field related to automatic driving, in particular to a trajectory prediction method based on adaptive interaction and dynamic intention, which comprises the following steps: firstly, constructing a heterogeneous interaction map, dividing a traffic scene into a vehicle grid, an environment grid and a non-driving area grid, and embedding multi-dimensional dynamic features; then dynamically adjusting a region of interest based on the behavior intention of the target vehicle, and extracting a high-correlation interaction subnet; modeling an interaction relationship by adopting a heterogeneous graph convolutional network, and processing the motion characteristics of the target vehicle and the neighbor vehicle through a sub-channel coding strategy; further realizing dynamic intention perception through a double-branch parallel attention architecture, and fusing macroscopic intention and dynamic intention information; and finally, iteratively generating a future trajectory prediction result based on a decoding architecture of a message passing mechanism. The method can effectively improve the long-term prediction performance in a lane changing scene, adaptively captures a dynamic interaction relationship, and improves the adaptability of a prediction system to the behavior intention change of a driver.

The invention provides a vehicle identity anonymous authentication method in a space-air-ground fusion vehicle-mounted network. The method comprises the following steps: carrying out multi-source data acquisition; generating a dynamic area identifier based on the vehicle real-time position data, and performing dynamic updating according to a vehicle moving threshold value; vehicle equipment identification information is acquired, a salted hash value is generated in combination with the dynamic region identifier, and an anonymous certificate containing dynamic effective duration is generated; extracting spatio-temporal data fluctuation parameters according to the environmental perception data, and extracting delay trend parameters and channel stability parameters according to the regional network state data; the weight is dynamically adjusted according to the link type and the time period type, and the dynamic trust quantized value of the vehicle is calculated through weighted summation; differential authentication is executed based on the dynamic trust quantized value of the vehicle and the anonymous voucher, and the differential authentication comprises the steps that lightweight verification is adopted when the vehicle is highly trusted, two-factor authentication is started when the vehicle is low trusted, and link timeout redundancy authentication is combined. According to the method, the trust evaluation accuracy can be improved, and the dynamism of a privacy protection mechanism is enhanced.

The invention discloses an electric power measurement data management system based on cloud edge collaboration and an electric quantity distributed acquisition method, and relates to the technical field of electric power information acquisition and processing. The system comprises an intelligent electric meter terminal layer, an edge computing node layer, a regional collaborative gateway layer and a cloud data center. The intelligent terminal can dynamically adjust the sampling frequency according to the load change rate and the historical volatility, and identifies abnormity through an LSTM-ATT model; the edge nodes realize prediction caching based on Kalman filtering and RMSE judgment; the regional gateway executes dynamic time warping and consistency arbitration of topological weighting; and the cloud end completes digital twinborn modeling and exception evidence storage. According to the method, the real-time performance and accuracy of electric power data acquisition are improved, the communication bandwidth occupation is reduced, the system abnormity sensing capability and the operation stability are enhanced, and the method is suitable for an intelligent power distribution network and a distributed energy metering scene.

The invention discloses a security check door security check process optimization scheduling system and method based on big data, and belongs to the technical field of intelligent security check, a whole security check area is divided into a plurality of functional areas and mapped into network nodes according to security check process links and physical space distribution, directed edges among the nodes represent passenger flow paths, and the flow paths of passengers are distributed in the network nodes. A weight matrix of edges is calculated through historical flow data, and a security check area network topology model is constructed; fusing ticket business, historical security check and real-time sensor data, constructing a load evaluation model, and calculating a node load index and an influence conduction coefficient; based on passenger ticket business time and historical behavior records, establishing a time urgency index and risk level model, and forming a two-dimensional decision matrix to dynamically divide priorities; constructing and training a congestion propagation model, predicting a future congestion path in combination with priority distribution, and identifying bottleneck nodes; and according to a prediction result, cooperatively implementing a grooming strategy from four dimensions of personnel, channels, equipment and processes.

