Intelligent management system and method applied to VR large-space virtual tourism platform

Abstract

The invention discloses an intelligent management system and method applied to a VR large-space virtual tourism platform, and relates to the technical field of intelligent management. The system comprises a data acquisition module, a fault quantitative grading module, a priority dynamic judgment module and a repair strategy matching module. The data acquisition module acquires multi-dimensional data and associates and stores the multi-dimensional data, the fault quantitative grading module realizes synchronous fault scientific grading and experience link importance judgment, the priority dynamic judgment module dynamically determines the repair priority in combination with resource conditions, and the repair strategy matching module adapts to differentiated repair opportunities and modes. According to the method, through a complete technical link, the defects that an existing repairing mode destroys immersion and experiences are split are overcome, collaborative experience continuity and efficient utilization of system resources are balanced, the bottleneck of multi-person collaborative VR virtual tourism experience upgrading is broken through, and the platform operation stability and the user satisfaction degree are improved.

Description

Technical Field

[0001] This invention relates to the field of intelligent management technology, specifically to an intelligent management system and method applied to a VR large-space virtual tourism platform. Background Technology

[0002] In the field of VR large-space virtual tourism, multi-person collaborative experiences have become a core application scenario. Their core value lies in achieving immersive collective experiences through spatiotemporal synchronization, such as watching virtual cultural performances together or collaboratively completing interactive tasks in historical scenes. However, in actual operation, due to factors such as fluctuations in device performance, network latency, and differences in user operations, "synchronization gaps" are prone to occur. These gaps manifest as some users falling behind due to device lag, asynchronous scene progress, and misaligned interactive actions, severely impacting the integrity of the collaborative experience.

[0003] The existing intelligent management systems of VR large-space virtual tourism platforms have obvious flaws in their methods for repairing synchronization gaps: they either adopt "immediate forced synchronization," waiting for those who fall behind by pausing all user experiences and resetting scene progress, directly destroying the immersion of most users; or they adopt "passive waiting for synchronization," without intervening in the gaps, resulting in a fragmented experience.

[0004] These solutions all rely on fixed rules to trigger repairs, failing to scientifically define and classify the severity of synchronization disruptions, nor considering key factors such as the importance of the current experience segment, system computing power, and remaining bandwidth resources. They lack a scientific basis for judging the optimal repair timing. This is similar to the drawbacks of traditional technologies that either handle anomalies immediately or delay them, either wasting experience resources or triggering the risk of experience disruptions. It's difficult to balance the need for continuous collaborative experiences with efficient use of system resources, becoming a key bottleneck restricting the upgrading of multi-user collaborative VR virtual tourism experiences. Summary of the Invention

[0005] The purpose of this invention is to provide an intelligent management system and method for VR large-space virtual tourism platforms to solve the problems mentioned in the background art.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: The intelligent management method applied to VR large-space virtual tourism platforms includes the following steps: S1. Real-time collection of multi-person collaborative experience data, experience stage attribute data, and system operation resource data; the multi-person collaborative experience data includes scene progress, interactive action synchronization status, device lag duration, and lagging duration; the experience stage attribute data includes type identifiers of core experience stages and non-core transition stages; the system operation resource data includes remaining computing power, available bandwidth, and energy storage data. S2. Based on multi-user collaborative experience data, the severity of synchronization gaps is quantified. Combining the ratio of the actual time spent falling behind to the preset maximum tolerance time and the ratio of the number of times the interaction action is misaligned to the preset maximum tolerance number, synchronization gaps are divided into minor gaps and severe gaps. When multiple users experience a gap simultaneously, it is directly determined as a severe gap, and the importance level of the current experience segment is simultaneously clarified. S3. Determine the initial priority based on the correlation between the severity of the synchronization fault and the importance level of the current experience segment, verify the feasibility of repairing the corresponding priority by combining system operation resource data, and then determine the repair priority of the synchronization fault; determine whether the system has the resource conditions for immediate repair by comparing the remaining computing power, available bandwidth and the threshold of resources required for immediate repair. S4. Match the repair timing and method according to the repair priority and resource conditions. The highest priority repair is performed immediately when resources are sufficient, and redundant resources are scheduled for repair when resources are insufficient. The medium priority repair is performed at the natural node of the current stage. The lowest priority repair is delayed until the next non-core transition stage, and the repair process does not interrupt the normal experience of other users.

[0007] Furthermore, S1 includes the following: The VR terminal uses a built-in position sensor and motion capture module to collect scene coordinate data and interactive action posture data of each user in real time, and calculates the user's scene progress based on the scene coordinate data. The platform collects the sending and receiving confirmation times of each user's interaction actions through interaction synchronization logs, calculates the action synchronization delay, determines interaction action synchronization anomalies, and records the number of anomalies. The VR terminal performance monitoring module collects the device frame interval time, determines device lag and accumulates the duration of lag, and calculates the difference between the user's and the group's average scene progress to determine if the user has fallen behind and accumulates the duration of falling behind. The platform's scenario configuration module reads the type identifier field of the current experience stage to distinguish between core experience stages and non-core transition stages, and reads the unique identifier and timestamp of the current stage to associate it with multi-person collaborative experience data. The system collects system operation resource data and calculates remaining computing power, available bandwidth, and remaining energy storage ratio. After preprocessing the multi-person collaborative experience data, experience stage attribute data, and system operation resource data, an association mapping table is established using timestamps and experience stage identifiers as a joint index, and stored in the platform's distributed database to support millisecond-level query calls.

[0008] Furthermore, S2 includes the following: Based on multi-user collaborative experience data, two-dimensional quantitative indicators are extracted. The ratio of a single user's cumulative time lost at the current timestamp to the preset maximum tolerable time lost, and the ratio of the cumulative number of synchronization anomalies in interactive actions to the preset maximum tolerable number of misalignments in interactive actions are calculated. Based on the experience priority of multi-user collaborative virtual tourism, the above two ratios are weighted and calculated to obtain the synchronization failure severity of the single user. The severity of synchronous faults is classified into fault levels based on a preset threshold range, and multi-user collaborative judgment rules are set. If the severity of a single user's synchronous fault is not greater than the preset threshold, it is judged as a minor fault; if it is greater than the preset threshold, it is judged as a severe fault. If the proportion of users with faults at the same timestamp to the total number of online users exceeds a preset proportion, it is directly judged as a severe fault. The system synchronously reads the collected experience stage attribute data, matches the preset core experience stage identifier library according to the type identifier of the experience stage, and clarifies the importance level of the current experience stage. Among them, core experience stages correspond to the first level of importance, and non-core transition stages correspond to the second level of importance, with the first level of importance having a higher priority than the second level.

