351 results about "Adaptive communications" patented technology

The invention discloses a self-adaptive communication method and system for ubiquitous electric power Internet of Things intelligent metering equipment, relates to the technical field of Internet of Things communication, and solves the problems of inaccurate quantitative communication, insufficient communication efficiency and poor flexibility in existing intelligent metering equipment communication. According to the invention, the accuracy and reliability of data transmission are improved through a dynamic network self-organizing algorithm and a multi-hop communication mechanism, the communication efficiency is optimized through multi-path transmission and dynamic spectrum management, and the flexibility and adaptability of the network are enhanced through an adaptive modulation coding model and a real-time optimization link selection strategy. And secure transmission of the data is further guaranteed through a multi-layer security mechanism, and the communication performance and flexibility of the intelligent metering equipment are remarkably improved.

The invention relates to the field of low-altitude economy, in particular to a server communication optimization method and system based on low-altitude economy. The method comprises the following steps: monitoring an unmanned aerial vehicle communication relay node in a low-altitude field; carrying out node space position positioning calculation on the unmanned aerial vehicle communication relay nodes one by one, carrying out distributed relay topology fitting, and constructing a low-altitude relay communication network; collecting low-altitude real-time interaction information based on a low-altitude relay communication network; performing communication link bandwidth calculation on the low-altitude real-time interaction information, performing dynamic communication protocol modulation, and constructing a dynamic low-altitude adaptive communication protocol; identifying real-time communication state parameters of the relay nodes based on the low-altitude relay communication network; performing inter-node communication channel identification on the real-time communication state parameters of the relay nodes, performing optimal channel scheduling decision, and constructing an optimal channel scheduling strategy; current user communication data of the ground server is monitored. According to the invention, low-delay and high-efficiency server communication optimization is realized.

The invention relates to the technical field of ship communication, in particular to a multi-link converged communication method and system for a ship. The method comprises the following steps: receiving navigation information broadcasted by other ships in a preset range, evaluating the availability of a communication frequency band, and generating sea area communication channel state data; acquiring geographic position data of each ship; space communication link potential analysis is carried out according to the geographic position data of each ship and the sea area communication channel state data, and cross-chain space communication potential data is generated; constructing a multi-link ad hoc network topological structure according to the cross-chain space communication potential data; and task adaptation communication link allocation is carried out based on a multi-link ad hoc network topological structure, and a multi-link fusion transmission strategy is constructed, so that real-time communication link safe switching management is realized. According to the invention, on the basis of communication service adaptation and a multi-link fusion transmission strategy, real-time communication safe switching and high-reliability transmission of the marine formation are realized.

The invention relates to the technical field of VOIP product communication, and discloses a multi-scene adaptive communication method and system of a VOIP product. The method comprises the following steps: carrying out collection and feature extraction on network state parameters to obtain a scene category, and calling reference communication parameters corresponding to the scene category from a scene parameter library; calculating a composite cumulative distribution function based on the reference communication parameters to obtain an optimized communication parameter combination; applying the optimized communication parameter combination to an edge cloud collaborative coding and decoding framework, and carrying out coding and decoding processing on audio and video data to obtain coded communication data; performing block processing on the encoded communication data, and determining a storage position and a communication node of a data block; according to the method, the communication nodes are divided into the master node and the slave node, and the master node and the slave node are subjected to multi-objective optimization to obtain the data transmission path, so that the dynamic optimization of the communication parameters is realized, a VOIP product has scene self-adaptive capability, and the communication service quality of the VOIP product is improved.

The invention provides a power grid energy disturbance suppression method for electric heating gas state information transmission collaboration, and relates to the technical field of information, and the method comprises the steps: obtaining multi-source heterogeneous state information of an electric heating gas energy network; aiming at the multi-source heterogeneous state information, dynamically converting a heterogeneous communication protocol into a unified protocol format by adopting a self-adaptive communication protocol conversion technology; and for the decoupled state information, parallel processing is carried out by adopting a distributed stream computing framework, so that the real-time performance and expandability of state information processing are improved. A distributed stream computing framework is adopted to construct an efficient processing assembly line, the block chain technology is utilized to guarantee the integrity and reliability of data transmission, a deep learning algorithm is applied to construct an intelligent analysis model, a multi-energy-flow coupling relationship and an evolution law are mined, and a multi-energy-flow analysis result is obtained. According to the method, data processing results of all links are fused to form a global state information view, decision support is provided for power grid energy disturbance suppression, and efficient processing, analysis and visualization of the state information of the electric heating gas multi-energy flow system are achieved.

