Metacosmic-based information transmission method, robot and group robot system

Abstract

The invention relates to the technical field of information transmission, in particular to a meta-universe-based information transmission method, robot and group robot system.The meta-universe-based information transmission method comprises the following steps that a real-time data flow is based on a meta-universe platform, the network bandwidth utilization rate is monitored, the data packet type is recognized, classification is conducted according to the flow size and the data type, and the real-time data flow is obtained; and real-time data stream classification information is obtained. According to the method and the device, more efficient resource allocation and utilization can be realized through classification, priority evaluation and bandwidth dynamic configuration of the data streams, so that different types of data streams are optimized in transmission, the bandwidth requirement of key information is ensured to be preferentially met, communication parameters are adjusted in combination with the current interactive data of a user, and the user experience is improved. The method can adapt to the change of the network condition in time, improves the response speed and stability of the whole network, effectively reduces the resource waste through the prediction of the future bandwidth demand, and guarantees the interaction experience of the user in the virtual environment.

Description

Technical Field

[0001] The present invention relates to the field of information transmission technology, and in particular to a metaverse-based information transmission method, a robot, and a group robot system. Background Art

[0002] The field of information transmission technology covers the methods of sending and receiving data between systems through different communication protocols and transmission media. The field of information transmission includes wireless communication, fiber optic communication, and wired cable communication. The core goals of information transmission are to increase data transmission speed, ensure data transmission security, reduce error rates, and optimize bandwidth utilization of communication networks. In terms of technical implementation, this field continues to explore efficient data compression algorithms, encryption technology, modulation and demodulation technology, and error correction coding.

[0003] Among them, the metaverse-based information transmission method is designed to support data exchange and interaction in a virtual environment. The method involves the use of an information transmission protocol to securely and efficiently transmit information on a metaverse platform. The metaverse is an integrated, persistent virtual space in which users can interact, trade, and socialize through their digital avatars. The main purpose of the metaverse-based information transmission method is to provide seamless, real-time communication capabilities for users in virtual reality and augmented reality environments. The technology has a wide range of applications, including online education, virtual meetings, online games, and social media platforms, which improves user experience and promotes the development of the digital economy.

[0004] Traditional transmission methods lack the ability to monitor and adjust in real time, resulting in irrational allocation of network resources and the inability to adjust in time according to actual needs. For example, during peak hours, insufficient bandwidth may occur due to the failure to effectively predict the increase in user activities, resulting in communication delays and data loss. This makes users face unstable experiences in important scenarios such as virtual meetings, affecting overall user satisfaction and participation. It is unable to meet the rapidly changing user needs and network environment. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings existing in the prior art and to propose an information transmission method, robot and group robot system based on the metaverse.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical solution: a method for information transmission based on the metaverse, comprising the following steps: S1: Based on the real-time data flow of the Metaverse platform, monitor the network bandwidth usage, identify the data packet type, classify it according to the traffic size and data type, and obtain real-time data flow classification information; S2: Based on the real-time data flow classification information, by using the basic priority corresponding to the data flow type, combined with the size and real-time performance of the data flow, evaluating the priority of the differentiated data flow, and prioritizing the differentiated category data flow to obtain a priority sorting result; S3: Based on the priority sorting result, dynamically configure network resources, adjust the bandwidth allocation ratio of differentiated priority data flows according to the current available network bandwidth, and allocate data flows with priorities lower than a preset threshold to a slow channel for transmission, thereby obtaining dynamic bandwidth configuration information; S4: Based on the dynamic bandwidth configuration information, according to the user's current interaction data, analyze the impact of the user interaction data on network resources, adjust the communication parameters to match the current network status and user needs, and obtain communication parameter adjustment information; S5: Based on the communication parameter adjustment information, by analyzing the active data of the number of people and the bandwidth usage data of the Metaverse platform over a period of time, combined with the activity information of the future time period, predict the bandwidth demand of the future target time period, adjust the bandwidth supply according to the predicted bandwidth demand, and obtain the bandwidth pre-adjustment information.

[0007] As a further solution of the present invention, the real-time data stream classification information includes the type of data stream, the size of the data stream and the urgency level, the priority sorting result includes the priority tag and sorting sequence of the data stream, the dynamic bandwidth configuration information includes the bandwidth allocation amount and the predetermined transmission time window of the data stream, the communication parameter adjustment information includes the adjusted data compression ratio, delay time and error recovery strategy, and the bandwidth pre-adjustment information includes the pre-adjusted bandwidth amount, the predetermined activation time and the target user group.

