318 results about "Location area" patented technology

The invention relates to the technical field of account authentication, in particular to an account authentication method and system and a storage medium. The method comprises the following steps of collecting account and password information of a user, detecting synchronous reaction of equipment for the account and password information of the user, performing character error elimination and structure standardization on the account of the user based on a detection result, generating account block data, obtaining IP positioning of terminal equipment and performing longitude and latitude mapping. Generating a positioning area number to construct a dynamic fingerprint, performing key matrix projection based on the dynamic fingerprint of a user, generating projection fingerprint data, constructing a layered authentication code, performing disturbance offset simulation on the layered authentication code, generating an offset authentication key, performing dynamic rule verification, and generating dynamic token data; and constructing a terminal equipment trust link by using the dynamic token data, and performing authority control mapping, thereby constructing an authentication account session. According to the invention, a safer and more flexible account authentication method is realized.

The invention provides a water network monitoring method and system based on intelligent water supply and drainage, and the method comprises the steps: obtaining multi-source heterogeneous monitoring data of a water network in real time, carrying out the unified format conversion and time-space synchronization processing of the multi-source heterogeneous monitoring data based on a protocol adaptive fusion mechanism, and obtaining a standardized multi-source time series data set; performing exception identification processing on the standardized multi-source time sequence data set based on the time-varying statistical characteristics and the dynamic control limit to obtain a candidate exception event set; performing multi-sensor cross validation processing on the candidate abnormal event set based on a pipe network topological space association knowledge graph to obtain a high-confidence abnormal event set; performing reverse scene matching analysis on the high-confidence abnormal event set based on a hydraulic numerical simulation model to obtain a preliminary positioning area; performing positioning optimization processing on the preliminary positioning area based on a graph theory pressure wave propagation algorithm to obtain an abnormal position; and performing multi-dimensional fusion display processing on the abnormal position to generate a monitoring report. According to the method, accurate positioning of the abnormal position is realized.

The invention relates to the field of computer vision and intelligent transportation, in particular to an SAM and YOLOV8 model-based unmanned aerial vehicle visual angle infrastructure identification method, which comprises the following steps of: SI, segmenting a scene area by using an SAM, performing semantic segmentation on a picture shot by an unmanned aerial vehicle by using the SAM, segmenting a road area, and calibrating the road area; s2, target detection is carried out by using YOLOv8, infrastructures on pictures shot by the unmanned aerial vehicle are all detected, and a Neck part of a YOLOv8 model adopts a three-layer PAFPN structure; s3, if the target position area detected by the YOLOv8 and the road area segmented by the SAM have a boundary, indicating that the target is on the road or on the edge of the road; according to the method, semantic segmentation can be quickly performed on the road by using the SAM model, the target can be quickly detected by using the YOLOv8 model, whether the recognized target is the road infrastructure or not can be judged in different scenes through a judgment method, and real-time recognition and real-time segmentation can be realized by combining the SAM model and the YOLOv8 model.

The invention relates to the technical field of warehouse management, in particular to an intelligent warehouse management system based on deep learning, which constructs a space-time diagram model comprising nodes and edges by combining historical warehouse-in and warehouse-out records, AGV (Automatic Guided Vehicle) tracks and scheduling logs on the basis of spatial distribution information and channel communication relations of warehouse goods locations and function bits. And through deep space-time diagram convolution modeling, outputting a goods allocation value score and a traffic congestion probability, and identifying a goods allocation area which should be preferentially allocated by the high-frequency SKU. And a goods allocation strategy is generated through a reinforcement learning model, and excessive occupation and deadlock of channels are avoided while high-frequency goods are quickly put in and put out of a warehouse. And finally, generating an AGV scheduling instruction set through a path planning algorithm, and issuing and executing the AGV scheduling instruction set. Dynamic collaborative optimization of goods allocation planning and AGV scheduling is realized, the high-frequency goods operation efficiency is improved, meanwhile, path congestion and conflicts are effectively avoided, and the throughput rate and the operation reliability of the system are improved.

