99 results about "Location awareness" patented technology

The invention belongs to the technical field of computer vision and three-dimensional scene reconstruction, and discloses a coarse-to-fine point cloud automatic registration method and system for overlapping mask optimization. The method comprises the following steps: firstly, performing feature extraction on an input point cloud by using a KPConv encoder, and obtaining a coarse-scale super-point feature through a local aggregation mechanism guided by a nuclear point and a down-sampling operation; secondly, a position perception attention module is introduced, position information is embedded in super-point features, geometric constraints are provided for an attention mechanism, a local geometric structure and global context information are adaptively fused through self-attention and cross-attention operation, and the feature expression ability is enhanced; then, the enhanced super-point features are input into an overlapping prediction network, overlapping masks are generated to eliminate non-overlapping areas, a similarity matrix is constructed based on reserved super-points, a sample correction loss function is introduced for optimization, and establishment of a coarse-scale super-point corresponding relation is completed;

The invention provides a RIS-assisted location awareness-based communication and sensing integration method, which is used for further improving the calculation efficiency of atomic norms and improving the accuracy of parameter estimation by utilizing priori knowledge between a base station and a reconfigurable intelligent surface. By incorporating priori knowledge into the scheme design, the calculation complexity can be significantly reduced, and the accuracy of channel estimation and positioning can be ensured at the same time. The method has the advantages that super-resolution channel estimation can be achieved, and the performance of the method is superior to that of an existing orthogonal matching pursuit method. The comparison of various performance indexes shows that the method provided by the invention has obvious advantages. The advantage is crucial for realizing accurate positioning service in a complex environment.

The invention discloses a YOLOv5n-based industrial part surface defect detection method and device, and the method comprises the steps: embedding an attention mechanism into a convolution layer of a backbone network, introducing dynamic snakelike convolution to capture cross-channel information, capturing direction perception and position perception information, and carrying out the detection of the surface defect of an industrial part. Inputting the industrial part surface defect image data set into the backbone network for feature extraction to obtain three feature maps with different scales; a Gold-YOLO structure is introduced, multi-layer features are globally fused, global information is injected to a higher level, and a feature map highlighting the global information is generated; inputting the obtained feature maps into a feature pyramid network, and carrying out weighted fusion on the feature maps on different scales step by step through a down-sampling mode and an up-sampling mode; and outputting a defect detection result, and marking a detection frame, a defect type and confidence. The device comprises a processor and a memory. According to the invention, the detection precision of the surface defects of the industrial parts is higher, and the requirements of monitoring and maintaining the health conditions of the parts in industrial production are met.

In various examples, systems and methods described herein may cause a machine to establish a network connection with a network access device based at least on map data indicating to use the network access device for network connectivity at a location of the machine. In some examples, the map data may be generated based at least on one or more network performance scores associated with one or more network access devices disposed in the environment. In some instances, the network performance score(s) may be determined based at least on one or more wireless network signals transmitted by the network access device(s) and obtained using the machine and / or another machine. The network performance score(s) may, in some examples, be indicative of a signal strength associated with the network access device(s) at the location of the machine.

The invention discloses an Internet of Things equipment position sensing and superposed pilot frequency transmission method, which relates to the technical field of Internet of Things, and comprises the following steps: firstly, constructing a wireless frame structure comprising two parts of position sensing and superposed pilot frequency transmission; secondly, based on a wireless frame structure, a user carries out position estimation according to a base station pilot signal reflected by a reconfigurable intelligent surface RIS; then, on the basis of a position estimation result, a closed expression of the uplink reachable rate of the user is established; then, according to the closed expression, constructing a weighting and rate maximization problem for optimizing the RIS phase, and solving by utilizing a genetic algorithm to obtain an optimized RIS phase; then, based on the optimized RIS phase, the user sends a pilot frequency and a data superposition signal, and the base station performs channel estimation after receiving the superposition signal; and based on the channel estimation result, the base station performs data detection by adopting a maximum ratio merging detector. According to the method, under the condition that spectrum resources and transmission power are limited, the UE position can be accurately obtained, and the system transmission rate is remarkably improved.

