30results about How to "Reduce bandwidth pressure" patented technology

The invention relates to the technical field of network acceleration, and discloses an edge-end large language model reasoning acceleration method and accelerator, and the method comprises the following steps: reconstructing a calculation process of a decoding stage, and carrying out the deep fusion of a multi-head attention mechanism and the calculation operation of a feedforward network; the weight and key value data are stored in HBM, and the coefficient and the accumulated attention score are stored in DDR; for linear matrix calculation, a unified matrix calculation unit is used for executing multi-precision matrix operation; for nonlinear function calculation, a mathematical transformation and linear fitting method is adopted, a Softmax function is converted into operation with 2 as the bottom through a bottom conversion formula, and truncation and third-order linear fitting are conducted on a Sigmoid function; and constructing a key value screening algorithm based on the accumulated attention score, dynamically adjusting a key value storage position, maintaining a recent key value cache region and an important key value cache region in a limited cache space, and realizing key value efficient cache in long text reasoning.

The invention relates to a Keystone-based deep ground security heterogeneous data fusion method and system, and the method comprises the steps: deploying a Keystone trusted execution environment on a deep ground edge computing node, creating a security enclave, carrying out the encryption access of multi-source heterogeneous data on the basis of remote authentication and key agreement, completing the space-time alignment and feature extraction after decryption in the enclave, and carrying out the fusion of the multi-source heterogeneous data. And performing cross-modal association analysis and risk assessment based on a preset model or a rule engine to obtain a fusion result, encrypting and signing the fusion result in the enclave, distributing the fusion result to an authorized receiver through a secure channel, and realizing one-time task destruction, long-term task cycle reconstruction and key refreshing in combination with enclave full life cycle management. According to the method, the credibility and the real-time performance of heterogeneous data fusion processing in a complex scene can be improved while the confidentiality and the integrity of deep operation and maintenance data are guaranteed.

This invention discloses a power distribution IoT communication and equipment management system based on dynamic optimization algorithms. It adopts a four-layer architecture: a perception layer, an edge layer, a platform layer, and an application layer. The end devices in the perception layer are used to collect power distribution data and execute control commands. The edge devices in the edge layer, and their managed sub-devices, are used for protocol conversion, data preprocessing, and executing dynamic optimization algorithms. The platform layer is used for message parsing, algorithm optimization, device management, and data storage. The application layer provides a visual user interface. Through dynamic optimization algorithms and a full lifecycle device management scheme, the system significantly improves the reliability of power distribution IoT data transmission, optimizes network resource utilization, enhances equipment operating efficiency, ensures the real-time performance of critical services, and features strong compatibility, security, and concurrent processing capabilities.

The present application relates to the technical field of Internet of Things, in particular to a city intelligent guardrail real-time monitoring method based on Internet of Things, comprising the following steps: collecting original vibration signals of the guardrail through an Internet of Things sensing terminal deployed on a city guardrail node, projecting and reducing dimension of the original vibration signals by using a preset compressive sensing observation matrix to obtain a compressed measurement value data packet; in the present application, time-frequency feature extraction is performed on the reconstructed time-domain vibration waveform, the impact event type is identified according to the characteristic data, and the rapid response and processing of traffic accidents are ensured; in the case that no impact occurs and the waveform presents a free decay trend, the decay tail wave data segment is intercepted, the guardrail structure fastening integrity evaluation index is calculated, and comparison with the safety benchmark threshold value is performed, so that the loosening state of the connecting piece can be quantitatively determined, and external impact monitoring and internal structure health condition diagnosis can be simultaneously realized by using a single vibration source without additional deployment of stress sensors.

The invention provides a state monitoring method and device and a storage medium, and relates to the technical field of communication, the method is applied to a first center universal terminal, and comprises the following steps: sending a heartbeat message to at least one universal terminal, the at least one universal terminal being a universal terminal establishing a connection with the first center universal terminal; determining whether heartbeat response messages sent by the at least one ubiquitous terminal are received or not; based on whether heartbeat response messages sent by the at least one ubiquitous terminal are received, the state of the at least one ubiquitous terminal is determined, and the state is an online state or an offline state; and for each generic terminal in the at least one generic terminal, state information of other generic terminals except the generic terminal in the at least one generic terminal is sent to the generic terminal, and the state information of other generic terminals is used for indicating states of other generic terminals. According to the scheme provided by the embodiment of the invention, the network bandwidth pressure is reduced, the network performance is improved, and the power consumption of each generic terminal is reduced.