A channel state information determination method and device, in the method, a network device determines N rows of base vectors corresponding to N time units based on mobile state information and a channel map of a terminal device, each row of the N rows of base vectors comprises X base vectors, and the channel map is used for indicating channel characteristics based on a location area; the network equipment sends first indication information, wherein the first indication information is used for indicating N rows of base vectors; the network equipment respectively sends pilot signals in N time units; the network equipment receives second indication information, the second indication information is used for indicating weighting coefficients of Y base vectors in the X base vectors, and the weighting coefficients of the Y base vectors are determined based on the pilot signal; and the network equipment determines channel state information corresponding to M time units based on the weighting coefficients of the Y base vectors and the N rows of base vectors, and the M time units comprise N time units. The method can improve the accuracy of the channel state information.

The invention provides a video transmission method and device based on key frame semantics, electronic equipment, a storage medium and a program product, and relates to the technical field of video transmission. The method comprises the following steps: extracting semantic information of an IDR frame at a sending end by utilizing a graph-to-text model, and determining a foreground target object and position area information of the foreground target object from a common I frame; extracting prediction errors and motion vector information contained in the prediction frame; and the background semantic information of the H.26X video stream and the dynamic behavior information of the foreground target object are obtained and transmitted. According to the method, an IDR frame, a common I frame and a prediction frame are sequentially generated by using acquired video semantic information at a receiving end, and an original H.26X video is orderly recovered according to H.26X frame structure configuration characteristics, so that the requirement of effectively reducing transmission bandwidth pressure is met on the premise of ensuring basic reliability of video transmission.

The invention discloses a fire-fighting intelligent early warning system and method based on the Internet of Things, and belongs to the technical field of fire-fighting intelligent early warning. Temperature, smoke concentration and CO concentration data are obtained through an Internet of Things detector, and site position, regional function division and object flammability degree distribution data are synchronously collected; after preprocessing, generating a composite attribute label containing space coordinates, function partitions and flammability grades; constructing an equipment operation state spatial-temporal feature network based on equipment historical data, extracting multi-dimensional time sequence features, calculating a regional risk conduction coefficient in combination with a composite attribute tag, and fusing multiple parameters to generate a differentiated early warning threshold matrix; virtual monitoring grids are divided according to the correlation degree of regional functions and flammability grades, and early warning is triggered after a suspected risk area is identified and judged as an effective risk through space-time cross validation; when early warning is triggered, fire spreading is simulated in combination with site topological data, a dynamic risk map is generated, early warning information is pushed, and an emergency scheme is generated.

The present invention relates to the technical field of cable fault analysis, and specifically discloses a distribution network line fault analysis method. The method is based on a line fault location area, collects fault state information of a line fault location area in a distribution network, and analyzes to obtain the fault loss degree of the line fault location area, so as to understand in real time the loss degree of the distribution network when a fault occurs, thereby matching the fault type of the line fault location area, and by collecting equipment protection information of the line fault location area, it is possible to determine the paths of occurrence of each fault in the line fault location area, and finally match each fault repair plan of the line fault location area, so as to reduce the fault maintenance cost of the distribution network, complete the line fault repair process of the distribution network, improve the power supply reliability of the distribution network, and improve the normal operation efficiency of the power system.

The invention provides an air-ground wireless network deployment method, device and equipment, a medium and a program product, and relates to the technical field of wireless communication. The method comprises the following steps: determining the number of air base stations in the air-to-ground wireless network and the positions of a plurality of ground user terminals required to be covered by the air-to-ground wireless network; based on the number of the base stations and the position of each ground user terminal, performing clustering processing on the plurality of ground user terminals to obtain a plurality of clusters; respectively determining the initial position of each air base station based on the central position of the position area represented by each cluster; and based on the initial position of each air base station, solving the optimization problem to obtain the deployment position of each air base station. According to the method, the influence of burst flow caused by dynamic change of user positions in a disaster scene on the network and the condition of dynamic change of interference are fully considered, and the ground user terminals are clustered by adopting clustering so as to reasonably deploy the positions of air base stations, so that the coverage integrity of the air-ground wireless network is improved.