[0008] As a further solution of the present invention, based on the real-time data flow of the Metaverse platform, the network bandwidth usage is monitored, and the data packet type is identified, and classified according to the flow size and data type. The steps of obtaining the real-time data flow classification information are specifically as follows: S101: Based on the real-time data stream of the Metaverse platform, collect data stream information in the Metaverse, record the transmission rate and timestamp of each data stream, identify the flow size, and obtain flow monitoring information; S102: Based on the traffic monitoring information, the differentiated data streams are classified according to preset classification rules to distinguish real-time voice, video and text data, and obtain data stream category information; S103: Based on the data flow category information, the data packet type in each category is refined, including subdividing voice data into real-time voice calls and voice messages, to obtain real-time data flow classification information.

[0009] As a further solution of the present invention, based on the real-time data stream classification information, by using the basic priority corresponding to the data stream type, combined with the size and real-time performance of the data stream, the priority of the differentiated data stream is evaluated, and the differentiated category data stream is prioritized. The steps of obtaining the priority ranking result are specifically as follows: S201: Based on the real-time data flow classification information, according to the preset priority classification rule, according to the data flow type, a corresponding basic priority is set for each type of data flow to obtain basic priority information; S202: Based on the basic priority information and in combination with the size and real-time performance of the data flow, the priority of each data flow is adjusted to obtain an adjusted data flow priority; S203: Based on the adjusted data stream priorities, prioritize the differentiated data streams, construct a data stream processing sequence, and obtain a priority ranking result.

[0010] As a further solution of the present invention, the calculation formula of the adjusted data stream priority is: ; in, Represents the current size of the data stream, Represents the real-time indicators of data flow, Represents the basic priority of the data stream. Represents the system load, Represents the magnitude of the data flow change. , and is the weight coefficient, The adjusted data flow priority.

[0011] As a further solution of the present invention, based on the priority sorting result, the network resources are dynamically configured, the bandwidth allocation ratio of the differentiated priority data streams is adjusted according to the current network available bandwidth, and the data streams with a priority lower than the preset threshold are allocated to the slow channel for transmission. The steps of obtaining the dynamic bandwidth configuration information are specifically as follows: S301: Based on the priority sorting result, evaluate the available bandwidth in the current network, check the bandwidth requirements of differentiated data flows, identify the minimum and maximum bandwidth ranges required for each type of data flow, and obtain bandwidth requirement evaluation information; S302: Based on the bandwidth demand evaluation information and in combination with the priority of the data flow, a corresponding bandwidth ratio is allocated to each data flow to obtain bandwidth allocation strategy information.

[0012] S303: Based on the bandwidth allocation strategy table, adjust resource allocation in the network, allocate data flows with priorities lower than a preset threshold to a slow channel, and obtain dynamic bandwidth configuration information.

[0013] As a further solution of the present invention, based on the dynamic bandwidth configuration information, according to the user's current interaction data, the impact of the user interaction data on the network resources is analyzed, and the communication parameters are adjusted to match the current network status and user needs. The steps of obtaining the communication parameter adjustment information are specifically as follows: S401: Based on the dynamic bandwidth configuration information, collect user interaction data of the current Metaverse platform, including the number of online users and activity types, evaluate the real-time demand of the interactive activities for network bandwidth, and obtain interaction impact analysis information; S402: Based on the interaction impact analysis information, adjust network communication parameters to optimize user experience, including reducing data transmission delay and improving data compression efficiency, matching high-density user interaction, and obtaining parameter adjustment records; S403: Based on the parameter adjustment record, adjust the error recovery mechanism of the communication to avoid data loss, match the current network status and user needs, and obtain communication parameter adjustment information.

[0014] As a further solution of the present invention, based on the communication parameter adjustment information, by analyzing the active data of the number of people and the bandwidth usage data of the Metaverse platform over a period of time, combined with the activity information of the future time period, predicting the bandwidth demand of the future target time period, adjusting the bandwidth supply according to the predicted bandwidth demand, and obtaining the bandwidth pre-adjustment information in the following steps: S501: Based on the communication parameter adjustment information, collect user activity data and bandwidth usage data of the Metaverse platform over a period of time, including the peak activity period and the maximum demand point of the data flow, to obtain historical activity and bandwidth demand records; S502: Based on the historical activity and bandwidth demand records, combined with large events and activity types in the future period, analyze future activity plans and expected user participation, predict bandwidth demand in the target period, and obtain future bandwidth demand prediction information; S503: Based on the future bandwidth demand prediction information, adjust the bandwidth supply setting of the network to provide matching bandwidth for the predicted high-demand period, optimize user experience, and obtain bandwidth pre-adjustment information.

