Metaverse-based information transmission method, robot, and swarm robot system

Abstract

The application relates to the technical field of information transmission, in particular to an information transmission method, a robot and a group robot system based on a meta universe, and comprises the following steps: monitoring network bandwidth usage based on real-time data flow of a meta universe platform, identifying data packet types, classifying according to flow size and data type, and obtaining real-time data flow classification information. In the application, through classification, priority evaluation and dynamic bandwidth configuration of the data flow, more efficient resource allocation and utilization can be realized, different types of data flow are optimized in transmission, the bandwidth demand of key information is preferentially satisfied, the communication parameters are adjusted in combination with the current interaction data of the user, the network condition changes can be timely adapted, the response speed and stability of the overall network are improved, the future bandwidth demand is predicted, resource waste is effectively reduced, and the interaction experience of the user in the virtual environment is guaranteed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of information transmission, and in particular to an information transmission method based on a meta-universe, a robot and a group robot system. BACKGROUND

[0002] The technical field of information transmission 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, optical fiber communication and wired cable communication. The core goal of information transmission is to improve data transmission speed, ensure data transmission security, reduce error rate, and optimize bandwidth utilization of communication networks. In terms of technical implementation, this field is constantly exploring efficient data compression algorithms, encryption technologies, modulation and demodulation technologies, and error correction coding.

[0003] Among them, the information transmission method based on the meta-universe aims to support data exchange and interaction in a virtual environment. The method involves using information transmission protocols to securely and efficiently transmit information on a meta-universe platform. The meta-universe is an integrated and persistent virtual space where users can interact, transact and socialize through their digital avatars. The main use of the information transmission method based on the meta-universe is to provide seamless and real-time communication capabilities for users in virtual reality and augmented reality environments. The application of this technology is widespread, including online education, virtual meetings, online games and social media platforms, improving user experience and driving the development of the digital economy.

[0004] Traditional transmission methods lack the ability to monitor and dynamically adjust in real time, resulting in unreasonable allocation of network resources and inability to adjust in a timely manner according to actual needs. For example, during peak hours, due to the inability to effectively predict the increase in user activity, there may be a lack of bandwidth, resulting in communication delays and data loss. This makes users face unstable experience in important scenarios such as virtual meetings, affecting overall user satisfaction and participation. Unable to meet the rapidly changing needs of users and network environment. SUMMARY

[0005] The purpose of the present application is to solve the shortcomings in the prior art, and the information transmission method based on the meta-universe, the robot and the group robot system are proposed.

[0006] In order to achieve the above-mentioned purpose, the present application adopts the following technical scheme: the information transmission method based on the meta-universe comprises the following steps:

[0007] S1: Based on the real-time data stream of the meta-universe platform, monitor the network bandwidth usage and identify the data packet type, classify according to the traffic size and data type, and obtain real-time data stream classification information;

[0008] S2: Based on the real-time data stream classification information, the priority of the differentiated data stream is evaluated by using the basic priority corresponding to the data stream type, combining the size and real-time of the data stream, and the priority of the differentiated category data stream is sorted, and a priority sorting result is obtained;

[0009] S3: Based on the priority sorting result, dynamically configure network resources, adjust the bandwidth allocation proportion of the differentiated priority data stream according to the current network available bandwidth, and allocate the data stream with a priority lower than a preset threshold to a slow channel for transmission, and obtain dynamic bandwidth configuration information;

[0010] S4: Based on the dynamic bandwidth configuration information, according to the user's current interaction data, analyze the influence of user interaction data on network resources, adjust the communication parameters, match the current network status and user demand, and obtain communication parameter adjustment information;

[0011] S5: Based on the communication parameter adjustment information, by analyzing the number of active data and bandwidth usage data of the meta-universe platform in a period of time, combining 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 bandwidth pre-adjustment information.

[0012] As a further scheme of the application, the real-time data stream classification information includes the type, size and urgency level of the data stream, the priority sorting result includes the priority label 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, predetermined activation time and target user group.

[0013] As a further scheme of the application, based on the real-time data stream of the meta-universe platform, the network bandwidth usage is monitored, and the data packet type is identified, and the classification is performed according to the traffic size and data type, and the real-time data stream classification information is obtained.

[0014] S101: Based on the real-time data stream of the meta-universe platform, collect the data stream information in the meta-universe, record the transmission rate and timestamp of each data stream, identify the traffic size, and obtain traffic monitoring information;

[0015] S102: Based on the traffic monitoring information, classify the differentiated data stream according to the preset classification rule, and distinguish real-time voice, video and text data, and obtain data stream category information;

[0016] S103: Based on the data flow category information, refine the data packet type in each category, including subdividing voice data into real-time voice calls and voice messages, to obtain real-time data flow classification information.