To provide a home electric appliance control information generation system for generating control information that can more optimally operate a home electric appliance in accordance with an installed environment.SOLUTION: A home electric appliance control information 1 for generating control information of a home electric appliance on the basis of operation history information from a plurality of home electric appliances is provided with a server 31 having a storage part for storing acquired data to process data. The operation history information includes position information that can specify a region at which each of a plurality of home electric appliances is installed, setting information, and power consumption, and an information processing part acquires location region weather information with the plurality of home electric appliances are installed on the basis of the operation history information and the position information from the plurality of home electric appliances through a network, classifies the operation history information about the plurality of home electric appliances belonging to the location region to be location-based operation history information, classifies the location-based operation history information into a plurality of groups on the basis of the amount of power consumption, analyzes the location-based operation history information belonging to the same group, and outputs control information of home electric appliances.SELECTED DRAWING: Figure 1

Various aspects of the present disclosure relate to techniques for session management signaling for partial network slice support in a registration area. An apparatus is configured to receive a first session management (SM) message for a protocol data unit (PDU) session associated with a network slice and a user equipment (UE), determine that the network slice is not supported or not available in a location area of the UE, and transmit a second SM message and an indication that the network slice is not supported or not available in the location area of the UE.

The invention discloses a programmable logic controller, a downtime diagnosis method and device of the programmable logic controller and a readable storage medium, and relates to the technical field of programmable logic controllers. Acquiring abnormal downtime site information and position area information corresponding to the user program; converting an instruction address corresponding to the downtime abnormal site information into a corresponding function name, determining an instruction address corresponding to the user program based on the position area information, and converting the instruction address corresponding to the user program into the corresponding function name; and adding each function name into the initial function call stack to obtain a downtime abnormal field function call stack. According to the method and the device, the technical problem that a current downtime diagnosis scheme for the programmable logic controller cannot process downtime abnormity caused by a user program and has limitation is solved.

The invention discloses an intelligent vehicle control method and device based on a multi-Bluetooth system and a vehicle, and relates to the field of automobiles. The method comprises the following steps: acquiring an RSSI (Received Signal Strength Indicator) signal generated by communication between a Bluetooth key and at least one Bluetooth anchor point under the condition that the Bluetooth key establishes communication connection with the at least one Bluetooth anchor point; determining a target sub-area where the Bluetooth key is located according to the RSSI signal and the position of the corresponding Bluetooth anchor point; wherein the space region taking the vehicle as the base point is divided into a plurality of sub-regions, and the target sub-region is one of the sub-regions; and executing a vehicle control instruction corresponding to the target sub-region. According to the invention, the position area of the Bluetooth key can be evaluated according to the RSSI signal and the position of the Bluetooth anchor point, so that the digital key is effectively supported to execute specific operation in a specific area, and the control of the vehicle-mounted terminal is non-inductive to a user, so that the vehicle-mounted terminal is more intelligent.

The present invention relates to the field of data processing technology, and in particular to a distribution transformer fault detection method and system. The method includes: acquiring data sequences of various position areas on the distribution transformer in real time; determining the noise performance degree of each data point in each data sequence; correcting the noise performance degree of the data point according to the correlation between the data sequence and the preset local range sequence of the corresponding data point in other data sequences in its neighborhood; determining the noise influence degree of each data sequence; determining the number of adaptive segmentation trees when the corresponding position area is detected using the RRCF model according to the noise influence degree of each data sequence; and performing detection through the RRCF model to perform distribution transformer fault detection. By analyzing the noise influence degree of each data sequence, the number of segmentation trees in the adaptive RRCF model is adjusted, thereby saving distribution transformer fault detection computing resources, improving computing efficiency and detection accuracy.

The invention provides a single-terminal line defect detection method and system based on image processing, and the method comprises the steps: extracting a standard sequence of each detection target from a template image of a single-terminal line with a detection frame, and extracting the feature information of each detection frame of the standard sequence and the image feature information of the detection target in each detection frame; according to the standard sequence, mapping each detection frame of the to-be-detected image detected by the deep learning model, marking the position not mapped by the standard sequence as a missing position, and according to the position information of the detection frame adjacent to the missing position and the position information of each detection frame in the standard sequence, determining the position area of the missing position, extracting image feature information of the position area, performing multi-dimensional feature matching on the image feature information and a standard sequence, and determining whether matching succeeds or not; the standard sequence and the feature information of each detection target of the single-terminal line are extracted, and detection and feature matching are performed on the missing position of the to-be-detected image based on the standard sequence, so that missing detection and error detection can be effectively prevented.

