1748 results about "Application layer" patented technology

The invention discloses a quality management and control system for fabricated decoration construction, and the system comprises a sensing layer which constructs a multi-modal data collection network, carries out the three-dimensional real-time data synchronous collection through combining logistics API docking and an OCR recognition system, and constructs a construction process digital twin bottom plate; in the edge calculation layer, an edge node carries out lightweight processing on the original data; the cognitive layer is used for calling a Prolog rule through a process knowledge graph engine to reasone the feature snapshots, carrying out defect instant diagnosis and dynamic constraint propagation, outputting a root cause path with probability weight through three-stage verification, and quantifying intervention influence; the decision-making layer is used for constructing a dynamic prediction model based on a bidirectional LSTM and an attention mechanism, automatically activating a compensation mode when key interference is detected in combination with an anti-fact memory bank and a case-based reasoning compensator, and generating an alternative scheme of optimal cost / optimal construction period / comprehensive balance through a multi-target optimizer; and in the application layer, a Unity engine is utilized to develop the digital twinborn billboard.

The invention provides a multi-screen cabin entertainment system, and relates to the technical field of embedded systems and intelligent cabins, and the multi-screen cabin entertainment system is characterized in that an application layer is deployed with a plurality of cabin entertainment applications, and when the application layer is started, content rendering requests are sent out respectively; the hardware layer is provided with a development board, is provided with a CPU core cluster and a coprocessor, and is connected with different cabin display screens through different video output interfaces. The system layer respectively distributes an independent thread and an independent frame buffer area for each content rendering request on the CPU core cluster, and establishes a mapping relation between each frame buffer area and each video output interface; and sending operation result data of each independent thread to a coprocessor for rendering, correspondingly storing a rendering result in a frame buffer area, and then sending the rendering result to a cabin display screen for display through a video output interface. The method has the advantages that on the premise that the number of hardware coprocessors is not increased, complete separation of multi-screen rendering threads and frame buffer is achieved, and multiple cockpit entertainment applications can run at the same time and do not interfere with one another.

The invention belongs to the technical field of railway inspection, and particularly relates to a space-air-ground integrated railway power transformation and distribution intelligent inspection method and system which comprises a sensing layer, a platform layer, a data and intelligent center, an application layer and a user and presentation layer. The sensing layer is composed of an aerial inspection layer, a ground inspection layer and a fixed monitoring layer; the platform layer is based on a cloud computing center and edge computing node collaborative architecture, combines data and an intelligent center, integrates multi-source heterogeneous data through a big data platform, carries an AI algorithm engine to realize automatic identification of equipment defects, analyzes images, synchronously predicts the images, and realizes automatic identification of the equipment defects. And the application layer is combined to complete the functions of automatic generation of an inspection report, automatic distribution of a maintenance work order, equipment health state evaluation and the like. According to the method, functions of railway power place inspection, power supply line inspection, power supply and distribution facility operation and maintenance emergency and the like can be realized, deep fusion analysis of multi-dimensional data is realized, and meanwhile, the problems of insufficient training samples, sparse defect types and the like of an existing AI model are solved.

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 belongs to the technical field of intelligent engineering management, and discloses an automatic monitoring and control method of an engineering management system based on the Internet of Things. According to the method, a four-layer Internet of Things architecture comprising a sensing layer, a network layer, a platform layer and an application layer is constructed, and the four-layer Internet of Things architecture is uploaded to a cloud platform through a 5G / narrowband Internet of Things dual-mode transmission channel. A digital twinborn technology is innovatively adopted to construct a three-dimensional visual engineering model, intelligent identification and prediction of abnormal working conditions are realized through a machine learning algorithm, and a multi-stage linkage control mechanism is established. And when construction deviation or equipment failure is detected, the system automatically generates an optimization control strategy and issues the optimization control strategy to the execution terminal, so that accurate regulation and control of the construction machinery and intelligent pushing of early warning information are realized. According to the method, a manual inspection mode of traditional engineering management is broken through, full-process automatic supervision is realized through data fusion analysis and closed-loop control, the construction quality supervision precision is effectively improved by more than 30%, the safety accident rate is reduced by 50%, and the engineering management efficiency is remarkably improved.

