950 results about "Transport layer" patented technology

The invention relates to the technical field of abnormal state prediction, provides a multi-dimensional time sequence equipment abnormal state prediction method and system, and solves the problems of high false alarm rate and risk prediction inaccuracy in the prior art. The method comprises the following steps: collecting a multi-node operation state data set and communication transmission layer time sequence offset information of an equipment distributed system; jitter and delay association processing is carried out on the data, and a communication stability feature set is generated by quantizing space-time correlation of a jitter extreme value and delay fluctuation; obtaining physical layer deformation and temperature drift data of the communication cable, analyzing and generating a physical layer disturbance feature sequence based on optical signal feature offset, and converting the physical layer disturbance feature sequence into channel abnormal strength features; and cross-level feature coupling is carried out on the communication stability feature and the channel abnormal strength feature, and a communication node failure or data transmission abnormal risk is predicted based on a coupling result. According to the invention, millisecond-level linkage prediction of equipment-level physical disturbance and system-level communication risks is realized, the fault false alarm rate is reduced, and the cascade failure risk is blocked.

The invention provides an energy storage cabin terminal remote upgrading method and system based on communication protocol optimization, and relates to the technical field of digital information transmission, and the method comprises the steps: deploying a bandwidth detection mechanism, adjusting a self-adaptive block transmission strategy, and dividing upgrading firmware into M dynamic data packets; constructing a dual-path transmission layer, and configuring a dual-path redundancy check mechanism; a missing block query rule is adopted, and a local flash memory is used for caching Hash check values of the received N dynamic data packets; analyzing a mapping relation between the block index and a multi-path redundancy check mechanism, and establishing a check mapping table; and performing real-time verification and state marking, and configuring a remote upgrading process to execute the upgrading operation of the energy storage cabin terminal equipment after incremental recombination is performed by comparing and verifying abnormal data packets. According to the invention, the technical problem of insufficient reliability of data transmission caused by lack of adaptability to a dynamic network environment due to the fact that most of energy storage cabin remote upgrading technologies in the prior art depend on a single communication path to carry out data transmission is solved.

The invention provides a digital twin hydrological station system which is characterized in that the system comprises a layered architecture system and a multi-dimensional safety protection mechanism, the layered architecture system is composed of a sensing layer, a transmission layer, a data layer, a model layer, an application layer and a display layer from bottom to top, the sensing layer comprises a heterogeneous hydrological monitoring equipment cluster, and the transmission layer comprises a heterogeneous hydrological monitoring equipment cluster. The equipment cluster is provided with a water level sensor array, a Doppler flowmeter, a spectrum water quality analyzer and an environment monitoring terminal, and total element acquisition of hydrological element data, equipment operation state data and environment data is realized; the transmission layer adopts a hybrid communication protocol stack, integrates an ultra-short wave communication module, an NB-IoT narrowband communication module and an optical fiber communication module, and constructs a multi-path redundant transmission channel, and a key data transmission channel is configured with a dynamic link selection algorithm; the data layer comprises a distributed storage architecture, adopts a mixed storage mode of a relational database cluster and an unstructured database, and is internally provided with a data cleaning engine and a spatio-temporal data fusion module.

The invention discloses an equipment real-time monitoring and intelligent scheduling system based on IoT and AI fusion, which comprises a sensing layer, a transmission layer, an edge computing layer, a cloud intelligent center layer and an application interaction layer, and is characterized in that the sensing layer maps heterogeneous data collected by a sensor to a unified space-time coordinate system by adopting a space-time encoder technology; the transmission layer is responsible for transmitting the data collected by the sensing layer to the edge computing layer and the cloud; the edge calculation layer calculates a three-dimensional risk field in real time based on the current operation state data of the equipment; the cloud intelligent center layer constructs digital twinborn bodies, and synchronizes the running state of equipment in real time; the application interaction layer presents equipment operation risk distribution through the risk field thermodynamic diagram; by constructing a multi-layer and multi-module collaborative architecture and fully applying advanced IoT and AI technologies, all-around real-time monitoring, accurate fault prediction and intelligent scheduling decision making of industrial equipment are realized, an intelligent, efficient and reliable operation environment is created for enterprises, and industrial production is promoted to be transformed into intelligentization and digitization.