[0009] Furthermore, S3 includes the following: Based on the severity of the synchronization fault and the importance level of the experience links, a two-dimensional correlation judgment logic is used to determine the initial repair priority of the synchronization fault. The severity of the synchronization fault is divided into minor fault and severe fault, and the importance level of the experience links is divided into first-level corresponding to core experience links and second-level corresponding to non-core transition links. The two-dimensional correlation judgment logic is as follows: severe fault and first-level importance level correspond to the highest initial priority, minor fault and first-level importance level or severe fault and second-level importance level correspond to medium initial priority, and minor fault and second-level importance level correspond to the lowest initial priority. The system reads the collected data on remaining computing power and available bandwidth, and calculates the degree to which system resources meet each initial repair priority based on the resource requirement characteristics of different initial repair priorities. The degree of satisfaction is calculated with computing power as the core weight and bandwidth as the auxiliary weight. A preset resource satisfaction threshold is set, and a dual-condition verification logic is used to verify the resource feasibility of each initial repair priority. The dual-condition verification logic is as follows: the core resources, i.e., computing power, meet the minimum requirements of the corresponding initial priority, and the system resource satisfaction reaches the preset threshold. If both conditions are met, the resources are determined to be supportable; otherwise, they are determined to be unsupportable. The final repair priority is dynamically determined based on the resource feasibility verification results. When resources are available, the initial repair priority is maintained. When resources are not available, the initial repair priority is adjusted downward to adapt. The highest initial priority is adjusted to medium priority, the medium initial priority is adjusted to the lowest priority, and the lowest initial priority remains unchanged. For the synchronization fault with the highest priority in the final repair, the remaining computing power and available bandwidth of the system are directly compared with the minimum computing power threshold and minimum bandwidth threshold required for the highest priority repair to determine whether the resource conditions for immediate repair are met. If they are met, the relevant logic for immediate repair is executed; otherwise, the redundant resource scheduling logic is triggered.

[0010] Furthermore, S4 includes the following: Based on the final repair priority and the immediate repair resource condition determination result of the highest priority synchronous fault, combined with the collected system energy storage data, the repair strategy of each synchronous fault is matched according to the core principles of priority adaptation timing, resource matching method and uninterrupted experience. All repair operations must meet the requirements of scene rendering smoothness and interactive synchronization for non-fault users. For the synchronous fault with the highest final repair priority, a repair strategy is matched based on the immediate repair resource condition determination result. If it is determined that the immediate repair resource conditions are met, the repair is immediately executed at the current timestamp. If it is determined that the immediate repair resource conditions are not met, redundant resource scheduling is triggered first. After the scheduling is completed, the repair is executed. If the scheduling fails, it is temporarily downgraded to medium priority and the medium priority repair strategy is used. The redundant resource scheduling is constrained based on system energy storage data. For synchronization gaps with a final repair priority of medium, the repair timing is set to the natural node of the current experience segment. The natural node is determined based on the node identifier field in the experience segment attribute data collected by S1. A batch synchronization strategy is used to perform the repair, and the synchronization process does not occupy core experience resources. For the synchronization faults with the lowest final repair priority, the repair timing is delayed until the next non-core transition stage. The non-core transition stage is determined based on the experience stage type identifier field in the experience stage attribute data collected by S1. A centralized batch repair strategy is adopted to process all the lowest priority synchronization faults within this period. After all repair operations are completed, the repair effect is verified based on the collected VR terminal performance monitoring data and the preset synchronization threshold. If the repair meets the standard, the experience data of the corresponding user is updated; if it does not meet the standard, the user is included in the next round of repair process from S2 to S4.

[0011] The intelligent management system applied to the VR large-space virtual tourism platform includes: a data acquisition module, a fault quantification and grading module, a priority dynamic determination module, and a repair strategy matching module; The data acquisition module collects multi-user collaborative experience data, experience stage attribute data, and system operation resource data in real time, and preprocesses and stores the collected data in association. The fault quantification and grading module quantifies the severity of synchronous faults and classifies fault levels based on the multi-person collaborative experience data output by the data acquisition module, while also clarifying the importance level of the current experience segment. The priority dynamic determination module determines the initial repair priority based on the severity of synchronous faults and the importance level of the experience link output by the fault quantification and grading module. It also verifies the feasibility of priority repair by combining the system operation resource data output by the data acquisition module, dynamically determines the final repair priority, and determines the immediate repair resource conditions for the highest priority synchronous faults. The repair strategy matching module, based on the final repair priority output by the priority dynamic determination module and the real-time repair resource condition determination result, combined with the system energy storage data output by the data acquisition module, matches the repair timing and method for each synchronous fault, executes the repair operation, and verifies the repair effect.

[0012] Furthermore, the data acquisition module includes a multi-dimensional data acquisition unit and a data association and storage unit; The multi-dimensional data acquisition unit collects user scene coordinate data, interaction action posture data, action synchronization log data, device performance data, and system operation resource data; The data association storage unit performs validity verification and format standardization preprocessing on various types of collected data, establishes an association mapping table using timestamps and experience stage identifiers as a joint index, and stores the processed data in the platform's distributed database, supporting millisecond-level query calls.

[0013] Furthermore, the fault quantification and grading module includes a two-dimensional quantification unit and a fault level and importance determination unit; The dual-dimensional quantification unit extracts the cumulative time spent falling behind and the cumulative number of synchronization anomalies in interactive actions from the multi-person collaborative experience data, calculates the ratio of these values ​​to the corresponding preset tolerance threshold, and performs a weighted calculation of the two ratios based on experience priority to obtain the synchronization failure severity of a single user. The fault level and importance determination unit divides minor faults or severe faults based on the preset threshold range of synchronous fault severity, performs collaborative determination rules in combination with the fault ratio of multiple users, and matches the preset core experience link identifier library to clarify the importance level of the current experience link.