The invention discloses a forestry ecological environment real-time monitoring and management method based on big data, and belongs to the technical field of forestry ecological environment management, and the method comprises the following steps: S1, multi-source heterogeneous data collection and sensor network deployment; s2, multi-modal data fusion and intelligent transmission: developing an adaptive communication protocol dynamic switching module, and automatically switching to a satellite communication link in a 4G / 5G network blind area; s3, mass data storage and distributed calculation: constructing a hybrid cloud storage architecture, and storing real-time monitoring data into a Redis cache queue; s4, intelligently extracting ecological environment indexes; s5, dynamically evaluating the ecological bearing capacity; s6, performing multi-level early warning and emergency response; s7, making a precise forestry management decision; and S8, carrying out system self-optimization and closed-loop management. According to the method, the air-space-ground integrated monitoring network is constructed, so that the comprehensiveness and the real-time performance of forestry ecological environment perception are remarkably improved; multi-source data of the unmanned aerial vehicle, the satellite remote sensing and the ground sensor are complementary.

The invention discloses an intelligent online monitoring device for a transformer, and relates to the technical field of transformers. The intelligent on-line monitoring device for the transformer comprises a front-end acquisition layer, a data transmission layer, a data processing and analysis layer, a cloud monitoring and management layer and an emergency response layer, through the deployment of the high-precision sensor network and the edge computing nodes, the system can accurately collect and process the operation data of the transformer in real time, and the monitoring accuracy and efficiency are improved. And secondly, the data transmission layer adopts a self-adaptive communication protocol and a data encryption technology, so that real-time and reliable transmission and security protection of the data are ensured, and meanwhile, traceability and tampering prevention of the data are realized by utilizing a block chain technology. In the data processing and analysis layer, the system realizes intelligent early warning and continuous optimization of transformer data through an integrated learning and deep learning model, and improves the accuracy and reliability of early warning. And the emergency response layer is arranged, so that the system can quickly respond to faults.

Various aspects of the present disclosure relate to a UE that receives an indication of one or more system information transmission repetition periodicity values corresponding to a respective subset of synchronization signal blocks (SSBs) within a burst of SSBs. The UE selects at least one SSB from the burst of SSBs, and receives a system information message via one or more physical downlink control channel (PDCCH) monitoring occasions in a search space set for the system information message. The one or more PDCCH monitoring occasions, for instance, are determined based on a system information transmission repetition periodicity value of the one or more system information transmission repetition periodicity values, and the system information transmission repetition periodicity value corresponds to the selected SSB. The UE can implement wireless communication using system information determined from the received system information message.

The invention relates to an energy self-adaptive communication method and system based on a sensing acquisition system, which are applied to the technical field of sensor networks, and the method comprises the following steps: arranging sensors at preset node positions, and carrying out network initialization; detecting the energy state of the sensor at the node position in real time, wherein the energy state at least comprises the residual electric quantity and the voltage level; dynamically adjusting communication parameters according to the energy state, and selecting an optimal communication protocol; sharing the information of the energy state among the nodes in a low-power-consumption broadcast mode; and performing node data relay and energy transfer based on the shared energy state. Through energy detection and communication parameter adjustment between sensor nodes, energy state information can be shared between the nodes, and the communication mode is cooperatively adjusted based on the information, so that optimal utilization of energy is realized.

The invention discloses a navigation robot self-adaptive communication system and method based on multi-network collaboration, and relates to the technical field of network communication, the system comprises a network management module which is responsible for safely storing encrypted AP information and network topology data and providing a function of receiving AP configuration update through NFC; the signal detection module is responsible for detecting network parameters and generating a network quality evaluation report; the switching control module is responsible for predicting the signal intensity in future set time, realizing microsecond-level decision response by combining a dynamic threshold algorithm and a manufacturer protocol adapter, and providing a decision basis for optimization of network connection; and the dual-channel communication module is integrated with a WiFi chip and a cellular network modem, realizes operator link redundancy through dual SIM (Subscriber Identity Module) card slots, dynamically optimizes WiFi and cellular signal reception by utilizing a built-in intelligent antenna array, and executes network connection optimization and switching operation according to a decision of the switching control module. The navigation robot can automatically adapt to different network environments.

