97 results about "Network adaptation" patented technology

The embodiment of the invention provides a data transmission method and device of Internet of Things equipment, electronic equipment and a storage medium, and relates to the technical field of Internet of Things, and the method comprises the steps: obtaining business data collected by the Internet of Things equipment, and determining the target business priority of the business data; acquiring network index data of communication equipment connected with the Internet of Things equipment; performing data volume prediction according to the service data to obtain a corresponding predicted data volume; performing transmission mode selection according to the predicted data volume and the network index data to obtain a first transmission strategy for the service data; and issuing the first transmission strategy to the Internet of Things equipment, so that the Internet of Things equipment transmits the service data according to the first transmission strategy, thereby optimizing the data transmission mode, realizing dynamic adjustment of the transmission strategy, improving the network adaptability, improving the success rate of data transmission, and reducing the probability of network congestion.

A system and method for a hierarchical thought supervision network with adaptive processing capabilities. The system processes data through a base graph layer of interconnected computational nodes, a telemetry layer for real-time monitoring, and one or more supervision layers composed of supervisory nodes. The base layer handles thought processing and management, while the telemetry layer continuously tracks operational metrics to evaluate processing efficiency. Supervisory nodes adapt network operations by optimizing thought encodings, generating new nodes when needed, and pruning inefficient nodes based on performance objectives. A telemetry layer continuously tracks processing efficiency using adaptive kernel functions and topology-aware distance metrics. The system maintains effective processing while dynamically adjusting to computational demands through coordinated supervision across multiple layers. This approach enables real-time network adaptation while optimizing performance and efficiency across the system.

The invention belongs to the technical field of information technology and intelligent health service, and discloses a community old-age care service resource optimal configuration method based on edge computing, which comprises the following steps: collecting physiological data, environmental data and activity data of old people to form original heterogeneous data, uploading the original heterogeneous data to a data warehouse through an urban and rural community network adaptation mechanism, generating a space-time tagging multi-modal data set; constructing a dynamic digital twinborn model, generating a space thermodynamic diagram, identifying different level priority requirements, and generating a time period allocation scheme through a conflict priority scoring mechanism; an MILP model is constructed to dynamically optimize edge node computing power and functional area space resources, and a resource optimization report and a block chain transaction list are generated; desensitizing the original data of the old people, creating a digital identity card, generating an encrypted service log, and synchronously recording migration behaviors of the old people; and triggering network strategy switching and priority threshold self-adaption, and carrying out resource scheduling and strategy closed-loop optimization.

The invention discloses an ultrasonic image off-line acquisition and dynamic synchronous processing method and system, which realizes off-line acquisition and dynamic synchronous processing of an ultrasonic image under the condition of network interruption through six functional modules, namely a network state monitoring module, an online data synchronization module, an image acquisition processing module, an off-line mode switching module, an off-line diagnosis processing module and an increment synchronization module. The method comprises the following steps: acquiring network connection state data and judging a working mode; pulling and caching tasks and template data in an online state; obtaining multi-modal image data and performing double-writing storage; detecting network interruption and switching to an offline mode; performing AI analysis on the images acquired offline and generating a report; and detecting network recovery and executing incremental data synchronization. According to the invention, the problem of service interruption caused by dependence of a traditional PACS system on a network is solved, the network adaptability and robustness of the system are improved, the operation and maintenance cost is reduced, and the system fault recovery time is shortened.

The invention relates to the field of multimedia communication and network control, in particular to an intelligent network control method for low-delay video return and related equipment. The intelligent network control method comprises the following steps: acquiring network key indexes including bandwidth, delay, jitter and packet loss rate of a network link in real time, and providing real-time network environment data support for transmission strategy adjustment. According to the method, an intelligent control mechanism combining network state perception and video content feature recognition is constructed, so that the technical problem of low-delay video return in a complex network environment is effectively solved. Specifically, key indexes of a network link are collected in real time, and a lightweight CNN model is introduced to analyze the video content activeness, so that dual perception capabilities for a network environment and content features are formed, data support is provided for dynamic adjustment of coding parameters, and accurate balance between video quality and network adaptability is realized.