The invention provides a rail transit vehicle-ground security encryption control method based on a national cryptographic algorithm. The method comprises the following steps: realizing rail transit vehicle-ground security encryption control enabled by the national cryptographic algorithm by adopting a layered and segmented three-level security encryption architecture of a vehicle-mounted terminal layer-a network transmission layer-a core network layer; cooperative control of a national cryptographic algorithm is realized through three stages of terminal authentication, data encryption and tunnel encapsulation; in order to solve the problem of encryption interruption caused by wireless link switching such as 5G signal attenuation, the technical scheme of the patent realizes lossless switching through a three-layer linkage mechanism of signal monitoring, switching decision and key synchronization; self-adaptive intelligent adjustment of a key strategy is realized through a three-layer closed-loop architecture of environmental perception, intelligent evaluation and dynamic regulation and control; and the self-adaptive intelligent adjustment of the key strategy is realized through a three-layer closed-loop architecture of environmental perception, intelligent evaluation and dynamic regulation and control. And the national secret algorithm is combined with the block chain evidence storage technology to realize data tampering prevention, and the speed is high.

The invention discloses a bridge structure health state intelligent sensing and early warning system, relates to the technical field of bridge monitoring, and provides the following scheme that the bridge structure health state intelligent sensing and early warning system comprises a sensing layer, a transmission layer, a data layer, an analysis layer and an application layer which are connected in sequence and work cooperatively: the sensing layer is used for comprehensively collecting health state parameters of a bridge structure; according to the method, the comprehensiveness of monitoring parameters is guaranteed, the effectiveness and transmission efficiency of collected data are improved, redundant data are prevented from occupying resources, deep mining is achieved, a more scientific basis is provided for health status assessment and disease diagnosis, misjudgment caused by single parameter analysis is reduced, the diagnosis precision is improved, and the method is suitable for popularization and application. The intelligent optimization and simulation evaluation of the maintenance scheme are realized, the limitation of the traditional empirical scheme is avoided, the maintenance cost is reduced, the construction period is shortened, the influence on traffic is reduced, the performability of the scheme is improved, the stable and safe transmission of monitoring data in a complex environment is ensured, and the data loss or leakage is avoided.

The invention discloses an area-level distributed photovoltaic power station intelligent management method based on a cloud side end architecture, and the method comprises the steps: building a layered architecture: the layered architecture building comprises a sensing layer, a transmission layer, an edge calculation layer, a platform layer and an application layer, and relates to the technical field of energy management and information technology crossing. By deploying various high-precision sensors in the sensing layer, the equipment operation state and environmental factors are sensed comprehensively, and richer data can be obtained. In the aspect of equipment performance analysis, indexes such as average power generation efficiency and the like are calculated, multi-dimensional comparison is carried out by applying time sequence analysis and data normalization processing, and equipment performance abnormity can be found more timely and accurately.

The invention belongs to the technical field of seismic equipment monitoring, and provides a seismic network communication fault positioning method based on multi-dimensional protocol diagnosis, which comprises physical layer IOT analysis, network layer protocol analysis, transport layer protocol analysis, application layer protocol analysis, a protection mechanism adaptive adjustment algorithm and a cross-layer collaborative analysis state mechanism. According to the method, multi-dimensional protocol fault analysis is realized, and the analysis accuracy is higher than that of a single-dimensional mode through analysis of application, transmission, network and physical four-layer protocols. Analysis is carried out through the sequence from the physical layer to the application layer, positioning can be completed after the problem is positioned on the upper layer, and high analysis efficiency is achieved. According to the method, the analysis process is completed mainly in a network detection mode, only physical layer analysis needs IOT hardware equipment to participate, the analysis can be achieved in a pure soft mode, and the method has the good cost advantage.

