869 results about "Network delay" patented technology

The invention belongs to the field of intelligent edge systems and privacy enhancement computing, and particularly relates to a privacy protection-oriented robot large model cloud edge end collaborative reasoning and federated learning system, which comprises a cloud server layer used for deploying a large-scale pre-training model and executing complex reasoning and global federated learning coordination; the edge calculation layer is used for deploying an intermediate layer model and executing local data aggregation, privacy protection processing and intermediate feature calculation; the terminal equipment layer is used for deploying a lightweight model and executing data acquisition, primary processing and lightweight reasoning; the federated learning framework is used for optimizing the model; the privacy protection module is used for integrating data localization, differential privacy, homomorphic encryption, secure multi-party computing and a block chain verification mechanism; the adaptive allocation module is used for dynamically adjusting computing resources. According to the method, the problems of privacy leakage risk, computing resource limitation, network delay, insufficient data isolation and the like of the traditional AI service in a robot scene are solved, and efficient privacy protection and data security isolation are realized.

The invention relates to the technical field of prediction and alarm, in particular to a school computer room data operation monitoring and early warning method and system, and the method comprises the following steps: obtaining real-time data, such as CPU utilization rate, memory occupancy rate and network delay, through a sensor, generating a parameter sequence after standardization, extracting a difference sequence through a sliding window, and recognizing the output trend risk of a continuous rising interval. And extracting a behavior frequency to generate an abnormal coefficient, carrying out weighted analysis on the coupling degree to obtain an early warning threshold, and generating an early warning instruction if the growth rate exceeds the threshold and lasts for three time slices. According to the method, difference characteristics are extracted through a standardized time sequence and a sliding window, behavior state association is analyzed in combination with a periodic frequency, coupling degree dynamic early warning is calculated, a continuous deviation trend is screened, a real-time threshold range is formed, abnormal confusion is reduced, occupation of irrelevant alarm resources is reduced, risk identification capability is improved, and stable operation of equipment is guaranteed. And hidden danger accumulation occurrence probability is reduced.

The invention relates to the technical field of software time synchronization, and discloses a software time synchronization method and system for multi-sensor data fusion, and the method comprises the steps: extracting temperature, load and drift frequency characteristics through principal component analysis based on the working state and historical drift data of a sensor, and constructing a confidence evaluation model to calculate the credibility of a timestamp; identifying an abnormal node group by using k-means and an isolated forest algorithm, analyzing a phase deviation fluctuation and network delay interaction effect, extracting a nonlinear drift feature in combination with a Prophet algorithm, and calculating a phase correlation value by using Hilbert cross-correlation; and dynamically adjusting node clock parameters and generating a calibration timestamp according to the network influence weight and the stability evaluation result. According to the method, the problem of time desynchrony caused by clock drift and network delay factors in a distributed system is effectively solved, and the overall time consistency and reliability of the system are improved.

The invention relates to a server cluster monitoring system based on multi-node collaboration and an implementation method thereof, a dynamic topology network module is configured to reconstruct a connection topology among monitoring nodes in real time according to node performance and link quality, support mixed configuration of a star type, a ring type and a net structure, and realize multi-node collaboration. Multi-dimensional data capture from a physical layer to an application layer is realized through a cross-level index acquisition module based on an integrated hardware sensor interface and a virtualization layer probe, and each node is enabled to perform collaborative reasoning through parameter encryption sharing through a decision model based on federated learning. A monitoring task fragmentation strategy is dynamically adjusted through an adaptive elastic fragmentation unit according to network delay and load fluctuation, and an abnormal event association rule base is updated in real time through an incremental knowledge graph construction unit. High availability and elastic expansion are realized through a multi-node collaborative architecture, the monitoring efficiency is improved in combination with dynamic load balancing and hybrid detection, and an intelligent multi-level response mechanism is constructed to guarantee the service continuity.

The invention provides a method, a device and a system for switching master and standby control centers of a smart home. In the scheme, real-time operation state data of each control center in the smart home and the number of times of downtime in a first preset time period are acquired, and based on the real-time operation state data and the number of times of downtime, a long-term short-term memory network model is used to score each control center to obtain a final score of each control center; sorting all the final scores from large to small, and determining the control centers corresponding to the final scores ranked in the front preset number as candidate control centers; an improved PBFT protocol is adopted to carry out consensus election on the candidate control hub, a target control hub is elected, the main control hub is switched to the target control hub for operation, and the target control hub meets at least one of the following preset conditions: the highest network communication efficiency, the shortest network delay and the lowest power consumption. The problem that the switching efficiency of the main and standby control centers in the smart home system is low is solved.