The invention discloses a court cross-network audio and video signaling two-way interaction system and method. The system comprises a multi-protocol access adaptation module, a security isolation module and the like. The multi-protocol access adaptation module is provided with a special access adaptation unit for multiple protocols; the security isolation module realizes physical isolation through a security data exchange platform and a one-way audio and video optical shutter, and a built-in signaling security detection unit detects signaling; the signaling conversion module converts the signaling into an internal uniform format and adapts to the internal uniform format; the signaling processing module processes signaling, extracts information, schedules resources and feeds back a result; the network adaptation module adjusts transmission parameters; the identity authentication and authorization module uses multi-factor authentication and fine-grained authorization. The method comprises the steps of signaling initiating and receiving, identity authentication and authorization, multi-protocol access adaptation, signaling conversion processing and the like. The system solves the problems of cross-network communication protocol compatibility and the like, and improves the convenience and safety of judicial services.

The invention relates to the field of industrial Internet of Things, in particular to an edge computing communication method and system for the industrial Internet of Things, and the method comprises the following steps: 1, a user issues a task to a service platform through a user platform, and after the service platform receives a task request, the service platform sends the task request to the user platform based on a device type and a task type associated with the task; classifying and marking the tasks, and determining real-time levels of the tasks and importance weights of associated production links; 2, the service platform transmits the classified tasks to a corresponding service sub-platform, the service sub-platform obtains historical operation data and edge node basic information of task associated equipment, generates a first calculation task carrying a task attribute tag according to a classification result, and sends the first calculation task to a management platform; and step 3, the management platform carries out unified management on the plurality of first computing tasks. By adopting the technical scheme of the invention, industrial scene characteristics can be fit, and task priority, resource dynamics and network adaptability are considered.

A system and method for adaptive neural network architecture implementing sophisticated supervision and signal transmission capabilities. The system comprises a layered neural network monitored by a hierarchical supervisory system that collects operational data and implements architectural modifications. A meta-supervisory system oversees the supervisory process, tracking adaptation patterns and extracting generalizable principles from successful modifications. The system implements novel signal transmission pathways that enable direct communication between non-adjacent network regions through adaptive transformation components and coordinated timing mechanisms. This multi-level approach enables dynamic network adaptation while maintaining operational stability through careful monitoring and controlled modification procedures. The system's innovative architecture allows neural networks to evolve their processing capabilities during operation while preserving reliable performance through sophisticated supervision and controlled signal propagation.

The invention relates to a method and apparatus for generating a project-specific network architecture. The invention relates to a method for generating a project-specific network architecture, said method comprising the steps of:-providing (S1) a base model, in particular a large language model, with LoRa network adaptation; providing (S2) a model library having training data pairs, each of which consists of input data having a model application and / or model and / or hardware and / or software specification, and output data having at least one network architecture belonging to the respective input data; -selecting (S3) item-specific training pairs on the basis of said library of models; and-training (S4) the LoRa network of the base model on the basis of the item-specific training pair for generating the item-specific network architecture.

The invention provides a low-power-consumption wireless ad hoc network dynamic configuration method and system based on adaptive routing, and relates to the technical field of network protocols, and the method comprises the steps: determining a data transmission path through obtaining node working state parameters and calculating an energy level value, and setting a multi-level data cache occupation threshold value; calculating a network load distribution state, and carrying out differentiated scheduling on nodes; selecting a low-power-consumption forwarding channel based on node routing adaptability; and monitoring the network state in real time and updating parameters. According to the invention, the network adaptability is improved, the communication power consumption is reduced, the network life cycle is prolonged, and the data transmission efficiency is improved.

A 3D development engine-oriented adaptive flow loading method relates to the technical field of 3D development engines, and comprises the following steps: collecting environment state data through an environment sensing module; continuously acquiring a network state index through a network monitoring module; establishing a dynamic priority calculation model, taking the environment state data and the network state indexes as input parameters, and generating a quantitative priority score for each resource project; performing dynamic reconstruction and sorting processing on the resource loading task queue based on a priority scoring result, adjusting the execution number of concurrent loading tasks according to a real-time network state index, and selecting a corresponding resource compression strategy; and establishing a resource life cycle management system, and executing allocation optimization and recovery cleaning operation of the memory resources. According to the invention, adaptive flow loading of 3D resources can be realized, and the fluency of a large-scale scene, the network adaptability and the system resource utilization efficiency are improved.