The invention discloses a multi-channel high-precision water level dynamic real-time monitoring system for a drilling water pumping test, and the system comprises a sensing layer which is used for deploying a multi-source sensor array, inhibiting interference through distributed layout and electromagnetic shielding, collecting multi-dimensional data in real time, and carrying out the preliminary filtering; according to the transmission layer, an optical fiber and twisted pair redundant network is constructed, an EtherCAT protocol is adopted for low-delay transmission, AES-128 encryption tampering prevention is integrated, and edge nodes compress data and verify integrity; the processing layer is used for carrying out real-time preprocessing on edge calculation and switching a standby sensor in abnormal detection; the cloud end predicts the water level trend through Spark Streaming analysis and an LSTM model, distinguishes interference through a random forest algorithm, and outputs calibration data and an analysis report; the application layer is used for constructing a three-dimensional drilling model based on Unity, dynamically displaying water level changes, synchronizing a multi-parameter curve and supporting historical backtracking; the early warning module notifies abnormity through sound and light and short messages, the decision module generates a report and supports multi-drill-hole comparison, and the test strategy is optimized.

The invention provides a multi-stage desensitization electricity charge sensitive data protection system, belongs to the technical field of information security in the power industry, and relates to a full-life-cycle protection scheme of sensitive data such as an identity label, account information and contact information in an electricity charge service system. The problems that in the prior art, only simple masking or full-table encryption is carried out on a database layer, the desensitization dimension is single, multiple links are prone to leakage, no role fine-grained desensitization strategy exists, and exported files are difficult to trace are solved. The system comprises a data acquisition source and acquisition layer desensitization, a transmission layer encryption, a storage layer transparent encryption, an API gateway, a desensitization strategy center, a front-end dynamic mask, a watermark export, a log desensitization plug-in and an auditing log module, covers the whole process from data acquisition to log auditing, dynamically regulates and controls data display according to roles, and exports a file embedded identity watermark. And desensitizing the log and reserving operation marks. Full-link leakage prevention, fine-grained permission control and leakage traceability can be realized, and the transformation cost is low.

The invention relates to the technical field of edge computing, and discloses an edge computing intelligent decision-making system based on edge cloud collaboration, which comprises a terminal sensing layer, an edge computing layer, a network transmission layer and a cloud center layer. The terminal sensing layer is configured to collect original data; the edge computing layer comprises edge computing equipment, a resource scheduling module and a distributed synchronous triggering module which are respectively used for data preprocessing and model reasoning, dynamic resource allocation based on multi-agent deep reinforcement learning and multi-equipment synchronous acquisition realized through a precision time protocol; the network transmission layer dynamically adjusts a transmission strategy based on a reinforcement learning algorithm during data transmission; and the cloud center layer carries out training optimization on the model through a federal learning mechanism and issues the model to an edge side. According to the method, millisecond-level real-time intelligent decision making of an industrial site and sustainable evolution of the AI model are realized through a side cloud collaborative architecture, and the efficiency, the reliability and the self-adaptive capability of the system are effectively improved.

The invention discloses an electric power multi-protocol data conversion method and system based on object model dynamic mapping, and the method comprises the steps: receiving an original protocol message, recognizing a protocol type, extracting a logic name as a unique identifier of equipment, extracting an object identifier as a measurement point identifier, and extracting an electric energy array as a measurement point value; according to the protocol type and the equipment unique identifier, matching a corresponding object model template from a unified object model library; mapping the equipment unique identifier, the measuring point identifier, the measuring point numerical value and the acquisition timestamp obtained by analysis to corresponding fields in a template; and generating an object model data object conforming to a standard format, packaging the object into a message, executing an encryption authentication mechanism of a network layer and a transmission layer through the power Internet of Things security access gateway, and sending the message to an Internet of Things management platform. According to the invention, standardized, automatic and secure access of different protocol terminals is realized through protocol analysis and the unified object model library.