[0015] An information transmission robot based on the metaverse, the information transmission robot based on the metaverse is used to execute the above-mentioned information transmission method based on the metaverse, and the robot includes: The data flow classification module monitors the network bandwidth usage based on the real-time data flow of the Metaverse platform, identifies the data packet type, and classifies it according to the flow size and data type to obtain real-time data flow classification information; The priority evaluation module evaluates the priority of the differentiated data stream based on the real-time data stream classification information, prioritizes the differentiated category data streams, and obtains a priority ranking result; The bandwidth adjustment module adjusts the bandwidth allocation ratio of the differentiated priority data streams based on the priority sorting result, and allocates the data streams with a priority lower than the preset threshold to the slow channel for transmission, analyzes the impact of user interaction data on network resources, adjusts communication parameters, matches the current network status and user needs, and obtains communication parameter adjustment information; The bandwidth demand prediction module is based on the communication parameter adjustment information. By analyzing the active data of the number of people and the bandwidth usage data of the Metaverse platform over a period of time, combined with the activity information of the future time period, it predicts the bandwidth demand of the future target time period, adjusts the bandwidth supply according to the predicted bandwidth demand, matches the bandwidth usage of the future time period, and obtains the bandwidth pre-adjustment information.

[0016] The information transmission swarm robot system based on the metaverse includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned information transmission method based on the metaverse when executing the computer program.

[0017] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, by classifying data streams, evaluating priorities and dynamically configuring bandwidth, more efficient resource allocation and utilization can be achieved, so that different types of data streams are optimized during transmission, ensuring that the bandwidth requirements of key information are met first, and adjusting communication parameters in combination with the user's current interactive data can timely adapt to changes in network conditions, thereby improving the response speed and stability of the overall network. By predicting future bandwidth requirements, resource waste is effectively reduced, the user's interactive experience in a virtual environment is guaranteed, the speed, security and reliability of information transmission are optimized, and a more solid foundation is provided for virtual reality and augmented reality applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a schematic diagram of the method flow of the present invention; Figure 2 A detailed flow chart of step S1 of the present invention; Figure 3 A detailed flow chart of step S2 of the present invention; Figure 4 A detailed flow chart of step S3 of the present invention; Figure 5 A detailed flow chart of step S4 of the present invention; Figure 6 A detailed flow chart of step S5 of the present invention; Figure 7It is a schematic diagram of the modules of the robot of the present invention. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0020] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the robot or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In addition, in the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0021] See also Figure 1 , the present invention provides a technical solution: a method for information transmission based on the metaverse, comprising the following steps: S1: Based on the real-time data flow of the Metaverse platform, by monitoring the traffic and type of data flow in the Metaverse, monitoring the network bandwidth usage, and identifying the data packet type, classifying according to the traffic size and data type, distinguishing real-time voice, video and text data, and obtaining real-time data flow classification information; S2: Based on the real-time data flow classification information, by using the basic priority corresponding to the data flow type, combined with the size and real-time performance of the data flow, the priority of the differentiated data flow is evaluated, and the differentiated category data flow is prioritized to obtain the priority ranking result; S3: Based on the priority sorting results, dynamically configure network resources, adjust the bandwidth allocation ratio of differentiated priority data flows according to the current available network bandwidth, match the bandwidth requirements of differentiated data flows, and allocate data flows with priorities lower than the preset threshold to the slow channel for transmission, thereby obtaining dynamic bandwidth configuration information; S4: Based on the dynamic bandwidth configuration information and according to the current user interaction data, including the number of participants, activity type, and interaction activity, analyze the impact of user interaction data on network resources, adjust communication parameters, including delay, data compression level, and error recovery strategy, to match the current network status and user needs, and obtain communication parameter adjustment information; S5: Based on the communication parameter adjustment information, by analyzing the active data of the number of people and the bandwidth usage data of the Metaverse platform over a period of time, combined with the activity information of the future time period, the bandwidth demand of the future target time period is predicted, and according to the predicted bandwidth demand, the bandwidth supply is adjusted to match the bandwidth usage of the future time period to obtain the bandwidth pre-adjustment information.

[0022] Real-time data flow classification information includes the type of data flow, data flow size and urgency level, priority sorting results include the priority tag and sorting sequence of the data flow, dynamic bandwidth configuration information includes the bandwidth allocation amount and the scheduled transmission time window of the data flow, communication parameter adjustment information includes the adjusted data compression ratio, delay time and error recovery strategy, bandwidth pre-adjustment information includes the pre-adjusted bandwidth amount, scheduled activation time and target user group.