The invention relates to the technical field of automatic driving vehicle control, in particular to a drive-by-wire chassis whole vehicle test device and method, which considers the delay compensation of a vehicle steering actuator and comprises an upper computer, a real-time controller, a drive-by-wire chassis vehicle, a combined navigation system and a USB-CAN (Universal Serial Bus-Controller Area Network) acquisition module. The method comprises the following steps that a vehicle in-loop system is built on a rack, and the delay characteristic of a steering actuator is identified through step and sine mixed excitation signals; establishing a vehicle trajectory tracking error model containing delay compensation based on an identification result; deploying a delay compensation model in a real vehicle environment, and verifying trajectory tracking performance; comparing the transverse error and the course angle error before and after compensation, and evaluating the compensation effect. The invention provides a drive-by-wire chassis whole vehicle test device and method integrating delay identification, model injection and real vehicle verification, and an engineering scheme is provided for dynamic rapid calibration and algorithm migration of an automatic driving drive-by-wire chassis actuator.

A system manages network traffic in a distributed system comprising a plurality of network devices. The network devices are divided into a plurality of network slices, each of the network slices including a subset of the network devices such that there is no overlap of network devices between the network slices. Individual network slices are associated with individual slice controllers, and an individual slice controller is configured to manage network routing of an individual network slice. Each of the individual slice controllers route the network traffic within each respective individual network slice. The network traffic is independently routed based on expected network conditions for each respective individual network slice, and data defining routing decisions is contained within each network slice to limit fault effects between the network slices.

The invention relates to the field of vehicle-mounted bus testing, and discloses a vehicle-mounted CAN bus terminal resistor configuration method and system for node testing, and the method comprises the steps: obtaining a node identifier and a terminal resistor identifier corresponding to each test node in a vehicle-mounted CAN bus test, the terminal resistor identifier being used for identifying the terminal resistor access state of the test node; obtaining a first node position of a first test node corresponding to the first node identifier, configuring a terminal resistor for the first test node when the first node position is an end node of the vehicle-mounted CAN bus, and canceling the configured terminal resistor for the test node of a non-end node; and updating the terminal resistor identifier of each test node according to the terminal resistor access state corresponding to each test node. According to the invention, the terminal resistor can be automatically configured in the CAN bus test.

The invention belongs to the crossing field of space geodetics, satellite navigation positioning technology and atmospheric science, and discloses a real-time troposphere delay modeling method for enhancing a global forecasting system. The method comprises the following specific steps: firstly, acquiring zenith fluid static delay and zenith wet delay predicted by earth surface GFS, and constructing a regional grid difference time sequence by taking a fusion result of ERA5 data and a GNSS troposphere delay product as a reference; secondly, fitting the difference to form a GFS enhanced core model; meanwhile, a troposphere delay correction model from the grid height to the target site height is constructed based on ERA5 stratified atmosphere data, time sequence modeling is carried out on model coefficients, and finally refined troposphere delay output at different heights is achieved. The method has the advantages that (1) the real-time troposphere model is high in precision; (2) real-time application can keep robust performance without depending on a GNSS network; (3) expansion and deployment are facilitated; and (4) the real-time performance is strong, and seamless integration precision positioning application can be realized.

The invention relates to a vehicle remote diagnosis method and system and a medium, and the method comprises the steps: collecting diagnosis data from a vehicle, and the diagnosis data comprises vehicle controller area network data, vehicle electronic control unit logs, fault diagnosis codes and vehicle driving data; transmitting the diagnosis data to a cloud platform through a wireless network; analyzing the diagnosis data on the cloud platform by using an artificial intelligence model, wherein the artificial intelligence model comprises a fault diagnosis model and a fault prediction model; generating a diagnosis result based on an analysis result of the artificial intelligence model, wherein the diagnosis result comprises current fault diagnosis and potential fault prediction; sending the diagnosis result to the vehicle or the user equipment; and executing corresponding maintenance or preventive maintenance operation based on the diagnosis result. According to the invention, real-time monitoring, remote diagnosis and predictive maintenance of vehicle faults can be realized, so that the diagnosis efficiency is improved, and the maintenance cost is reduced.