[0017] As a further scheme of the application, based on the real-time data flow classification information, the priority of the differentiated data flow is evaluated by using the basic priority corresponding to the data flow type, in combination with the size and real-time performance of the data flow, to prioritize the differentiated category data flow, to obtain a priority sorting result, and the step is specifically as follows:

[0018] S201: Based on the real-time data flow classification information, according to a preset priority division rule, set a corresponding basic priority for each data flow according to the data flow type, to obtain basic priority information;

[0019] S202: Based on the basic priority information, in combination with the size and real-time performance of the data flow, adjust the priority of each data flow, to obtain an adjusted data flow priority;

[0020] S203: Based on the adjusted data flow priority, prioritize the differentiated data flow, to construct a data flow processing sequence, to obtain a priority sorting result.

[0021] As a further scheme of the application, the calculation formula of the adjusted data flow priority is:

[0022] ;

[0023] Wherein, represents the current size of the data flow, represents the real-time performance index of the data flow, represents the basic priority of the data flow, represents the system load, represents the data flow size change amplitude, , and is a weight coefficient, is the adjusted data flow priority.

[0024] As a further scheme of the application, based on the priority sorting result, dynamically configure network resources, adjust the bandwidth allocation proportion of the differentiated priority data flow according to the current network available bandwidth, and allocate data flow with a priority lower than a preset threshold to a slow channel for transmission, to obtain dynamic bandwidth configuration information, and the step is specifically as follows:

[0025] S301: Based on the priority ranking result, the amount of available bandwidth in the current network is evaluated, the bandwidth demand of the differentiated data flow is checked, the minimum and maximum bandwidth range required by each type of data flow is identified, and bandwidth demand evaluation information is obtained.

[0026] S302: Based on the bandwidth demand evaluation information, the priority of the data flow is combined to allocate the corresponding bandwidth proportion to each type of data flow, and bandwidth allocation strategy information is obtained.

[0027] S303: Based on the bandwidth allocation strategy table, adjust the resource allocation in the network, allocate the data flow with a priority lower than the preset threshold to the slow channel, and obtain dynamic bandwidth configuration information.

[0028] As a further scheme of the present application, based on the dynamic bandwidth configuration information, according to the user's current interactive data, the influence of user interactive data on network resources is analyzed, the communication parameters are adjusted to match the current network status and user demand, and the step of obtaining communication parameter adjustment information is:

[0029] S401: Based on the dynamic bandwidth configuration information, collect the user interactive data of the current meta-universe platform, including the number of online users and the type of activities, evaluate the real-time demand of interactive activities on network bandwidth, and obtain interactive influence analysis information;

[0030] S402: Based on the interactive influence analysis information, adjust the 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 record;

[0031] S403: Based on the parameter adjustment record, adjust the error recovery mechanism of communication to avoid data loss, match the current network status and user demand, and obtain communication parameter adjustment information.

[0032] As a further scheme of the present application, based on the communication parameter adjustment information, by analyzing the number of active users and bandwidth usage data of the meta-universe platform in a period of time, combining the activity information of the future period, predicting the bandwidth demand of the future target period, and adjusting the bandwidth supply according to the predicted bandwidth demand, the step of obtaining bandwidth pre-adjustment information is:

[0033] S501: Based on the communication parameter adjustment information, collect the user activity data and bandwidth usage data of the meta-universe platform in a period of time, record including activity peak period and data flow maximum demand point, and obtain historical activity and bandwidth demand record;

[0034] S502: Based on the historical activity and bandwidth demand records, combined with large-scale events and activity types in future time periods, analyze future activity plans and expected user participation, predict bandwidth demand in the target time period, and obtain future bandwidth demand prediction information;

[0035] S503: Based on the future bandwidth demand prediction information, adjust the bandwidth supply settings of the network, provide matching bandwidth for the predicted high demand period, optimize user experience, and obtain bandwidth pre-adjustment information.