[0014] Furthermore, the priority dynamic determination module includes a preliminary priority determination unit, a resource feasibility verification unit, and an immediate repair condition determination unit. The preliminary priority determination unit determines the preliminary repair priority of each synchronous fault based on a two-dimensional correlation logic between the severity of the synchronous fault and the importance level of the experience link. The resource feasibility verification unit reads the system's remaining computing power and available bandwidth data, calculates the degree to which the system resources meet each preliminary repair priority, uses a dual-condition verification logic to determine resource supportability, and dynamically lowers the preliminary repair priority based on the verification results to determine the final repair priority. The instant repair condition determination unit directly compares the system's remaining computing power and available bandwidth with the minimum resource threshold required for the highest priority repair of the synchronization fault to determine whether the resource conditions for instant repair are met.

[0015] Furthermore, the repair strategy matching module includes a hierarchical repair execution unit and a repair effect verification unit; The hierarchical repair execution unit matches corresponding repair strategies for synchronous faults with different final repair priorities. The highest priority faults are repaired immediately or by scheduling redundant resources based on the conditions for immediate repair resources. The medium priority faults are repaired in batches at the natural nodes of the current experience stage. The lowest priority faults are delayed until the next non-core transition stage to perform centralized batch repair. All repair operations meet the constraint of uninterrupted user experience for non-faulty faults. The repair effect verification unit verifies the interaction synchronization, scene progress consistency, and device smoothness of users after the repair based on VR terminal performance monitoring data and preset synchronization thresholds. If the repair meets the standards, the user experience data is updated; if it does not meet the standards, the user is reintroduced into the subsequent repair process.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: By adopting a two-dimensional weighted accounting method that combines the cumulative lag time ratio and the cumulative abnormal interaction action synchronization times ratio to determine the severity of the synchronization fault, and adding a multi-user collaboration determination rule, the present invention achieves a scientific and accurate definition of the synchronization fault level, solves the defect that the prior art does not scientifically classify the severity of the fault, and provides a reliable basis for subsequent repair strategy matching; By combining the severity of the synchronization fault and the importance level of the experience link to construct a two-dimensional preliminary priority determination logic, and at the same time carrying out two-condition feasibility verification based on the system operation resource data and dynamically lowering the priority, the present invention achieves an accurate match between the repair requirements, the experience value, and the system resources, avoiding the risk of resource waste or experience fault caused by the fixed rule triggering repair in the prior art; By setting up a two-condition resource verification mechanism that the computing power meets the minimum requirement and the system resource satisfaction reaches the threshold, and the redundant resource scheduling is restricted by the system energy storage data, the present invention improves the stability and reliability of the repair operation, and eliminates the failure problem caused by forced repair when the resources are insufficient; By matching different final repair priorities with different repair times and methods, immediately repairing or scheduling redundant resources to repair the highest-priority fault, repairing at the natural node of the current experience link for the medium-priority fault, and delaying the centralized repair of the lowest-priority fault to the next non-core transition link, the present invention not only ensures the timely solution of the high-priority fault, but also avoids the repair operation from interfering with the immersive experience of non-fault users, and completely solves the core defects of the prior art that the immediate forced synchronization destroys the immersion and the passive waiting causes the experience fragmentation; By constructing a complete technical link of data collection, fault classification, priority determination, and repair matching, the present invention achieves a dual balance of the continuity of the collaborative experience and the efficient utilization of system resources, breaks through the key bottleneck restricting the upgrade of the multi-user collaborative VR virtual tourism experience, and improves the overall operation stability and user experience satisfaction of the platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention, and do not constitute a limitation to the present invention. In the drawings: Figure 1 It is a schematic diagram of the modules of the intelligent management system of the present invention applied to the VR large-space virtual tourism platform. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0019] Please see Figure 1 The present invention provides the following technical solution: The intelligent management system applied to the VR large-space virtual tourism platform includes: a data acquisition module, a fault quantification and grading module, a priority dynamic determination module, and a repair strategy matching module; The data acquisition module collects multi-user collaborative experience data, experience stage attribute data, and system operation resource data in real time, and preprocesses and stores the collected data in association. The fault quantification and grading module quantifies the severity of synchronous faults and classifies fault levels based on the multi-person collaborative experience data output by the data acquisition module, while also clarifying the importance level of the current experience segment. The priority dynamic determination module determines the initial repair priority based on the severity of synchronous faults and the importance level of the experience link output by the fault quantification and grading module. It also verifies the feasibility of priority repair by combining the system operation resource data output by the data acquisition module, dynamically determines the final repair priority, and determines the immediate repair resource conditions for the highest priority synchronous faults. The repair strategy matching module, based on the final repair priority output by the priority dynamic determination module and the real-time repair resource condition determination result, combined with the system energy storage data output by the data acquisition module, matches the repair timing and method for each synchronous fault, executes the repair operation, and verifies the repair effect.

[0020] The data acquisition module includes a multi-dimensional data acquisition unit and a data association and storage unit; The multi-dimensional data acquisition unit collects user scene coordinate data, interaction action posture data, action synchronization log data, device performance data, and system operation resource data; The data association storage unit performs validity verification and format standardization preprocessing on various types of collected data, establishes an association mapping table using timestamps and experience stage identifiers as a joint index, and stores the processed data in the platform's distributed database, supporting millisecond-level query calls.

[0021] The fault quantification and grading module includes a two-dimensional quantification unit and a fault level and importance determination unit; The dual-dimensional quantification unit extracts the cumulative time spent falling behind and the cumulative number of synchronization anomalies in interactive actions from the multi-person collaborative experience data, calculates the ratio of these values ​​to the corresponding preset tolerance threshold, and performs a weighted calculation of the two ratios based on experience priority to obtain the synchronization failure severity of a single user. The fault level and importance determination unit divides minor faults or severe faults based on the preset threshold range of synchronous fault severity, performs collaborative determination rules in combination with the fault ratio of multiple users, and matches the preset core experience link identifier library to clarify the importance level of the current experience link.

[0022] The priority dynamic determination module includes a preliminary priority determination unit, a resource feasibility verification unit, and an immediate repair condition determination unit; The preliminary priority determination unit determines the preliminary repair priority of each synchronous fault based on a two-dimensional correlation logic between the severity of the synchronous fault and the importance level of the experience link. The resource feasibility verification unit reads the system's remaining computing power and available bandwidth data, calculates the degree to which the system resources meet each preliminary repair priority, uses a dual-condition verification logic to determine resource supportability, and dynamically lowers the preliminary repair priority based on the verification results to determine the final repair priority. The instant repair condition determination unit directly compares the system's remaining computing power and available bandwidth with the minimum resource threshold required for the highest priority repair of the synchronization fault to determine whether the resource conditions for instant repair are met.