The invention provides a system and a method for generating CAN (Controller Area Network) mailbox configuration and data routing configuration based on a communication matrix table. The method comprises the following steps of: reading a predefined finished automobile CAN communication network signal routing information table; analyzing the whole vehicle CAN communication network signal routing information table to obtain CAN communication configuration parameters of each CAN channel; the number of receiving mailboxes and the number of sending mailboxes of each CAN channel are distributed according to the maximum number of receiving mailboxes and the maximum number of sending mailboxes supported by the whole vehicle CAN communication network hardware for each CAN channel and CAN communication configuration parameters of each CAN channel; and when the number of the messages to be processed of a certain CAN channel exceeds the allocated mailbox number, classifying the messages, and multiplexing the same mailbox by the messages belonging to the same class. According to the method, CAN mailbox resources are used to the greatest extent, and the reliability of data routing is ensured; when the whole vehicle communication network signal routing table is frequently changed, the reliability of the routing function is ensured, and meanwhile, the development efficiency is improved.

The invention provides a data transmission method and device, equipment and a storage medium. The data transmission method is applied to the controller, at least two buffer areas are arranged in the controller, and the data transmission method comprises the steps that in response to starting of a first timer, CAN data sent by external equipment through a CAN controller local area network bus is stored in the buffer area in an idle state in the at least two buffer areas; in the process of storing the CAN data through the buffer area in the idle state, forwarding the CAN data stored in the buffer area in the occupied state in the at least two buffer areas through a serial peripheral interface (SPI) bus; wherein the data transmission rate of the CAN bus is smaller than that of the SPI bus.

The invention relates to the technical field of cable safety monitoring, and discloses a cable thermal risk monitoring method and system based on multi-source data fusion, and the method comprises the steps: collecting, standardizing and processing multi-source data, extracting thermal risk features, recognizing abnormal point locations, constructing a regional network topology analysis risk propagation path, and dynamically adjusting and monitoring resource configuration. And generating graded early warning signals in real time, simulating risk propagation influence, adjusting cable operation parameters, and tracking a control effect. According to the invention, intelligent monitoring and early warning of the cable thermal risk are realized, and the operation safety and reliability of the cable are improved.

The present disclosure relates to a delay module for a CAN device. The delay module is configured to delay only a single signal change of an RXD signal, wherein the single signal change forms the end of an idle state. Use of the delay module allows a second RXD signal to be generated. The present disclosure further relates to a CAN device comprising two CAN controllers. Each of the two CAN controllers may be provided with one of the two RXD signals. The CAN device may further be configured to detect possible errors based on the decoded bits of the RXD signals. As a result, the CAN device can communicate error-free with both distantly located further CAN devices and closely located further CAN devices, while ensuring a high data rate. The present disclosure also relates to a method for the delay module.

A network control method for improving energy consumption by an electrified vehicle during ignition-off involves a supervisory controller configured to control a propulsion system or electrified powertrain of the electrified vehicle and a security gateway (SGW) module. The supervisory controller and the SGW module are each connected to a controller area network (CAN) of the electrified vehicle and the CAN includes a plurality of buses. When one of a plurality of conditions exist to keep one or more of the plurality of buses of the CAN awake during an ignition-off period, the supervisory controller sends a signal to the SGW module that causes it to only communicate on a specific set of buses of the plurality of buses of the CAN to thereby reduce energy consumption of components on the CAN that would have otherwise been awoken by the SGW module.

The invention relates to the technical field of cross-border trade settlement, and discloses a cross-border trade settlement risk prevention and control system based on a block chain smart contract, and the system comprises a regional network which serves as a distributed account book infrastructure and is used for storing and sharing the transaction data of all participants; the cross-border trade settlement risk prevention and control system comprises a block chain intelligent contract, a trusted data acquisition and uplink module used for acquiring and verifying off-chain entity trade data and uploading the verified trusted data to a local area network, and the off-chain entity trade data comprises logistics information sensed by Internet of Things equipment. The problem of traditional cross-border trade settlement pain points can be effectively solved, and fraud is prevented and controlled in the whole process by means of dual verification and intelligent contracts; a sharing platform is constructed through the block chain, an information island is broken, the settlement efficiency is greatly improved, and data security and traceability are guaranteed.