[0023] See also Figure 2 Based on the real-time data flow of the Metaverse platform, by monitoring the traffic and type of data flow in the Metaverse, monitoring the network bandwidth usage, and identifying the data packet type, classifying according to the traffic size and data type, distinguishing real-time voice, video and text data, the specific steps for obtaining real-time data flow classification information are as follows: S101: Based on the real-time data stream of the Metaverse platform, collect data stream information in the Metaverse, record the transmission rate and timestamp of each data stream, identify the flow size, and obtain flow monitoring information; Based on the real-time data stream of the Metaverse platform, data stream information in the Metaverse is collected. Through the data capture unit deployed on the distributed server, the data stream generated by each node in the Metaverse is monitored and captured in real time. The data stream is transmitted directly to the distributed server by the Metaverse application. The data capture unit on the server records the specific transmission rate, transmission time and size of each data stream according to preset parameters. The time synchronization protocol is used to ensure that the timestamp of each data stream is accurate. The recorded information is stored in the specified data structure of the server to reduce delays in data processing. At the same time, the server analyzes the changing trend of data traffic in real time and performs preliminary classification processing on the data stream. During the recording process, the server updates the statistical information and classification results related to the data stream to the database of the monitoring platform in real time to obtain traffic monitoring information.

[0024] S102: Based on the traffic monitoring information, the differentiated data streams are classified according to preset classification rules, and real-time voice, video and text data are distinguished to obtain data stream category information; Based on the traffic monitoring information, differentiated data streams are classified according to the preset classification rules. Using the classification algorithm, the server first evaluates the type of transmission content based on the traffic monitoring information of the data stream, and accurately distinguishes the real-time voice, video and text data in the data stream by analyzing the header information and load characteristics of the data packet. In this process, the server adopts multi-level data classification technology to ensure the fast and accurate identification of data streams. The server labels each identified data stream for subsequent data processing and access. The data stream of each data type is assigned to the corresponding processing queue to obtain the data stream category information.

[0025] S103: Based on the data flow category information, the data packet type in each category is refined, including subdividing voice data into real-time voice calls and voice messages, to obtain real-time data flow classification information.

[0026] Based on the data flow category information, the data packet types in each category are refined. The server refines the processing of various data flows according to the data flow category information, including subdividing voice data into two categories: real-time voice calls and voice messages. This classification operation uses specific identifiers and communication protocol types in the data flow for identification. The server distinguishes between real-time calls and non-real-time voice messages based on the protocol and header information of the data packet. The processing module of each type of data flow is adjusted accordingly to meet the processing requirements of different data flows. Data packets of real-time voice calls are given priority to reduce call delays, while voice messages are scheduled according to the cache strategy to ensure the reasonable allocation and efficient use of system resources and obtain real-time data flow classification information.

[0027] See also Figure 3 Based on the real-time data flow classification information, by using the basic priority corresponding to the data flow type, combined with the size and real-time performance of the data flow, the priority of the differentiated data flow is evaluated, and the differentiated category data flow is prioritized. The specific steps for obtaining the priority sorting result are as follows: S201: Based on the real-time data flow classification information, according to the preset priority classification rules, according to the data flow type, a corresponding basic priority is set for each type of data flow to obtain basic priority information; Based on the real-time data flow classification information and in accordance with the preset priority classification rules, the server first receives the classified data flow information, and sets the initial priority for each type of data flow, such as real-time voice, video and text data, according to its type characteristics. Data flows with higher real-time characteristics, such as real-time voice calls, are given a higher basic priority, while non-real-time text data are given a lower priority. Priority setting is based on preset rules, which are formulated according to the actual application scenarios and business needs of the data flow. Priority setting involves detailed setting and adjustment of parameters. The server records and stores the priority information of each data flow in the database. Each access to a data flow triggers the priority setting program to ensure that new data flows can be quickly identified and given an appropriate basic priority to obtain basic priority information.

[0028] S202: Based on the basic priority information and in combination with the size and real-time performance of the data flow, the priority of each data flow is adjusted to obtain an adjusted data flow priority; The calculation formula for the adjusted data flow priority is: ; in, Represents the current size of the data stream, Represents the real-time indicators of data flow, Represents the basic priority of the data stream. Represents the system load, Represents the magnitude of the data flow change. , and is the weight coefficient, The adjusted data flow priority.

[0029] formula: ; Parameter details and how to obtain them: Indicates the size of the data flow, which is obtained in real time through the network monitoring system and records the total size of each data packet.

[0030] It is a real-time indicator of data flow, usually measured by delay time, and obtains real-time network delay data from the network management system.

[0031] Indicates the basic priority of a data stream, which is a fixed value preset according to the type of data stream (such as real-time action and real-time voice).

[0032] Represents the current system load, expressed as a percentage. The current system resource usage can be read from the system monitoring tool.

[0033] Represents the variation range of the data flow size, which can be set by the standard deviation of the data flow size.

[0034] , , It is the weight coefficient, which is set based on historical data and business needs. For example, it can be set to 0.5, 0.3, or 0.2, reflecting the relative importance of the corresponding parameter.