[0023] The repair strategy matching module includes a tiered repair execution unit and a repair effect verification unit; The hierarchical repair execution unit matches corresponding repair strategies for synchronous faults with different final repair priorities. The highest priority faults are repaired immediately or by scheduling redundant resources based on the conditions for immediate repair resources. The medium priority faults are repaired in batches at the natural nodes of the current experience stage. The lowest priority faults are delayed until the next non-core transition stage to perform centralized batch repair. All repair operations meet the constraint of uninterrupted user experience for non-faulty faults. The repair effect verification unit verifies the interaction synchronization, scene progress consistency, and device smoothness of users after the repair based on VR terminal performance monitoring data and preset synchronization thresholds. If the repair meets the standards, the user experience data is updated; if it does not meet the standards, the user is reintroduced into the subsequent repair process.

[0024] The intelligent management method applied to VR large-space virtual tourism platforms includes the following steps: S1. Real-time collection of multi-person collaborative experience data, experience stage attribute data, and system operation resource data; the multi-person collaborative experience data includes scene progress, interactive action synchronization status, device lag duration, and lagging duration; the experience stage attribute data includes type identifiers of core experience stages and non-core transition stages; the system operation resource data includes remaining computing power, available bandwidth, and energy storage data. S2. Based on multi-user collaborative experience data, the severity of synchronization gaps is quantified. Combining the ratio of the actual time spent falling behind to the preset maximum tolerance time and the ratio of the number of times the interaction action is misaligned to the preset maximum tolerance number, synchronization gaps are divided into minor gaps and severe gaps. When multiple users experience a gap simultaneously, it is directly determined as a severe gap, and the importance level of the current experience segment is simultaneously clarified. S3. Determine the initial priority based on the correlation between the severity of the synchronization fault and the importance level of the current experience segment, verify the feasibility of repairing the corresponding priority by combining system operation resource data, and then determine the repair priority of the synchronization fault; determine whether the system has the resource conditions for immediate repair by comparing the remaining computing power, available bandwidth and the threshold of resources required for immediate repair. S4. Match the repair timing and method according to the repair priority and resource conditions. The highest priority repair is performed immediately when resources are sufficient, and redundant resources are scheduled for repair when resources are insufficient. The medium priority repair is performed at the natural node of the current stage. The lowest priority repair is delayed until the next non-core transition stage, and the repair process does not interrupt the normal experience of other users.

[0025] S1 includes the following: The VR terminal uses a built-in position sensor and motion capture module to collect scene coordinate data and interactive action posture data of each user in real time, and calculates the user's scene progress based on the scene coordinate data. The platform collects the sending and receiving confirmation times of each user's interaction actions through interaction synchronization logs, calculates the action synchronization delay, determines interaction action synchronization anomalies, and records the number of anomalies. The VR terminal performance monitoring module collects the device frame interval time, determines device lag and accumulates the duration of lag, and calculates the difference between the user's and the group's average scene progress to determine if the user has fallen behind and accumulates the duration of falling behind. The platform's scenario configuration module reads the type identifier field of the current experience stage to distinguish between core experience stages and non-core transition stages, and reads the unique identifier and timestamp of the current stage to associate it with multi-person collaborative experience data. The system collects system operation resource data and calculates remaining computing power, available bandwidth, and remaining energy storage ratio. After preprocessing the multi-person collaborative experience data, experience stage attribute data, and system operation resource data, an association mapping table is established using timestamps and experience stage identifiers as a joint index, and stored in the platform's distributed database to support millisecond-level query calls.

[0026] In this embodiment, the VR terminal uses its built-in position sensor and motion capture module to collect scene coordinate data (Xi,t) and interactive action posture data (θi,t) of each user in real time. Here, i is the user identifier, t is the collection timestamp, Xi is the three-dimensional spatial coordinates of user i in the virtual scene at timestamp t, and θi is the set of posture angles of key limb joints of user i at timestamp t. Based on the scene coordinate data, the user's scene progress Pi(t) is calculated using the formula: Pi(t)=(Li(t) / L)×100%, where Li(t) is the length of the scene path completed by user i at time t, and L is the total scene path length of the current experience segment. By collecting the sending time ts and receiving confirmation time ta of each user's interaction action through the platform's interaction synchronization log, the action synchronization delay Δti(t) = ta - ts is calculated; when Δti(t) is greater than the preset synchronization delay threshold Ts, it is determined that the interaction action synchronization is abnormal, and the number of abnormalities Ci(t) is recorded. The VR terminal performance monitoring module collects the device frame interval time Δtf; when Δtf is greater than the preset frame interval threshold Tf, it is determined that the device is stuck, and the cumulative stuttering duration is Tc; calculate the difference between user i and the average scene progress of the group ΔPi(t)=|Pi(t)-Pa(t)|, where Pa(t) is the average scene progress of all users at time t. When ΔPi(t) is greater than the preset progress difference threshold TP, it is determined that the user has fallen behind, and the cumulative falling behind duration is Td; Collect attribute data of the experience stage, and read the type identifier field F of the current experience stage through the platform scenario configuration module; when F belongs to the preset core experience stage identifier library, it is determined to be a core experience stage; otherwise, it is determined to be a non-core transition stage; and read the unique identifier ID and timestamp of the current stage for association with multi-person collaborative experience data; The system collects operational resource data, specifically including: collecting CPU utilization Uc through the platform server's CPU performance monitoring interface and calculating the remaining computing power C=Ct×(1-Uc), where Ct is the server's rated total computing power; collecting the current uplink or downlink network bandwidth usage Bu through the network switch's traffic monitoring module and calculating the available bandwidth B=Bt-Bu, where Bt is the rated network bandwidth allocated by the platform; and collecting the remaining energy storage capacity Er and the rated total energy storage capacity Et through the energy storage device's battery management system and calculating the remaining energy storage ratio R=(Er / Et)×100%. The collected three types of data are preprocessed before storage, and the preprocessing includes data validity verification and data format standardization. Using timestamp t and experience stage ID as a joint index, an association mapping table is established for multi-person collaborative experience data, experience stage attribute data, and system operation resource data. This table is stored in the platform's distributed database and supports millisecond-level query calls.