The application relates to the field of robot control, in particular to a multi-modal perception pipeline inspection robot control method and an inspection robot. The method comprises the following steps: based on the inspection robot, pipeline detection perception is carried out, and a real-time three-dimensional structure map is generated; the real-time three-dimensional structure map is compressed and uploaded to a cloud monitoring platform; when the cloud monitoring platform receives the real-time three-dimensional structure map, spatial topology analysis is carried out, an inspection instruction is generated, and the inspection instruction is sent to the pipeline internal inspection robot; the internal inspection robot receives the inspection instruction, carries out adaptive path planning, and generates a path execution sequence; the inspection robot carries out dynamic inspection operation based on the path execution sequence, synchronously collects data and returns the data to the cloud monitoring platform, and completes the inspection control operation. The application realizes high-precision and automatic buried oil pipeline inspection operation, and improves the detection efficiency and safety of the buried oil pipeline.

The application discloses a communication method, an IMS network element, a storage medium and a computer program product, relates to the technical field of communication, and the method comprises the following steps: receiving a first SIP invitation request from a first terminal, the first SIP invitation request being a request of initiating a video call by the first terminal to a second terminal; in response to the first SIP invitation request, determining that the first terminal opens a semantic service function and has video semantic extraction capability, sending a first SIP invitation response carrying a first SDP response to the first terminal, the first SDP response comprising first information used for instructing the first terminal to convert video data collected in the video call into video semantic features; performing timestamp alignment based on video semantic features and audio data sent by the first terminal, and generating first video call data based on the video semantic features and the audio data after the timestamp alignment, and sending the first video call data to the second terminal. The application can realize generative communication in the IMS.

This invention relates to the field of byte processing technology, providing a method and apparatus for accelerating byte encryption and decryption. The invention adds operation bits to bitwise operation instructions; uses corresponding operation bits to perform byte selection, endianness conversion, single-input multiple shift processing, and / or efficient table lookup operations. Specifically, byte selection avoids invalid bit calculations, improving instruction utilization. Endianness conversion ensures correct data order, minimizing duplicate data requests due to order errors, thus reducing the need for bitwise operations and improving GPU bandwidth utilization. Single-input multiple shift processing reduces the number of shift instructions, increasing throughput and avoiding repeated loading of the same data; efficient table lookup operations improve bitwise computation throughput, significantly reducing bandwidth pressure. This invention optimizes the granularity of bitwise operations, enabling encryption and decryption algorithms to efficiently utilize computing resources on the GPU while minimizing bandwidth consumption.

This application relates to a method and apparatus for substation equipment condition monitoring based on edge computing. The method includes: deploying edge computing nodes at the substation side, which aggregate real-time condition data collected by monitoring equipment; preprocessing and extracting features from the real-time condition data at the edge computing nodes to obtain equipment feature vectors representing the health status of the equipment; dynamically determining high-risk monitoring areas within the substation based on historical operation and maintenance data and real-time power grid operation requirements, and deploying corresponding lightweight intelligent diagnostic models at the edge computing nodes according to these high-risk monitoring areas; using the lightweight intelligent diagnostic models to perform real-time analysis of the equipment feature vectors to obtain equipment condition diagnostic results including fault types and fault probabilities; and executing tiered early warning or rapid control operations at the edge side based on the equipment condition diagnostic results. This method can improve the diagnostic results of substation equipment condition monitoring.

The invention relates to the technical field of industrial process control and data acquisition, and particularly discloses a transformer copper strip production process data real-time monitoring and wireless transmission system which comprises a data acquisition and edge processing layer, a deterministic wireless transmission layer and a centralized analysis and display layer. The data acquisition and edge processing layer acquires and preprocesses production data in real time; the deterministic wireless transmission layer constructs a low-delay and high-reliability wireless transmission channel based on a time division multiple access and frequency division multiplexing mechanism; and the centralized analysis and display layer stores, analyzes and visualizes the data. By means of the scheme, millisecond-level and deterministic wireless transmission and omnibearing intelligent monitoring of data in the production process are achieved, and the production reliability and the intelligent level are improved.

