2644 results about "Network connection" patented technology

The invention relates to a charging pile intelligent operation management method and system based on the Internet of Things. The method comprises the following steps: performing Internet of Things topology construction on charging pile nodes to obtain a node communication distance matrix and a network connectivity matrix; performing deep learning dimension reduction and node screening based on the network connectivity matrix to obtain a fault feature vector; the fault feature vector and the charging pile operation state data are input into a hybrid neural network for risk calculation, a fault risk assessment value is obtained, and the hybrid neural network comprises a space perception sub-network and a time sequence analysis sub-network; performing normalization and dimension reduction mapping on the power response data of the charging pile to obtain a time domain mapping matrix; and performing particle swarm optimization calculation based on the time domain mapping matrix and the fault risk assessment value to obtain a charging power distribution scheme, and generating a control instruction set according to the charging power distribution scheme. According to the invention, the dynamic optimization of the charging power distribution scheme is realized, and the charging efficiency and the load balance are effectively balanced.

According to the 5G portable WiFi signal enhancement method and system provided by the invention, surrounding environment data are collected through an environment sensing sensor, and a device placement scheme is optimized in combination with a deep learning algorithm, so that the signal coverage range is expanded; the strategy of dynamically adjusting the transmitting power, the signal frequency and the modulation mode can optimize the signal strength according to the environmental change; interference signals are analyzed through quantum calculation, null is formed through the beam forming technology, interference signal receiving is effectively restrained, and the signal strength in the target direction is enhanced. In combination with the Internet of Things technology, uploading equipment state data to an edge server in real time for big data analysis, and pushing a personalized signal enhancement scheme according to different user use environments; through precise placement guidance and a dynamic frequency band switching strategy, a user can enjoy smoother network connection in a use process, and good signal quality is ensured to be kept in a complex environment. According to the invention, not only can the signal quality of 5G portable WiFi be improved, but also more intelligent and personalized network experience can be provided for users.

The invention discloses an edge computing power sharing method, an edge computing power sharing device, edge computing power sharing equipment and a medium, and the edge computing power sharing method comprises the following steps: connecting edge nodes through a decentralized P2P network, constructing a network connection module, and realizing computing power resource sharing among the nodes; collecting and monitoring computing power resource state data of each edge node through a computing power resource management module, judging nodes in an idle state through an evaluation algorithm, and adding computing power resources of the nodes into a shared pool; the node matching module is used for screening out an optimal matching node from the shared pool by utilizing a preset screening algorithm according to task demand information released by a computing power demand side; and the distribution execution module sends the task instruction to the selected optimal node from the cloud, and after the task is executed, the node releases the computing power resource and performs expense settlement through the charging module. According to the method, the utilization efficiency of computing power resources is optimized through decentralized node management and an intelligent matching mechanism, so that edge computing resources are more easily integrated and utilized.

Methods and systems for providing network connectivity are disclosed. In an embodiment, a method for providing network connectivity involves receiving from a Mobile Network Operator (MNO) an access ID, an IP address, and an Access Point Name (APN) at a SASE domain, wherein the access ID, the IP address, and the APN correspond to a wireless device, updating IP address-to-tenant mappings at the SASE domain in response to the access ID, the IP address, and the APN, and forwarding traffic received at the SASE domain from the wireless device via the MNO according to the updated IP address-to-tenant mappings.

The invention discloses an intelligent water affair monitoring and management system based on digital twinning, and relates to the technical field of intelligent water affair. The intelligent water affair monitoring and management system comprises a water affair monitoring and management platform, and the water affair monitoring and management platform is in communication connection with the following modules: a multi-source data acquisition module; the water affair monitoring system is used for collecting and preprocessing water affair monitoring data from a plurality of monitoring points of the water affair system, monitoring changes of a pipe network topological structure and obtaining dynamic data of a pipe network connection relation and geometric parameters. Through the digital twinborn technology, data of multiple monitoring points can be integrated in real time, abnormal events such as water quality pollution, equipment faults, water shortage and hydraulic change can be rapidly recognized in combination with the abnormal trend analysis module, early warning signals are automatically generated, the response time is remarkably shortened through an instant early warning mechanism, and the early warning efficiency is improved. Therefore, the management personnel can take measures at the initial stage of the abnormal event, the problem expansion is effectively prevented, and the timeliness and accuracy of water management are improved.