Methods related to wireless communication systems and uplink (UL) rank adaptation are provided. A user equipment (UE) receives, from a base station (BS), a configuration indicating a resource associated with a plurality of UL reference signal ports. The UE determines, based on at least one of an overheating status, a throughput, or a latency, a quantity of transmission layers for a transmission. The UE transmits, to the BS, an indication of at least one of (1) one or more UL reference signal ports of the plurality of UL reference signal resources associated with the UL reference signal resource based on the quantity of transmission layers, or (2) a number of UL reference signal ports associated with the multi-port UL reference signal resource based on the quantity of transmission layers.

The invention discloses an Android equipment OTA upgrading optimization method based on local area network collaborative distribution, and relates to the technical field of mobile equipment upgrading. According to the method, the problems of bandwidth waste, high time cost and low success rate in a weak network environment in traditional OTA upgrading are solved through multi-device cooperation. The method comprises the following steps: dynamically electing master equipment based on parameters such as version number and electric quantity; the master device downloads the upgrade package, blocks the upgrade package, distributes the upgrade package to the slave device through a P2P protocol, verifies the upgrade package by the slave device, and retransmits the upgrade package if the verification fails; using SQLite to record the progress to realize breakpoint resume; the block transmission sequence is adjusted according to the state of the slave device, and the optimal path is selected by measuring the RTT. The method also comprises a fault-tolerant mechanism, reconstructs failed blocks by using RS coding, and adopts TLS 1.3 encryption and other technologies for a transmission layer. The bandwidth cost is remarkably reduced, the upgrading efficiency and success rate are improved, and the data security is guaranteed.

The invention relates to an anti-quantum password migration method and system, electronic equipment and a storage medium, and belongs to the technical field of anti-quantum data transmission. The method comprises the following steps: carrying out adaptive expansion on a transport layer security protocol; the encryption end and the decryption end perform secure transmission of the application data based on the expanded transport layer security protocol, and the secure transmission process of the application data comprises the following steps: generating a master key, a multi-level sub-key and a path key chain according to a chain type post-quantum key generation mechanism based on the expanded cipher suite; the encryption end generates an encryption key through a part of the sub-keys, encrypts application data in a symmetric encryption mode to generate a ciphertext, and sends the ciphertext and a path node key at the tail end of the path key chain to a decryption end; and the decryption end verifies the path node key, generates a decryption key by using part of the sub-keys after the verification of the path node key is passed, and decrypts the ciphertext. According to the invention, the security and high efficiency of data transmission in the anti-quantum cryptography migration process are realized.

The present disclosure belongs to the technical field of communications. Disclosed in the present disclosure are an uplink data transmission method and a terminal device. The uplink data transmission method comprises: receiving, by a terminal device, SRS resource indication information, the SRS resource indication information is used for indicating a plurality of SRS resources; and, based on the SRS resource indication information, executing, by the terminal device, PUSCH transmission, wherein the PUSCH transmission comprises a first transport layer, and the first transport layer corresponds to at least two SRS resources of said SRS resources. By means of the plurality of SRS resources indicated by the SRS resource indication information, at least two SRS resources can be simultaneously transmitted on one transmission layer, thereby improving transmission efficiency.

The invention discloses a data integrity verification method and system based on label embedding and homomorphic encryption. The method comprises the following steps: constructing a multi-dimensional authorization label for power internet of things data; according to a homomorphic encryption algorithm, performing encryption processing on the power Internet of Things data and the multi-dimensional authorization tag to generate a first ciphertext; calculating a chained hash fingerprint value of the ciphertext and the multi-dimensional authorization tag; packaging the first ciphertext, the multi-dimensional authorization tag and the fingerprint to generate a first data packet, and sending the first data packet to a receiver through a transport layer protocol; the receiver performs legality verification on the authorization label according to the local strategy set; if the verification is passed, recalculating the hash fingerprint and comparing the hash fingerprint with the original hash fingerprint; and if yes, determining that the electric power Internet of Things data is not tampered and belongs to integrity data. According to the method, data integrity verification and access control can be completed in an encryption state, the privacy protection capability is improved, and the decryption exposure risk is reduced.