The invention discloses a ship management method and system based on digital twinborn scene construction. The method comprises the following steps: acquiring multi-source scene data of a target water area in real time, and constructing a corresponding ship management digital twin model; performing integrity evaluation on the constructed digital twinborn model, and performing defect compensation according to an evaluation result to obtain an optimized digital twinborn model; further collecting ship density and weather condition data of each sub-region of the target water area, constructing a network transmission delay prediction model, analyzing related data based on the model, and generating a network delay coefficient distribution diagram of the target water area; and according to the delay distribution diagram, determining the real-time updating lag amount of each subunit of the optimization model, and correcting the ship position information in the digital twin model. According to the method, the real-time performance and accuracy of the digital twin model can be remarkably improved, and the ship operation management efficiency and safety in a complex water area environment are enhanced.

The invention discloses a vehicle-mounted controller firmware upgrading method, which relates to the technical field of intelligent networked automobiles, and comprises the following steps of: accurately describing a dependency relationship between versions by introducing a directed acyclic graph, providing a clear topological sorting basis for an upgrading process, and improving the upgrading efficiency. The system function conflict and disorder caused by disordered upgrading sequence are fundamentally avoided; a distributed consensus protocol is utilized to ensure that each controller achieves state coordination before upgrading, so that the overall robustness of a multi-controller cluster is effectively improved when the multi-controller cluster faces network delay or individual node abnormity, and upgrading failure or version bifurcation caused by the fact that part of nodes are not ready is avoided; through the combination of the group-level binding token and the atomic switching mechanism, the controller group with a strong function dependency relationship can be ensured to be effective and updated as a unified transaction unit, and the safety and reliability of cross-domain function linkage are remarkably enhanced.

The invention discloses a network optimization method based on an online conference, which relates to the technical field of real-time audio and video transmission, and comprises the following steps: in a transnational network, deploying monitoring probes at nodes participating in the online conference for monitoring network parameters such as network delay, bandwidth, packet loss rate and jitter in real time; the method comprises the following steps: processing network parameters and predicting abnormity by using a statistical analysis algorithm and a time sequence model to obtain network condition information, and then combining global network topology and using a reinforcement learning Q-Learning model and a graph neural network GNN topology prediction algorithm; according to the method, the network condition is monitored and predicted in real time, the optimal transmission path is output by using the reinforcement learning Q-Learning model and the GNN topology prediction algorithm, the bandwidth fluctuation is predicted through the LSTM, the packet loss rate is predicted based on the Bayesian network, the data transmission strategy is optimized, the network delay, the packet loss rate and the jitter are effectively reduced, and the network performance is improved. And the smoothness and the stability of the conference are improved.

The invention relates to the technical field of operation and maintenance management, and discloses a cloud operation and maintenance management method, system and equipment for a charging station, and the method comprises the steps: monitoring the WiFi signal strength, 5G network quality and wired network delay parameters of each floor of a stereo garage in real time, and building a network environment database; when the charging pile detects that the SOC change amplitude exceeds a set threshold value, an optimal target transmission path set is screened out; carrying out differential bit coding on the collected charging data to generate a charging data frame, and sending the charging data frame to a cloud server in a multi-path concurrent mode; the cloud server receives and gathers the charging data frames from different floors of the stereo garage, and analyzes the charging load distribution condition of the whole garage; and calculating a power distribution scheme of the charging pile of each floor based on the whole garage charging load distribution condition, and issuing a scheduling instruction to the charging pile of the corresponding floor, thereby improving the intelligent operation and maintenance management level and resource utilization efficiency of the stereo garage charging station.

The invention relates to the technical field of power supply, and particularly discloses a peak and frequency regulation heat supply method for a multi-element energy storage coupling coal power unit, which is used for solving the problems that only active frequency is optimized, electric heating coordination and charge state constraint are lacked and time delay compensation is insufficient in the prior art. The method provided by the invention comprises the steps of system modeling, controller design, coupling constraint, adaptive parameter adjustment, delay compensation and distributed consensus. According to the method, a dual-domain electric power-thermal interconnection model is constructed, a cooperative controller based on delay compensation distributed model prediction control is designed, electric-thermal cooperative penalty and charge state constraint are introduced into a target function, a prediction window and weight parameters are adaptively adjusted, and network delay is identified and compensated online. And a consensus algorithm is adopted to realize multi-region power-heat collaborative optimization.