[0035] Calculation example: The following specific data are set: Data stream size MB, real-time indicator milliseconds, base priority , system load , data variation range , the weight coefficient is set to , , .

[0036] Calculation process:

[0037] Calculation results , represents the adjusted priority value, which reflects the comprehensive priority value after considering the size, real-time performance, basic priority and system load of the data flow. This value will be used to determine the processing priority of the data flow in the network resources.

[0038] S203: Based on the adjusted data stream priorities, prioritize the differentiated data streams, construct a data stream processing sequence, and obtain a priority ranking result.

[0039] Based on the adjusted data flow priority, differentiated data flows are prioritized and sorted according to the adjusted priority of each data flow. The implementation process includes the use of data flow sorting algorithm. According to the priority information of the data flow, the data flow is allocated to different levels in the processing queue. High-priority data flows are processed first to reduce response time and improve processing efficiency. The sorting process is updated in real time to ensure that each data flow can be reasonably processed at its corresponding priority. The server records and updates the sorting results to the database of the data flow processing sequence to provide a reference for subsequent data access and management, and obtain the priority sorting results.

[0040] See also Figure 4, based on the priority sorting results, dynamically configure network resources, adjust the bandwidth allocation ratio of differentiated priority data flows according to the current network available bandwidth, match the bandwidth requirements of differentiated data flows, and allocate data flows with priorities lower than the preset threshold to the slow channel for transmission. The steps for obtaining dynamic bandwidth configuration information are as follows: S301: Based on the priority sorting result, the available bandwidth in the current network is evaluated, the bandwidth requirements of the differentiated data flows are checked, the minimum and maximum bandwidth ranges required for each type of data flow are identified, and bandwidth requirement evaluation information is obtained; Based on the priority sorting results, the available bandwidth in the current network is evaluated. The server obtains real-time network bandwidth usage status through the network monitoring system, including the total bandwidth and the current bandwidth occupancy of various data streams. Using this information, the server determines the bandwidth requirements of each type of data stream at different time points for different categories of data streams, such as real-time voice, video and text data. This evaluation is based on statistical analysis of historical data and real-time data streams to determine the minimum and maximum bandwidth range required for each type of data stream. During the evaluation process, the server updates the changes in bandwidth requirements in real time to ensure the timeliness and accuracy of bandwidth allocation. These evaluation results are recorded in the database to provide a basis for dynamic bandwidth allocation and obtain bandwidth demand evaluation information.

[0041] S302: Based on the bandwidth demand evaluation information and in combination with the priority of the data flow, a corresponding bandwidth ratio is allocated to each data flow to obtain bandwidth allocation strategy information.

[0042] Based on the bandwidth demand assessment information and the priority of the data flow, a corresponding bandwidth ratio is allocated to each data flow. The server uses a bandwidth management algorithm to dynamically adjust the bandwidth allocation based on the priority of each data flow and the bandwidth demand assessment information. Taking into account the real-time nature, size and service type of the data flow, according to the set bandwidth allocation rules, high-priority data flows such as real-time voice calls are allocated a larger bandwidth ratio, while non-real-time data flows such as text messages are allocated a smaller bandwidth. This bandwidth allocation strategy ensures the transmission efficiency and service quality of key data flows, while optimizing the use of network resources to obtain bandwidth allocation strategy information.

[0043] S303: Based on the bandwidth allocation strategy table, adjust resource allocation in the network, allocate data flows with priorities lower than a preset threshold to the slow channel, and obtain dynamic bandwidth configuration information.

[0044] Based on the bandwidth allocation strategy information, the resource allocation in the network is adjusted. The server allocates data streams with a priority lower than the preset threshold to the slow channel according to the bandwidth allocation strategy information and the current network status. According to the priority and bandwidth requirements of each data stream, the network resources are automatically configured, and non-critical data streams are transferred to the low-priority channel of the network, reducing the pressure on the main channel, optimizing the performance of the entire network, improving the response speed and reliability of key applications, and obtaining dynamic bandwidth configuration information.

[0045] See also Figure 5 , based on the dynamic bandwidth configuration information, according to the current user interaction data, including the number of participants, activity type and interaction activity, analyze the impact of user interaction data on network resources, and adjust communication parameters, including delay, data compression level and error recovery strategy, to match the current network status and user needs. The specific steps for obtaining communication parameter adjustment information are as follows: S401: Based on the dynamic bandwidth configuration information, collect the user interaction data of the current Metaverse platform, including the number of online users and activity types, evaluate the real-time demand of the interactive activities for network bandwidth, and obtain the interaction impact analysis information; Based on dynamic bandwidth configuration information, users’ online status and the types of activities they participate in are regularly collected from various nodes of the Metaverse platform, including real-time statistics of the number of online users and analysis of bandwidth consumption of different types of activities, in order to evaluate the real-time demand for network bandwidth of different interactive activities. This analysis helps identify high-traffic activities and peak usage periods, so as to prioritize bandwidth resources and obtain interaction impact analysis information.