The invention relates to the technical field of image geographic positioning, in particular to a progressive cross-view-angle image geographic positioning method based on spatial feature aggregation and position awareness, which comprises the following steps: acquiring paired satellite images and ground panoramic images as sample images, and constructing a training sample set; a cross-view image geographic positioning model composed of a double-branch backbone network and a fine-grained prediction network is constructed, two branches of the double-branch backbone network are a satellite processing branch and a ground panorama processing branch, and the fine-grained prediction network is composed of a bird's-eye view image transformation module and a position sensing prediction module; inputting training samples in the training sample set into the cross-view image geographic positioning model, and performing iterative training on the cross-view image geographic positioning model until convergence; and inputting a to-be-positioned paired satellite image and ground panoramic image into the trained cross-view-angle image geographic positioning model to obtain a positioning result output by the trained cross-view-angle image geographic positioning model.

The invention discloses a traffic prediction method based on a position-aware dynamic graph convolution circulation network, which comprises the following steps: taking road network sensors as nodes, taking connectivity between the sensors as edges, calculating the weight of the edges, modeling a traffic road network into a weighted directed graph, and taking historical traffic observation data recorded by the sensors as graph signals; dividing the historical traffic observation data into training and verification data; using the weighted directed graph and the training and verification data as the input of a position-aware dynamic graph convolutional loop network; the position-aware dynamic graph convolution circulation network comprises a position-aware dynamic graph learning module and a dynamic graph convolution circulation module; training the position sensing dynamic graph convolution circulation network to obtain an optimal prediction model; the weighted directed graph and the traffic observation data are used as input of the optimal prediction model, the traffic state in a period of time in the future is predicted, and the problem of data distribution difference in different stages can be effectively relieved.

The invention relates to a high-altitude insulator detection method based on laser radar point cloud data decoding. The high-altitude insulator detection method comprises the following steps: converting laser radar point cloud data into a pseudo image; constructing an insulator detector based on a convolutional backbone network fused with a dynamic deformation convolution attention mechanism, and inputting the pseudo image into the insulator detector for insulator detection; distance detection is carried out on each insulator by calculating depth information of the point cloud, and when the detection distance of the insulator is smaller than a preset threshold value, an alarm is given; compared with an existing insulator detection method, the method has the advantages that the detection accuracy is improved, the insulator space position sensing capability is achieved, and safety guarantee is provided for insulator guiding unmanned aerial vehicle autonomous inspection flight; the high-altitude insulator detection method based on laser radar point cloud data decoding has a wide application prospect, and is particularly suitable for safety monitoring and maintenance of a high-voltage transmission line.

The present invention relates to a location-awareness-based network intermediate device, at least comprising a scheduling module, which is configured to fuse short-term historical data about short-term and / or real-time network performance and location-awareness-based multi-day network performance data, so as to generate context data for predicting network performance, and acquire a deterministic connectivity mode in a mobile network environment based on the context data so as to enhance performance of end-to-end transmission. With this configuration, the concept of location-awareness-based packet scheduling can be translated into an actual system for end-to-end multi-path transmission. From the location-awareness-based long-term multi-day network performance data, the deterministic connectivity pattern of trains in the high-speed mobile network environment can be acquired, and after being fused with the short-term historical data observed in a short time period, a good basis for calibration of prediction of network performance can be provided, thereby enhancing robustness of network connectivity in a high-speed movement scene.

The invention relates to the field of cable fault sensing, and discloses a cable distributed fault sensing method and system based on a visual image, and the method comprises the following steps: determining a key position of a cable line, installing an electric power data sensor at the key position of the cable line, and collecting a real-time image of the corresponding position for state analysis; and the wireless communication system for constructing nodes is used for constructing a visual image algorithm model, positioning a fault position of a target cable, introducing a neural network algorithm to carry out fault position real-time prediction, finally carrying out traceability analysis on a cable fault distribution position, and making a repair scheme for the cable fault position. According to the invention, fault position sensing of the cable is realized through visual images, real-time monitoring, accurate positioning and rapid response of cable line faults are realized, and a powerful guarantee is provided for safe and stable operation of a power grid.