This invention discloses a method, system, equipment, and medium for the synchronous distribution and analysis of aerospace simulation training scenarios. The method includes: the director notifying both sides of the adversarial training to acquire scenario information; both sides processing the acquired scenario information to generate scenario model data and satellite model data respectively; both sides loading the scenario model data and satellite model data and conducting adversarial exercises; and the maneuver information of one side being sent to the other side after a delay by the director. This invention employs a unified distribution of basic simulation scenario information and satellite, ground station, orbit, and sensor data by the director; both sides acquiring data and constructing dynamic model mapping relationships through modular interfaces, and synchronously initializing using an orbit predictor; real-time acquisition of one's own satellite maneuver parameters and delayed maneuver information during the adversarial process; and improved information interaction efficiency and security through a lightweight data transmission mechanism.

This invention belongs to the field of mine safety monitoring technology, specifically involving an intelligent management system based on miners' positioning data processing. The system includes a wearable precision inertial measurement device, a multi-source data fusion gateway, an underground wireless transmission network, a biomechanical feature extraction server, a behavioral quality evaluation management platform, and a multi-dimensional early warning terminal. The wearable device collects high-frequency motion vector data of miners in real time, performs preliminary noise reduction using the gateway, and the server establishes a gait cycle segmentation model to accurately extract gait feature parameters such as stride length, ground contact time interval, and body center of gravity oscillation frequency. This invention realizes a shift from simple spatial location monitoring to in-depth monitoring of biological signals and behavioral quality, filling the monitoring blind spots caused by passive displacement and improving the proactiveness of mine risk early warning and the accuracy of safety supervision.

The application relates to the technical field of fault diagnosis, in particular to a distributed industrial fault diagnosis system and method, which comprises edge terminals and edge servers arranged in various industrial components. The edge terminal is provided with a rapid diagnosis module, a high-level diagnosis module and a dual-mode trigger communication module. The dual-mode trigger communication module independently and in parallel controls uploading of deep feature data according to event triggering and periodic triggering conditions. The edge server is provided with a synchronous sampling module, a feature fusion module and a global diagnosis module, which are used for aligning and fusing multi-source heterogeneous data on a unified time axis, and performing system-level fault diagnosis. The application guarantees real-time response to sudden faults and continuous monitoring of system states through dual-mode triggering, realizes efficient resource utilization and accurate identification of cross-component implicit faults through a hierarchical collaborative architecture, and significantly improves the comprehensive performance of fault diagnosis of complex industrial systems.

The application provides a data incremental synchronization method and device and a terminal device. The method comprises the following steps: receiving a plurality of incremental logs sent by a source database; extracting table data involved in DML operations from the plurality of incremental logs, and generating compressed logs based on the table data, and sending the compressed logs to each target database; wherein the compressed logs are used to instruct the target database to send a first request when the target database determines that the compressed logs match a query request received by the target database, or to instruct the target database to send a second request after the target database receives the compressed logs for a preset time; receiving the first request or the second request sent by each target database, and sending corresponding incremental logs to the corresponding target database according to the received first request or second request. The application can improve the data synchronization efficiency.

The embodiment of the invention discloses a law enforcement officer post abnormal behavior monitoring method and device and a medium, belongs to the technical field of video data monitoring, and solves the problem that the post supervision accuracy of law enforcement officers is low in the prior art. Comprising the following steps: analyzing monitoring video data corresponding to a law enforcement place, and identifying a target law enforcement object in a video frame; in the monitoring video data, extracting a structured semantic element corresponding to the target law enforcement object; according to a preset law enforcement place type rule base, scene adaptation packaging is carried out on the structured semantic elements, and supervision semantic data frames are generated; and based on the continuously generated supervision semantic data frames, constructing an encrypted supervision semantic stream, and transmitting the encrypted supervision semantic stream to a cloud supervision analysis platform, so that the cloud supervision analysis platform matches the supervision semantic data frames with a preset reference law enforcement knowledge graph, and outputs a post monitoring result corresponding to the target law enforcement object according to a matching result.