[0027] S2 includes the following: Based on multi-user collaborative experience data, two-dimensional quantitative indicators are extracted. The ratio of a single user's cumulative time lost at the current timestamp to the preset maximum tolerable time lost, and the ratio of the cumulative number of synchronization anomalies in interactive actions to the preset maximum tolerable number of misalignments in interactive actions are calculated. Based on the experience priority of multi-user collaborative virtual tourism, the above two ratios are weighted and calculated to obtain the synchronization failure severity of the single user. The severity of synchronous faults is classified into fault levels based on a preset threshold range, and multi-user collaborative judgment rules are set. If the severity of a single user's synchronous fault is not greater than the preset threshold, it is judged as a minor fault; if it is greater than the preset threshold, it is judged as a severe fault. If the proportion of users with faults at the same timestamp to the total number of online users exceeds a preset proportion, it is directly judged as a severe fault. The system synchronously reads the collected experience stage attribute data, matches the preset core experience stage identifier library according to the type identifier of the experience stage, and clarifies the importance level of the current experience stage. Among them, core experience stages correspond to the first level of importance, and non-core transition stages correspond to the second level of importance, with the first level of importance having a higher priority than the second level.

[0028] In this embodiment, for user i at timestamp t, the cumulative time Td(i,t) of falling behind is calculated as the ratio RT(i,t) to the preset maximum tolerable time falling behind, and RT(i,t)=Td(i,t) / Tmax, where Tmax is the preset maximum tolerable time falling behind, and the specific value is set by relevant personnel in combination with the interaction response requirements of the core experience links; For user i at timestamp t, calculate the ratio RC(i,t) of the cumulative number of abnormal interaction actions Ci(t) to the preset maximum tolerable number of interaction action misalignments, and RC(i,t)=Ci(t) / Nmax, where Nmax is the preset maximum tolerable number of interaction action misalignments, and the specific value is set by relevant personnel based on the average interaction action frequency within a single experience segment; Based on the two-dimensional ratio and preset weight coefficients, the severity of the synchronization fault S(i,t) of user i at timestamp t is calculated, and S(i,t)=α×RT(i,t)+β×RC(i,t), where α and β are preset weight coefficients, and α+β=1. The specific values ​​are set by relevant personnel in combination with the experience priority of multi-person collaborative virtual tourism, and the value of α is greater than β. This solution considers both the synchronization of scene progress and the synchronization of interactive actions by weighted fusion of two core indicators, which is more in line with the experience needs of multi-person collaborative virtual tourism.

[0029] The severity threshold S0 for synchronous outages is dynamically adjusted by relevant personnel based on the type of experience segment. Combining the severity quantification results and multi-user outage collaborative judgment rules, outage levels are classified as follows: if a single user's S(i,t)≤S0, it is judged as a minor outage; if S(i,t)>S0, it is judged as a severe outage; if at the same timestamp t, the proportion of users with outages to the total number of online users exceeds a preset proportion, such as 30%, it is directly judged as a severe outage. Based on the experience stage attribute data collected by S1, the type identifier field F of the current stage is read and matched with the preset core experience stage identifier library to directly determine the importance level of the current stage: if it is a core experience stage, the importance level is level one; if it is a non-core transition stage, the importance level is level two; among them, level one has higher priority than level two.

[0030] S3 includes the following: Based on the severity of the synchronization fault and the importance level of the experience links, a two-dimensional correlation judgment logic is used to determine the initial repair priority of the synchronization fault. The severity of the synchronization fault is divided into minor fault and severe fault, and the importance level of the experience links is divided into first-level corresponding to core experience links and second-level corresponding to non-core transition links. The two-dimensional correlation judgment logic is as follows: severe fault and first-level importance level correspond to the highest initial priority, minor fault and first-level importance level or severe fault and second-level importance level correspond to medium initial priority, and minor fault and second-level importance level correspond to the lowest initial priority. The system reads the collected data on remaining computing power and available bandwidth, and calculates the degree to which system resources meet each initial repair priority based on the resource requirement characteristics of different initial repair priorities. The degree of satisfaction is calculated with computing power as the core weight and bandwidth as the auxiliary weight. A preset resource satisfaction threshold is set, and a dual-condition verification logic is used to verify the resource feasibility of each initial repair priority. The dual-condition verification logic is as follows: the core resources, i.e., computing power, meet the minimum requirements of the corresponding initial priority, and the system resource satisfaction reaches the preset threshold. If both conditions are met, the resources are determined to be supportable; otherwise, they are determined to be unsupportable. The final repair priority is dynamically determined based on the resource feasibility verification results. When resources are available, the initial repair priority is maintained. When resources are not available, the initial repair priority is adjusted downward to adapt. The highest initial priority is adjusted to medium priority, the medium initial priority is adjusted to the lowest priority, and the lowest initial priority remains unchanged. For the synchronization fault with the highest priority in the final repair, the remaining computing power and available bandwidth of the system are directly compared with the minimum computing power threshold and minimum bandwidth threshold required for the highest priority repair to determine whether the resource conditions for immediate repair are met. If they are met, the relevant logic for immediate repair is executed; otherwise, the redundant resource scheduling logic is triggered.