Systems and methods of identifying wearable tags or other items within a facility. The location of the identifiable item can be calculated by the system and used to improve the efficiency of the facility or to dispatch emergency help or maintenance to the location of the badge.

The invention belongs to the technical field of network abnormal behavior detection, and particularly relates to an abnormal behavior detection method based on a TransGAN network. The method comprises the following steps: firstly, dynamically evaluating feature importance by utilizing a time sliding window mechanism in combination with a time sequence sensitive XGBoost algorithm, and screening a basic feature set and an attention key feature set through double thresholds; then, a TransGAN model in which a generator and a discriminator cooperatively work is constructed, the generator adopts a position sensing embedding technology to strengthen key feature focusing and introduces a gating mechanism to dynamically adjust basic feature weight, and the discriminator fuses depth separable convolution to extract local features and carries out global distribution comparison with a lightweight Transform decoder; and finally, through a dual-channel detection assembly line and a reconstruction channel, calculating residual features of input data and generating output, judging channel generation anomaly confidence, and fusing the two to form a comprehensive anomaly score to realize accurate judgment. The accuracy, robustness and real-time performance of anomaly detection are improved, and the method is suitable for various anomaly detection scenes.

The embodiment of the invention provides a communication perception integration implementation method, a position perception method, a position perception device and equipment. The method comprises the following steps: generating detection signals by using a first communication unit, respectively mapping the detection signals to a plurality of first sensing symbols of a first flexible frame, and sending the detection signals according to a preset first frame structure, the first flexible frame being a frame in the first frame structure; a second communication unit is used for receiving echo signals at each second sensing symbol of a second flexible frame according to a preset second frame structure and sending the echo signals to a sensing processing unit, the second frame structure is the same as the first frame structure, and the symbol ratios of the first flexible frame and the second flexible frame are different; the echo signal is a signal obtained after the detection signal is reflected by a target object; the relative position of the communication device and the target object is determined by using the perception processing unit. While the position is sensed, the normal communication service is not influenced, and the communication function and the position sensing function can be completed in the same communication device.

The invention provides a dynamic right distribution method, medium and system based on position awareness, and belongs to the technical field of dynamic right distribution, and the method comprises the steps: collecting the real-time position data of a consumer through a mobile terminal, building a position trajectory diagram, and calculating a position residence intensity index; then, merchant positions in a business district are obtained to construct a position matrix, and the merchant positions where consumers are located are determined by combining the wireless network identifiers to generate position association degrees; analyzing historical consumption data and behavior characteristics of consumers by using a prediction model of a multi-head space-time attention network structure, and calculating a merchant attraction index by combining a position residence intensity index and a position correlation degree; a time sensitivity coefficient is further adjusted through a consumer value judgment function, and a right issuing threshold value is dynamically adjusted according to a business district people flow density factor; and finally, selecting a proper right and interest type according to the consumer portrait and accurately pushing the right and interest type, thereby realizing dynamic accurate right and interest distribution based on location awareness.

The present invention belongs to the technical field of computer vision and three-dimensional scene reconstruction, and discloses an overlapping mask optimized coarse-to-fine point cloud automatic registration method and system. First, the KPConv encoder is used to extract features from the input point cloud, and through the kernel point-guided local aggregation mechanism and downsampling operation, the coarse-scale superpoint features are obtained; secondly, a position-aware attention module is introduced to embed position information in the superpoint features, providing geometric constraints for the attention mechanism, and adaptively fusing local geometric structures and global context information through self-attention and cross-attention operations to enhance the feature expression ability. Then, the enhanced superpoint features are input into the overlapping prediction network to generate an overlapping mask to eliminate non-overlapping regions, and a similarity matrix is constructed based on the retained superpoints, and a sample correction loss function is introduced for optimization to complete the establishment of the superpoint correspondence relationship at the coarse scale.