The invention relates to the technical field of computers, and provides a game acceleration method, a game accelerator and a storage medium. The method comprises the following steps: in response to a game acceleration request initiated by a game client for an external service game, sending a network state detection packet set to an acceleration node group according to a preset detection period, and receiving a network state data packet set fed back by the acceleration node group; determining a current cycle packet loss rate and a next cycle packet loss rate corresponding to each acceleration node based on the network state detection packet set and the network state data packet set; determining a target transmission path and a target transmission mode based on the packet loss rate of the current period and the packet loss rate of the next period; and transmitting the original game data packet to a target game server through the target transmission path and the target transmission mode to complete game acceleration. According to the method, the network delay and the packet loss rate when the game user plays the outer clothing game can be effectively reduced, so that the game experience of the user is improved.

The invention discloses a real-time interaction and intelligent management method for a multi-dimensional data space, and relates to the technical field of data interaction management, and the method comprises the following steps: I, collecting multi-source data, including structured data, unstructured data and spatio-temporal data, in real time through a diversified collection terminal, and dynamically adjusting the sampling frequency based on a data entropy value, carrying out cross-device space-time synchronization calibration and edge end lightweight processing on the acquired data; iI, preprocessing the data flow in real time, fusing the multi-modal data, and the like. According to the method, the sampling frequency is dynamically adjusted based on the data entropy value, and in combination with edge end lightweight processing, invalid data transmission is reduced, and the key data acquisition efficiency is improved; hot data is stored in a time sequence database and a memory database, real-time monitoring of an emergency scene and second-level response of emergency command are supported, dynamic capacity expansion and shrinkage of computing resources are matched, edge-cloud end collaboratively distributes tasks, network delay is reduced, and system stability and response speed in a high-concurrency scene are guaranteed.

The invention relates to the field of broadband alarm, in particular to a broadband user-based optical modem power failure and fiber break alarm real-time monitoring method, which comprises the following steps of: S1, monitoring and recording the online state, the light attenuation level, the flow information, the packet loss rate, the network delay and the log of an optical modem under OLT (Optical Line Terminal) equipment in real time; s2, automatically identifying an abnormal mode and a potential fault according to a model established by a machine learning algorithm and a deep learning algorithm; s3, automatically diagnosing problem reasons according to the collected data, and optimizing the knowledge base in combination with an expert system; s4, performing deep mining and analysis on historical fault data, and predicting a potential fault risk based on the historical data and a real-time monitoring result; and S5, continuously updating and optimizing a fault detection and diagnosis model through a self-learning algorithm model, and uniformly monitoring and managing all data acquisition, analysis and alarm modules. The fault detection accuracy and timeliness can be improved, and potential fault prediction and preventive maintenance are realized.

The invention relates to the technical field of data processing, can be applied to business scenes such as financial science and technology and medical health, and discloses a cross-platform information interaction method, device and equipment and a medium, and the method comprises the steps: obtaining original information sent by a source platform, and analyzing the original information into a standardized data structure according to a preset data format; extracting multimedia content elements from the structure and performing format conversion to generate standardized multimedia content; packaging the structure and the content into a to-be-transmitted data packet; acquiring network delay and bandwidth parameters of the target platform, and selecting a transmission path based on the parameters; compressing the to-be-transmitted data packet and sending the compressed to-be-transmitted data packet to the target platform through the selected path; and the target platform receives and analyzes the compressed data packet and presents the original information content. Information format compatibility is achieved through a standardized structure and content packaging, transmission efficiency is improved through network parameter perception and path selection, complete presentation of information is guaranteed in combination with compression processing and terminal adaptation, and stability and consistency of cross-platform interaction are enhanced.

The invention is suitable for the technical field of data processing, and provides a distributed data consistency control method and system, and the method comprises the steps: constructing an enhanced vector clock containing a fuzzy membership parameter and a time window deviation value; a dynamic fuzzy inference engine is built in combination with factors such as network delay jitter; calculating conflict event logic precedence relation probability distribution by utilizing an engine; generating an execution sequence hypothesis by integrating the multi-dimensional information; selecting an optimal scheme based on a dynamic confidence threshold; and resources and consistency are balanced through a three-level conflict processing mechanism. According to the method, the problem that a traditional vector clock cannot process conflict event sorting is solved, the accuracy and adaptability of distributed data consistency control are improved, and efficient collaboration of the system is guaranteed.