The invention relates to the technical field of network communication, provides a dual-stack network adaptive scheduling method and system based on a DNS analysis strategy, and is used for establishing an effective protocol stack feature association mechanism so as to realize cross-protocol-layer intelligent scheduling. The method comprises the steps that a DNS analysis request sent by a client side is received, and the DNS analysis request carries a target domain name and a request protocol type; analyzing the request protocol type to determine a network protocol stack type supported by the client; generating an adaptive scheduling strategy corresponding to the target domain name according to the network protocol stack type and a preset address type priority list; selecting a target IP address type from a pre-configured IP address pool based on the self-adaptive scheduling strategy; and returning an analysis result corresponding to the target IP address type to the client so as to guide the client to establish network connection through the target IP address type.

The invention provides a cross-platform network speed measurement and adaptive path switching method and device and a storage medium. The method comprises the following steps: receiving a target domain name and a multi-source DNS server list; extracting historical network quality data corresponding to the environment identifier and each candidate IP address, inputting the historical network quality data into a link quality prediction model to obtain a prediction score of each candidate IP address, and screening according to a preset threshold to obtain a target IP subset; performing active detection of limited times on each IP address in the target IP subset to obtain a detection index; calculating the comprehensive score of each IP address based on the prediction score and the detection index, determining the optimal IP address with the highest comprehensive score, and recording the DNS server address of the optimal IP address; and establishing a network connection path according to the optimal IP address, and providing a DNS server address of the optimal IP address for a service layer. According to the method and the device, the cross-platform maintenance cost can be reduced, the real-time performance and the performance overhead are considered, the path is dynamically optimized, and rapid connection switching is realized.

The invention discloses an unsupervised deep learning image splicing method for portable fundus color photo equipment. The method comprises the following steps: constructing a multi-scale feature extraction module of an image registration network; the feature matching module is used for constructing an image registration network; the multi-scale feature extraction module and the feature matching module are sequentially connected to form the constructed image registration network; constructing a shallow feature extractor; constructing a feature reconstruction module; constructing a joint generator; sequentially connecting the shallow feature extractor, the feature reconstruction module and the seam generator to form a fusion network; constructing a fusion network; connecting the image registration network and the image fusion network to form an image splicing model; collecting data; preprocessing the data; obtaining a trained image registration network; obtaining a trained image fusion network; forming a fundus image splicing model by using the trained image registration network and the trained image fusion network; and splicing the images by using the eye fundus image splicing model. According to the method, a high-quality fundus spliced image can be efficiently generated.

A live mapping framework may be generated for large enterprise- wide networks and systems. The live mapping framework includes identification of key attributes of every device connected to the network. The key attributes may include device type, installed software packages, network connection information, device usage information, and other information. Frequent updates to the live mapping framework and trending over time enable the identification of system vulnerabilities. Generative and explainable Al may additional be used for penetration testing of virtual replicas of the enterprise- wide networks, leading to the generation of solution sets addressing the identified vulnerabilities.

A system for an automated real-time digital identity verification based on predictive analytics of user identity data, including a processor of a digital identity verification (DIV) node configured to host a machine learning (ML) module and connected to at least one verifier entity node over a network and a memory on which are stored machine-readable instructions that when executed by the processor, cause the processor to: acquire an identity verification request associated with a user from the at least one verifier entity node, wherein the identity verification request comprising user biographic data and a truncated facial biometric hash extracted from a digital identity feature embedded into an identification document of the user and user biographic data acquired from the identification document and a facial biometric hash generated from the user identification document; parse the identity verification request to derive a plurality of key features; generate at least one feature vector based on the plurality of the key features; and provide the at least one feature vector to the ML module configured to execute a predictive model based on underlying neural network configured to produce at least one user identity verification parameter for generation of a user identity verification verdict.

Monitoring is performed for the activation of a set of one or more previously attached Kprobes. A determination is made that a strategy pattern match has occurred. The strategy pattern comprises a set of one or more behaviors including the activation of the at least one Kprobe included in the set of Kprobes. A remedial action is taken in response to the determination. Examples of such remedial actions include generating an alert and terminating a network connection.