The embodiment of the invention discloses a vehicle data processing method and device, electronic equipment and a readable storage medium, and the method comprises the steps: obtaining the position sensing information of a vehicle, and responding to the position sensing information which comprises at least one traffic marker. Determining a target reference object corresponding to the at least one traffic marker and a distance between the vehicle and the target reference object, determining a second distance between a positioning point of the vehicle on the navigation page and the mapping reference position based on the map data, and determining a longitudinal error according to a difference value between the second distance and the first distance, and adjusting the position of the positioning point on the navigation page according to the longitudinal error. Therefore, through the method, the longitudinal error existing in vehicle positioning can be determined and improved, and the accuracy of vehicle positioning is improved.

The invention provides a wireless device deployment position optimization method and system based on Wi-Fi signals, relates to the technical field of wireless communication device deployment and intelligent wireless sensing, and aims to solve the problems that in the prior art, only indoor communication quality and communication safety are considered, a wireless sensing layer is not considered, and the position of a wireless device is not optimized in combination with the surrounding environment. The method comprises the steps of extracting key evaluation parameters of measurement data; constructing a fingerprint matching data set based on position-perception; constructing a two-dimensional quantitative model according to the key evaluation parameters; acquiring fine-grained characteristic parameters by adopting an energy compensation mechanism; and inputting the position factors, the fine-grained characteristic parameters and the position data of the fingerprint matching data set into a spatio-temporal information self-learning model, and determining the optimal position of deployment of the wireless equipment. According to the method, the communication quality and the sensing range of the Wi-Fi signal are combined, so that the position of the wireless equipment in the known indoor environment can be optimized, and the optimal position of the wireless equipment in the unknown environment can be recommended.

The invention discloses an aerial target detection method based on cross weighted pixel reconstruction, which comprises the following steps: acquiring an image data set containing an aerial target, and making a training sample; the method comprises the following steps: constructing an air target detection network model comprising a CPR module and an FS-PANet network module by taking a Yolov10 network as a basic network; inputting a training sample into the air target detection network model for training, and storing parameters of the trained network model; and inputting a to-be-detected image into the trained aerial target detection network model for aerial target detection. The method has the remarkable effects that direction perception and position perception information can be captured by mining information of the height, width and channel direction of the input feature map, so that the model can more accurately position and identify an interested target, and noise contained in the low-resolution feature map can be well removed through average pooling operation, so that the accuracy of the target recognition is improved. Interference enhancement target features are reduced; and the feature fusion efficiency is improved, so that the target detection precision is improved.

This invention relates to the field of target detection technology, specifically disclosing a target detection method, device, and storage medium for dedicated railway operation scenarios. The method includes: constructing a training dataset; building a basic target detection model based on the detection accuracy requirements of dedicated railway operation scenarios; optimizing the basic target detection model, including constructing a location-aware space-frequency coordination module in the backbone network to generate a spatial high-frequency saliency map using a dual-stream architecture and local frequency domain changes; constructing a frequency-guided cascaded feature alignment module in the feature pyramid network to guide the geometric offset of the predicted feature map based on the spatial high-frequency saliency map, and deforming and aligning the semantic attention map; and performing multi-round iterative training based on a combined loss function including detection loss and auxiliary constraint loss. The target detection method for dedicated railway operation scenarios provided by this invention can improve the accuracy of detecting small targets in dedicated railway scenarios.

The invention discloses an operator switching method and device based on position information, and relates to the technical field of network switching, and the operator switching method based on position information comprises the steps: generating a multi-source position data set according to satellite positioning data, base station signaling data and IP address data; performing feature extraction and fusion processing on the multi-source position data set to obtain structured state data including country codes, region codes and network service levels; writing the structured state data into a working memory of a rule engine, and sorting business rules in a rule base of the rule engine to obtain a rule execution queue; and generating an operator switching instruction according to the structured state data in the working memory and the service rules in the rule execution queue, and completing operator switching according to the operator switching instruction. According to the invention, intelligent switching of cross-border operators can be realized based on multi-source location awareness and a dynamic rule engine.