The invention relates to the technical field of multi-agent cooperative control, and discloses a multi-agent reinforcement learning formation adaptive method fusing a graph attention mechanism. According to the method, a dynamic graph state space is constructed, and a speed self-adaptive communication mechanism and a multi-target return function are combined, so that the problem of insufficient generalization ability during intelligent agent number change or topological structure dynamic adjustment is solved. The scheme comprises the following steps: establishing a virtual leader-following formation model and a motion dynamics model; designing an adaptive communication radius formula based on speed change; constructing a graph state space, and dynamically aggregating neighbor information by using a multi-head attention mechanism; designing a strategy network and a value evaluation network with residual connection; and a centralized training distributed execution framework is adopted to update model parameters. Adaptive extraction of key neighbor information is realized through a graph attention mechanism, and adaptability and stability of a formation system in a complex environment are improved by combining dynamic communication range adjustment. The method is suitable for unmanned aerial vehicle group control, robot cooperation and other scenes.

The invention provides an equipment connection method, electronic equipment and a computer readable storage medium, and relates to the technical field of terminals. In the application, terminal equipment can obtain a target communication protocol for communicating with auxiliary equipment according to an identifier of a communication protocol in a protocol data packet sent by the auxiliary equipment, and after the target communication protocol for communicating with the auxiliary equipment is obtained, a communication protocol confirmation packet is sent to the auxiliary equipment; in this way, according to the connection address, the terminal device can establish a communication connection with the auxiliary device based on the adaptive communication protocol, the stability of the connection can be ensured, and the transmission delay between the terminal device and the auxiliary device is reduced.

The invention relates to the technical field of smart home, in particular to a device and method for applying a portable modular edge AI to a smart home system. The device is characterized in that the device comprises a portable outer shell and a PCB multi-layer stack modular board card; the system also comprises a main control circuit board card, an edge calculation module, and one or more expansion circuit board system modules. The main control circuit board card comprises an MCU processor, a GPU graphics processor, a DSP digital signal processor, a power management module, a user interaction module, a storage module, a control module, a sensor module and a self-adaptive communication module. The edge calculation module comprises an NPU localization model reasoning chip, a built-in lightweight AI model, a privacy desensitization module and a storage device; the devices are connected and integrated to form a complete system which is used for realizing localized data processing and equipment control in a smart home system, and can execute complex tasks, disperse heat, reduce the size and cost and improve the intelligence and automation of the system under the condition of low power consumption.

The invention discloses a hydraulic power plant automatic debugging system with a self-adaptive communication function. The system comprises a processing unit, a storage unit, a communication module, an input / output interface, a task classification module, a model architecture configuration module and other functional modules. The use method comprises the following steps: analyzing task complexity and high-dimensional features of input data through a task classification module, and grading by adopting algorithms such as principal component analysis and a support vector machine; the model architecture configuration module is used for matching a model architecture according to the complexity level and determining an initial calculation path; the dynamic path adjustment module optimizes a calculation path in combination with real-time data, and the resource distribution module redistributes resources when the calculation power exceeds the limit; the model compression module generates a compression model adaptive to the edge device through pruning and quantization algorithms; the parameter fine tuning module is used for jointly optimizing model parameters for a multi-task scene; according to the method, the adaptability and efficiency bottleneck of an existing debugging tool in a complex scene is effectively solved, and the intelligent debugging level of an automatic system of a hydraulic power plant is improved.

The invention discloses a vehicle-mounted controller network communication control system, relates to the technical field of network communication control, and effectively relieves systematic defects of a traditional vehicle-mounted network under a congestion working condition through deep coupling of a dynamic start-stop prediction model and a self-adaptive communication strategy. A probability model is constructed in real time based on brake operation characteristics, a start-stop period is accurately pre-judged, a driving instruction recombination module generates a composite control frame, and the number of redundant messages is remarkably reduced; by introducing a cross splicing technology and a verification flag bit, efficient fusion and fault-tolerant analysis of multi-source data are realized on the premise that the bandwidth is not increased; the adaptive arbitration unit intelligently optimizes bus resource allocation by dynamically closing an ACK confirmation mechanism and priority adjustment, and instruction stacking and conflicts in a high-frequency start-stop scene are avoided.

The present teaching relates to conduct persona-adaptive communications with a customer at a geo-locale. Transcripts of a current and historic communications involving the customer are used to characterize the persona of the customer. Transcripts of historic communications with customers at the geo-locale are used to characterize the persona of the geo-locale. Current persona of the customer exhibited in the current communication is combined with the customer's persona and the geo-locale's persona to compute a response input vector, A language model generates, based on the response input vector, a persona-adaptive response, which is then sent to the customer a response.