[0046] S402: Based on the interaction impact analysis information, adjust network communication parameters to optimize user experience, including reducing data transmission delay and improving data compression efficiency, matching high-density user interaction, and obtaining parameter adjustment records; Based on the interaction impact analysis information, adjust network communication parameters, optimize user experience, and adjust parameters for discovered network bottlenecks and user experience issues, including optimizing route selection, reducing data transmission delays, and selecting different data compression algorithms, especially in high user density and high data interaction activities. Automatically test the adjustment effect and monitor the adjusted network performance to ensure improved data transmission efficiency. The adjustment process is recorded in the parameter management log, which includes comparative data on network communication parameters, response time, and compression efficiency before and after the adjustment to obtain parameter adjustment records.

[0047] S403: Based on the parameter adjustment record, adjust the error recovery mechanism of the communication to avoid data loss, match the current network status and user needs, and obtain communication parameter adjustment information.

[0048] Based on the parameter adjustment records, the error recovery mechanism of communication is adjusted to avoid data loss and match the current network conditions and user needs. After analyzing the parameter adjustment records, the server optimizes the error recovery mechanism, especially in scenarios where data transmission is susceptible to interference, to enhance the error detection and correction capabilities. The adjustments include updating the packet loss retransmission strategy and strengthening the signal integrity check to ensure that data loss is minimized even when the network load is heavy. The adjusted effect is verified through real-time monitoring and logging systems to evaluate the efficiency and accuracy of the recovery mechanism and obtain communication parameter adjustment information.

[0049] See also Figure 6 Based on the communication parameter adjustment information, by analyzing the active data of the number of people and the bandwidth usage data of the Metaverse platform over a period of time, combined with the activity information of the future period, the bandwidth demand of the future target period is predicted, and according to the predicted bandwidth demand, the bandwidth supply is adjusted to match the bandwidth usage of the future period. The specific steps for obtaining the bandwidth pre-adjustment information are as follows: S501: Based on the communication parameter adjustment information, collect the user activity data and bandwidth usage data of the Metaverse platform over the past period of time, including the peak activity period and the maximum demand point of the data flow, and obtain the historical activity and bandwidth demand records; Based on the communication parameter adjustment information, the user activity data and bandwidth usage data of the Metaverse platform over the past period of time are collected. The server extracts records of user activity and bandwidth usage from the historical database, including peak activity periods and points with the greatest demand for data flows. During the analysis process, the server aggregates and counts the data, identifies the time periods when users are active and the amount of bandwidth used during this period, marks the time periods with the greatest historical bandwidth demand, and obtains historical activity and bandwidth demand records.

[0050] S502: Based on the historical activity and bandwidth demand records, combined with the major events and activity types in the future period, analyze the future activity plan and expected user participation, predict the bandwidth demand in the target period, and obtain future bandwidth demand prediction information; Based on historical activity and bandwidth demand records, combined with major events and activity types in the future period, the server analyzes future activity plans and expected user participation, compares current historical data with upcoming activities, and evaluates the potential impact of each activity on user participation and bandwidth demand. Considering the scale of the activity, the expected number of participants, and the type of activity, a comprehensive analysis of future bandwidth demand is generated, bandwidth demand fluctuations in the future period are recorded, and corresponding forecasting strategies are formulated based on this data to ensure reasonable planning of future bandwidth demand forecasts and obtain future bandwidth demand forecast information.

[0051] S503: Based on the future bandwidth demand prediction information, adjust the bandwidth supply setting of the network to provide matching bandwidth for the predicted high-demand period, optimize the user experience, and obtain bandwidth pre-adjustment information.

[0052] Based on the future bandwidth demand forecast information, the network's bandwidth supply settings are adjusted. The server adjusts the network resource configuration in advance according to the bandwidth demand forecast results to adapt to the expected high-demand periods. By dynamically allocating bandwidth resources, it is ensured that the network can provide sufficient bandwidth during peak user demand periods, so that various data streams can be transmitted smoothly during high-demand periods. The adjustment results are recorded in the network configuration system to provide a basis for subsequent bandwidth allocation and obtain bandwidth pre-adjustment information.