The invention discloses a power equipment fault prediction method based on multi-modal data and related equipment, and belongs to the technical field of power operation safety monitoring, and the method comprises the steps: collecting the multi-modal data of a power operation site; inputting the data into a target detection model, determining a target category and position information in combination with a target identity re-association algorithm, and performing position tracking; performing preprocessing according to the channel state information of the real-time position of the target, performing attitude reasoning in combination with a deep neural network to obtain a target attitude, and determining an abnormal state of a target behavior; determining a position area of the target according to the real-time position of the target and an electronic fence technology; and when the target is in the dangerous operation area, determining the abnormal wearing state of the protection equipment of the target personnel based on the image of the target and by adopting a personal protection equipment detection model, and outputting early warning information through edge cloud cooperative early warning. High-precision safety monitoring of an electric power operation site is realized, the personnel behavior identification capability is improved, and the operation risk is comprehensively reduced.

The invention discloses a large-scale constellation general calculation collaborative resource allocation method facing non-uniform service requirements, and mainly solves the problems of time delay and high energy consumption overhead when task unloading is carried out by utilizing a satellite network under the condition that ground network resources are limited in the prior art. According to the implementation scheme, a large-scale constellation network is constructed; the method comprises the following steps: dividing the ground into a plurality of position areas, taking one area as a reference, jointly optimizing task scheduling by adopting an improved DRL-DAO (Deep Reinforcement Learning Differentiated Task Offload) algorithm, realizing efficient dynamic resource allocation to complete calculation of an offload task, and calculating the offload task between adjacent areas according to channel space-time correlation and task correlation. And performing fine adjustment on the trained model through transfer learning to complete task scheduling and resource allocation of all regions. According to the method, differentiated services can be provided for different types of tasks, resources are reasonably utilized to improve the user service quality, the high task completion rate and the minimum time delay and energy consumption weighted sum are achieved, and the method can be used for scheduling processing of various types of tasks of a user terminal.

The invention provides a communication method, communication equipment and a storage medium. The communication method applied to a first communication node comprises the following steps: sending indication information; wherein the indication information comprises at least one of the following information: a position; an area; an SSB; and a beam. In the scheme, the first communication node actively sends the indication information including at least one of the position, the area, the SSB and the beam to the second communication node so as to assist the second communication node to select the SMTC and / or the GAP and / or configure the SMTC configuration information and / or the GAP configuration information, so that the situation that the first communication node adopts the SMTC and / or the GAP of an unnecessary adjacent cell for measurement is avoided, and the measurement efficiency is improved. Therefore, the energy consumption of the first communication node is effectively reduced, and the measurement efficiency is improved.

The invention discloses a risk assessment method and device, electronic equipment, a storage medium and a program product, and aims to solve the problems of relatively high labor cost and relatively low risk assessment efficiency when an existing risk assessment mode is adopted. The method comprises the steps of obtaining historical claim settlement data of a position area where a target property insurance object is located; determining a conduction risk value of the historical claim settlement event to the target property insurance object according to the historical claim settlement data, and determining an aggregation risk value of the claim settlement disaster cause of the historical claim settlement event to the target property insurance object; wherein the conduction risk value is used for representing the risk influence degree of the historical claim settlement event on the target property insurance object; the aggregation risk is used for representing a nonlinear risk amplification effect generated by the interaction relationship among the multiple claim settlement disaster causes on the target property insurance object; determining an environment risk value of a position area where the target property insurance object is located; and evaluating risk information of the target property insurance object according to the conduction risk value, the aggregation risk value and the environment risk value.