Operating effectively in an increasingly prolific Internet of Things environment, one needs the ability to message, whether device status, actions taken, recommendations for actions or other information to those with a need to know and support responses to actionable messages. Texts and e-mail are limited; they can neither provide other outputs, be targeted in intelligent fashion nor selectively relayed or contain execution instructions for target devices. The present invention is an Extended-Capability Messaging Appliance (ECMA) that communicates with other IoT devices that provides these capabilities and can include AI. ECMA and non-ECMA AI elements can constitute a Hybrid AI Backbone. The Hybrid AI Integrator receives results from multiple A elements and develops one or more conclusions. An ECMA may be configured as a Body-Area Network for individuals or a Business-Area Network for industry and other commercial applications with an AI Agent called BANDIT that processes requests from a user.

The invention discloses a regional grid safety evaluation method and device based on smart gas and a medium, belongs to the technical field of gas safety supervision, and aims to solve the technical problem of how to overcome the defects of insufficient matching between grid division and gas facility characteristics and lagging leakage risk prediction in the prior art. In order to realize full-process intelligence from risk identification to closed-loop management and improve supervision efficiency and early warning precision, the technical scheme adopted by the invention is as follows: dividing a pressure sensitive grid: performing optimization division on a regional grid based on a gas pipeline pressure grade and facility distribution characteristics, and realizing accurate division of the regional grid where a pipe network is located by combining a GIS and an improved DBSCAN algorithm; acquiring three-level Internet of Things data: integrating sensor data of an unmanned aerial vehicle, a pipe network pressure device and a leakage monitoring device, and covering a full-link data system of a terminal sensing layer, an edge computing layer and a cloud storage layer; constructing a double-engine evaluation model; carrying out digital twinborn visualization; and scheduling the capability matrix.

Systems, methods and apparatus of vehicle control. For example, a vehicle includes: a multi-master serial bus (e.g., a controller area network (CAN) bus); electronic control units connected to the bus and configured to communicate with each other through the bus; a transceiver connected to the bus and configured to monitor communication traffic on the bus to generate inputs; and an artificial neural network configured to generate, based on the inputs, a classification of anomaly for the communication traffic on the bus. The vehicle is configured to apply a security measure in response to the classification of anomaly for the communication traffic on the bus.

The invention discloses an urban garbage classified collection and scheduling method based on the Internet of Things, and relates to the technical field of urban garbage classified collection, and the method comprises the steps: deploying an intelligent garbage can with the filling rate and environmental parameter perception capability in each region of a city, and uploading the collected state data to an edge gateway of the region through a low-power wide area network; the edge gateway performs localized priority evaluation based on the received real-time state data of each intelligent garbage can in combination with the capacity information, the last clearance time and the attribute of the area where the intelligent garbage can is located, and generates a dynamic priority score of each garbage can; when the dynamic priority score of any dustbin exceeds a preset response threshold value, the edge gateway triggers an event reporting mechanism and sends a clearance alarm containing position and priority information to a regional dispatching center; and on the basis of receiving the clearance alarm, the regional dispatching center combines weather forecast, festival calendar and regional people flow density data to carry out trend prediction on the garbage cans which are not alarmed yet and have high filling risks.