The application belongs to the technical field of Internet, and particularly relates to an industrial Internet cross-domain metadata trusted fusion method and system, comprising the following steps: collecting structured metadata, time series metadata and relationship metadata of each industrial domain node, and constructing an intra-domain metadata graph based on field attributes and call relationships; performing semantic coding and time series coding on the intra-domain metadata graph, obtaining corresponding semantic representations and time series representations, and calculating inter-field consistency; identifying stable field clusters, drift field clusters and abnormal nodes according to the inter-field consistency in each industrial domain node; and performing segmented aggregation on the stable field clusters and the drift field clusters by each industrial domain node to generate anchor field summaries and drift trajectory summaries. The application combines metadata graph coding, field clustering and federal dynamic weighting, and realizes industrial cross-domain metadata private trusted fusion through abnormal compensation correction.

The application relates to the technical field of monitoring data processing, and discloses a monitoring terminal of a combined overflow pipeline system and a data processing method, which comprises the following steps: time alignment of liquid level data and gas concentration data based on timestamps, frequency domain filtering of time series data sets based on the set blocking bandwidth of astronomical tidal periods, segmentation and interception of target time series data sets based on a sliding time window in an edge computing terminal, determination of the correlation result of the liquid level and the gas concentration based on a correlation rule algorithm, matching of the change rate, the change gradient and the correlation result with the pipe network structure correlation, determination of the risk identification of the corresponding monitoring terminal based on the pipe section connection relationship and the flow direction information, and division of the event level based on the risk identification in the edge computing terminal. The monitoring data is processed through edge computing, so that the response timeliness, data efficiency and intelligent level of the combined overflow pipeline system monitoring are ensured.

The invention provides a visualization method and system for self-adaptive matching of a display object resolution and a fusion processing mode. The method provided by the invention comprises the following steps: before to-be-displayed content reaches a video physical port of a visualization system, determining a display template according to a plurality of to-be-controlled visualization system display sizes; selecting a target visualization system according to the content density of the to-be-displayed content; determining a display object type in the to-be-displayed content, determining a fusion processing mode of the display object according to the display object type, determining a fused display position of each display object according to the display scene, supplementing a display template corresponding to the target visualization system, and obtaining a target display template; different types of display objects are obtained by utilizing a video physical port, each display object is processed by utilizing a video processor according to a fusion processing mode of each display object, and a plurality of processed to-be-fused display objects are displayed in the same canvas according to a fused display position in a target display template to obtain a fused canvas; and displaying in the target visualization system.

The application discloses a transformer state monitoring and data transmission method, system, device and medium based on cloud edge cooperation, belongs to the technical field of power equipment monitoring, and comprises the following steps: collecting transformer data through an edge layer; judging whether matched fault physical characteristics exist in a fault characteristic library; triggering a diagnostic rule engine to obtain a first diagnostic result when the matched fault physical characteristics exist; calling a lightweight diagnostic model to obtain a second diagnostic result; calculating the final probability of various faults according to the first diagnostic result and the second diagnostic result; determining a health state according to the final probability; determining a data transmission level according to the health state; determining data to be transmitted according to the data transmission level; predicting available bandwidth and determining a transmission mode; and transmitting the data to be transmitted from the edge layer to a cloud layer. Through the cloud edge cooperation architecture and the data hierarchical transmission mechanism, the application meets the real-time requirement of data transmission and maintains the fault diagnosis capability when communication is interrupted.

This application discloses a privacy-preserving feature extraction method and system applicable to data base generation, relating to the field of IoT privacy protection technology. The method includes: operating in a first power consumption mode and with a first computational precision to acquire environmental perception data and obtain a complexity level; if the complexity level exceeds a first preset threshold, waking up a second feature extraction unit to extract first structured feature data and uploading it to a cloud data base; if the confidence score of the first structured feature data is lower than a second preset threshold, extracting local area data and uploading it to the cloud data base; performing refined identification on the local area data to generate second structured feature data and storing it in the cloud data base. This solves the technical problems of insufficient feature extraction accuracy, excessive power consumption, and high bandwidth pressure in existing vehicle-side applications due to edge computing power limitations.

The application is a kind of MCB distribution box real-time data acquisition and diagnosis system based on edge computing; its core is a dual-mode acquisition unit, which continuously monitors the transient fluctuation index of the line under low power consumption; only when the index exceeds the preset threshold, the system will instantaneously switch to high-precision mode to acquire compressed waveform data; after receiving the data, the edge diagnosis unit reconstructs the high-fidelity fault waveform and generates structured diagnostic results using the diagnostic model; the timing correlation positioning unit accurately locates the physical position of the fault based on the high-precision timestamps of multiple diagnostic results by calculating the arrival time difference; the cloud unit then aggregates all results, evaluates and optimizes the entire system, and issues new model parameters and trigger thresholds to the front end to form a closed-loop control; this design reduces the power consumption and network communication bandwidth pressure of the front-end device.