The invention provides a self-adaptive communication equipment fault prediction and maintenance system based on artificial intelligence. According to the system, data analysis and machine learning technologies are utilized, multi-mode sensor data are analyzed in real time, and a fault prediction model is dynamically adjusted to adapt to equipment state changes. Performance evaluation, intelligent maintenance decision, predictive maintenance and fault diagnosis functions and self-healing capability are integrated, and timeliness and accuracy of maintenance are ensured. Through cloud edge cooperative computing, the system quickly responds to data processing, and the security is enhanced. Continuous updating of the knowledge base is maintained, and the system is optimized to adapt to the new technology. The system improves the reliability and maintenance efficiency of equipment, provides a personalized intelligent maintenance scheme for a user, and has wide application prospects and practical values.

The invention discloses a wireless transmission anchor rod multipoint stress sensor system, which relates to the technical field of intelligent monitoring of geotechnical engineering and comprises a data sensing and acquisition module, a data processing and transmission module, a data receiving and storage module, a data analysis and decision module and a user interaction and management module. The technical key points are as follows: multi-protocol adaptive communication and quantum encryption are carried out, a multi-protocol adaptive communication stack is based on an improved near-end strategy optimization algorithm, intelligent switching of communication protocols can be completed in an extremely short time according to an actual environment, and the intelligent switching of the communication protocols can be completed in scenes such as mountainous area tunnels with complex and changeable signals. The problem that transmission of a traditional single protocol is prone to being interrupted is effectively avoided, continuity of data transmission is guaranteed, meanwhile, the integrated quantum key distribution unit adopts a BB84 protocol and is combined with a two-factor encryption system, data transmission safety is remarkably improved, quantum attacks can be effectively resisted in a monitoring scene with the extremely high requirement for data safety in confidential work, and the security of data transmission is improved. And the data leakage risk is avoided.

The invention discloses an area terminal adaptive communication method and system based on link quality perception, and relates to the technical field of power area terminal communication by predicting link quality, comprising the following steps: predicting link quality according to multi-dimensional perception data to obtain link quality prediction data; determining a candidate link based on the service-link adaptation rule base, determining a target link according to the link quality prediction data of the candidate link, and performing data transmission through the target link; according to the real-time link quality data of the target link, whether switching is needed or not is judged in combination with the power grid operation state, and if switching is needed, the link priority is calculated to obtain an optimal link, and link switching is carried out; the method can adapt to a complex operation scene of a power grid, improves the link switching efficiency, improves the communication efficiency and communication reliability between the station area terminals, and solves the problem of low communication efficiency caused by poor environmental adaptability and relatively high switching time delay between a communication protocol and a module in an existing station area terminal communication technology.

The invention relates to the technical field of old people health management, and discloses a personalized health auxiliary management system based on artificial intelligence, which comprises a multi-mode sensing module, an intelligent preprocessing module, a dynamic knowledge graph module, a personalized inference engine module and a self-adaptive communication and interaction module. The multi-mode sensing module is used for acquiring physiological, environmental and behavioral data; the intelligent preprocessing module desensitizes and cleans data through federal learning, and extracts core features; the dynamic knowledge graph module constructs and updates an exclusive graph containing basic and dynamic nodes and associated edges; the personalized inference engine module generates a layered intervention scheme; and the adaptive interaction module adapts to the cognitive ability and synchronizes the scheme. According to the invention, health information integration and dynamic intervention are realized, the management accuracy and compliance are improved, and the method is suitable for home non-clinical scenes.

The invention relates to the field of computer big data, and discloses a self-adaptive parallel computing high-dimensional data dimension reduction and classification optimization system which comprises a quantum tensor decomposition module, a dynamic routing module, a heterogeneous computing classification module and a feedback regulation and control module. The quantum tensor decomposition module realizes nonlinear feature extraction of high-dimensional data through super-adjacency tensor modeling and entanglement entropy constraint; the dynamic routing module generates an adaptive communication path based on pulse time sequence weight optimization and quantum key verification; the heterogeneous calculation classification module dynamically schedules a quantum processor according to data characteristics, and FPGA and GPU resources execute mixed gradient aggregation; and the feedback regulation and control module guarantees the robustness of the system through multi-dimensional parameter closed-loop correction and a multi-stage fault-tolerant mechanism. All the modules cooperate to form a closed loop of dimension reduction, transmission, classification and regulation, the problems of feature extraction distortion, low resource utilization rate and poor dynamic environment adaptability in the prior art are solved, and the real-time performance and reliability of high-dimensional data processing are remarkably improved.