[0036] The meta-universe-based information transmission robot is used to execute the above-mentioned meta-universe-based information transmission method, and the robot comprises:

[0037] The data flow classification module monitors the network bandwidth usage based on the real-time data flow of the meta-universe platform, and identifies the data packet type, classifies according to the traffic size and data type, and obtains real-time data flow classification information;

[0038] The priority evaluation module evaluates the priority of the differentiated data flow based on the real-time data flow classification information, and prioritizes the differentiated category data flow, and obtains a priority sorting result;

[0039] The bandwidth adjustment module adjusts the bandwidth allocation ratio of the differentiated priority data flow based on the priority sorting result, and allocates the data flow with a priority lower than a preset threshold to a slow channel for transmission, analyzes the influence of user interaction data on network resources, adjusts communication parameters, matches the current network status and user demand, and obtains communication parameter adjustment information;

[0040] The bandwidth demand prediction module predicts the bandwidth demand of the future target time period by analyzing the number of active data and bandwidth usage data of the meta-universe platform within a period of time, combined with activity information in future time periods, adjusts the bandwidth supply according to the predicted bandwidth demand, matches the bandwidth usage in future time periods, and obtains bandwidth pre-adjustment information.

[0041] The meta-universe-based information transmission group robot system comprises a memory and a processor, the memory stores a computer program, and the processor executes the computer program to realize the steps of the above-mentioned meta-universe-based information transmission method.

[0042] Compared with the prior art, the advantages and positive effects of the present application are:

[0043] In the present application, through the classification, priority evaluation and bandwidth dynamic configuration of the data flow, more efficient resource allocation and utilization can be realized, so that different types of data flow are optimized in transmission, and the bandwidth demand of key information is ensured to be satisfied in priority, and the adjustment of communication parameters combined with the current interactive data of the user can adapt to the changes of the network state in time, improve the response speed and stability of the whole network, predict the future bandwidth demand, effectively reduce the resource waste, protect the interactive experience of the user in the virtual environment, optimize the speed, safety and reliability of information transmission, and provide a more solid foundation for virtual reality and augmented reality application. BRIEF DESCRIPTION OF DRAWINGS

[0044] Figure 1 It is a method flowchart of the present application.

[0045] Figure 2 It is a S1 step refinement flowchart of the present application.

[0046] Figure 3 It is a S2 step refinement flowchart of the present application.

[0047] Figure 4 It is a S3 step refinement flowchart of the present application.

[0048] Figure 5 It is a S4 step refinement flowchart of the present application.

[0049] Figure 6 It is a S5 step refinement flowchart of the present application.

[0050] Figure 7 It is a module schematic diagram of the robot of the present application. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical scheme and advantages of the present application more clear, the present application is further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application, and are not used to limit the present application.

[0052] In the description of the present application, it should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only used to facilitate the description of the present application and simplify the description, and do not indicate or imply that the indicated robot or element must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application. In addition, in the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise specifically limited.

[0053] Referring to Figure 1 The application provides a technical solution: a meta-universe-based information transmission method, including the following steps:

[0054] S1: Based on the real-time data flow of the meta-universe platform, monitor the network bandwidth usage by monitoring the flow and type of data flow in the meta-universe, identify the type of data packet, classify according to the flow size and data type, distinguish real-time voice, video and text data, and obtain real-time data flow classification information;

[0055] S2: Based on the real-time data flow classification information, evaluate the priority of the differentiated data flow by using the basic priority corresponding to the data flow type, combining the size and real-time of the data flow, and sorting the priority of the differentiated category data flow, and obtaining the priority sorting result;

[0056] S3: Based on the priority sorting result, dynamically configure the network resources, adjust the bandwidth allocation proportion of the differentiated priority data flow according to the current network available bandwidth, match the bandwidth demand of the differentiated data flow, and allocate the data flow with priority lower than the preset threshold to the slow channel for transmission, and obtain the dynamic bandwidth configuration information;

[0057] S4: Based on the dynamic bandwidth configuration information, according to the user's current interaction data, including the number of participants, activity type and interaction activity, analyze the influence of user interaction data on network resources, adjust the communication parameters, including adjusting the delay, data compression level and error recovery strategy, match the current network status and user demand, and obtain the communication parameter adjustment information;

[0058] S5: Based on the communication parameter adjustment information, by analyzing the number of active data and bandwidth usage data of the meta-universe platform in a period of time, combining 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, matching the bandwidth usage of the future period, and obtaining the bandwidth pre-adjustment information.

[0059] The real-time data flow classification information includes the type, size and urgency level of the data flow, the priority sorting result includes the priority label and sorting sequence of the data flow, the dynamic bandwidth configuration information includes the bandwidth allocation amount and the predetermined transmission time window of the data flow, 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.