The invention discloses a high-performance CPU-GPU (Central Processing Unit-Graphics Processing Unit) cooperative processing architecture of an audio frequency integrated signal processor, belonging to the technical field of audio frequency integrated signal processing, the architecture is based on a dynamic priority scheduling model and realizes efficient collaboration of a CPU and a GPU through hierarchical resource management and protocol level optimization, a hardware layer adopts a multi-GPU cluster and a distributed storage node, and the CPU-GPU cooperative processing architecture has the advantages that the multi-GPU cluster and the distributed storage node are integrated; high-concurrency task processing is supported; the transmission layer fuses RapidIO and an Ethernet protocol, and adapts to a short frame control signal and a long packet data stream respectively; and the application layer calculates task resource demands through dynamic priority weights, and ensures low time delay of key tasks in combination with a normalized allocation algorithm. According to the architecture, in an audio signal processing scene, the task scheduling efficiency is improved by 40%, the short frame transmission delay is as low as 0.5, the throughput of a long data stream reaches 100 Gbps, and the requirements for real-time performance and calculation precision in a complex acoustic environment can be met.

The invention discloses a link tracking monitoring method, system and device and a computer readable storage medium, and relates to the technical field of communication, the method tracks a link needing to be tracked through a preset link tracking model, unnecessary byte code injection, interception and excessive tracking data are prevented from being generated, and the link tracking monitoring efficiency is improved. The influence on a network, a CPU (Central Processing Unit), a memory and the like caused by transmission, analysis and storage of the tracking data is avoided, the relation among the invasion degree of the existing code, the link tracking granularity and the performance overhead is balanced, and the influence on the existing service performance and the concurrent processing capability is avoided; a byte code enhancement technology is adopted to enhance original service processing logic, enforcement coding and decoding byte codes are injected, execution calling information of a specified link (function / method) is intercepted, enhanced, recorded and sent, zero invasion and zero development are carried out on existing service codes, and tracking of the full-link calling process of an application layer data protocol HTTP / RPC and a transmission layer protocol UDP is achieved.

The invention provides a VR game data synchronous transmission method based on a 5G network, and the method comprises the steps: obtaining a multi-type data stream generated during the operation of a VR game, extracting scene rendering data and player interaction data from the multi-type data stream, separating a feature value of each data type, and obtaining a data priority sequence; analyzing the real-time requirements of the scene rendering data and the interaction data according to the data priority sequence, and judging a key data packet which needs to be transmitted immediately; the method comprises the following steps: monitoring a current bandwidth fluctuation condition through a network transmission layer, calculating available bandwidth and delay parameters from network state data acquired in real time, and obtaining a resource allocation reference value in a dynamic scene; and for high-priority data packets, a dynamic resource allocation algorithm is adopted to adjust a transmission queue sequence, a resource allocation reference value is corrected through a bandwidth fluctuation parameter, and a transmission time slot allocation scheme of the key data packets is determined.

The invention discloses a network traffic restoring and monitoring method, which relates to the technical field of network monitoring, and comprises the following steps of: capturing an original encrypted traffic data packet, and dynamically embedding steganography marks in non-key fields reserved at message headers of a network layer and a transmission layer to generate an encrypted traffic data packet carrying steganography metadata; injecting the behavior element triple set into the constructed cross-protocol threat knowledge graph to perform adjacency relation matching, and outputting a high-risk threat matching result when the overlap ratio of an unknown protocol behavior path and a graph threat link exceeds a preset safety threshold; and triggering real-time blocking according to a high-risk threat matching result, generating an auditing alarm record, updating a cross-protocol threat knowledge graph, and completing encrypted flow reduction and intelligent monitoring closed loop. According to the method, the steganography marks are dynamically embedded in the message heads of the network layer and the transmission layer, so that the encrypted traffic carries steganography metadata in the transmission process, and the hidden marking of the encrypted traffic is realized.