The invention belongs to the technical field of base station equipment management, and discloses a base station equipment management method and system based on big data. The method comprises the following steps: firstly, collecting security situation data of a physical layer, a network layer and an application layer, extracting time sequence behavior characteristics, performing cross-layer correlation analysis, and constructing an equipment security credibility dynamic evaluation model; then, identifying vulnerability indexes of control nodes according to the trust attenuation curve, and constructing a cascade risk conduction model in combination with a topological connection relationship; dynamically dividing a security isolation domain based on the model and generating protection parameters and control rules; further, a differentiated security policy is configured, and a cross-domain collaborative response channel is established; and finally, dynamically adjusting the isolation domain boundary and the security policy by monitoring the security event frequency and the interception success rate in real time. According to the invention, the conversion from passive defense to active prediction is realized, and the safety protection capability and operation stability of the base station equipment are improved.

There is provided a method in a node of a wireless communication network. The method comprises receiving from an application a protocol data unit (PDU) set corresponding to an encoded application data unit (ADU). The method further comprises determining an Application-Layer Forward Error Correction (AL-FEC) coding configuration associated with the encoded ADU and transmitting the PDU set. The method further comprises determining whether a cease criterion is satisfied, wherein the cease criterion is based on the AL-FEC coding configuration, and ceasing transmission of the PDU set based on the cease criterion being satisfied.

The invention discloses an industrial software cloud base intelligent operation and maintenance and fault self-healing method based on digital twinning, and relates to the technical field of digital twinning. According to the method, the hierarchical digital twinborn model is constructed and dynamically updated, and the operation state of the cloud base is accurately mapped and visually displayed in combination with independent visual modules of a physical layer, a logic layer and an application layer; the method comprises the following steps: calibrating a reference value in real time through a dynamic reference library, quickly identifying abnormity of each layer, generating graded early warning, improving abnormity response timeliness, constructing a dynamically updated fault knowledge graph based on historical fault data, integrating a multi-dimensional correlation analysis and confidence coefficient verification mechanism, positioning a unique fault reason, greatly shortening a fault diagnosis period, and improving fault diagnosis efficiency. And a strategy library is constructed based on a fault knowledge graph and historical self-healing cases, simulation verification is carried out on candidate strategies through a digital twin model, the effectiveness of the self-healing strategies is ensured, and then the self-healing strategies are issued and executed, so that intelligent and automatic fault repair is realized, and stable operation of the cloud base is ensured.

The invention discloses an intelligent early warning system for safety of buildings around foundation pit construction, and relates to the technical field of construction safety monitoring. The platform adopts a four-layer architecture of a sensing layer, a transmission layer, a platform layer and an application layer. The sensing layer collects data in real time through a multi-class sensor array; the transmission layer wirelessly transmits data by using the Internet of Things technology; the platform layer serves as a core, comprises a data management module, a digital twin modeling module and an intelligent analysis early warning engine, and is responsible for data preprocessing, three-dimensional model driving and intelligent risk study and judgment based on machine learning and a dynamic threshold value; and the application layer provides visual display and early warning push service through a Web terminal and a mobile APP. All-weather automatic monitoring, intelligent advanced early warning and accurate risk prevention and control of the surrounding environment of the foundation pit are achieved, a complete intelligent management closed loop is formed, and the construction safety level is effectively improved.

Embodiments include methods for a user equipment (UE), particularly for performing quality of experience (QoE) measurements configured by a wireless network. Such methods include receiving, from a radio access network node (RNN) in the wireless network, a request for QoE measurement reports that are available at the UE and that are associated with one or more services provided by the UE application layer. Such methods also include sending one or more QoE measurement reports to the RNN in accordance with the request. Other embodiments include complementary methods for a RNN, as well as UEs and RNNs configured to perform such methods.