[0060] Referring to Figure 2, based on the real-time data flow of the metaverse platform, by monitoring the flow and type of data flow in the metaverse, monitoring the network bandwidth usage, and identifying the type of data packet, classifying according to the flow size and data type, distinguishing real-time voice, video and text data, obtaining the steps of real-time data flow classification information are:

[0061] S101: 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;

[0062] Based on the real-time data flow of the metaverse platform, collect data flow information in the metaverse, through the data capture unit deployed in the distributed server, real-time monitoring and capture of data flow generated by each node in the metaverse, data flow is directly transmitted 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 flow according to the preset parameters, uses time synchronization protocol to ensure the accuracy of the timestamp of each data flow, the recorded information is stored in the designated data structure of the server, to reduce the delay in data processing, at the same time, the server analyzes the trend of data flow change in real time, and classifies the data flow, in the process of recording, the server updates the statistical information and classification results related to the data flow to the database of the monitoring platform in real time, to obtain the flow monitoring information.

[0063] S102: Based on the flow monitoring information, classify the differentiated data flow according to the preset classification rules, distinguish real-time voice, video and text data, and obtain data flow category information;

[0064] Based on the flow monitoring information, classify the differentiated data flow according to the preset classification rules, use classification algorithm, the server first evaluates the type of transmission content according to the flow monitoring information of the data flow, accurately distinguishes real-time voice, video and text data in the data flow by analyzing the header information and load characteristics of the data packet, in this process, the server uses multi-level data classification technology to ensure the fast and accurate identification of data flow, the server performs labeling processing on each identified data flow for subsequent data processing and access, each type of data flow is assigned to the corresponding processing queue, and the data flow category information is obtained.

[0065] S103: Based on the data flow category information, refine the data packet type in each category, including subdividing voice data into real-time voice call and voice message, and obtaining real-time data flow classification information.

[0066] Based on the data stream category information, the server refines the data packet types in each category and processes each type of data stream according to the data stream category information, including subdividing voice data into real-time voice calls and voice messages. This classification operation uses specific identifiers and communication protocol types in the data stream to identify real-time calls and non-real-time voice messages. The server distinguishes real-time calls from non-real-time voice messages based on the protocol and header information of the data packet. The processing module for each type of data stream is adjusted accordingly to meet the processing needs of different data streams. Real-time voice call data packets are processed preferentially to reduce call delay, while voice messages are scheduled according to a caching strategy to ensure efficient allocation and use of system resources. Real-time data stream classification information is obtained.

[0067] Referring to Figure 3 Based on the real-time data stream classification information, the server evaluates the priority of differentiated data streams by using the corresponding basic priority of the data stream type, combining the size and real-time nature of the data stream, and prioritizing the differentiated category data streams. The steps to obtain the priority ranking result are as follows:

[0068] S201: Based on the real-time data stream classification information, set the corresponding basic priority for each type of data stream according to the preset priority division rule based on the data stream type, and obtain the basic priority information;

[0069] Based on the real-time data stream classification information, the server first receives the classified data stream information. For each type of data stream, such as real-time voice, video, and text data, set the initial priority according to its type characteristics. Data streams with higher real-time nature, such as real-time voice calls, are assigned higher basic priorities, while non-real-time text data obtains lower priorities. The priority setting is based on a preset rule, which is formulated according to the actual application scenario and business needs of the data stream. The priority setting involves detailed setting and adjustment of parameters. The server records and stores the priority information of each type of data stream in the database. Each time a data stream is accessed, the priority setting program is triggered to ensure that new data streams can be quickly identified and assigned appropriate basic priorities. The basic priority information is obtained.

[0070] S202: Based on the basic priority information, adjust the priority of each type of data stream in combination with the size and real-time nature of the data stream, and obtain the adjusted data stream priority;

[0071] The calculation formula of the adjusted data stream priority is:

[0072] ;

[0073] Wherein, represents the current size of the data stream, represents the real-time nature index of the data stream, Base priority of data flow, System load, Data flow size variation, , And is the weight coefficient, is the adjusted data flow priority.

[0074] Formula:

[0075] ;

[0076] Parameter details and acquisition method:

[0077] Data flow size, which is obtained in real time through network monitoring system, records the total size of each data packet.

[0078] Real-time indicator of data flow, usually measured by delay time, real-time network delay data is obtained from network management system.

[0079] Base priority of data flow, according to the type of data flow (such as real-time action, real-time voice) preset fixed value.

[0080] System load, expressed in percentage, current system resource usage can be read from system monitoring tools.

[0081] Data flow size variation, which can be set by the standard deviation of data flow size.

[0082] , , 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, 0.2, reflecting the relative importance of the corresponding parameters.