The invention relates to the technical field of address allocation, in particular to an automatic discovery and dynamic address allocation method for 485 bus equipment, which comprises the following steps: a host verifies a broadcast address and transmits an instruction to a bus, captures a delay response of a slave to establish a response queue, analyzes dense signals and peels off conflict fragments, dynamically adjusts sampling to generate rhythm mapping, and sends the rhythm mapping to the slave; address instructions are issued according to the sequence, the slave machines check, update and return receipts, the host machine collects and generates an allocation table, monitors signal drift, adjusts time sequence parameters, reconfigures response time periods, updates a synchronization state and completes recording. According to the method, a mapping mechanism based on a broadcast response time sequence is established, stable node distinguishing is obtained through signal multi-dimensional analysis, independent extraction and sequence self-correction are achieved through differential allocation and dynamic sampling, a self-adaptive communication structure is constructed, unified recognition pairing and rhythm coordination are achieved in address allocation, and the self-organization capacity is remarkably improved; concurrency conflicts are reduced, precision is improved, and communication consistency and efficient automatic addressing in a dynamic environment are ensured.

The invention provides a theoretical modeling method and system for describing the relationship between the gradient entropy and the compression rank, and provides a theoretical basis for gradient compression strategy design and adaptive communication optimization. According to the method, modeling is carried out on gradient matrix eigenvalue distribution, internal relation between eigenvalues and compression errors is revealed by applying a random matrix theory and characteristic spectrum analysis, and a function relation between a compression rank and a reconstruction error is constructed. On the basis, a constraint condition that a compression error absolute value is kept constant is introduced, the standard deviation of the gradient matrix is incorporated into error estimation, a corresponding relation between the standard deviation and a compression rank is derived, and the effect of the standard deviation serving as a compression error intermediate variable is clarified from the statistical angle. According to the method, the minimum compressible rank under specific precision can be estimated, a unified analysis framework is provided for analyzing compressibility differences of different training stages or network layer gradients, and the method has good theoretical universality and engineering practicability.

The invention discloses a help-calling emergency response system based on an intelligent communication network, particularly relates to the field of intelligent communication, and comprises a multi-source data acquisition layer, a preprocessing and feature extraction layer, a progressive analysis engine, a decision fusion center and an execution control layer. According to the method, the data integrity and the anti-interference capability are remarkably improved, the time-space reference unification module adopts a PTP protocol and a coordinate system conversion technology, accurate alignment of multi-source data is achieved, a multi-dimensional feature matrix is generated through time-frequency conjoint analysis, and the problem that the feature extraction dimension of a traditional system is single is solved; the progressive analysis engine triggers a hierarchical response strategy based on dynamic fusion of a transmission robustness index, a space confidence coefficient and an environmental risk value, combines terrain refraction compensation and a timeliness attenuation mechanism to optimize decision logic, breaks through the limitation of a fixed threshold response mode, adapts to communication quality fluctuation and environmental sudden change, reduces rescue delay risk, and improves rescue efficiency. And the resource scheduling accuracy and the system intelligence level are improved.

The invention discloses a multifunctional remote monitoring system for safe operation of chemical plant electrical equipment, which relates to the technical field of remote monitoring of chemical plant electrical equipment and comprises a data acquisition unit, an edge calculation unit, a self-adaptive communication unit, an intelligent diagnosis unit and a remote monitoring unit. The data acquisition unit is used for acquiring valve state, liquid level, temperature and pressure signals in real time; the edge computing unit is integrated in a programmable logic controller (PLC) and is used for data preprocessing and local analysis; the adaptive communication unit is used for optimizing the data transmission priority based on the existing industrial Ethernet protocol Profinet / EtherNet / IP; the intelligent diagnosis unit is used for equipment health state evaluation and fault prediction; the remote monitoring unit realizes visualization and remote control through an upper computer; the programmable logic controller PLC is AB 1756-L71 and is used for integrating an edge computing unit to complete tasks of data preprocessing and local analysis.