The invention discloses a network system security monitoring device, which comprises an intelligent sensing layer for scanning network traffic, logs and user behaviors by deploying AI-driven detection nodes; when a potential threat is detected, a structured alarm is generated immediately and pushed to a trusted transmission layer; the trusted transmission layer is used for generating a unique block identifier by adopting a Hash algorithm after the data integrity is verified through a consensus node; automatically triggering a repair process by using an intelligent contract; the self-adaptive decision-making layer is used for synchronizing configuration, flow and vulnerability states of physical equipment; after the vulnerability information is received, simulating various repair schemes in a virtual environment, evaluating the influence of the schemes on services, dynamically adjusting the priority, generating an optimal strategy, and pushing the optimal strategy to the automatic execution layer; the automatic execution layer is used for automatically executing and monitoring the repair progress through an agency-free technology after receiving the repair instruction of the self-adaptive decision-making layer, and triggering a rollback mechanism and generating a fault report if abnormity is detected; and after repairing is completed, a verification script is automatically generated.

The invention relates to the technical field of wireless communication, and discloses an interface protocol switching method and device, equipment, a storage medium and a product, and the method comprises the steps: obtaining state features between a transmitting end and a receiving end through a sensing layer, and collecting data information of a corresponding type according to the state features, the state features including a service feature, a network state and a server state; inputting data information into the intelligent decision layer, determining a switched transport layer protocol stack, and transmitting the transport layer protocol stack to a protocol execution layer; and switching the sending end and the receiving end to a transport layer protocol stack based on the protocol execution layer to perform data transmission. According to the application, the service features, the network state and the server state are dynamically perceived and extracted through the intelligent protocol adaptation system, the protocol stack of the optimal transmission layer is dynamically decided according to the extracted data, protocol requirements under different interaction scenes are adapted, and the flexibility and accuracy of data transmission are guaranteed.

The invention discloses a wire feeding processing intelligent operation and maintenance system based on cloud computing, and relates to the technical field of industrial automation and cloud computing. The problems that in an existing system, due to data transmission delay, abnormal response of equipment is not timely, system stability is affected by unreasonable computing resource scheduling, and the operation and maintenance effect is poor due to poor adaptability of a dynamic maintenance strategy are solved. Comprising an edge layer, a transmission layer, a scheduling layer, a cloud layer and an application layer. The edge layer collects data and makes an emergency response; the transmission layer optimizes data interaction based on network parameters; the scheduling layer balances task allocation through a deep reinforcement learning algorithm; the cloud layer constructs a prediction model and generates a dynamic maintenance strategy according to a result; the application layer visually displays and distributes operation and maintenance tasks; according to the method, the fault response speed, the resource scheduling balance and the maintenance strategy adaptivity are greatly improved, and the production continuity and the product quality are remarkably improved.

The invention discloses an AI-driven transport layer security protocol adaptive optimization system, which relates to the technical field of traffic data access and comprises a data access module, a state sensing module, a risk assessment module, an optimization transmission module and an adaptive encryption module. The data access module is used for capturing an original data flow from a network and a host in real time; the state sensing module is used for receiving the original data stream and setting a feature engineering state index; the risk assessment module is used for quantitatively assessing the safety score of the current state according to the current traffic environment state; the self-adaptive encryption module is used for constructing a password strategy library and generating an encryption configuration strategy according to a current traffic state; and the optimization transmission module is used for constructing a parameter intelligent optimization model and controlling algorithm interaction to generate performance scheduling optimization actions.

A method for authenticating an application program interface (API) invoker enhances secure communication between API invokers and a Common Application Program Interface Framework (CAPIF). The method involves sending authentication information from the API invoker to the CAPIF function, which authenticates the invoker's identity. The process includes obtaining enrollment information to establish a secure transport layer security (TLS) connection with the CAPIF function. Advanced authentication mechanisms leverage an authentication and key management for applications (AKMA) anchor key, enabling secure derivation and verification of application function keys (KAF). Additionally, the CAPIF function uses received authentication data to retrieve API invoker configuration information, onboard signing keys, and certificates. These elements facilitate secure API access and interaction while ensuring compliance with authentication protocols.