[0053] See also Figure 7 , an information transmission robot based on the metaverse, the information transmission robot based on the metaverse is used to execute the above-mentioned information transmission method based on the metaverse, and the robot includes: The data flow classification module monitors the network bandwidth usage based on the real-time data flow of the Metaverse platform, identifies the data packet type, and classifies it according to the flow size and data type to obtain real-time data flow classification information; The priority evaluation module evaluates the priority of the differentiated data stream based on the real-time data stream classification information, prioritizes the differentiated category data streams, and obtains the priority ranking result; The bandwidth adjustment module adjusts the bandwidth allocation ratio of differentiated priority data streams based on the priority sorting results, and allocates data streams with priorities lower than the preset threshold to slow channels for transmission. It analyzes the impact of user interaction data on network resources, adjusts communication parameters, matches the current network status and user needs, and obtains communication parameter adjustment information. The bandwidth demand prediction module is based on the communication parameter adjustment information. By analyzing the active data of the number of people and the bandwidth usage data of the Metaverse platform over a period of time, combined with the activity information of future time periods, it predicts the bandwidth demand of future target time periods, adjusts the bandwidth supply according to the predicted bandwidth demand, matches the bandwidth usage of future time periods, and obtains the bandwidth pre-adjustment information.

[0054] The information transmission swarm robot system based on the metaverse includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the steps of the above-mentioned information transmission method based on the metaverse are implemented.

[0055] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. The information transmission method based on the metaverse is characterized by: The following steps are involved: Based on the real-time data flow of the Metaverse platform, monitor the network bandwidth usage, identify the data packet type, classify it according to the traffic size and data type, and obtain real-time data flow classification information; Based on the real-time data stream classification information, by utilizing the basic priority corresponding to the data stream type and combining the size and real-time performance of the data stream, the priority of the differentiated data stream is evaluated, and the differentiated category data streams are prioritized to obtain a priority ranking result; Based on the priority sorting result, dynamically configure network resources, adjust the bandwidth allocation ratio of differentiated priority data streams according to the current available network bandwidth, and allocate data streams with priorities lower than a preset threshold to a slow channel for transmission, thereby obtaining dynamic bandwidth configuration information; Based on the dynamic bandwidth configuration information, according to the current user interaction data, the influence of the user interaction data on the network resources is analyzed, and the communication parameters are adjusted to match the current network status and user needs to obtain the communication parameter adjustment information; Based on the communication parameter adjustment information, by analyzing the active data of the number of people and the bandwidth usage data of the Metaverse platform over a period of time, combined with the activity information of the future time period, the bandwidth demand of the future target time period is predicted, and the bandwidth supply is adjusted according to the predicted bandwidth demand to obtain the bandwidth pre-adjustment information.

2. The information transmission method based on the metaverse according to claim 1 is characterized in that: The real-time data stream classification information includes the type of data stream, the size of data stream and the urgency level, the priority sorting result includes the priority tag and sorting sequence of the data stream, the dynamic bandwidth configuration information includes the bandwidth allocation amount and the scheduled transmission time window of the data stream, the communication parameter adjustment information includes the adjusted data compression ratio, delay time and error recovery strategy, and the bandwidth pre-adjustment information includes the pre-adjusted bandwidth amount, scheduled activation time and target user group.

3. The information transmission method based on the metaverse according to claim 1 is characterized in that: Based on the real-time data flow of the Metaverse platform, the network bandwidth usage is monitored, and the packet type is identified. The data packet is classified according to the traffic size and data type. The specific steps to obtain the real-time data flow classification information are as follows: Based on the real-time data flow of the Metaverse platform, collect data flow information in the Metaverse, record the transmission rate and timestamp of each data flow, identify the flow size, and obtain flow monitoring information; Based on the traffic monitoring information, the differentiated data streams are classified according to preset classification rules to distinguish real-time voice, video and text data to obtain data stream category information; Based on the data flow category information, the data packet type in each category is refined, including subdividing voice data into real-time voice calls and voice messages, to obtain real-time data flow classification information.

4. The information transmission method based on the metaverse according to claim 1, characterized in that: Based on the real-time data stream classification information, by using the basic priority corresponding to the data stream type, combined with the size and real-time performance of the data stream, the priority of the differentiated data stream is evaluated, and the differentiated category data stream is prioritized. The steps of obtaining the priority sorting result are specifically as follows: Based on the real-time data flow classification information, according to the preset priority classification rules, according to the data flow type, a corresponding basic priority is set for each type of data flow to obtain basic priority information; Based on the basic priority information, combined with the size and real-time performance of the data stream, the priority of each data stream is adjusted to obtain an adjusted data stream priority; Based on the adjusted data stream priorities, the differentiated data streams are prioritized, a data stream processing sequence is constructed, and a priority ranking result is obtained.