The invention provides a visible light communication, position awareness and energy collection integrated method based on OFDM, and relates to the technical field of visible light communication. The method comprises the following steps: at a sending end, performing OFDM modulation on user information to be sent to generate an OFDM signal, and sending the OFDM signal to a receiving end through a plurality of LEDs; at a receiving end, adopting a silicon photocell as a photoelectric detector to receive the OFDM signals sent by the plurality of LEDs to obtain received signals; at a receiving end, separating a direct-current component and an alternating-current component in a received signal by adopting an alternating-current and direct-current separation circuit, and performing energy collection on the separated direct-current component; at a receiving end, processing the separated AC component, extracting a positioning subcarrier and a communication subcarrier, performing OFDM demodulation on the communication subcarrier, recovering user information, and determining the position information of the user according to the light intensity information contained in the positioning subcarrier and the position information of the LED; in this way, communication, location awareness and energy harvesting functions can be provided for users at the same time.

This invention discloses an embodied intelligent agent position perception method and system based on wireless radio frequency fingerprinting, belonging to the field of embodied intelligent agent wireless position perception technology. The method includes: using a full-band multi-directional wireless signal acquisition device to collect radio frequency signals in a time-division manner and obtain digital signals containing radio frequency fingerprints; clustering and grouping the digital signals, assigning identity authentication IDs, and removing invalid data; training a classification model using the grouped data and realizing ID recognition; determining relative position by combining angle arrival algorithm and signal power strength; dynamically sensing relative position time changes based on its own position changes; and performing the clustering to dynamic sensing steps in a long-cycle loop to realize the dynamic discovery and deletion of intelligent agents. This invention is based on physical layer autonomous perception, requires no central node, and has the characteristics of low latency, low power consumption, and high accuracy. It is suitable for the dynamic collaborative needs of multiple intelligent agents in power scenarios and can be widely used in embodied intelligent agent collaborative operations in power scenarios such as substations and converter stations.

The embodiment of the invention provides a distributed cooperative positioning method and system facing non-convex topology and DOS attack, and the method comprises the steps: obtaining a plurality of communicable vehicles closest to a to-be-positioned vehicle, and enabling the plurality of communicable vehicles to be not collinear; obtaining symbolized barycentric coordinates of the to-be-positioned vehicle relative to the plurality of communicable vehicles; when a communication link is normal, iteratively updating the current position information of the to-be-positioned vehicle based on the previous position information of the to-be-positioned vehicle, the symbolized barycentric coordinates and the current position information of the plurality of communicable vehicles; when the communication link is subjected to the DoS attack, position compensation is obtained based on the influence condition of the DoS attack on the communication link; and iteratively updating the current position information of the to-be-positioned vehicle based on the position compensation. According to the embodiment of the invention, reliable position sensing support can be provided for an intelligent motorcade in a high-dynamic and weak communication guarantee environment.

The invention discloses an electric vehicle charging state detection method based on multi-scale feature extraction and a multi-attention mechanism. The multi-scale feature extraction and the multi-attention mechanism are fused. Firstly, a data set containing normal charging and simulated attack behaviors is constructed, and an enhanced sample is generated through preprocessing. The core innovation lies in designing an MSMA-Net model and integrating three key modules: an ACK-CCI module strengthens the multi-scale feature extraction capability through an adaptive channel convolution kernel; the PARA module introduces a position perception residual attention mechanism, and accurately captures data internal structure and channel-space information; the LMA module uses linear transformation to reduce calculation complexity and enhance global information perception at the same time. Experiments show that the model significantly improves the anomaly detection precision in a complex charging scene through the synergistic effect of multi-scale spatio-temporal feature learning and an attention mechanism, and provides efficient technical guarantee for the charging safety of the electric vehicle.

The present invention discloses a test system for the alignment guidance function of an electric vehicle wireless charging system in the field of radio transmission technology, which is intended to solve the test and installation problems of the secondary side equipment of the electric vehicle charging system of different manufacturers and the position perception accuracy test problems. The test system includes a control processor, a loading shell, a sample clamping module and a positioning and navigation module, wherein the sample clamping module includes a clamping assembly, a centering clamping drive mechanism and a lifting drive mechanism, and the positioning and navigation module includes a positioning device and a distance measuring device, which can identify the position relationship between a specified reference point and the primary side equipment and the secondary side equipment within the detection range, and then the control processor can calculate the position relationship between the secondary side equipment and the primary side equipment. The present invention can accurately test the position perception accuracy and deviation correction guidance of the alignment guidance function of the electric vehicle wireless charging system, and the operation is simple and efficient.