A computer system for adaptive neural network architecture implementing sophisticated supervision, pruning, and signal transmission capabilities. The system operates a layered neural network monitored by a hierarchical supervisory system that collects activation data, identifies operation patterns, implements architectural changes, detects network sparsity, coordinates pruning decisions, and manages resource redistribution. A meta-supervisory system tracks supervisory behavior patterns, stores successful modification and pruning patterns, and extracts generalizable principles from these patterns. The system manages signal transmission pathways that enable direct communication between non-adjacent network regions through signal modification and temporal coordination. This multi-level approach enables dynamic network adaptation and efficient resource utilization through pruning while maintaining operational stability. The system's innovative architecture allows neural networks to evolve their processing capabilities during operation while preserving reliable performance through sophisticated supervision and controlled modification.

The invention provides a resource loading method and system based on user behavior prediction, and relates to the technical field of data processing, and the method comprises the steps: collecting user behavior data; preprocessing the user behavior data; extracting data features of the preprocessed user behavior data; according to the data features, predicting resource demand weight distribution of the user through a double-layer LSTM based on fusion of an attention mechanism and interest drift perception; calculating the priority of each resource according to the prediction result of the resource demand weight distribution of the user in combination with the importance coefficient, the resource value density and the network adaptation coefficient of each resource; constructing a resource loading priority queue according to the priority of each resource from high to low; and dynamically adjusting a loading strategy of each resource in the resource loading priority queue in combination with a network state, and loading the resources as required. According to the method, the resources can be loaded as required, the resources possibly required by the user are preferentially loaded, and the resource utilization efficiency is improved.

The invention discloses a spacecraft Hall propulsion device test working medium flow stability control system, which comprises a sensing module for detecting working condition state parameters of working medium supply equipment, and an adaptation module for exploring current working condition control parameters by combining detection data of the sensing module and similar working condition control parameter empirical data fusion, the adjusting module is used for receiving the control parameters and dynamically adjusting the adjusting weight of the adjusting device according to different phase change periods, an experience library unit and a self-adaption unit are arranged in the adaption module, the experience library unit provides experience data of similar working conditions and control parameters, and the self-adaption unit provides self-adaption data of the control parameters. And the autonomous adaptation unit fuses and explores control parameters by constructing a neural network adaptation model, so that working condition automatic identification and control parameter autonomous adaptation under the environment that the working medium type or the working medium state rapidly changes are realized; the problems of low control precision and slow response speed caused by manual presetting of control parameters of different working media in a traditional control technology are solved, and stable control of the working medium flow is realized.

The invention provides a multi-scene user controllable personalized recommendation method and system based on super network adaptation. The method comprises the following steps: acquiring a natural language query input by a user; mapping the natural language query into a control condition text based on a large language model; encoding the control condition text into a condition embedding vector by using a pre-trained text encoder; inputting the condition embedding vector into a super network, and generating an adapter parameter matrix for at least one dense layer in the basic recommendation model by the super network; adding the adapter parameter matrix and an original weight matrix of a corresponding dense layer in the basic recommendation model to obtain an adapted recommendation model; and using the adapted recommendation model to predict preference scores of the user for the articles, and generating a recommendation list based on the preference scores. According to the technical scheme, the super network is introduced to dynamically generate the lightweight adapter, so that the limitation of a traditional recommendation system in the aspects of user controllability, scene adaptability and semantic comprehension is effectively solved.

The invention relates to a personalized network guarantee service pushing method and device, equipment and a storage medium. The method comprises the steps that a specific scene where a user is located is recognized through a terminal side intention perception SDK, credibility verification is carried out, and the specific scene comprises at least one of access to a preset place network, poor network quality or starting of a high-network-demand application; based on a specific scene in which the user is located, obtaining signing state data of a current service of the user; comprehensively analyzing the user service demand and the network adaptation capability based on the signing state data of the current service of the user; formulating or updating a personalized QoS (Quality of Service) network guarantee strategy matched with the specific scene, or pushing a personalized network guarantee service ordering request to a user, and performing state feedback; and executing a network service guarantee operation according to the network guarantee strategy. By adopting the method, precise scene perception and network side multi-network element cooperation can be realized, and the reach rate and the order conversion rate of the network guarantee service are improved.