The invention discloses an optimal signal selection intelligent network switching management method based on a super SIM multi-network, and relates to the field of intelligent network switching management, and the main scheme is as follows: analyzing and calculating operation state data to obtain a network delay score, a downloading rate score and a network stability score in a current network environment, and carrying out comprehensive analysis to obtain an optimal signal selection score; obtaining a current network state score; judging whether to execute a network switching instruction or not by evaluating the current network state score; the coverage degree data, the network state data and the switching cost data are analyzed and calculated to respectively obtain coverage matching degree indexes, network state indexes and switching cost-benefit ratios of different operators; switching priority indexes of different operators are obtained through comprehensive analysis, the switching priority is determined, and the problem that switching decisions and requirements are disjointed due to the fact that switching is triggered only based on signal strength or a single rate threshold and core indexes such as network delay and stability which affect user experience are not fused is solved.

The invention discloses a control method, system and equipment of a remote rehabilitation robot, a medium and a product, and belongs to the technical field of robots. The method comprises the steps of obtaining multi-modal data of a patient end, obtaining a time delay prediction value through prediction of a long short-term memory network model, dynamically adjusting admittance parameters of an admittance model according to the multi-modal data and the time delay prediction value, and finally controlling the remote rehabilitation robot according to the dynamically adjusted admittance parameters. According to the method, the admittance parameters of the admittance model are dynamically adjusted in real time based on the time delay predicted value predicted by the long-short-term memory network model and the electromyographic signals of the patient in the multi-modal number, dual adaptation of the network state and the physiological features of the patient is achieved, the admittance parameters are dynamically adjusted through the electromyographic signals, and the change requirement of the complete rehabilitation cycle of the patient is met; admittance parameters are dynamically adjusted through the time delay prediction value reflecting the network time delay state, and the time delay disturbance requirement in the remote communication environment is met.

The invention provides a multi-operator card AIOT management method and system based on the Internet of Things, and the method comprises the following steps: carrying out API butt joint, calling a mobile CMNet API, a Unicom WorAPI and a Telecom CTWing API, and obtaining the state, flow and signal intensity data of an Internet of Things card; a heterogeneous protocol is converted into a unified JSON format through a protocol conversion gateway; network delay and base station loads are monitored in real time, and network scores of all operators are calculated based on the base station loads, the network delay, the signal strength, the tariff cost and the historical stability; and judging whether a switching trigger condition is met or not, and when the switching trigger condition is met, determining to switch the network based on the network scores of the operators, and executing a network switching process. According to the method, the network condition is monitored in real time, and the score of each operator network is calculated based on multiple factors, so that the available network can be quickly switched to when a single operator network has a fault or a poor signal, and the stability of the Internet of Things system is improved.

The invention discloses a seamless switching method and system for a high-speed terminal of a ground-non-ground convergence network based on trajectory prediction and resource pre-reservation, and belongs to the technical field of space-ground convergence communication. The core of the method is that a switching area is accurately judged through bidirectional motion prediction of a terminal and an NTN node; a dynamic switching window is calculated in a self-adaptive mode by combining factors such as terminal speed and network time delay; intelligently selecting an optimal target link by using an AI enabled link scoring model; and cooperative pre-reservation and uplink and downlink synchronization of resources are completed before the window. The method has the advantages that the problem of failure of traditional RSRP judgment in an NTN dynamic environment is solved, the switching success rate and prediction accuracy in a high-speed moving scene are remarkably improved, the service interruption time and signaling overhead are greatly reduced, the continuity and reliability of communication are effectively guaranteed, and the method is suitable for large-scale popularization and application. The method is suitable for high-dynamic service scenes such as intelligent network connection vehicles and unmanned aerial vehicles in a 6G network.

The invention discloses a cross-regional computing power resource collaborative allocation method based on computing power centers, and relates to the technical field of computing power resource scheduling and optimizing.The cross-regional computing power resource collaborative allocation method comprises the steps that real-time load data, historical task execution data and network delay data of all computing power centers are collected, and a regional load feature database is constructed; predicting the load demand of each computing power center in a future time window by using a long short-term memory network model to generate a load prediction value; calculating a resource gap coefficient and a resource margin coefficient of each region according to the load prediction value and the current resource capacity, identifying a resource insufficient region and a resource surplus region, and generating a resource collaborative matching matrix between the regions; and optimizing and solving the cross-regional task allocation scheme by adopting an improved genetic algorithm to generate an optimal resource allocation strategy, and allocating the to-be-processed task to a corresponding computing power center according to the optimal resource allocation strategy. According to the method, the cooperative utilization rate and the distribution efficiency of the computing power resources in the cross-regional scene are effectively improved.