[0031] In this embodiment, the initial repair priority of the synchronization fault is determined based on the severity of the synchronization fault output by S2 and the importance level of the current experience stage. The severity of the synchronization fault is divided into minor and severe faults, and the importance level of the experience stage is divided into Level 1 for core experience stages and Level 2 for non-core transition stages. Specifically, the determination logic is as follows: when the synchronization fault is severe and the importance level of the experience stage is Level 1, the initial repair priority is determined to be the highest; when the synchronization fault is minor and the importance level of the experience stage is Level 1, or when the synchronization fault is severe and the importance level of the experience stage is Level 2, the initial repair priority is determined to be medium; when the synchronization fault is minor and the importance level of the experience stage is Level 2, the initial repair priority is determined to be the lowest. Read the system operation resource data collected by S1, including the remaining computing power C and available bandwidth B. Combine the resource demand characteristics corresponding to different initial repair priorities, calculate the system resource satisfaction degree Rs for each initial repair priority, and Rs=γ×(C / C0)+(1-γ)×(B / B0), where C0 is the minimum computing power threshold required for the corresponding initial repair priority, B0 is the minimum bandwidth threshold required for the corresponding initial repair priority, γ is the computing power weight coefficient, and γ>1-γ. The core basis is that the core resource bottleneck of the repair operation of the VR large space virtual tourism platform is server computing power, and bandwidth is an auxiliary constraint. The preset resource satisfaction threshold K is set based on the following criteria: VR platform repair operations need to reserve a certain amount of resource redundancy to avoid repair interruptions due to resource fluctuations. Simultaneously, given that computing power is a core bottleneck, the threshold value must ensure that core resources (computing power) are prioritized. The specific judgment logic must simultaneously meet two conditions: the computing power satisfaction ratio C / C0 ≥ 1 (sufficient core resources); and the resource satisfaction level Rs ≥ K. Only when both conditions are met is the system resource deemed capable of supporting the corresponding initial repair priority; if either condition is not met, the system is deemed unsupportable. For example, let the computing power weight coefficient γ = 0.6, the bandwidth weight coefficient (1-γ) = 0.4, the minimum computing power threshold C0 = 100 (unit: GFLOPS) and the minimum bandwidth threshold B0 = 50 (unit: Mbps) required for a medium priority repair, and the preset resource satisfaction judgment threshold K = 1.1; The current system has a remaining computing power C=115 and available bandwidth B=52; the computing power satisfaction ratio C / C0=115 / 100=1.15≥1 (core resources are sufficient); the bandwidth satisfaction ratio B / B0=52 / 50=1.04; the resource satisfaction Rs=0.6×1.15+0.4×1.04=0.69+0.416=1.106≥K=1.1; therefore, the core resources (computing power) are sufficient, and the overall resource satisfaction and redundancy meet the threshold requirements, so the system can stably support this medium-priority repair.

[0032] Based on the resource satisfaction level (Rs), the feasibility of the initial repair priority is verified, and the final repair priority is dynamically determined. When it is determined to be supportable, the original initial repair priority is maintained as the final repair priority. When it is determined to be unsupportable, the initial repair priority is adjusted downwards: if the initial priority is the highest, it is adjusted to medium; if the initial priority is medium, it is adjusted to the lowest; if the initial priority is the lowest, it remains unchanged. The core of the adjustment logic is to achieve efficient utilization of system resources while ensuring that the core experience is not compromised. For the synchronization fault with the highest priority in the final repair, a separate real-time repair resource condition determination is carried out; the remaining computing power C and available bandwidth B collected by S1 are read and directly compared with the minimum computing power threshold Ca and minimum bandwidth threshold Ba required for the highest priority repair; when C≥Ca and B≥Ba, it is determined that the real-time repair resource conditions are met; otherwise, it is determined that they are not met, and the logic of subsequent scheduling of redundant resource repair is triggered; this independent determination can improve the stability of real-time repair operation and avoid repair failure due to resource fluctuations.

[0033] S4 includes the following: Based on the final repair priority and the immediate repair resource condition determination result of the highest priority synchronous fault, combined with the collected system energy storage data, the repair strategy of each synchronous fault is matched according to the core principles of priority adaptation timing, resource matching method and uninterrupted experience. All repair operations must meet the requirements of scene rendering smoothness and interactive synchronization for non-fault users. For the synchronous fault with the highest final repair priority, a repair strategy is matched based on the immediate repair resource condition determination result. If it is determined that the immediate repair resource conditions are met, the repair is immediately executed at the current timestamp. If it is determined that the immediate repair resource conditions are not met, redundant resource scheduling is triggered first. After the scheduling is completed, the repair is executed. If the scheduling fails, it is temporarily downgraded to medium priority and the medium priority repair strategy is used. The redundant resource scheduling is constrained based on system energy storage data. For synchronization gaps with a final repair priority of medium, the repair timing is set to the natural node of the current experience segment. The natural node is determined based on the node identifier field in the experience segment attribute data collected by S1. A batch synchronization strategy is used to perform the repair, and the synchronization process does not occupy core experience resources. For the synchronization faults with the lowest final repair priority, the repair timing is delayed until the next non-core transition stage. The non-core transition stage is determined based on the experience stage type identifier field in the experience stage attribute data collected by S1. A centralized batch repair strategy is adopted to process all the lowest priority synchronization faults within this period. After all repair operations are completed, the repair effect is verified based on the collected VR terminal performance monitoring data and the preset synchronization threshold. If the repair meets the standard, the experience data of the corresponding user is updated; if it does not meet the standard, the user is included in the next round of repair process from S2 to S4.

[0034] In this embodiment, based on the final repair priority output by S3 and the immediate repair resource condition determination result of the highest priority synchronization fault, combined with the system energy storage remaining ratio R collected by S1, the repair strategy for each synchronization fault is matched according to the core principles of priority adaptation timing, resource matching method, and uninterrupted experience; all repair operations must meet the requirements of smooth rendering and interactive synchronization in non-fault user scenarios, as detailed below: For the repair strategy of the highest priority synchronization fault, it is determined according to the result of the immediate repair resource condition judgment. If it is determined that the immediate repair resource condition is met, the repair is executed immediately at the current timestamp; if it is determined that the condition is not met, redundant resource scheduling is triggered first. For example, the scheduling needs to meet the system energy storage remaining ratio R≥20% to avoid insufficient energy storage affecting the platform stability. After the scheduling is completed, the repair is executed. If the scheduling fails, it is temporarily downgraded to medium priority and the medium priority repair strategy is used. For the medium-priority synchronization gap repair strategy, the repair timing is set to the natural node of the current experience segment. This natural node is triggered by the node identifier field in the experience segment attribute data collected by S1, specifically the task completion node of the core experience segment, the scene switching interval, and other time periods without core interaction. The repair method adopts a batch synchronization strategy, which does not occupy core experience resources during the synchronization process, ensuring that the user experience of non-disruption users is not affected. For the repair strategy of the lowest priority synchronization fault, the repair time is delayed until the next non-core transition stage. This stage is determined by the experience stage type identifier field F collected by S1, that is, F is not a stage in the preset core experience stage identifier library. The repair method adopts a centralized batch repair strategy to centrally handle the synchronization problems of all the lowest priority faults within this period, so as to avoid scattered repairs occupying system resources. After all repair operations are completed, the repair effect is verified based on the VR terminal performance monitoring data collected by S1 and the synchronization threshold preset by S2. If the synchronization delay of the user's interaction action after the repair is ≤Ts, the difference between the scene progress and the group average progress is ≤TP, and the device is not lagging, the repair is considered successful, and the experience data of the corresponding user in the distributed database is updated. If the standards are not met, the user is included in the next round of repair process S2-S4 to ensure that the problem of the disconnection is completely resolved and to avoid secondary synchronization disconnection.