The invention discloses an electric power operator behavior edge identification and AR correction method and system based on a double-flow heterogeneous lightweight network. The method comprises the following steps: acquiring a first visual angle video stream and sensor data of a six-axis inertial measurement unit through intelligent equipment; performing normalization and de-noising processing on the video frame, and segmenting the video frame into short-time video clips according to a time window; running the pre-trained double-flow heterogeneous lightweight network, performing real-time reasoning on the video clip, and outputting a current behavior category label; the behavior confidence degree output by the double-flow heterogeneous lightweight network model is compared with a preset threshold value to judge whether the event is a violation event or not; if the event is identified as a violation event, a deviation correction mechanism is triggered immediately; and encrypting and uploading the violation event log to an enterprise security management platform or other third-party platforms for users to check, count and trace. The method can effectively solve the problems of high behavior identification delay, dependence on cloud, low edge equipment operation efficiency, insufficient multi-behavior identification precision and the like in the prior art.

The present invention relates to the technical field of automated maintenance operations in power systems. Specifically, it relates to a complete set of operation systems and methods for power verification and grounding wire hanging and removal based on an unmanned aerial vehicle (UAV). The method includes: determining whether the transmission wire is charged, and generating a permission signal after confirming that there is no electricity; under the trigger of the permission signal, controlling the UAV to perform the operation of hanging or removing the grounding wire, and identifying and discriminating the state of the grounding wire device during the operation; monitoring the operation process in the steps of hanging and removing the grounding wire in real time, and transmitting the operation status and associated operation site images to the ground terminal. Through the present invention, a systematic process integrating power verification, state identification, and operation monitoring is achieved, realizing full-process automation and intelligence from power verification to hanging and removing operations and then to process monitoring, improving operation safety and efficiency.

The application discloses a task processing method and system based on a large language model and electronic equipment. The method comprises the following steps: obtaining target task data corresponding to the large language model; determining an input embedding vector corresponding to the target task data; determining a shared key-value vector corresponding to the input embedding vector and broadcasting the shared key-value vector; splitting the input embedding vector to obtain a plurality of sub-task vectors; determining target wireless terminals corresponding to the plurality of sub-task vectors from a plurality of candidate wireless terminals according to the input embedding vector, the shared key-value vector and a resource state vector; sending corresponding sub-task data to the corresponding target wireless terminals; receiving intermediate result vectors corresponding to the plurality of target wireless terminals respectively, and determining a task output result corresponding to the target task data according to the plurality of intermediate result vectors. The application solves the technical problem of large communication transmission overhead and high time delay in the related art when performing task processing.

The invention provides a tensor arithmetic unit based on an RISC-V instruction set, and the tensor arithmetic unit comprises a microinstruction splitting and scheduling unit which receives a decoded macroscopic tensor instruction and an operation size parameter thereof, splits the macroscopic tensor instruction into microinstruction sequences according to a fixed physical scale of a reconfigurable calculation array, and transmits the microinstruction sequences to the reconfigurable calculation array; a zigzag traversal sequence and microinstruction scheduling are achieved through quintuple hardware circulation, and the loading, using and replacing sequence of the data blocks in the block register array is planned; the reconfigurable computing array is used for executing matrix multiply-accumulate operation of various data formats by designing a reconfigurable data path and fusing and multiplexing a floating point multiplier and a multi-precision accumulation tree under data paths with different bit widths; and the hardware multi-buffer unit is a multi-buffer architecture automatically managed by hardware and is matched with a zigzag traversal sequence to realize pipeline overlapping of data prefetching and calculation execution. The invention further provides an intelligent processor. Therefore, the invention can efficiently execute tensor operation with variable precision and variable scale.