The invention relates to the technical field of edge cloud and distributed storage hybrid computing, and discloses an edge cloud and distributed storage hybrid computing task scheduling system, which comprises an edge computing module, a distributed storage module, a task scheduling module, a network communication module, a monitoring and management module, a security and privacy module, a cloud edge collaboration module and an application layer interface module. According to the hybrid computing task scheduling system based on the edge cloud and the distributed storage, computing and storage resources are collaboratively optimized, a computing task is sunk to an edge node close to a data source, the time for transmitting data to the cloud is shortened, the data are fragmented and stored in a plurality of edge nodes, parallel reading and writing are supported, the single-point bottleneck is avoided, and the computing efficiency is improved. And the real-time response capability is improved, and decision lag caused by network delay is avoided, so that the resource scheduling efficiency is improved.

The invention belongs to the technical field of satellite positioning, and particularly discloses a high-precision PPP (Point-to-Point Protocol) positioning method based on SSR (Simple Sequence Repeat) correction prediction, which comprises the following steps that: a receiver receives and stores an SSR correction in real time to obtain an SSR sequence; inputting the stored SSR sequence into a pre-trained prediction model, and outputting an SSR correction number prediction value in a future time period; the broadcast ephemeris is corrected through the predicted SSR correction number, and a precise satellite orbit and clock correction are obtained; and constructing an ionosphere-free combination model based on the double-frequency observation value, and resolving the position of the receiver through Kalman filtering in combination with the corrected satellite orbit and clock correction. According to the method, long-time-sequence prediction is carried out on the SSR correction number through the prediction model, the problem of positioning precision jump caused by satellite correction data interruption is effectively solved, it is guaranteed that PPP positioning continuously outputs centimeter-level precision results under the scenes of signal shielding, network delay and the like, and the limitation that traditional PPP strongly depends on real-time SSR data is broken through.

The present application relates to the technical field of middleware, and in particular to a cache data semi-synchronization method, comprising comprises the following steps: writing and running a distributed cache proxy layer service using a preset programming language, receiving a read / write command request from an application client, parsing a Key consistent hashing value and sending same to a rear-end Redis sharding node. A master instance parses a message packet, marks a write operation and records same in an AOF file. Upon write to disk, the master instance sends an AOF file transfer command to a slave instance node, and the slave instance acknowledges reception. When receiving a reception response, the master instance updates an acknowledgment offset of the slave node and responds to the client. When network delay is high, data of a master node and a slave node is marked as "asynchronous", and it is automatically downgraded to asynchronous replication. According to the present application, by means of a self-developed Redis kernel, an asynchronous ack mechanism is used to optimize redis to achieve master-slave semi-synchronization, thereby enhancing data reliability of a single point of failure, and eliminating the influence introduced by a native Redis asynchronous replication mechanism such as data delay and data consistency.

The invention belongs to the field of passwords, and discloses an anti-quantum threshold digital signature method and system capable of tolerating high network delay. The method comprises the following steps: in a secret key generation stage, a trusted third party randomly selects a secret key and performs Shamir secret sharing on the secret key, and distributes a secret sharing value to each signer; in a distributed signature stage, each signer carries out packaging and secret sharing on a secret sharing value, a proving sub-circuit of a public key is operated based on a secure multi-party computing protocol, and each participant outputs a signature through two rounds of interaction. The anti-quantum threshold digital signature scheme has function interchangeability, that is, the signature generated by the threshold scheme and the signature generated by the original signature scheme can be verified by the same verification algorithm; meanwhile, the threshold digital signature scheme is efficient and achievable, and a threshold signature protocol in a scene of two parties of a wide area network only needs 2 seconds; moreover, the method has a better number of rounds, and the signature algorithm only needs two rounds.

The invention belongs to the technical field of front-end performance optimization. According to the webpage resource preloading method and system based on multi-factor dynamic evaluation, a network quality score is obtained according to an obtained bandwidth factor, a network delay factor and a resource stability factor of a current webpage; dynamically adjusting the behavior weight score of each webpage resource according to the user behavior; determining corresponding loading priority weight scores according to the types of different webpage resources; and taking the weighted sum of the network quality score, the behavior weight score and the loading priority weight score as a final loading score, and carrying out corresponding webpage resource loading according to the final loading score. According to the method, the network quality evaluation and the user behavior prediction are combined by monitoring the network quality score and the user interaction behavior in real time and dynamically adjusting the loading priority and the strategy of the key resource, the limitation of a traditional static resource loading strategy is broken through, and the page loading speed and the overall performance are remarkably improved.