[0035] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0036] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An intelligent management method applied to VR large-space virtual tourism platforms, characterized by: The method includes the following steps: S1. Real-time collection of multi-person collaborative experience data, experience stage attribute data, and system operation resource data; the multi-person collaborative experience data includes scene progress, interactive action synchronization status, device lag duration, and lagging duration; the experience stage attribute data includes type identifiers of core experience stages and non-core transition stages; the system operation resource data includes remaining computing power, available bandwidth, and energy storage data. S2. Based on multi-user collaborative experience data, the severity of synchronization gaps is quantified. Combining the ratio of the actual time spent falling behind to the preset maximum tolerance time and the ratio of the number of times the interaction action is misaligned to the preset maximum tolerance number, synchronization gaps are divided into minor gaps and severe gaps. When multiple users experience a gap simultaneously, it is directly determined as a severe gap, and the importance level of the current experience segment is simultaneously clarified. S3. Determine the initial priority based on the correlation between the severity of the synchronization fault and the importance level of the current experience segment, verify the feasibility of repairing the corresponding priority by combining system operation resource data, and then determine the repair priority of the synchronization fault; determine whether the system has the resource conditions for immediate repair by comparing the remaining computing power, available bandwidth and the threshold of resources required for immediate repair. S4. Match the repair timing and method according to the repair priority and resource conditions. The highest priority repair is performed immediately when resources are sufficient, and redundant resources are scheduled for repair when resources are insufficient. The medium priority repair is performed at the natural node of the current stage. The lowest priority repair is delayed until the next non-core transition stage, and the repair process does not interrupt the normal experience of other users.

2. The intelligent management method for VR large-space virtual tourism platforms according to claim 1, characterized in that: S1 includes the following: The VR terminal uses a built-in position sensor and motion capture module to collect scene coordinate data and interactive action posture data of each user in real time, and calculates the user's scene progress based on the scene coordinate data. The platform collects the sending and receiving confirmation times of each user's interaction actions through interaction synchronization logs, calculates the action synchronization delay, determines interaction action synchronization anomalies, and records the number of anomalies. The VR terminal performance monitoring module collects the device frame interval time, determines device lag and accumulates the duration of lag, and calculates the difference between the user's and the group's average scene progress to determine if the user has fallen behind and accumulates the duration of falling behind. The platform's scenario configuration module reads the type identifier field of the current experience stage to distinguish between core experience stages and non-core transition stages, and reads the unique identifier and timestamp of the current stage to associate it with multi-person collaborative experience data. The system collects operational resource data and calculates remaining computing power, available bandwidth, and remaining energy storage ratio. After preprocessing the multi-person collaborative experience data, experience stage attribute data, and system operational resource data, an association mapping table is established using timestamps and experience stage identifiers as a joint index, and stored in the platform's distributed database to support millisecond-level query calls.

3. The intelligent management method for VR large-space virtual tourism platforms according to claim 2, characterized in that: S2 includes the following: Based on multi-user collaborative experience data, two-dimensional quantitative indicators are extracted to calculate the ratio of a single user's cumulative time lost at the current timestamp to the preset maximum tolerable time lost, and the ratio of the cumulative number of abnormal interaction actions to the preset maximum tolerable number of interaction action misalignments. Based on the experience priority of multi-person collaborative virtual tourism, the two ratios mentioned above are weighted and calculated to obtain the synchronization fault severity of the individual user. The severity of synchronous faults is classified into fault levels based on a preset threshold range, and multi-user collaborative judgment rules are set. If the severity of a single user's synchronous fault is not greater than the preset threshold, it is judged as a minor fault; if it is greater than the preset threshold, it is judged as a severe fault. If the proportion of users with faults at the same timestamp to the total number of online users exceeds a preset proportion, it is directly judged as a severe fault. The system synchronously reads the collected experience stage attribute data, matches the preset core experience stage identifier library according to the experience stage type identifier, and clarifies the importance level of the current experience stage. Among them, core experience stages correspond to the first level of importance, and non-core transition stages correspond to the second level of importance, with the first level of importance having a higher priority than the second level.

4. The intelligent management method for VR large-space virtual tourism platforms according to claim 3, characterized in that: S3 includes the following: Based on the severity of the synchronization fault and the importance level of the experience links, a two-dimensional correlation judgment logic is used to determine the initial repair priority of the synchronization fault. The severity of the synchronization fault is divided into minor fault and severe fault, and the importance level of the experience links is divided into first-level corresponding to core experience links and second-level corresponding to non-core transition links. The two-dimensional correlation judgment logic is as follows: severe fault and first-level importance level correspond to the highest initial priority, minor fault and first-level importance level or severe fault and second-level importance level correspond to medium initial priority, and minor fault and second-level importance level correspond to the lowest initial priority. The system reads the collected data on remaining computing power and available bandwidth, and calculates the degree to which system resources meet each initial repair priority based on the resource requirement characteristics of different initial repair priorities. The degree of satisfaction is calculated with computing power as the core weight and bandwidth as the auxiliary weight. A preset resource satisfaction threshold is set, and a dual-condition verification logic is used to verify the resource feasibility of each initial repair priority. The dual-condition verification logic is as follows: the core resources, i.e., computing power, meet the minimum requirements of the corresponding initial priority, and the system resource satisfaction reaches the preset threshold. If both conditions are met, the resources are determined to be supportable; otherwise, they are determined to be unsupportable. The final repair priority is dynamically determined based on the resource feasibility verification results. When resources are available, the initial repair priority is maintained. When resources are unavailable, the initial repair priority is adjusted downwards to adapt. The highest initial priority is adjusted to medium priority, the medium initial priority is adjusted to the lowest priority, and the lowest initial priority remains unchanged. For the synchronization fault with the highest priority in the final repair, the remaining computing power and available bandwidth of the system are directly compared with the minimum computing power threshold and minimum bandwidth threshold required for the highest priority repair to determine whether the resource conditions for immediate repair are met. If they are met, the relevant logic for immediate repair is executed; otherwise, the redundant resource scheduling logic is triggered.