5. The information transmission method based on the metaverse according to claim 4 is characterized in that: The calculation formula of the adjusted data flow priority is: ； in, Represents the current size of the data stream, Represents the real-time indicators of data flow, Represents the basic priority of the data stream. Represents the system load, Represents the magnitude of the data flow change. , and is the weight coefficient, The adjusted data flow priority.

6. The information transmission method based on the metaverse according to claim 1, characterized in that: Based on the priority sorting result, the network resources are dynamically configured, the bandwidth allocation ratio of the differentiated priority data streams is adjusted according to the current network available bandwidth, and the data streams with a priority lower than the preset threshold are allocated to the slow channel for transmission. The steps of obtaining the dynamic bandwidth configuration information are specifically as follows: Based on the priority sorting result, the amount of available bandwidth in the current network is evaluated, the bandwidth requirements of the differentiated data streams are checked, the minimum and maximum bandwidth ranges required for each type of data stream are identified, and bandwidth requirement evaluation information is obtained; Based on the bandwidth demand evaluation information and in combination with the priority of the data flow, a corresponding bandwidth ratio is allocated to each data flow to obtain bandwidth allocation strategy information; Based on the bandwidth allocation strategy table, resource allocation in the network is adjusted, and data flows with priorities lower than a preset threshold are allocated to the slow channel, thereby obtaining dynamic bandwidth configuration information.

7. The information transmission method based on the metaverse according to claim 1 is characterized in that: Based on the dynamic bandwidth configuration information, according to the current user interaction data, the impact of the user interaction data on the network resources is analyzed, and the communication parameters are adjusted to match the current network status and user needs. The steps of obtaining the communication parameter adjustment information are specifically as follows: Based on the dynamic bandwidth configuration information, collect user interaction data of the current Metaverse platform, including the number of online users and activity types, evaluate the real-time demand of interactive activities for network bandwidth, and obtain interaction impact analysis information; Based on the interaction impact analysis information, adjust network communication parameters to optimize user experience, including reducing data transmission delay and improving data compression efficiency, matching high-density user interaction, and obtaining parameter adjustment records; Based on the parameter adjustment record, the error recovery mechanism of the communication is adjusted to avoid data loss, match the current network status and user needs, and obtain communication parameter adjustment information.

8. The information transmission method based on the metaverse according to claim 1, characterized in that: Based on the communication parameter adjustment information, by analyzing the active data of the number of people and the bandwidth usage data of the Metaverse platform over a period of time, combined with the activity information of the future period, predicting the bandwidth demand of the future target period, adjusting the bandwidth supply according to the predicted bandwidth demand, and obtaining the bandwidth pre-adjustment information in the following steps: Based on the communication parameter adjustment information, collect user activity data and bandwidth usage data of the Metaverse platform over the past period of time, including the peak activity period and the maximum demand point of the data flow, and obtain historical activity and bandwidth demand records; Based on the historical activity and bandwidth demand records, combined with large events and activity types in the future period, future activity plans and expected user participation are analyzed to predict bandwidth demand in the target period, thereby obtaining future bandwidth demand prediction information; Based on the future bandwidth demand prediction information, the bandwidth supply setting of the network is adjusted to provide matching bandwidth for the predicted high-demand period, optimize the user experience, and obtain bandwidth pre-adjustment information.

9. Metaverse-based information transmission robot, characterized in that: The information transmission robot based on the metaverse is used to execute the information transmission method based on the metaverse according to any one of claims 1 to 8, and the robot comprises: The data flow classification module monitors the network bandwidth usage based on the real-time data flow of the Metaverse platform, identifies the data packet type, and classifies it according to the flow size and data type to obtain real-time data flow classification information; The priority evaluation module evaluates the priority of the differentiated data stream based on the real-time data stream classification information, prioritizes the differentiated category data streams, and obtains a priority ranking result; The bandwidth adjustment module adjusts the bandwidth allocation ratio of the differentiated priority data streams based on the priority sorting result, and allocates the data streams with a priority lower than the preset threshold to the slow channel for transmission, analyzes the impact of user interaction data on network resources, adjusts communication parameters, matches the current network status and user needs, and obtains communication parameter adjustment information; The bandwidth demand prediction module is based on the communication parameter adjustment information. By analyzing the active data of the number of people and the bandwidth usage data of the Metaverse platform over a period of time, combined with the activity information of the future time period, it predicts the bandwidth demand of the future target time period, adjusts the bandwidth supply according to the predicted bandwidth demand, matches the bandwidth usage of the future time period, and obtains the bandwidth pre-adjustment information.

10. An information transmission swarm robot system based on the metaverse, comprising a memory and a processor, characterized in that: The memory stores a computer program, and when the processor executes the computer program, the steps of the metaverse-based information transmission method described in any one of claims 1 to 8 are implemented.

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