The invention relates to the technical field of crossing of atmospheric science and machine learning, in particular to a vertical atmospheric profile fine-grained processing method, system and equipment based on a KAN network, and aims to solve the problems that an existing NWP model is insufficient in vertical resolution, poor in physical consistency, mismatched with high-resolution observation and the like. The method comprises the following steps: acquiring input data of a KAN network; performing nonlinear mapping on the input data through a B-spline function in the KAN network to obtain control point parameters and bias terms of the B-spline function; introducing a physical knowledge constraint into the KAN network, converting an atmospheric physical law into a constraint term of a loss function, and constraining the output of the KAN network; defining control point parameters and bias terms of the B spline function as training parameters of the KAN network, and training the training parameters of the KAN network in stages by adopting a predefined staged training strategy; and outputting an atmospheric variable function in a continuous height range through the trained KAN network so as to realize conversion from an NWP coarse-grained profile to a high-resolution continuous vertical profile.

The present disclosure relates to the technical field of intelligent driving, in particular to a vehicle driving intelligent assistance system, which includes an electronic control unit and a Controller Area Network (CAN) module, wherein the CAN module is connected with a driving detection module, a vehicle body state detection module, an engine detection module and an environment detection module, wherein the vehicle body state detection module is configured to acquire a steering angle of a steering wheel and a suspension condition, the environment detection module is configured to acquire environmental information around the vehicle and road conditions; the electronic control unit is connected with a vehicle body stabilization system, a vehicle control system and a lane departure early warning module, and the vehicle control system is configured to control acceleration, steering or braking of a vehicle to achieve assisted driving.

To provide a multi-drone cooperative map creation method and device that can combine compositions of a plurality of drones totally to create a wide-range environmental map.SOLUTION: A method includes the steps of: automatically dividing multi-drone images, in which matching of identical points among images has been completed, into a plurality of sub-areas so that image nodes in the plurality of divided sub-areas include in-area points appearing only in one sub-area and area connection points appearing simultaneously in different divided areas; and obtaining an aerial triangulation calculation result by using image nodes in the respective divided sub-areas to unify coordinates of the divided sub-areas through parallel aerial triangulation calculation using an area network cooperatively set by multiple drones, performing error integration compensation after eliminating issues of internal parameters and distortion of cameras, and automatically integrating the divided sub-areas thereafter.SELECTED DRAWING: Figure 1

An Internet of Things (IoT) edge gateway device information handling system executing an IoT edge gateway device location optimization and carbon dioxide (CO2) minimization system may comprise a network interface device receiving, at an edge gateway initial location, power consumption analytics and locations of AP IoT servers transceiving IoT data with the IoT edge gateway in an enterprise wireless area network (WAN), a processor executing code instructions to determine an optimal location for the IoT edge gateway that reduces total estimated CO2 emissions during IoT data transmission between the AP IoT servers and the IoT edge gateway, based on the power consumption analytics and current locations of the AP IoT servers to a new optimal location in the enterprise WAN, and the network interface device transmitting an instruction to physically move the IoT edge gateway to the optimal geographic location to minimize CO2 emitted during transceiving of the IoT data.

A system is provided for generating artificial intelligence based visualizations of computing device security and stability. In particular, the system may aggregate various types of data and metrics related to the operational performance, security, and stability of the computing devices and applications within an entity's computing environments. Based on the aggregated data, the system may use an artificial intelligence engine to determine whether a particular area, network, application, or device may be vulnerable. Based on analyzing the data, the system may generate one or more visualizations of the data that reflect the current state of the entity's computing environment as a whole. The system may further be configured to transmit notifications to one or more relevant users associated with the applications or devices subject to the vulnerabilities.

The invention provides an air-space-ground integrated network switching method, device and equipment and a storage medium, and relates to the technical field of communication, and the air-space-ground integrated network switching method comprises the steps: obtaining the movement track information of mobile equipment, the moving track information comprises the current position of the mobile equipment and the position of the mobile equipment within a first preset duration after the current time; acquiring first network state information of the air-space-ground integrated network, wherein the first network state information comprises current network state information of the air-space-ground integrated network and network state information of the air-space-ground integrated network within a first preset duration after the current time; and according to the moving track information and the first network state information, switching a connection network of the mobile equipment from the first regional network to a second regional network in a moving process of the mobile equipment. According to the invention, the seamless switching technology of the space-air-ground integrated network can be realized, and rapid and stable switching among different networks can be realized.