A system and method for an adaptive network architecture utilizing dynamically-encoded agents. The system processes data through a base graph layer of interconnected computational nodes, a telemetry layer for real-time monitoring, and one or more agent layers composed of dynamically-encoded agents. These agents optimize encoding strategies, generate new agents, and prune inefficient agents based on network performance objectives. A telemetry layer continuously tracks network operations using adaptive kernel functions and topology-aware distance metrics. The system may dynamically adjust network structure and resource allocation, maintaining efficient operations through encoding optimization. By leveraging short-term and long-term memory systems, the system adapts over time, improving learning retention and responsiveness. Error detection and recovery mechanisms ensure network stability during agent generation and pruning. This approach enables real-time network adaptation, optimizing performance and efficiency across multiple layers while maintaining system resilience and stability.

The invention provides a DTU, a data transmission method, a data transmission device and a medium. Wherein the DTU is in communication connection with the serial port equipment and the cloud platform; the DTU comprises a protocol analysis layer and a network adaptation layer, and the protocol analysis layer is in communication connection with the low-code development platform; the protocol analysis layer receives serial port data sent by serial port equipment; analyzing the serial port data according to the target protocol analysis rule to generate structured data; sending the structured data to a network adaptation layer; the target protocol analysis rule is generated and issued by the low-code development platform according to the target protocol configuration parameters; and the network adaptation layer encapsulates the structured data based on the target network protocol, generates network protocol data and sends the network protocol data to the cloud platform. According to the embodiment of the invention, efficient conversion from the serial port data to the network protocol data can be realized, and the data transmission efficiency and accuracy of the DTU are improved.

The invention relates to a virtual reality and network interaction technology, and discloses a virtual space multi-person interaction synchronous control method oriented to an end-cloud collaborative architecture. Through combination of end-side prediction and cloud arbitration, low-delay transmission and global consistency of a multi-user interaction state are realized. The method specifically comprises the steps that an end side carries out prediction and feature extraction on action and voice data, and redundant transmission is reduced; the key state parameters are uploaded to a cloud end and are judged by a global consistency model and a conflict arbitration mechanism in a unified manner, and a synchronization instruction is generated; and the end side performs rendering and feedback according to a result. According to the method, end-cloud hierarchical prediction and arbitration, a priority-driven protocol and bandwidth adaptive control are combined, delay and conflicts are effectively reduced, and cooperation efficiency, immersion and network adaptability are improved. The method can be widely applied to the fields of universe, online education, remote collaboration, virtual simulation and the like.

The invention relates to the technical field of video return, in particular to an unmanned vehicle video return control method and system based on an SIP (Session Initiation Protocol) communication protocol. The control method comprises the steps that a home terminal serves as an SIP client and sends an SIP connection request to an unmanned vehicle terminal through TLS encryption, it is determined that the home terminal is a video only decoding terminal and the unmanned vehicle terminal is a video only coding terminal, meanwhile, the audio two-way communication capacity is negotiated, and encrypted signaling connection is established. As a mature multimedia communication protocol, the SIP has a perfect and safe session establishment, modification and termination mechanism. The method has good network adaptability, supports NAT traversal and firewall traversal, can stably work in different network environments, and is suitable for unmanned vehicle moving scenes. According to the invention, by constructing a systematized control scheme based on the SIP protocol, the problems of dynamic bandwidth adaptation and safe and reliable transmission control of unmanned vehicle video return in a complex network environment are solved.