The invention discloses a traffic scheduling method and electronic equipment, and relates to the technical field of traffic scheduling, and the method comprises the steps: responding to a condition that a to-be-sent data stream accords with a transport layer protocol and the traffic size of the to-be-sent data stream is greater than a preset threshold value, and generating a plurality of candidate port values used for identifying the to-be-sent data stream at a data sending end; creating a plurality of detection data packets, wherein source port fields of the detection data packets are set as different candidate port values; sending the detection data packets to a data receiving end, and obtaining performance indexes of candidate network paths corresponding to the plurality of detection data packets based on the response of the data receiving end; determining a target source port value from the plurality of candidate port values based on the performance index; according to the embodiment of the invention, the source port field of the data packet corresponding to the to-be-sent data stream is modified into the target source port value, and the modified data packet corresponding to the to-be-sent data stream is sent to the data receiving end, so that the technical problem of load imbalance of a multi-path network in related technologies is solved, and the reliability of traffic scheduling is improved.

The invention discloses a multi-sensory interaction display system based on the Internet, and the system comprises a multi-sensory data collection layer which carries out the synchronous collection of visual, auditory, touch and temperature data, carries out the preprocessing of the collected multi-modal data, and generates a multi-modal data package with a unified timestamp; the multi-modal data coding and transmission layer is used for compressing a multi-modal data packet based on a space-time joint coding algorithm and transmitting the multi-modal data packet through a low-delay transmission protocol; the terminal rendering and interaction layer is used for generating user interaction feedback in real time by adopting a dynamic multi-sensory fusion algorithm; and the edge-cloud cooperative computing layer is used for realizing low-delay feedback control and privacy protection based on a federated learning distributed computing framework. According to the invention, through layered decoupling and cross-layer optimization, strong space-time consistency of multi-modal interaction is realized, and through three innovative technologies of space-time joint coding, dynamic multi-sensory fusion and low-delay tactile control, high-fidelity and low-delay multi-sensory interaction is realized.

The invention discloses a multi-protocol adaptive Internet of Things device communication management method and system, and relates to the technical field of Internet of Things device communication management, and the method comprises the steps: capturing an original message sent by a source device through a communication management node disposed at an edge side when an Internet of Things device initiates a communication request, obtaining a source device identifier, a target address and a transport layer protocol type of the original message; identifying a used application layer protocol according to the structural features and the communication context of the original message, extracting an operation intention contained in the original message, and generating a standardized semantic feature vector; on the basis of the difference degree between the standardized semantic feature vector and semantic feature vectors of other protocols, initial compatibility scores among the protocols are determined, and a communication topological graph is constructed in combination with real-time delay and node resource states of network links; and continuously recording communication execution results of different protocol pairs on each node, and generating a dynamic memory factor according to the change trend of the execution results.

The invention discloses a geographical intelligent data base station, which comprises a data sensing layer, a communication transmission layer, a management and calculation layer and a storage layer, and relates to the technical field of data communication. According to the geographical intelligent data base station, the intelligent data base station is arranged, the function boundary of a traditional base station is broken through, data localization storage, preprocessing and multi-modal analysis are achieved at the hierarchy of the base station, real-time decision feedback and data collaboration between distributed nodes are supported, and through a built-in self-adaptive algorithm, the intelligent data base station is obtained. Different scene requirements can be dynamically matched to complete tasks such as predictive analysis, anomaly detection and intelligent optimization, closed-loop data processing ecology is formed, response efficiency and system robustness are remarkably improved, infrastructure-level support is provided for intelligent internet-of-things application in a complex environment, various environmental factors are associated to establish an evaluation model, and the evaluation efficiency is improved. Data analysis and resource allocation are efficiently realized, and an execution strategy is timely generated for regulation and control.