An access network satellite network element receives an access request from a terminal, obtains network topology information of a plurality of core network satellite network elements from an interface management function network element, determines a candidate core network satellite network element set based on a location area in which the access network satellite network element is located and the network topology information, where the candidate core network satellite network element set is a subset of the plurality of core network satellite network elements, and determines, from the candidate core network satellite network element set, a core network satellite network element set corresponding to the terminal based on an identifier of the access network satellite network element, an identifier of the terminal, and / or a location of the terminal.

The present invention discloses a broiler abnormality monitoring method, system, medium, and terminal based on data analysis, relating to the field of data processing technology. The method primarily aims to address the accuracy and effectiveness issues of existing broiler abnormality monitoring. The method comprises: collecting multiple broiler image data from a broiler breeding facility using cameras located at different monitoring angles; parsing location region identifiers in the broiler image data, and performing pixel segmentation on the broiler image data according to the location region identifiers to obtain multiple block-level image data; performing feature extraction on the multiple block-level image data to obtain feature images, and comparing the multiple feature images according to the comparison time length to determine the abnormal area; and generating the broiler abnormality monitoring result if the abnormal area matches a preset broiler abnormality contour range.

Disclosed are a wireless communication method, controller, apparatus, NTN base station, device, medium, and program wherein the wireless communication method is applied to a controller of an anchor cell, the anchor cell representing a pre-delimited ground fixed cell for NTN communication; the method comprises the following steps: establishing an associated registration relationship with an NTN base station under the condition that the coverage range of the NTN base station in a mobile cell mode and the range of an anchor cell have an overlapping region; sending the first TAC and the first PCI of the anchor cell to the NTN base station based on the association registration relationship; the first TAC comprises a TAC of an anchor cell or a TAC of each overlapping sub-region; the overlapped sub-region is a sub-region corresponding to the overlapped region; the sub-regions are obtained by dividing the anchor point cell; the NTN base station is used for broadcasting the first PCI and the first TAC to the terminal in the overlapping area, and the first PCI and the first TAC are used for determining the location area of the terminal.

The invention relates to the technical field of vehicle tracing, and discloses a vehicle tracing analysis method and system in a hot event and electronic equipment. The method comprises the following steps: acquiring a hot event, identifying a target vehicle in an image or video associated with the hot event, and determining a target feature; searching based on the published information of the hotspot event, and determining the occurrence time period and the location area of the hotspot event; inputting the target feature, the time period and the position area into a cloud for joint retrieval, and determining a vehicle identification code to which the target vehicle belongs; vehicle information corresponding to the target vehicle in front and back time periods is called according to the vehicle identification code, data analysis is carried out on the vehicle information, an analysis report is determined, and the vehicle information including instrument data, central control screen display data and appearance data is stored in the cloud. Through cloud joint retrieval, accurate identification of the target vehicle is realized, rapid and accurate public gateway response and forward maintenance of the vehicle brand value are facilitated, and the event processing efficiency is improved at the same time.

The invention discloses a user terminal paging method for a satellite-ground convergence network of a large-scale constellation, and mainly solves the problems of low paging success rate and large time delay overhead in an independent ground network or a satellite network in the prior art. According to the implementation scheme, in a satellite-ground fusion network scene, when a calling party is a 5G network user and a called party is a satellite network user, the calling party queries a called management and control center in a ground core network, the core network forwards a paging request to the management and control center, the management and control center queries a called satellite location area, and a low-orbit satellite performs paging in the satellite location area; and when the calling party is a satellite network user and the called party is a 5G network user, the paging request is forwarded to a management and control center of a satellite network through a low-orbit satellite, the management and control center inquires a satellite location area identifier of the called party and forwards the paging request to a ground core network, and the base station performs paging in the satellite location area. According to the invention, the problem of paging failure caused by network switching is reduced, the paging success rate is improved, the paging delay and overhead are reduced, and the method can be used for satellite-ground convergence network communication.