The invention discloses a storage and calculation separation key value storage delay optimization method based on prediction driving, and aims to solve the problems of performance bottleneck and high tail delay caused by passive management and high network delay in a key value storage system in a storage and calculation separation scene. The method comprises the following steps: time load prediction: deploying a time sequence prediction model at a client, and predicting a future read-write request based on a historical access sequence; active cache prefetching: according to the predicted read request, actively preloading hotspot data from a server side to a client side for caching so as to improve the cache hit rate and hide network delay; active write-in optimization: according to the predicted write request, executing maintenance at a server side through predictive pre-insertion and active node splitting, and moving high index structure adjustment overhead out of a key request path to eliminate a write delay peak; and structure sensing batch synchronization: pre-fragmenting a local write buffer by using a server index top layer model of a client cache, and combining multiple independent remote insertion operations into one efficient batch update to reduce data synchronization overhead. Compared with an existing passive management system, the characteristics of model prediction and active cooperation are fully utilized, and the average delay and the tail delay of the system are reduced.

The invention relates to the technical field of computers, and discloses a proxy gateway scheduling method and device, a storage medium and computer equipment, and the method comprises the steps: receiving and analyzing a user request, determining a target processing demand, and determining a plurality of candidate service nodes meeting the target processing demand from schedulable service nodes; obtaining a first geographic position of the user and a second geographic position of each candidate service node, and calculating a target distance between the user and each candidate service node based on the first geographic position and the second geographic position; obtaining a network delay rate, node load data and node service quality data of each candidate service node, and calculating a comprehensive score of the candidate service node based on the target distance, the network delay rate, the node load data and the node service quality data; and determining a target service node from the plurality of candidate service nodes according to the comprehensive score, and scheduling the request to the target service node. The method can be applied to the fields of financial science and technology and medical health.

The invention relates to the technical field of cloud computing, and particularly provides a data cache prefetching method and device, a storage medium and a program product. According to the method, file access characteristics representing file access preferences of a user are obtained based on historical access data of the user, a target file meeting a cache prefetching strategy is determined based on the file access characteristics, and the target file is cached and prefetched. By dynamically analyzing the historical access data of the user, the system can adjust the cache content in real time, actively load the data possibly required by the user and ensure that the high-frequency access data is always available, and the mechanism not only improves the data access speed, but also remarkably reduces the influence caused by network delay.

The invention provides a node synchronous playing method and system for a distributed player, and relates to the field of video playing, and the method comprises the steps: carrying out the structural coding and node state clustering analysis of the state information of each node in a node cluster, obtaining the maximum one in a set of node performance deviation values through the calculation of the node performance deviation values, and obtaining the maximum one in the set of node performance deviation values; the corresponding node is used as a master node, and the rest are slave nodes. Then, acquiring basic information of the video through the main node, calculating playing frame information and sending a playing state; then, the target frame of the slave node is adjusted through the network delay between the slave node and the master node, and frame-level synchronization is maintained; thus, even in the face of local network jitter or transient communication interruption, it can be guaranteed that the nodes operate based on unified logic, visual coherence and expressive force in scenes such as light show and the like are improved, and accurate picture synchronization between large-scale node clusters is achieved.

The invention provides a remote internet-of-things control system and control method for home equipment, and the method comprises the steps: obtaining the operation data, environment data and user operation data of each piece of home equipment in a home system through a data obtaining module, and carrying out the edge calculation of the data; and online learning is carried out according to the processed data by adopting a deep reinforcement learning method through an instruction generation module, and an equipment control instruction set is constructed. The instruction verification module verifies the feasibility of each instruction in the equipment control instruction set through the preset virtual twin model based on the historical fault data and the user preference data corresponding to the home system, determines the initial control instruction set, and avoids the problem of equipment misoperation. The network state is monitored in real time through the network self-adaptive transmission module, a transmission path is dynamically adjusted according to factors such as network delay and packet loss rate, and it is ensured that a control instruction can be timely and accurately transmitted to home equipment. The instruction transmission delay or loss caused by network problems is avoided, and the user experience is improved.