The invention provides a cross-platform video decoding method and device, computing equipment and a computer readable storage medium, and the method is combined with a factory mode to completely package bottom layer differences of all platform types, and an application layer developer does not need to care about the bottom layer platform differences. The optimal implementation can be automatically selected on different engines and platforms through a uniform API (Application Program Interface); during rendering, a single-frame memory management strategy is used, and only one frame which is currently displayed is reserved in a memory; and in the aspect of performance, the advantages of a multi-thread platform and the parallel computing characteristics of the GPU are fully utilized. According to the embodiment of the invention, through deep fusion of a cross-platform soft decoding architecture, single-frame memory optimization, multi-thread parallel, GPU acceleration and other technologies, perfect balance of cross-platform, high performance and low memory is realized, and the development efficiency of the whole project is improved.

The invention relates to the technical field of knowledge management systems, and discloses a knowledge full-life-cycle management system and a construction method, and the system comprises a technical platform and multi-modal perception layer, a calculation and arrangement engine layer, a unified API gateway layer, a multi-modal processing module layer, a knowledge graph layer, a cognitive reasoning layer and an application layer. Real-time collection and batch processing of multi-source heterogeneous data are achieved through a standardized SDK / API; spark / Flink is combined with Kubernetes to complete the ETL (Extract Transform Load) and resource scheduling of the multi-modal data; constructing an entity-relationship-attribute knowledge graph through cross-modal feature fusion; intelligent decision support is realized based on rule reasoning, graph calculation and GNN; the application layer provides intelligent questioning and answering, decision support and personalized recommendation services; the technical problems of knowledge islands, sharing barriers, knowledge statics and the like in the prior art are solved.

The invention relates to a cache data processing method and device, computer equipment, a computer readable storage medium and a computer program product. The method is applied to a distributed storage system adopting a three-layer architecture design, and the three-layer architecture comprises a service application layer, a data processing layer and a persistence layer. Comprising the following steps: acquiring access request monitoring information through a service application layer to obtain an access feature data set, and performing pattern classification identification on the access feature data set to obtain a predicted access pattern; generating a prefetching task list and prefetching data according to the predicted access mode, and storing the prefetching data to a data processing layer for caching processing; and executing each prefetching task according to the sequence of the prefetching task list, and reading the prefetching data from the mechanical hard disk and writing the prefetching data into a cache space in a solid state disk resource pool under the condition that the prefetching data does not exist in the solid state disk resource pool of the persistence layer. By adopting the method, the cache performance can be improved.

The invention relates to a group type enterprise business opportunity conflict detection and cooperative processing system based on a dynamic rule engine and semantic analysis. The rear end of the system adopts a Python Flask framework to construct micro-service, and the front end adopts a response type design; the rear end further comprises a business opportunity admission management module and a cooperative processing module which are arranged on an application layer; the business opportunity admission management module comprises a standardized business opportunity establishment application form, a business opportunity conflict identification model and a business opportunity closing application form; the business opportunity conflict identification model adopts a dynamic rule engine and a weighted matching strategy to carry out weighted processing on structured fields, unstructured texts and industry-specific word libraries; performing accurate matching on the hard indexes, and calculating the similarity of business opportunity names by adopting cosine similarity on the flexible indexes; the semantic feature extraction layer for storing the industry-specific lexicon uses TF-IDF weighted word vectors to enhance the industry-specific lexicon; the cooperative processing mechanism integrates a WebSocket technology, pushes weighted messages in real time, carries out business opportunity tracking, and pushes the weighted messages to a business opportunity closing application form to carry out business opportunity closing.

This disclosure describes a large language model (LLM)-based agent operating system comprising an application layer, a kernel layer, and a hardware layer. The kernel layer comprises an AIOS kernel comprising: LLM core(s), an agent scheduler, a context manager, a memory manager, a storage manager, and a system call interface configured to manage interactions among the agent scheduler, the context manager, the memory manager, and the storage manager.