The invention discloses a homeland space planning auxiliary compilation method and system based on big data, and belongs to the technical field of land planning, and the method specifically comprises the steps: obtaining a remote sensing image map of a target region, and carrying out the land recognition of the remote sensing image map, and obtaining a specific position region and a region area of any land type in the target region; the method comprises the following steps: acquiring pre-planning information, calculating to obtain a to-be-planned area of any land type, screening lands of a target region, screening out a to-be-planned region corresponding to the to-be-planned area most conforming to the land type, and taking the to-be-planned region as an optimal planning region of the land type; and determining an optimal planning area of any land type, drawing a target boundary line corresponding to the optimal planning area, and outputting a planning remote sensing image map. According to the method, the land is planned by comprehensively considering the topographic features on the basis of the existing land planning of the target area, so that the accuracy of the land planning result is improved, the land resource allocation is optimized, and the planning operability is improved.

The present invention belongs to the technical field of tunnel defect detection and relates to a semi-supervised anomaly detection method for tunnel voids and loose defects. The method integrates GPS technology with ground penetrating radar equipment, collects and segments radar data blocks carrying corresponding position area information of a target tunnel lining structure, extracts signal features of each radar data block through dual channels and fuses them by referring to a mutual attention mechanism, significantly enhancing the integrity, comprehensiveness and accuracy of data extraction while helping to identify and emphasize the most critical feature parts for void and loose defect detection. Then, data is reconstructed on the fused signal features of each radar data block to analyze the data reconstruction error, and each radar data block with void and loose defects is identified with high precision and its specific position is located, which not only achieves a significant improvement in the accuracy and efficiency of tunnel lining structure defect detection, but also provides tunnel maintenance personnel with easy-to-understand defect indications.

The embodiment of the invention provides a group calling method and system in trunking communication, applied to a core network, and comprising: determining a target paging group, the target paging group comprising N terminal devices, N being an integer greater than or equal to 1; m access devices are determined based on the network location areas of the N terminal devices, M is an integer greater than or equal to 1, and the M access devices can cover the network location areas of all the terminal devices of the target paging group; and sending a group call message to each access device to enable the access device to execute a group call operation on the target paging group. According to the invention, the problem that beam selection cannot be carried out under the condition that the base station moves in the prior art is solved, and the effect of carrying out group calling on the terminal through the beam selected by the mobile base station is further achieved.

We provide a traffic management system, traffic management method, and traffic management program suitable for bus operations. [Solution] The operation management system includes: a setting unit that sets multiple location areas surrounded by multiple location information points in a continuous sequence in the direction of travel of the bus at the entrance and exit of a traffic facility where the bus is parked; an acquisition unit that acquires bus location information relating to the position of the bus running with a positioning sensor and bus time information relating to the time when the position is measured; a determination unit that determines whether the bus has passed through a location area based on the travel trajectory consisting of multiple bus positions recorded in the bus location information; and a recording unit that, if the determination unit determines that the bus has passed through a location area, records the bus's travel time based on the time recorded in the corresponding bus time information when the bus's position was measured.

The invention discloses a mobile ad hoc network route planning method and device based on LSTM node trajectory prediction, and the method comprises the steps: S1, adding mobile data containing the speed and position of a node into a Hello message, and periodically broadcasting the Hello message by each node in a mobile ad hoc network; s2, obtaining discrete mobile data of each node in the mobile ad hoc network through a Hello message, preprocessing the discrete mobile data, predicting the position of each node after a certain time period by using a trained LSTM model, and further obtaining position area data of a hop neighbor node of a local node within a certain time period; s3, based on the position prediction data of each node, a local node performs multi-point relay MPR selection in a one-hop neighbor node set by adopting a greedy algorithm; according to the method, while the balanced routing overhead is ensured, the data packet delivery rate is effectively improved, the average end-to-end delay is reduced, and the reliability requirement of the ad hoc network in the dynamic environment is met.

The embodiment of the invention provides a correction method, device and equipment for transmission data of a satellite. The method comprises the following steps: acquiring a first tilt total electron content (STEC) observation value of a satellite; wherein the position area covered by the satellite comprises a plurality of grid points, and the position area comprises a plurality of modeling stations and at least one monitoring station; and correcting transmission data of the satellite according to the first position information of the modeling station, the first STEC observation value and the second position information of the monitoring station. The method is used for achieving the effect of improving the positioning precision.