The invention discloses an AI development optimization system based on dynamic learning and an adaptive algorithm, and relates to the technical field of artificial intelligence, and the system comprises a collection module which collects GPU occupation data and transmission channel state data, and generates a separation operation signal; the identification module is used for triggering operation task analysis according to the separation operation signal and distributing a transmission channel identifier for the subtask; the path module queries the idle state of each computing unit of the GPU and generates an exclusive communication path; the detection module is used for running the subtasks in the exclusive communication path and outputting channel signal mixing degree; the triggering module is used for setting a mixing degree threshold value and triggering a path replacement signal and a merging operation signal; and the merging module suspends the sub-task processing process based on the merging operation signal, performs merging according to the operation sequence of the sub-tasks, and outputs a complete task. According to the method, efficient resource scheduling and task optimization of AI development are realized through coordination of dynamic task topology analysis and self-adaptive communication path binding.

The invention relates to an intelligent protocol configuration method for a Cat1 module. The method comprises the following steps: performing signal analysis on communication signal data to obtain an initial state sequence; performing multi-dimensional analysis on the signal change characteristics to obtain adaptive communication parameters; performing recursive analysis on the adaptive communication parameters to obtain a protocol configuration set; a configuration priority is obtained through calculation of the communication efficiency index; traversing the protocol parameter linked list to obtain a parameter sequence; analyzing and evaluating the parameter sequence to obtain effective configuration; performing mapping conversion through a protocol parameter mapping table to obtain a protocol instruction sequence; obtaining a protocol identifier according to the response feature; and executing the module configuration instruction and recording a configuration result. According to the invention, continuous acquisition and analysis of signal features are realized, the technical problem that a traditional single fixed window cannot give consideration to long-term trend and short-term fluctuation at the same time is solved, and standardized management and flexible adjustment of parameter configuration are realized.

The invention discloses a multi-serial-port peripheral automatic identification and protocol adaptive communication method in an embedded system. The method comprises the following steps: monitoring physical connection states of a plurality of serial ports in the embedded system; performing communication parameter self-learning on the target serial port, and determining a baud rate and a data format matched with the access equipment; automatically matching the features of the initial data frame with a plurality of protocol feature templates stored in a protocol feature library preset in the embedded system to obtain one or more candidate communication protocols; constructing a verification instruction by using a frame format of the candidate communication protocol, sending the verification instruction to the access equipment, performing interactive verification, and confirming a final target communication protocol according to a response result of the access equipment; and the self-adaptive communication link establishment aiming at the access equipment is completed. The method has the advantages that the problems that manual configuration is needed, deployment is tedious and errors are prone to occurring during mixed connection of multi-protocol equipment are solved, and the flexibility, expandability and deployment efficiency of an embedded system are remarkably improved.

The invention provides a ship magnetic conversion power state remote monitoring system comprising a magnetic conversion power parameter acquisition module which captures magnetic conversion power state parameters of magnetic field change, power output and the like of a ship under different working conditions through a multi-data acquisition device; the remote communication and data transmission module transmits the acquired magnetic conversion power state parameters to a remote control center through a self-adaptive communication protocol; the adaptive communication protocol automatically adjusts the transmission rate and the data compression mode according to the network condition; the optimization algorithm and safety control module operates in a remote control center, and receives and analyzes the transmitted magnetic conversion power state parameters; through a built-in magnetic transformation power optimization algorithm model, the operation state of the ship is evaluated in real time, and potential risks are predicted; when an anomaly is detected, a fluid-actuated safety device is enabled, and related personnel are notified via a remote fault alert system. According to the invention, comprehensive monitoring, efficient transmission and intelligent management of the magnetic conversion power state of the ship are realized.

The invention discloses a high-concurrency management and control method and system for centralized control of an unmanned aerial vehicle by adopting an instruction bus, and relates to the field of unmanned aerial vehicle management and control. According to the invention, the multi-protocol adaptive communication transceiver module automatically selects a proper communication mode, and accesses an unmanned aerial vehicle control management system in a centralized manner through an instruction bus; the data flow batch processing engine collects unmanned aerial vehicle control management information from the multi-protocol self-adaptive communication transceiver module in a real-time or off-line mode and performs data verification; the instruction arrangement control engine dynamically adjusts and arranges the high-concurrency control instruction of the unmanned aerial vehicle according to the verified unmanned aerial vehicle control management information and the instant requirement of the flight task of the unmanned aerial vehicle; the instruction arrangement control engine issues unmanned aerial vehicle high-concurrency control instructions in a centralized mode through an instruction bus, and instruction execution is completed through an unmanned aerial vehicle control management system. According to the invention, efficient, flexible and reliable centralized control of the unmanned aerial vehicle control management system can be realized, and the effectiveness and reliability of high-concurrency management and control of the unmanned aerial vehicle are improved.