This invention discloses a clustering method for underwater wireless sensor networks based on improved AP clustering, which relates to the field of underwater wireless sensor network topology optimization. By acquiring node status information in the underwater wireless sensor network and initializing node feature data, the method improves its adaptability to underwater environments by comprehensively considering inter-node distance, received signal strength, and node residual energy. It also employs an energy and position-aware mechanism to iteratively update attraction and affiliation information to form a preliminary cluster structure, effectively addressing node energy consumption and position changes in complex underwater environments. Based on the node communication range, preference values ​​are updated to adjust the cluster structure to ensure that no nodes leave the cluster. A comprehensive weight function for cluster head updates is designed to avoid bias due to a single factor. This invention can better adapt to complex underwater environments, effectively optimize network topology, balance sensor node energy consumption, and improve the stability and energy efficiency of underwater wireless sensor networks.

The invention discloses a coverage performance test method, a coverage performance test device and electronic equipment, relates to the technical field of communication, and aims to solve the problem that the coverage boundary capability of a single station cannot be scientifically and comprehensively evaluated in related technologies. The method comprises: according to working parameters of a base station, determining a plurality of test trajectories for a sector of the base station and a plurality of different test heights corresponding to each test trajectory, the plurality of test trajectories at least comprising: a first trajectory along a horizontal normal direction of the sector, and a second trajectory and a third trajectory along a horizontal coverage maximum angle direction of the sector; track test data is obtained, and the track test data comprises position sensing data of the base station to the test equipment in the process that the test equipment carries out movement test according to the multiple test tracks and the multiple different test heights; and according to the track test data, determining a coverage performance parameter set for representing the actually measured coverage range of the base station.

Program products, methods, and systems for providing location-aware fitness monitoring services are disclosed. In an embodiment of the present invention, a method of displaying a route traversed by an athlete equipped with a location-aware portable fitness monitoring device includes the steps of (a) receiving data describing a plurality of satellite navigational system waypoints that are acquired as the athlete engages in a fitness activity, (b) identifying a map area based on a location indicated by the data describing the plurality of satellite navigational system waypoints, (c) determining the route traversed by the athlete based on the data describing the plurality of satellite navigational system waypoints and based on the location of one or more known paths associated with the map area, and (d) displaying the route traversed by the athlete on top of the map area.

The invention discloses a sequence recommendation method based on a pulse graph neural network. The method comprises the following steps: dividing user-project interaction data into T adjacent matrixes according to time periods; the time perception interaction denoising module based on the attention mechanism is used for denoising each section of adjacent matrix by using a soft attention mechanism; a pulse driving graph neural network module is adopted, and node representation is updated through LIF pulse neurons, dual regulatory factors and a dual-threshold mechanism; explicitly modeling long-distance time dependence based on a position awareness attention sub-module; performing weighted integration on recent and historical interests based on a time-aware interest fusion sub-module to obtain an integrated user item representation; future interaction prediction is made based on the user item representation. According to the novel sequence recommendation method provided by the invention, long and short term interests and time dynamics of the user can be modeled at the same time, a pulse neuron and time contrast learning mechanism is introduced, and the defects of an existing recommendation system are overcome.

The present application relates to a position sensing method and apparatus, a computer device, a readable storage medium, and a program product. The method is applied to a receiver. The method comprises: processing a received reception signal to obtain a direct link signal corresponding to a signal source; on the basis of a serial interference cancellation policy and the direct link signal, determining a reflected link signal from the reception signal; performing sensing parameter estimation on the reflected link signal to obtain position sensing data; and determining coordinate information of a target device on the basis of the position sensing data. The present method can improve the accuracy of position sensing of reflection and scattering devices.