The invention provides an intelligent traffic guidance system and method based on an intelligent signboard, and relates to the technical field of intelligent traffic, and the method comprises the steps: a first intelligent signboard disposed at a road side recognizes a suspected emergent traffic event from a road real-time video stream through a lightweight dual-path network, and generates a first confidence coefficient; calling millimeter wave radar data, detecting a motion state mutation feature of the target object in the suspected sudden traffic event, and generating a second confidence coefficient; performing dual verification judgment based on the first confidence coefficient and the second confidence coefficient, and generating emergency information after the occurrence of the emergency traffic event is confirmed; broadcasting the emergency information to other intelligent signboards; each intelligent signboard calculates to obtain a collaborative guidance priority factor; and each intelligent signboard matches a corresponding guiding strategy according to the collaborative guiding priority factor and executes a traffic guiding action. The technical problems of high delay and insufficient guidance of sudden traffic incident detection in the prior art are solved.

This invention relates to a handheld integrated multimodal diabetic foot screening terminal and a cloud-edge-device collaborative screening system. It uses Time-of-Flight (ToF) and Induction Memory (IMU) fusion to estimate the relative pose and motion state of the terminal and the foot in real time, constructing a joint stability criterion based on distance, angle, and jitter. A three-dimensional mesh model of the foot is reconstructed based on the ToF depth map, mapping multispectral and thermal textures onto the three-dimensional surface and unfolding it onto a standard two-dimensional plane. Combined with distance-squared compensation, incident angle compensation, and low-confidence region masking, surface effects and uneven illumination are suppressed. The terminal uses a neural network acceleration unit to run a lightweight artificial intelligence model, outputting risk level, suspected lesion location, and model uncertainty. When uncertainty or quality control rules are triggered, only anonymized and encrypted difficult data packets are selectively uploaded to the cloud for human-in-the-loop annotation and retraining. This invention significantly improves the consistency and accuracy of screening under handheld imaging, and is suitable for mobile scenarios such as bedside, primary healthcare, and home follow-up.

The invention belongs to the technical field of large language models, and particularly relates to a large language model KV Cache unloading optimization method. Comprising the following steps: inputting a plurality of marks obtained by performing word segmentation processing on a to-be-processed text into a large language model; aiming at the current mark of the current attention layer, pre-selecting a key KV index set of the next mark of the current attention layer by using a cross-mark pre-selection mechanism; loading the key KV of the current mark in the next attention layer pre-selected by the previous mark by using a cross-mark pre-selection mechanism to the GPU from the external storage; the GPU adopts a KV cache adaptive hierarchical management strategy to manage the cache; the GPU executes sparse reasoning calculation which is currently marked on the current attention layer; taking the next attention layer as the current attention layer, and repeating the reasoning process until a final reasoning result of the large language model is output; according to the method, the transmission bottleneck caused by interlayer heterogeneity is relieved fundamentally, and low-delay and high-throughput large language model reasoning is realized.

The invention relates to the technical field of digital information, in particular to a real-time interactive visualization method based on multi-source heterogeneous data driving, which comprises the following steps of: acquiring multi-source heterogeneous data of each physical entity in a physical entity set through a multi-protocol adapter configured in a physical site, wherein the multi-source heterogeneous data carries a unique device identifier corresponding to each physical entity. According to the method, the execution states of the three-dimensional model instances are driven to be synchronized according to the mapping relation, the digital twinborn visual interface is generated by utilizing the graphic rendering engine, and abstract numerical value changes are converted into visual dynamic feedback in a three-dimensional space in real time, so that a user can perceive the operation situation of a physical site. And responding to an interactive operation generated by the visual interface, analyzing and generating a reverse control instruction, and sending the reverse control instruction to the target physical entity, so that a bidirectional control link from the virtual space to the physical equipment is opened, WYSIWYG remote control is realized, the fault response time is shortened, and the man-machine interaction experience is optimized.

The invention discloses a system architecture based on a global digital space project and a deployment method. The system architecture comprises a terminal user module, an edge device module, a regional server module and a regional digital space platform module. The system realizes multi-terminal access through the terminal user module, and a camera, a switch and an NVR are deployed on the edge side to complete video acquisition and local storage. And the regional server establishes connection with the NVR, receives a video stream and performs primary processing, and the regional digital space platform splices a multi-view video to generate a panoramic digital twinning scene. And the group-level platform realizes data integration with the Internet of Things platform through the AI algorithm center and provides a standardized interface service. According to the method, a cloud edge cooperative computing mode is adopted, the network bandwidth requirement is reduced, the data processing real-time performance and the system flexibility are improved, cross-region deployment is supported, and the method is suitable for digital space management scenes such as intelligent agriculture and intelligent manufacturing.