The invention relates to an intelligent metering box monitoring method, system and device and a storage medium, and the method comprises the steps: continuously collecting the operation data of an intelligent metering box in an offline state of the intelligent metering box, carrying out the abnormal trend recognition of the operation data through combining with a pre-trained edge side abnormality recognition model, and obtaining a local judgment result; abnormal record data are generated according to the local judgment result, the abnormal record data are cached in a local storage unit, and the abnormal record data comprise fault types, timestamps and index values; generating a communication connection request signal under the condition that the communication connection condition is met, and controlling the communication channel to establish network connection according to the communication connection request signal; and after the communication response is received, collecting the network signal strength, and uploading the abnormal record data to a remote management platform based on the network signal strength. The intelligent metering box has the effect of improving the monitoring reliability of the intelligent metering box.

The power supply conversion circuit includes an isolation transformer, and the isolation transformer includes at least two primary coils and at least one secondary coil. Each primary coil is connected to a half-bridge circuit by using a first resonant network, and half-bridge circuits corresponding to the at least two primary coils are connected in series between two electrodes of a power supply. The half-bridge circuit is connected in parallel to a voltage divider, the voltage divider includes a first capacitor and a second capacitor that are connected in series, a first terminal of the first resonant network is connected to an intermediate node of the half-bridge circuit, and a second terminal of the first resonant network is connected to a connection point between the first capacitor and the second capacitor.

The invention relates to the technical field of comprehensive factory control, in particular to a mold whole-process quality monitoring system and device and a storage medium, and the system comprises a data collection and synchronization module which is connected with a plurality of mold manufacturing machine tool connection networks, collects machining data and operation states of mold manufacturing machine tools, generates a real-time data flow, and carries out the real-time processing of the mold manufacturing machine tools based on the real-time data flow. And analyzing the working efficiency and state of the mold manufacturing machine tool to obtain an equipment state result. According to the method, the machining data and the operation state of the mold manufacturing machine tool are collected in real time, the real-time data flow is formed, the machine tool operation efficiency and the equipment state are dynamically analyzed, state monitoring and production quality prediction in the mold manufacturing process are achieved, and the transparency and the management and control capacity of the mold machining link are improved; and according to the quality prediction result obtained through analysis, the production line performance and the equipment efficiency are dynamically evaluated, the production tasks are scheduled in real time, the equipment load distribution is optimized, a dynamic production scheduling system is formed, and the production efficiency and the resource utilization rate are improved.

Examples provide improved methods for managing wireless network connectivity for a mobile device. Examples include receiving a network map that defines geographic availability of a first wireless network; determining that the first wireless network is accessible within a travel segment of a travel plan based on comparing geographic location data associated with the travel segment to the geographic availability of the first wireless network from the network map; creating a network plan that includes the travel segment and an associated connectivity waypoint, the connectivity waypoint defining when to alter connectivity status with the first wireless network; and causing the mobile device to alter connectivity status with the first wireless network based on proximity to the connectivity waypoint.

A method and system for automated routing of pictures taken on mobile electronic devices to a digital picture frame including a camera, microphone, and speaker integrated with the frame, and a network connection module allowing the frame for direct contact and upload of photos from electronic devices or from photo collections of community members. Clustering photos by content is used to improve display and to respond to photo viewer desires. Trends or patterns can be detected from the photo collections and that information is used for various purposes beyond photo display. The frame includes a conversational intelligence that provides a verbal communication with a viewer, such as for determining an identity or preferences of the frame viewer, determining photos to display for the viewer, discussing displayed photos with the viewer, or telling stories and life histories to the viewer based upon photo content.

The invention relates to the technical field of defect detection, in particular to a defect detection method, system and equipment based on improved YOLOv5 and a medium. Firstly, image data of industrial parts in the production process are collected through a high-definition camera, image preprocessing is carried out according to part surface defect characteristics, key frames are extracted, defect areas are marked, and a defect detection data set is constructed; secondly, configuring a training environment; constructing a CED-YOLO network model by taking the YOLOv5 network as a basic network, replacing a C3 module in a backbone network of the YOLOv5 network with a CEMS module as a feature extraction module, replacing a C3 module of a neck network connection detection layer part with differential attention DA, and enhancing extracted features; and finally, the CED-YOLO network model is trained and verified by using the data set after data enhancement, so that the calculation amount is effectively reduced, the detection efficiency is improved, and the detection performance of the model is greatly improved.