[0083] Calculation example:

[0084] Set the following specific data:

[0085] Data flow size MB, real-time indicator ms, base priority , system load , data variation , weight coefficient set to , , .

[0086] Computing process:

[0087]

[0088] Computing result , represents the adjusted priority value, reflecting the comprehensive priority value considering the size of the data stream, real-time, basic priority and system load. This value will be used to determine the processing priority of the data stream in the network resource.

[0089] S203: Based on the adjusted data stream priority, the priority of the differentiated data stream is sorted, the data stream processing sequence is constructed, and the priority sorting result is obtained.

[0090] Based on the adjusted data stream priority, the priority of the differentiated data stream is sorted, and each data stream is sorted according to the adjusted priority. The implementation process includes the use of data stream sorting algorithm, and the data stream is allocated to different levels in the processing queue according to the priority information of the data stream. High-priority data streams are processed first to reduce response time and improve processing efficiency. The sorting process is updated in real time to ensure that each data stream can be reasonably processed at its corresponding priority. The server records and updates the sorting result to the database of the data stream processing sequence, providing reference for subsequent data access and management, and obtains the priority sorting result.

[0091] Please refer to Figure 4 , based on the priority sorting result, dynamically configure the network resource, adjust the bandwidth allocation proportion of the differentiated priority data stream according to the current network available bandwidth, match the bandwidth demand of the differentiated data stream, and allocate the data stream with priority lower than the preset threshold to the slow channel for transmission, and obtain the dynamic bandwidth configuration information. The specific steps are as follows:

[0092] S301: Based on the priority sorting result, evaluate the available bandwidth in the current network, check the bandwidth demand of the differentiated data stream, identify the minimum and maximum bandwidth range required by each type of data stream, and obtain the bandwidth demand evaluation information;

[0093] Based on the priority sorting result, evaluate the available bandwidth in the current network. The server obtains the real-time network bandwidth usage through the network monitoring system, including the total bandwidth and the current bandwidth occupation of each type of data stream. Using this information, the server determines the bandwidth demand of each type of data stream at different time points, such as real-time voice, video and text data. This evaluation is based on historical data and real-time data stream statistical analysis to determine the minimum and maximum bandwidth range required by each type of data stream. During the evaluation process, the server updates the bandwidth demand in real time to ensure the timeliness and accuracy of bandwidth allocation. Record these evaluation results in the database to provide basis for dynamic bandwidth allocation, and obtain the bandwidth demand evaluation information.

[0094] S302: Based on the bandwidth demand evaluation information, the corresponding bandwidth proportion is allocated to each data flow in combination with the priority of the data flow, and bandwidth allocation strategy information is obtained.

[0095] Based on the bandwidth demand evaluation information, the corresponding bandwidth proportion is allocated to each data flow in combination with the priority of the data flow. The server dynamically adjusts the allocation of bandwidth by using a bandwidth management algorithm according to the priority and bandwidth demand evaluation information of each data flow. Considering the real-time performance, size and service type of the data flow, the bandwidth allocation rule is set, the data flow with high priority such as real-time voice call is allocated a larger bandwidth proportion, and the data flow with non-real-time performance such as text message is allocated a smaller bandwidth. This bandwidth allocation strategy guarantees the transmission efficiency and service quality of key data flow, optimizes the use of network resources, and obtains bandwidth allocation strategy information.

[0096] S303: Based on the bandwidth allocation strategy table, the resource allocation in the network is adjusted, and the data flow with a priority lower than a preset threshold is allocated to a slow channel, and dynamic bandwidth configuration information is obtained.

[0097] Based on the bandwidth allocation strategy information, the resource allocation in the network is adjusted. The server allocates the data flow with a priority lower than a preset threshold to a slow channel according to the bandwidth allocation strategy information and the current network condition. According to the priority and bandwidth demand of each data flow, the network resource is automatically configured, the non-key data flow is transferred to the low-priority channel of the network, the pressure of the main channel is reduced, the performance of the entire network is optimized, the response speed and reliability of the key application are improved, and dynamic bandwidth configuration information is obtained.

[0098] Please refer to Figure 5 Based on the dynamic bandwidth configuration information, the influence of user interaction data on network resources is analyzed according to the current user interaction data, including the number of participants, activity type and interaction activity, the communication parameters are adjusted, including adjusting the delay, data compression level and error recovery strategy, matching the current network condition and user demand, and the steps of obtaining the communication parameter adjustment information are as follows:

[0099] S401: Based on the dynamic bandwidth configuration information, the user interaction data of the current meta-universe platform is collected, including the number of online users and the type of activities, the real-time demand of the interaction activities on the network bandwidth is evaluated, and interaction influence analysis information is obtained.