The invention discloses a robot remote control system based on augmented reality and visual feedback, and the system comprises a visual collection module of a sensing layer which obtains an environment image in real time through a built-in camera; a rocker control module and a video stream transmission module of the augmented reality control layer realize a rocker control function and a video stream transmission function; a WebSocket client module and a WebSocket server module of the communication relay layer are used for transferring and transmitting instructions and data; and the robot execution control layer comprises a chassis control module and a motion execution module, and the chassis control module is operated and managed by the master control computing platform Intel NUC and is used for completing execution of a motion instruction. The invention further discloses a robot remote control method based on augmented reality and visual feedback. The invention belongs to the technical field of augmented reality technology and humanoid robot remote control, and solves the problems that in the prior art, an operation interface of a humanoid robot is not visual, visual feedback delay is serious, and network adaptability is insufficient.

The invention discloses a hyper-converged Internet of Things gateway, and relates to the technical field of Internet of Things. Comprising a network state preloading unit, a cellular automaton control unit and a protocol stack mapping unit, the network state preloading unit is used for carrying out multi-dimensional state acquisition on a heterogeneous access network connected with the hyper-converged Internet of Things gateway and generating a network state preloading set; the cellular automaton control unit is used for creating a cellular automaton node for each piece of network state baseline data based on the network state preloading set, and converging to obtain an evolution result; and the protocol stack mapping unit is used for mapping the to-be-transmitted data packet into a target protocol stack format according to the evolution result, adding a security label, and outputting the to-be-transmitted data packet to a corresponding external network interface. The method has the beneficial effects of improving the network adaptability, the abnormity identification precision, the protocol selection flexibility and the data transmission security, and is suitable for complex, dynamic and high-concurrency application scenes of the Internet of Things.

The invention provides a multi-agent heterogeneous client-server collaborative voice interaction system and method, and relates to the technical field of voice interaction based on artificial intelligence. The voice interaction system aims to solve the problems that an existing voice interaction system is weak in safety, poor in compatibility, insufficient in weak network adaptability and the like. The system comprises a client and a server, and access security and dialogue continuity are guaranteed through multi-factor joint authentication and abnormal dialogue compensation; the intelligent agent capability is split into independent modules, and unified adaptation and dynamic management of the multi-source heterogeneous intelligent agents are achieved through unique identification; and through a client local cache and module decoupling fault-tolerant mechanism, the system stability in weak network and fault scenes is improved. According to the invention, agent capability abstraction, resource decoupling and end cloud collaboration are realized, a voice interaction architecture with high expansibility, high stability and strong adaptability is constructed, and the method is suitable for various application scenes such as SDK integration and multi-role accompanying chat.

The invention discloses an LWIP TTE network adaptation system based on a static ARP table. The LWIP TTE network adaptation system comprises a transmission module, a protocol conversion module, an LWIP protocol stack and a network calling module. The transmission module enables the standard TTE frame to be normally transmitted on the TTE switch; the protocol conversion module is used for protocol adaptation and data conversion; the LWIP protocol stack is used for packaging data needing to be sent and analyzing a received standard IP data packet; and the network calling module is used for transmitting the data and the target IP address information to the LWIP protocol stack and receiving a data packet fed back by the LWIP protocol stack. Protocol adaptation and data conversion are carried out through the protocol conversion module, the communication barrier between an IP protocol and a TTE protocol is broken, and conversion from an IP address to a communication identifier supported by TTE is realized; the network adaptation system uses the simple query logic of the LWIP protocol stack and the static address mapping table, so that the embedded program developed by depending on the TCP / IP protocol stack can be accessed to the TTE network at low cost, and the complexity of program migration work is simplified.

The invention provides a network adaptation method and device of a built-in proxy browser, equipment and a medium. The method comprises the steps that the built-in proxy browser comprises a relay acceleration link and a direct connection link; a relay acceleration link is used by default; setting a timer, regularly accessing a set website through a local client, and judging network connectivity through an HTTPS request; if the HTTPS requests to detect that the network is connected, judging whether the link used by the current built-in proxy browser is a direct connection link or not, and if so, not changing; if not, using a direct connection link; if the HTTPS request detects that the network is not connected, judging whether the current built-in proxy server uses a relay acceleration link or not, and if so, not changing; if not, the built-in proxy browser uses a relay acceleration link for connection; therefore, the browser can switch the line in time, the network access speed is ensured, and the operation cost of an enterprise can be reduced.