The invention relates to the technical field of vehicle Internet of Things, and discloses a vehicle control method and device based on Internet of Things equipment, a vehicle and a storage medium, and the method comprises the steps: obtaining equipment configuration information of the Internet of Things equipment through a network connection domain controller, generating a plurality of standard service interfaces, generating an equipment registration request, and transmitting the equipment registration request to a cloud end; and the cloud end obtains the vehicle control authority according to the equipment configuration information and sends the vehicle control authority to the network connection domain controller. Then, the network connection domain controller performs permission configuration on the plurality of standard service interfaces based on the vehicle control permission to obtain a target service interface conforming to the vehicle control permission, so that the Internet of Things equipment can send a target control instruction consistent with the permission range of the target service interface through the target service interface; the network connection domain controller reasonably controls the vehicle according to the target control instruction, so that the vehicle is prevented from mistakenly executing an unauthorized instruction of the equipment, the driving safety of the vehicle is effectively ensured, authority control can be performed on data transmission between the vehicle and the Internet of Things equipment, and the data safety is ensured.

The invention discloses a tamper-resistant end-to-end service data storage method and system, and relates to the technical field of service data storage methods, and the method comprises the steps: initializing a hardware security module and a monotone increasing clock in terminal equipment, building a unique identity identifier of the equipment, and preparing a log environment for recording service data; the method comprises the following steps: collecting current business data and associated meta-information thereof, and constructing input content of current data processing in combination with an equipment identity, a clock value, a data structure template and an abstract value generated by previous business data; hash operation is carried out on the input content to generate an abstract of the business data, the abstract is signed by using a hardware security module to form an equipment side digital signature, and the abstract, the signature and meta-information are written into a log only increasing but not changing and an offline queue; and after the terminal recovers the network connection, generating a unique idempotent key based on the abstract of the service data or the combination of the equipment identity and the clock, and submitting an evidence storage request containing the abstract and the signature to the server.

An automated carbon asset network system and a carbon asset management method are provided. The automated carbon asset network system includes a carbon asset management digital platform realizing a carbon inventory executed for an enterprise through a computer system, and the carbon asset management digital platform includes a carbon asset network establishing module, a carbon asset network connection module, and a carbon asset network update module. The carbon asset management method includes: receiving data for stakeholders, internal or external carbon asset management digital platform, carbon asset management report formats, and carbon inventory obtained through automated customized questionnaires, by using the application program interface; automatically integrating carbon inventory data for supply chains and performing version control; digitally managing a full scope of an organizational greenhouse gas inventory and product carbon footprint information throughout product life cycles for brands in the enterprise; and generating documents according to requirements.

The invention belongs to the field of photovoltaic panel hot plate image processing, and particularly relates to a photovoltaic panel defect detection method fusing multi-scale wavelets and a lightweight attention mechanism. According to the method, an RHDWT discrete wavelet transform module based on multi-scale decomposition is added in a model input stage to strengthen image edge and texture detail representation; a Mix Structure Block module is introduced into a backbone network of the YOLOv11, so that multi-scale features are fused, and the feature expression capability is improved; an LWGA lightweight global attention mechanism is introduced into a neural network connection layer to enhance the context modeling capability, and the detection effect on small target defects such as fine cracks and hot spots is improved. According to the model, through collaborative optimization in three aspects of input preprocessing, feature extraction and an attention mechanism, the precision and robustness of defect detection in a complex photovoltaic module infrared or visible light image are remarkably improved, and the model is suitable for scenes such as high-precision photovoltaic panel image detection and intelligent maintenance.

The invention discloses an urban intelligent water affair risk dynamic identification and early warning method based on deep learning, and the method comprises the following steps: S1, collecting the water pressure, flow, residual chlorine concentration, elevation, rainfall, valve state, pump station state and accident label of each node in a water supply network, and constructing a time alignment data sequence; s2, constructing a dynamic adjacency matrix according to the pipe network connection relation and the event state information; s3, inputting the data sequence and the dynamic adjacency matrix into an improved space-time diagram wavelet neural network to generate space-time feature representation; s4, multi-scale features are extracted and fused through the high-frequency branches and the low-frequency branches; s5, constructing a hyperedge set, executing graph structure propagation, and generating a risk representation tensor; s6, inputting the risk representation tensor into the risk prediction network, and outputting a node risk probability and a confidence interval; and S7, determining a risk level according to the risk probability and the confidence interval, and generating a corresponding early warning signal. According to the invention, fine modeling and dynamic early warning of urban water supply risks are realized.