The invention relates to the crossing field of supply chain management and block chain technologies, discloses a block chain-driven circulating packaging ownership tracing and reuse optimization system, and solves the problems that existing circulating packaging ownership tracing is not credible, the reuse rate is low, data sharing is barrier and settlement is low in efficiency. The system comprises a sensing layer, a network layer, a block chain layer and an application layer, wherein the sensing layer collects and packages full life cycle data; the network layer carries out preprocessing and 5G data transmission; the block chain layer adopts an alliance chain to deploy ownership change, full life cycle records and privacy protection contracts; the application layer is internally provided with a core unit for XGBoost demand prediction and genetic algorithm scheduling, and functions of ownership tracing, multiplexing scheduling and the like are realized. Implementation shows that the ownership tracing credibility is 100%, the reuse rate is improved to 90% or above, the settlement time is shortened from 3 days to 1.5 hours, and the method is suitable for circulating packaging scenes such as cold chains.

The invention provides an SOA architecture vehicle-cloud integrated communication middleware system and a deployment method, and the system comprises a unified communication interface module which is used for providing a Topic-based publishing / subscribing model communication interface for an application layer, and providing a Method-based client / server model remote service calling interface; the communication abstraction and adaptation module is used for performing unified abstraction and protocol conversion on various heterogeneous physical buses and communication protocols in the vehicle and among vehicle clouds; the system configuration and management module is used for carrying out centralized configuration and management on definition of communication interfaces, mapping relations of communication channels and system operation parameters; the system receives a communication request of an application layer through the unified communication interface module, obtains configuration information through the system configuration and management module, and adapts the communication request to a specific physical bus or a network protocol for transmission through the communication abstraction and adaptation module. According to the system and the deployment method provided by the invention, the service logic of the application layer and the complex communication of the bottom layer are thoroughly decoupled.

A method performed by a wireless transmit / receive unit (WTRU) may comprise: receiving, from a base station, configuration information; receiving, from an application layer, one or more uplink protocol data units (PDUs); determining a buffering delay for transmitting the one or more uplink PDUs in resources associated with configured grant (CG) physical uplink shared channel (PUSCH) occasions; and on a condition that the buffering delay is greater than a delay threshold and that there are no available resources associated with semi-persistent scheduling (SPS) physical downlink shared channel (PDSCH)occasions within a time window, transmitting an indication of a time offset for the time window. The method may further comprise transmitting, to the base station, in a CG PUSCH occasion, the one or more uplink PDUs.

The invention discloses a dual-channel adaptive network stability testing method and system, and belongs to the technical field of computer network testing. The system adopts a dual-channel asynchronous communication architecture in which a control channel and a data channel are physically separated, instructions and state information are transmitted through an independent TCP control channel, and high-speed test data streams are transmitted through a UDP or TCP data channel. The method comprises the following steps: dynamically and adaptively adjusting a timeout parameter based on real-time network delay detection; nanosecond constant interval packet sending control is realized by using a high-precision monotonic clock source and busy waiting compensation mechanism; a packet loss detection, positioning and ACK confirmation mechanism based on the serial number is realized in an application layer; and real-time statistical display and idle detection automatic termination are realized through multi-thread parallel processing. According to the invention, the precision, the stability and the adaptive capability of network testing are remarkably improved, and the method is suitable for long-time stability testing in various scenes such as a high-speed Ethernet, a satellite link, an industrial Internet of Things gateway and the like.

The invention relates to the technical field of cross-platform application development, in particular to a cross-platform sky map component packaging method and device based on a unit-app X framework. According to the method, a four-layer packaging framework comprising an application layer, a communication layer, a WebView layer and a platform adaptation layer is constructed, and unified packaging and calling of sky map components of Android, iOS and a multi-platform gap are achieved. The application layer completes component initialization, instruction verification and standardization processing; the communication layer realizes data interaction and coordinate conversion; the WebView layer executes map API loading, instance management, covering rendering and event monitoring; the platform adaptation layer completes cross-platform authority management, WebView container adaptation and GPS position acquisition; and finally, the application layer integrates the data and encapsulates a TelchinaTdtUnix component to return a result. The problems that an existing cross-platform sky map component is poor in adaptability, disordered in authority management and low in interaction efficiency are solved, and the cross-platform compatibility, stability and development efficiency of the component are improved.