[0100] Based on the dynamic bandwidth configuration information, the online status and participation activity type data of users are collected from each node of the metaverse platform on a regular basis, including real-time statistics of online users and analysis of bandwidth consumption of different types of activities, to evaluate the real-time demand of different interactive activities on network bandwidth. This analysis helps to identify high-traffic activities and peak usage periods to prioritize bandwidth resource allocation, resulting in interactive impact analysis information.

[0101] S402: Based on the interactive 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.

[0102] Based on the interactive impact analysis information, adjust network communication parameters to optimize user experience, and adjust parameters for network bottlenecks and user experience problems found, including optimizing routing selection, reducing data transmission delay, selecting different data compression algorithms, especially in high user density and high data interaction activities, and automatically testing the adjustment effect, monitoring the network performance after adjustment to ensure the improvement of data transmission efficiency. The adjustment process is recorded in the parameter management log, including the comparison data of network communication parameters, response time and compression efficiency before and after adjustment, resulting in parameter adjustment records.

[0103] S403: Based on the parameter adjustment records, adjust the error recovery mechanism of communication to avoid data loss, match the current network status and user demand, and obtain communication parameter adjustment information.

[0104] Based on the parameter adjustment records, adjust the error recovery mechanism of communication to avoid data loss, match the current network status and user demand, and the server optimizes the error recovery mechanism after analyzing the parameter adjustment records, especially in scenarios where data transmission is easily disturbed, enhances error detection and correction capabilities, and adjustments include updating packet loss retransmission strategies and strengthening signal integrity checks to ensure minimal data loss even under heavy network load. The effectiveness of the adjustment is verified through real-time monitoring and log recording systems to evaluate the efficiency and accuracy of the recovery mechanism, resulting in communication parameter adjustment information.

[0105] Please refer to Figure 6 , based on the communication parameter adjustment information, by analyzing the number of active users and bandwidth usage data of the metaverse platform over a period of time, combining with the activity information of future time periods, predicting the bandwidth demand of future target time periods, adjusting the bandwidth supply according to the predicted bandwidth demand, matching the bandwidth usage of future time periods, and obtaining the steps of bandwidth pre-adjustment information as follows:

[0106] S501: Collect user activity data and bandwidth usage data of the metaverse platform in the past period based on the communication parameter adjustment information, record the active period and the maximum data flow demand point, and obtain the historical activity and bandwidth demand record;

[0107] Based on the communication parameter adjustment information, the server extracts the records of user activity and bandwidth usage from the historical database, including the active period and the maximum data flow demand point. In the analysis process, the server aggregates and counts the data, identifies the time period of user activity and the bandwidth usage during this period, marks the period with the maximum bandwidth demand in history, and obtains the historical activity and bandwidth demand record.

[0108] S502: Based on the historical activity and bandwidth demand record, combined with the large-scale 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 the future bandwidth demand prediction information;

[0109] Based on the historical activity and bandwidth demand record, combined with the large-scale events and activity types in the future period, the server analyzes the future activity plan and expected user participation, compares the current historical data with the upcoming activities, evaluates the potential impact of each activity on user participation and bandwidth demand, considers the scale, expected number of participants and activity type of the activity, generates a comprehensive analysis of future bandwidth demand, records the bandwidth demand fluctuation in the future period, and based on this data, formulates the corresponding prediction strategy to ensure reasonable planning of future bandwidth demand prediction, and obtains the future bandwidth demand prediction information.

[0110] S503: Based on the future bandwidth demand prediction information, adjust the bandwidth supply settings of the network, provide matching bandwidth for the predicted high demand period, optimize user experience, and obtain the bandwidth pre-adjustment information.

[0111] Based on the future bandwidth demand prediction information, adjust the bandwidth supply settings of the network, the server adjusts the network resource configuration in advance according to the bandwidth demand prediction result to adapt to the predicted high demand period, dynamically allocates bandwidth resources to ensure that the network can provide sufficient bandwidth during the user demand peak period, and makes various data flows smoothly during the high demand period. The adjustment result is recorded in the network configuration system to provide a basis for subsequent bandwidth allocation, and the bandwidth pre-adjustment information is obtained.

[0112] Please refer to Figure 7 , the information transmission robot based on metaverse is used to execute the above-mentioned information transmission method based on metaverse, the robot includes:

[0113] The data flow classification module monitors network bandwidth usage based on real-time data flow of the metaverse platform, and identifies packet types, classifies data flow according to traffic size and data type, and obtains real-time data flow classification information.