According to some embodiments, a method performed by a wireless device for non-terrestrial network (NTN) connection control comprises receiving a message comprising parameters from which the wireless device is informed that it is to disconnect from a terrestrial network (TN) and connect to one of one or more NTNs or disconnect from a NTN and connect to one of one or more TNs. Upon the parameters informing the wireless device to connect to one of one or more NTNs, the method further comprises: disconnecting from the TN; based at least in part on the one or more parameters, selecting one of the detected at least one of the one or more NTNs; and connecting to the selected NTN. Upon the parameters informing the wireless device to connect to one of one or more TNs: the method further comprises disconnecting from the NTN, and detecting, selecting, and connecting to the TN.

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 relates to the technical field of communication and electronics, and discloses a low-altitude unmanned system data processing method and gateway based on edge computing, and the edge computing gateway executes the following steps: obtaining sensor data collected by a low-altitude unmanned system in real time, continuously monitoring the network connection quality between the edge computing gateway and the cloud server; in response to the change of the network connection quality, dynamically selecting one adaptive mode from three preset data processing modes; processing the sensor data by adopting the selected data processing mode to obtain an analysis result; and based on the analysis result, locally generating a control instruction for controlling the low-altitude unmanned system at the edge computing gateway. By analyzing the preset task profile file and combining the utility evaluation and the model selection strategy, the computing resources and the AI model of the unmanned system are subjected to prospective pre-configuration.

There is provided a method performed by a user equipment, UE, for allowing the UE to use a localized service in a hosting network, the method comprising: obtaining configuration information, the configuration information containing a list of one or more preferred hosting networks for the localized service; determining one or more available networks; from the determined one or more available networks, identifying one or more hosting networks on the list of the UE, human-readable information, the human-readable information being based on the identified one or more hosting networks; receiving a user input indicative of a user of the UE selecting a hosting network of the identified one or more hosting networks; and establishing a network connection with the selected hosting network.

An electric valve includes a motor, a power transmission mechanism that converts rotational movement generated by the motor into axial movement of a valve body, a housing that accommodates at least a part of the power transmission mechanism and the motor, an external connector that is provided to the housing and enables power supply to the motor and communication with a control device connected via a network, and a control substrate that is provided in the housing, processes the communication and controls the motor, and has a connection position connected to an external connector-side terminal and a connection position connected to a motor-side terminal disposed on opposite sides to each other with respect to the axis of the motor.

The invention discloses a social risk management method based on a large model and multi-modal data, and relates to the technical field of risk management, and the method comprises the following steps: accessing multi-source heterogeneous data from multiple parties, and carrying out unified space-time alignment and cleaning; analyzing data, extracting entities and relationships thereof, and constructing a basic map; the method comprises the following steps: quantifying mechanical operation into dynamic disturbance to a nearest pipe network, calculating health degree attenuation of the mechanical operation, simulating a dynamic process of spreading a risk to peripheral nodes along a pipe network connection relation, and updating a risk state of the whole network in real time; when the pipeline health degree is lower than a critical value, causal reasoning is triggered, and early warning information is automatically generated and pushed to a related responsible unit; and collecting a feedback result of each early warning to periodically optimize and adjust parameters in the risk propagation model. According to the method, the space-time knowledge graph is constructed, and the dynamic risk propagation model is researched and developed based on the space-time knowledge graph, so that the dynamic influence of construction disturbance on the pipe network system can be accurately quantified, and the chain evolution path of the pipe network system can be simulated.

Systems and methods provide witness sled hardware that may be installed in a chassis and that is configurable using management resources of a chassis in which the witness sled is installed. The chassis may include data storage devices and Information Handling Systems (IHSs), each including one or more CPUs (Central Processing Units) that execute instructions that cause a respective IHS to store data redundantly to the plurality of data storage devices, such as part of a vSAN (Virtual Storage Area Network). The witness sled is configured to provide witness functions, such as arbitrating discrepancies in the redundantly stored data. The chassis includes a management controller that is configured to interface with the witness sled to set up high-speed network connections supported by the witness sled in order to configure the witness sled for providing witness functions within the vSAN, while accounting for the limited resources of the compute sled.

The invention provides a network connection method, electronic equipment and a computer readable storage medium. Under the condition that the access point equipment uses a WPA2 / WPA3 hybrid encryption mode, when the site equipment does not have the WPA3 encryption capability but declares to support WPA3 encryption, the access point equipment can guide the site equipment to adopt WPA2 encryption to carry out access authentication. Therefore, the site equipment can be smoothly connected to the network where the access point equipment is located, so that the compatibility when the access point equipment uses the WPA2 / WPA3 hybrid encryption mode is improved.