5. The intelligent management method for VR large-space virtual tourism platforms according to claim 4, characterized in that: S4 includes the following: Based on the final repair priority and the immediate repair resource condition determination result of the highest priority synchronous fault, combined with the collected system energy storage data, the repair strategy of each synchronous fault is matched according to the core principles of priority adaptation timing, resource matching method, and uninterrupted experience. All repair operations must meet the requirements of scene rendering smoothness and interactive synchronization for non-fault users. For synchronous faults with the highest final repair priority, a repair strategy is matched based on the results of the real-time repair resource condition determination. If it is determined that the conditions for immediate resource repair are met, repair is performed immediately at the current timestamp; if it is determined that the conditions for immediate resource repair are not met, redundant resource scheduling is triggered first, and repair is performed after scheduling is completed. If scheduling fails, it is temporarily downgraded to medium priority and the medium priority repair strategy is used. The redundant resource scheduling is constrained based on system energy storage data. For synchronization gaps with a final repair priority of medium, the repair timing is set to the natural node of the current experience segment. The natural node is determined based on the node identifier field in the experience segment attribute data. A batch synchronization strategy is used to perform the repair, and the synchronization process does not consume core experience resources. For the synchronization faults with the lowest final repair priority, the repair timing is delayed until the next non-core transition stage. The non-core transition stage is determined based on the experience stage type identifier field in the experience stage attribute data. A centralized batch repair strategy is adopted to process all the lowest priority synchronization faults within this period. After all repair operations are completed, the repair effect is verified based on VR terminal performance monitoring data and preset synchronization thresholds. If the repair meets the standard, the experience data of the corresponding user is updated; if it does not meet the standard, the user is included in the next round of repair processes from S2 to S4.

6. An intelligent management system applied to a VR large-space virtual tourism platform, which is based on the intelligent management method for a VR large-space virtual tourism platform as described in any one of claims 1-5, characterized in that: The system includes: a data acquisition module, a fault quantification and grading module, a priority dynamic determination module, and a repair strategy matching module; The data acquisition module collects multi-person collaborative experience data, experience stage attribute data, and system operation resource data in real time, and preprocesses and stores the collected data in association. The fault quantification and grading module quantifies the severity of synchronous faults and classifies fault levels based on the multi-person collaborative experience data output by the data acquisition module, while also clarifying the importance level of the current experience segment. The priority dynamic determination module determines the initial repair priority based on the severity of the synchronous fault and the importance level of the experience link output by the fault quantification and grading module. It also verifies the feasibility of priority repair by combining the system operation resource data output by the data acquisition module, dynamically determines the final repair priority, and determines the immediate repair resource conditions for the highest priority synchronous fault. The repair strategy matching module, based on the final repair priority output by the priority dynamic determination module and the real-time repair resource condition determination result, combined with the system energy storage data output by the data acquisition module, matches the repair timing and method of each synchronous fault, executes the repair operation, and verifies the repair effect.

7. The intelligent management system applied to a VR large-space virtual tourism platform according to claim 6, characterized in that: The data acquisition module includes a multi-dimensional data acquisition unit and a data association storage unit; The multi-dimensional data acquisition unit collects user scene coordinate data, interactive action posture data, action synchronization log data, device performance data, and system operation resource data; The data association storage unit performs validity verification and format standardization preprocessing on the collected data of various types. It establishes an association mapping table with timestamps and experience stage identifiers as a joint index and stores the processed data in the platform's distributed database, supporting millisecond-level query calls.

8. The intelligent management system applied to a VR large-space virtual tourism platform according to claim 6, characterized in that: The fault quantification and grading module includes a two-dimensional quantification unit and a fault level and importance determination unit; The dual-dimensional quantization unit extracts the cumulative time spent falling behind and the cumulative number of synchronization anomalies in interactive actions from the multi-person collaborative experience data, calculates the ratio of these values ​​to the corresponding preset tolerance threshold, and performs a weighted calculation on the two ratios based on experience priority to obtain the synchronization failure severity of a single user. The fault level and importance determination unit divides minor faults or severe faults according to the preset threshold range of synchronous fault severity, performs collaborative determination rules in combination with the fault ratio of multiple users, and matches the preset core experience link identifier library to determine the importance level of the current experience link.

9. The intelligent management system applied to a VR large-space virtual tourism platform according to claim 6, characterized in that: The priority dynamic determination module includes a preliminary priority determination unit, a resource feasibility verification unit, and an immediate repair condition determination unit. The preliminary priority determination unit determines the preliminary repair priority of each synchronous fault based on a two-dimensional correlation logic between the severity of the synchronous fault and the importance level of the experience link. The resource feasibility verification unit reads the system's remaining computing power and available bandwidth data, calculates the degree to which the system resources meet each preliminary repair priority, uses a dual-condition verification logic to determine resource supportability, and dynamically lowers the preliminary repair priority based on the verification results to determine the final repair priority. The instant repair condition determination unit directly compares the system's remaining computing power and available bandwidth with the minimum resource threshold required for the highest priority repair of the synchronization fault to determine whether the resource conditions for instant repair are met.

10. The intelligent management system applied to a VR large-space virtual tourism platform according to claim 6, characterized in that: The repair strategy matching module includes a hierarchical repair execution unit and a repair effect verification unit; The hierarchical repair execution unit matches corresponding repair strategies for synchronous faults with different final repair priorities. The highest priority faults are repaired immediately or by scheduling redundant resources based on the conditions for immediate repair resources. The medium priority faults are repaired in batches at the natural nodes of the current experience stage. The lowest priority faults are delayed until the next non-core transition stage to perform centralized batch repair. All repair operations meet the constraint of no interruption in the user experience of non-faulty users. The repair effect verification unit verifies the interaction synchronization, scene progress consistency, and device smoothness of the users after the repair based on VR terminal performance monitoring data and preset synchronization thresholds. If the repair meets the standards, the user experience data is updated; if it does not meet the standards, the user is reintroduced into the subsequent repair process.

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