The invention discloses a federal compression learning method and system based on knowledge distillation, and the method comprises the steps: enabling each terminal device to adaptively adjust the compression ratio of the terminal device according to a real-time network, and carrying out the compression sampling through the adjusted compression ratio; then, taking a compressed sampling value as a knowledge distillation medium between edge equipment and a cloud server of different levels, and carrying out cooperative training on heterogeneous models deployed by nodes of different levels in combination with a federated learning method and knowledge distillation; the knowledge distillation is introduced in the federated learning process, so that models with different capacities and architectures can be deployed at different hierarchy nodes, and the compressed sampling value with the internal privacy protection characteristic is used for replacing original data or proxy data as a distillation medium, so that the privacy risk caused by the knowledge distillation is eliminated from the data source. And the communication efficiency, privacy protection and computing power utilization optimization of the end-side cloud are realized.

The utility model relates to the technical field of Internet of Things equipment, in particular to an IoT (Internet of Things) module, which comprises a password authentication unit, a Wi-Fi (Wireless Fidelity) unit, an NB-IoT (Narrow Band Internet of Things) unit, a communication unit and a power supply unit for supplying power to each unit, the Wi-Fi unit, the NB-IoT unit and the communication unit are electrically connected to the password authentication unit respectively. Through integration of multiple functional units, the problems of security, network connection, communication efficiency, energy consumption management and the like of a traditional IoT module are solved, and remarkable beneficial effects including improvement of equipment security, enhancement of network adaptability, optimization of data transmission performance and realization of energy-saving management are also brought. The advantages jointly promote the performance improvement and the application range expansion of the IoT equipment.

The invention discloses a Cuckoo search algorithm-based network node interaction method and system, and the method comprises the steps: setting wireless sensor network parameters, constructing a node energy consumption model containing a free space and a multipath attenuation mode, and adaptively selecting an energy consumption mode according to the relation between a transmission distance and a threshold value; selecting a single-hop or multi-hop transmission mode according to the distance between the cluster head nodes and the base station, determining the optimal number of cluster heads, and optimally selecting the cluster head nodes by using a cuckoo search algorithm; and optimizing a data transmission path, and selecting a relay node through a fitness function to realize interaction with a core network control function node. The system comprises a network initialization and parameter configuration module, an energy consumption modeling module, a cluster head selection and optimization module and a path optimization and core network interaction module. According to the invention, network energy consumption can be effectively reduced, network life is prolonged, data transmission efficiency and network adaptability are improved, and intelligent network management is realized.

The utility model belongs to the technical field of AI edge computing, and particularly relates to a high-performance AI box, which comprises a casing, an HDMI (High Definition Multimedia Interface) data input interface, an HDMI data output interface and a power supply interface are arranged on the surface of the casing, and a circuit board is arranged in the casing. The circuit board is provided with a central processor, a data storage module, an HDMI data decoding module, a data transmission module, an FPGA module and a power supply module, and the box is based on an RK3588 processor, is strong in operational capability, supports the efficient operation of a complex AI algorithm, is better in speed and precision of processing algorithms such as face detection, and accords with a high-real-time scene. The communication interface of the high-performance AI box integrates network peripherals such as a gigabit Ethernet, a Wi-Fi module and a 4G module and CAN, RS485 and UART local interfaces, the network adaptability is high, industrial equipment connection is facilitated, and the application range is widened. In the aspect of interaction, the HDMI OUT, the HDMI IN and the audio interface provide multi-element man-machine interaction, video display and audio playing can be realized by accessing the display and audio equipment, and the system is suitable for scenes such as security monitoring and the like.

Methods and apparatuses for network operation adaptation in a spatial domain in a wireless communication system. A method for a user equipment (UE) to report channel state information (CSI) includes receiving: first information related to reception of CSI reference signals (CSI-RSs) on a cell, second information related to determining a first number of CSI reports respectively associated with a first number of operation states on the cell, third information related to triggering a second number CSI reports respectively associated with a second number of operation states from the first number of operation states, and the CSI-RSs based on the first information. An operation state is associated with a configuration for active antenna ports, antenna panels, or transmission reception points. The method further includes determining, based on the second information and the CSI-RSs, the second number of CSI reports and transmitting a channel with the second number of CSI reports.