The invention discloses a data zero-copy processing method and system based on an eBPF zero-trust gateway, and belongs to the technical field of computer network security. According to the method, an XDP program is loaded on a network card driving layer, and an AFXDP technology is combined to construct a kernel mode and user mode shared memory pool UMEM; when an original message arrives, an eBPF unit mounted by an XDP program intercepts the message in real time, a tunnel packaging space is reserved in situ in an original memory, and if the head space is insufficient, a new memory page is logically mapped from a UMEM standby buffer pool to achieve extension. Identity fingerprints are generated by extracting message feature vectors, load in-situ encryption is completed in cooperation with a kernel kTLS module, and data are prevented from being returned to a user mode for processing. According to the method, multiple copying and context switching of a kernel-user mode of a traditional SSL VPN are eliminated, the throughput is improved by 2-3 times, the delay is reduced to the microsecond level, the CPU utilization rate is reduced by 40% or above, application layer DDoS attacks are effectively defended, and the method is suitable for 5G edge computing and cloud native zero-trust gateway scenes.

The invention provides a port logistics intelligent simulation and decision optimization platform based on a digital twin technology, and the platform comprises a basic layer which provides calculation, storage, network and basic software support; the resource layer integrates data resources, model resources and algorithm resources and is used for managing port multi-source data, business process models and intelligent algorithms; the digital twinborn layer is used for constructing and maintaining a high-fidelity digital twinborn body synchronous with a physical port and realizing virtual-real mapping, dynamic data fusion and model self-evolution; the simulation layer is used for deducing based on the digital twin and comprises a simulation engine and an event driving and data interaction module; and the application layer is used for providing a user interface, analyzing decision and optimizing functions and supporting scheme simulation, evaluation and closed-loop optimization. According to the method, the high-fidelity digital twinborn body of the port can be constructed, real-time mapping, accurate simulation, prospective prediction and intelligent decision making of the whole process of port logistics are achieved, and a technical closed loop of data acquisition, digital twinborn, intelligent decision making and virtual-real linkage is formed.

The invention discloses a multi-protocol dynamic adaptation and session management method based on TCP / IP (Transmission Control Protocol / Internet Protocol), and belongs to the technical field of computer network communication. Comprising the following steps: S1, receiving TCP / IP connection from a client, and identifying a specific application layer protocol type through a protocol feature code; s2, dynamically loading an adapter of a corresponding protocol based on the protocol type identified in the S1, decoding original data into a unified intermediate format, and realizing protocol-independent data processing; s3, on the basis of decoding in the S2, different protocols are connected and bound to the same session object based on the device identifier, and cross-protocol sharing of the authentication state and the context is achieved; and S4, monitoring a network quality index based on the session binding in the S3, and dynamically allocating a high-priority service to the optimal protocol channel. According to the method, the problems of poor multi-protocol compatibility, isolated session management, unreasonable network resource allocation and the like are solved, and the flexibility, the reliability and the resource utilization rate of the system are remarkably improved.

The invention discloses a multi-machine multi-card distributed training optimization system and method oriented to a credential heterogeneous environment, and relates to the technical field of distributed training. In order to solve the defects existing in distributed training in a credential and credential heterogeneous environment, the system comprises an application layer for receiving a training task; the core system layer comprises a self-adaptive task scheduling module, a hybrid communication topological optimization module and a dynamic check point and elastic recovery control module, and the scheduling module generates a performance portrait and an optimal scheme based on a training task and adjusts the scheme according to a node fault; the optimization module executes the scheme, firstly detects node topology, constructs a hierarchical path, loads and initializes an optimal communication rear end for target equipment, and synchronizes the path to the target equipment; the control module periodically stores a complete training context and realizes reliable recovery of a training process; the credential hardware abstraction layer is used for providing a uniform interface for realizing underlying resource access and data acquisition; and the hardware resource layer comprises heterogeneous computing nodes and an RoCE network switch.