[0114] The priority evaluation module evaluates the priority of the differentiated data flow based on the real-time data flow classification information, prioritizes the differentiated category data flow, and obtains a priority ranking result.

[0115] The bandwidth adjustment module adjusts the bandwidth allocation ratio of the differentiated priority data flow based on the priority ranking result, and allocates data flow with a priority lower than a preset threshold to a slow channel for transmission, analyzes the influence of user interaction data on network resources, adjusts communication parameters, matches the current network status and user demand, and obtains communication parameter adjustment information.

[0116] The bandwidth demand prediction module predicts the bandwidth demand of a future target period based on the communication parameter adjustment information by analyzing the number of active users and bandwidth usage data of the metaverse platform over a period of time, combining activity information of future periods, and adjusting bandwidth supply according to the predicted bandwidth demand to match bandwidth usage in future periods, and obtains bandwidth pre-adjustment information.

[0117] The metaverse-based information transmission group robot system includes a memory and a processor, the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-mentioned metaverse-based information transmission method.

[0118] The above is only a preferred embodiment of the present application, and is not intended to limit the present application in other forms. Any skilled person in the art can modify or change the above-mentioned disclosed technical content to equivalent embodiments applied to other fields, but any simple modification, equivalent change and modification made according to the technical essence of the present application within the technical solution content of the present application shall be within the protection scope of the present application.

Claims

1. An information transmission method based on the metaverse, characterized in that, Includes the following steps: Based on the metaverse platform, real-time data streams are monitored to assess network bandwidth utilization and identify packet types. Data streams are then categorized according to traffic size and data type to obtain real-time data stream classification information. Based on the real-time data stream classification information, by utilizing the basic priority corresponding to the data stream type, combined with the size and real-time nature of the data stream, the priority of the differentiated data streams is evaluated, and the differentiated category data streams are prioritized to obtain the priority ranking result. Based on the priority ranking result, network resources are dynamically configured. According to the current available network bandwidth, the bandwidth allocation ratio of differentiated priority data streams is adjusted, and data streams with priority below a preset threshold are allocated to the slow channel for transmission, thereby obtaining dynamic bandwidth configuration information. Based on the dynamic bandwidth configuration information, the impact of user interaction data on network resources is analyzed according to the current user interaction data, and communication parameters are adjusted to match the current network conditions and user needs to obtain communication parameter adjustment information. Based on the dynamic bandwidth configuration information, the steps of analyzing the impact of user interaction data on network resources according to the current user interaction data, adjusting communication parameters to match the current network conditions and user needs, and obtaining communication parameter adjustment information are as follows: Based on the dynamic bandwidth configuration information, collect the current user interaction data of the metaverse platform, including the number of online users and activity types, assess the real-time network bandwidth requirements of the interaction activities, and obtain interaction impact analysis information. Based on the interaction impact analysis information, network communication parameters are adjusted to optimize user experience, including reducing data transmission latency and improving data compression efficiency, matching high-density user interactions, and obtaining parameter adjustment records; Based on the parameter adjustment records, the error recovery mechanism of communication is adjusted to avoid data loss, and communication parameter adjustment information is obtained by matching the current network conditions and user needs. Based on the communication parameter adjustment information, by analyzing the user activity data and bandwidth usage data of the Metaverse platform over a period of time, and combining it with the activity information of future time periods, the bandwidth demand for future target time periods is predicted. Based on the predicted bandwidth demand, the bandwidth supply is adjusted to obtain bandwidth pre-adjustment information. The real-time data stream classification information includes the data stream type, data stream size, and urgency level; the priority ranking result includes the priority marker and ranking 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, latency 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.

2. The information transmission method based on the metaverse according to claim 1, characterized in that, Based on the Metaverse platform, the real-time data stream monitoring network bandwidth utilization and packet type identification, along with classification based on traffic size and data type, yields real-time data stream classification information. The specific steps are as follows: Based on the real-time data stream of the metaverse platform, data stream information in the metaverse is collected, the transmission rate and timestamp of each data stream are recorded, the traffic size is identified, and traffic monitoring information is obtained. Based on the traffic monitoring information, the differentiated data streams are classified according to the preset classification rules to distinguish real-time voice, video and text data, and to obtain data stream category information. Based on the data stream 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 stream category information.

3. The information transmission method based on the metaverse according to claim 1, characterized in that, Based on the real-time data stream classification information, the steps for evaluating the priority of differentiated data streams by utilizing the basic priority corresponding to the data stream type, combined with the size and real-time nature of the data streams, and prioritizing the differentiated category data streams to obtain the priority ranking results are as follows: Based on the real-time data stream classification information, according to the preset priority division rules, a corresponding basic priority is set for each type of data stream according to the data stream type, and basic priority information is obtained. Based on the aforementioned basic priority information, and considering the size and real-time nature of the data stream, the priority of each data stream is adjusted to obtain the adjusted data stream priority. Based on the adjusted data stream priority, the differentiated data streams are prioritized, a data stream processing sequence is constructed, and the priority ranking result is obtained.

4. The information transmission method based on the metaverse according to claim 3, characterized in that, The formula for calculating the adjusted data stream priority is as follows: ； in, Represents the current size of the data stream. Metrics representing the real-time performance of data streams Represents the basic priority of data flow. Represents system load. Represents the magnitude of change in the size of the data stream. , and These are the weighting coefficients. This is the adjusted data stream priority.

5. The information transmission method based on the metaverse according to claim 1, characterized in that, Based on the priority ranking result, the network resources are dynamically configured. The bandwidth allocation ratio of differentiated priority data streams is adjusted according to the current available network bandwidth, and data streams with priorities below a preset threshold are allocated to the slow channel for transmission. The specific steps for obtaining dynamic bandwidth configuration information are as follows: Based on the priority ranking results, the available bandwidth in the current network is assessed, the bandwidth requirements of differentiated data streams are checked, the minimum and maximum bandwidth ranges required for each type of data stream are identified, and bandwidth requirement assessment information is obtained. Based on the bandwidth demand assessment information and the priority of the data streams, a corresponding bandwidth ratio is allocated to each data stream to obtain bandwidth allocation strategy information. Based on the bandwidth allocation policy table, the resource allocation in the network is adjusted, and data streams with priority lower than the preset threshold are allocated to slow channels to obtain dynamic bandwidth configuration information.

6. The information transmission method based on the metaverse according to claim 1, characterized in that, Based on the communication parameter adjustment information, the specific steps for obtaining bandwidth pre-adjustment information are as follows: By analyzing the user activity data and bandwidth usage data of the Metaverse platform over a period of time, and combining this with activity information for future periods, the bandwidth demand for future target periods is predicted. Based on the predicted bandwidth demand, the bandwidth supply is adjusted. Based on the communication parameter adjustment information, collect user activity data and bandwidth usage data of the Metaverse platform over a period of time, record peak activity periods and the point of maximum data flow demand, and obtain historical activity and bandwidth demand records; Based on the historical activity and bandwidth demand records, combined with the types of major events and activities in the future period, we analyze future activity plans and expected user participation, predict bandwidth demand in the target period, and obtain future bandwidth demand prediction information. Based on the predicted future bandwidth demand, the network bandwidth supply settings are adjusted to provide matching bandwidth for the expected high-demand periods, thereby optimizing the user experience and obtaining bandwidth pre-adjustment information.

7. An information transmission robot based on the metaverse, characterized in that, The metaverse-based information transmission robot is used to execute the metaverse-based information transmission method according to any one of claims 1-6, the robot comprising: The data stream classification module monitors network bandwidth utilization and identifies data packet types based on the real-time data stream of the Metaverse platform. It classifies the data streams according to their size and type to obtain real-time data stream classification information. The priority evaluation module evaluates the priority of differentiated data streams based on the real-time data stream classification information, sorts the differentiated category data streams by priority, and obtains the priority ranking result. Based on the priority ranking results, the bandwidth adjustment module adjusts the bandwidth allocation ratio of differentiated priority data streams and allocates data streams with priorities lower than a preset threshold to the slow channel for transmission. It analyzes the impact of user interaction data on network resources, adjusts communication parameters, matches the current network conditions and user needs, and obtains communication parameter adjustment information. The bandwidth demand prediction module adjusts the bandwidth supply based on the communication parameter adjustment information. By analyzing the user activity data and bandwidth usage data of the Metaverse platform over a period of time, and combining it with the activity information of future time periods, it predicts the bandwidth demand for future target time periods. Based on the predicted bandwidth demand, it adjusts the bandwidth supply to match the bandwidth usage of future time periods, thus obtaining bandwidth pre-adjustment information.

8. A metaverse-based information transmission swarm robot system, comprising a memory and a processor, characterized in that, The memory stores a computer program, and when the processor executes the computer program, it implements the steps of the information transmission method based on the metaverse as described in any one of claims 1 to 6.

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