The invention relates to the technical field of nuclear power data asset automatic management, in particular to a nuclear power digital twinning data warehouse structure system, which comprises a data processing layer, and is characterized in that the data processing layer reads original data of a nuclear power industrial internet platform, performs data standardization processing on the original data to obtain standard data, and sends the standard data to the nuclear power industrial internet platform; constructing a nuclear power industry theme library according to the standard data; the data integration layer performs data coding mapping, data classification and data fusion on the data of the nuclear power industry theme library to form a thematic library; the semantic enhancement layer marks the data of the nuclear power industry theme library and the data in the thematic library formed by the data integration layer, and constructs a structured feature tag library for the data associated with feature tags; the analysis application layer reads data of the feature tag library, and constructs a digital twinborn algorithm library and a digital twinborn sample library through algorithm analysis and sample training. The system supports equipment operation and maintenance from regular maintenance to predictive maintenance based on bottom support and four-layer progressive architecture of a nuclear power industrial internet platform.

The invention discloses a distributed file management system and method, and belongs to the technical field of computer software, the system adopts a tree hierarchical structure to organize files, and the system comprises an application layer used for receiving file operation requests from a plurality of independent clients, and each request carries a unique application identifier; the file system layer comprises a configuration module, an operation module, a metadata management module, a day module, a timed task module and a gateway module, and the request is routed to a corresponding logic storage partition in the data layer according to an application identifier; the data layer comprises a database cluster and an object storage cluster, and performs persistent storage and management of logic isolation on metadata and file data according to application identifiers; and the infrastructure layer provides an extensible server and network resources. Based on a distributed architecture, load balancing and efficient access are realized through data storage partitioning, a metadata management and index technology and a client load balancing technology, and the expandability, fault tolerance and performance of the system are improved.

The invention discloses a server health examination method and device, equipment and a medium. The method comprises the following steps: acquiring hardware layer data, system layer data, application layer data and physical environment layer data of a target server through a data acquisition component; determining a current value and a predicted change range of each health index regularly, and determining a current health level and a predicted health level range of the target server according to the current value and the predicted change range of each health index; when the current health level belongs to an abnormal level, executing a self-healing operation corresponding to the current health level; and when the predicted health level range contains an abnormal level, executing an early warning operation. According to the embodiment of the invention, real-time quantitative evaluation, abnormity prediction, early warning and automatic repair of the health state of the server can be realized, health evaluation and health pre-judgment can be comprehensively and accurately carried out on the server, and the operation stability of the server is improved.

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 provides an intelligent dispatching and remote control method for a tower crane, which is applied to the field of fabricated house building construction and engineering equipment and aims to solve the problems of difficulty in dispatching the tower crane, low construction efficiency, severe operation environment and high safety risk in a clustered fabricated building. The method comprises the following steps: S1, constructing a distributed system architecture comprising a physical layer, a sensing control layer, a data processing decision layer, an application layer and a communication layer, and deploying equipment; s2, collecting environment, tower crane state and BIM model related multi-source data, and transmitting the data to a data fusion processing center for fusion; s3, planning an optimal hoisting path and a task sequence through the intelligent scheduling subsystem based on an ant colony algorithm; s4, a control mode is selected, a hoisting instruction is issued to execute a task, and forced braking is triggered in emergency; and S5, mapping a construction scene through a digital twin system, monitoring and alarming through an intelligent monitoring system, feeding back data to realize closed-loop optimization, and recording a digital file. According to the method, tower crane dispatching and construction efficiency is improved, construction safety is guaranteed, and intelligent construction of the fabricated building is promoted.

The invention relates to the technical field of near-field communication security, in particular to a hardware-level identity authentication and end-to-end encryption near-field data interaction method and system for an electric red-connected terminal, and the method comprises the steps: a first electric red-connected terminal and a second electric red-connected terminal initiate pairing based on a Bluetooth secure connection pairing protocol, and negotiate to generate a long-term key through an ECDH algorithm; performing bidirectional identity verification by adopting an application layer authentication protocol; activating AES-CCM encryption by using a session key derived from a long-term key; bluetooth signal strength and a connection state are monitored in real time, and a negotiation key is automatically paired again when abnormity occurs; generating an interaction log, digitally signing the log by using a locally stored private key, and securely storing the signed log in a local secure storage area of the terminal; the digital signature of the latest log is verified, and if interaction abnormity is found, the local security module of the terminal recovers the local data to the pre-interaction state according to the last credible log record. The problem that traditional Bluetooth communication is prone to eavesdropping and tampering can be solved.