Theme-based 3D immersive sound field big data management system

Abstract

This invention relates to the field of data management and optimization technology, specifically a theme-driven 3D immersive sound field big data management system. It includes analyzing the spatiotemporal links of the sound field and the trajectory of the sound source listening point, identifying continuous conflict transmission paths in parameter mapping, rearranging time nodes to generate a priority scheduling table, measuring the scheduling response pressure within densely arranged cycles, and finally integrating the spatial and temporal scheduling relationships of the entire segment to generate a full-scene sound field scheduling basis set. This invention constructs a chain connection between the sound source and the listening point displacement to enhance the traceability of parameter changes, identifies and organizes parameter diffusion trajectories by combining transmission path identification, and coordinates node time reconstruction and rhythm adjustment to ensure that parameter scheduling and spatial changes are coordinated. Simultaneously, it divides cycles and marks pressure based on update concentration and spatial density, thereby reducing response fluctuations caused by local updates, ultimately ensuring the scheduling balance and coherence of multi-dimensional sound field data in a dynamic environment.

Description

Technical Field

[0001] This invention relates to the field of data management and optimization technology, and in particular to a theme-following 3D immersive sound field big data management system. Background Technology

[0002] The field of data management optimization technology encompasses standardized data acquisition and processing, data storage structure design, data index construction, data access control, data consistency maintenance, and multi-source data fusion. The core of this technology lies in achieving the management and scheduling of data from different sources within a unified system through structured data description rules, orderly data organization methods, and clear data update and verification mechanisms. This involves data identification and encoding rules, hierarchical data storage methods, data mapping relationship construction, and data access path definition. It also systematically constrains and configures data at each stage of generation, transmission, storage, and retrieval to support the data organization and management needs in large-scale data environments. With the deep integration of spatial audio technology and big data analytics, sound field data management is gradually evolving towards higher dimensions, stronger dynamics, and real-time response, placing higher demands on the precision of data processing and scheduling efficiency.

[0003] The theme-driven 3D immersive sound field big data management system refers to a system for organizing, recording, and scheduling three-dimensional spatial sound field data in dynamic scenes. Its technical aspects include recording sound source location coordinates, annotating listening point coordinate sequences, constructing sound field parameter data storage structures, establishing time-series data indexes, formulating spatial grid division rules, and defining multi-dimensional sound field data mapping relationships. Specifically, the system records spatial location information at different time points by establishing a coordinate association table between sound sources and listening points. It combines this with data such as sound pressure level, frequency band values, and reverberation time parameters to form structured data units, and regionalizes the sound field data according to spatial grid division rules. Simultaneously, it sequentially identifies and associates the dynamically changing sound field data through time-series indexing, aiming to achieve orderly management and scheduling of three-dimensional sound field data in different scenes.

[0004] In existing technologies, the real-time mapping relationship between sound source trajectories and listening point displacements in dynamic scenes exhibits redundancy. Under large-scale concurrent access, the matching accuracy between the spatial index structure and the time-series distribution of the data has room for optimization. The coupling mechanism between sound field parameters and spatial coordinates often exhibits high consistency maintenance costs in multi-source heterogeneous environments, and the response latency of scheduling paths in data hierarchical storage rules can be further improved when dealing with rapidly changing spatial grid divisions. Furthermore, for multi-dimensional sound field data in complex acoustic environments, existing management methods lack flexibility and systematic constraints in terms of the universality of data identification encoding and the dynamic reconstruction of data mapping relationships in different scenarios. This leads to a need to improve the efficiency of organizing and managing three-dimensional sound field data in large-scale data environments. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by proposing a theme-driven 3D immersive sound field big data management system.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a theme-following 3D immersive sound field big data management system, the system comprising: The sound field spatiotemporal link analysis module obtains the location information of all sound sources and listening points in the three-dimensional spatial sound field, identifies the temporal connection sequence between the trajectory of each sound source and the displacement of the listening point, locates the corresponding events of sound field parameter updates and spatial grid nodes, marks the connection structure between all spatial coordinate nodes and acoustic behavior, draws the path clue diagram between the sound source trajectory and the sound field parameters in sequence, and generates a sound field spatiotemporal connection structure map. The mapping conflict propagation identification module reads the dynamic path in the sound field spatiotemporal connection structure map, determines whether the sequential relationship between the sound source and the listening point causes a change in the order of sound field parameter mapping, identifies the segment where continuous spatial displacement forms scheduling interference, records the distribution of interference path and node sequence position, and generates a mapping conflict propagation distribution map. The sound field parameter scheduling and sorting module extracts the original spatial coordinate arrangement order based on the high interference nodes identified in the mapping conflict transmission distribution map, rearranges the corresponding sound field parameter update time order, updates the node ranking and adjusts the scheduling order, and generates a parameter priority scheduling order table. The scheduling response pressure measurement module calls the time period information in the parameter priority scheduling order table, identifies the concentration of data requests and changes in response distribution during the sound field parameter update time period, screens dense scheduling segments, marks time segments with continuous changes in fluctuation amplitude, and generates a periodic sound field scheduling pressure distribution map.

[0007] As a further aspect of the present invention, the sound field spatiotemporal connection structure map includes a spatial coordinate node sequence structure, sound field parameter update event nodes, coordinate and parameter pairing relationships, and path connection mapping elements. The mapping conflict transmission distribution map includes a set of paths affected by mapping delays, identifiers of time-continuous interference segments, and sound field parameter association chains. The parameter priority scheduling order table specifically includes a list of key parameter nodes, time order adjustment identifiers, and a priority sequence of conflict impacts. The periodic sound field scheduling pressure distribution map includes scheduling rhythm concentrated sections, densely arranged spatial grid intervals, and data request time pressure points.

[0008] As a further aspect of the present invention, the sound field spatiotemporal link analysis module includes: The sound field data extraction submodule obtains the spatial node number, sound field time label and acoustic description field from the parameter configuration list of the sound field execution stage. It checks whether the planned start time and end time fields corresponding to each node are complete. It calls the spatial node number and time label to construct the sound field time series array. It arranges the spatial node numbers in order according to the time order and marks their corresponding time intervals to generate the sound field time series structure matrix. The spatial trigger structure identification submodule determines whether there are overlapping or gap intervals between adjacent spatial time intervals based on the spatial node numbering order in the sound field time sequence structure matrix. If the start time of the current node is earlier than the end time of the previous node, it is marked as an overlapping trigger type. If the start time is equal to the end time of the previous node, it is marked as a continuous trigger type. If there is a gap, it is marked as a delayed trigger type. The marking results and spatial node numbers are used to construct a trigger link logic array and generate a trigger type identification vector between spatial nodes. The parameter mapping path generation submodule, based on the spatial node number order in the trigger type identifier vector between spatial nodes, calls the acoustic behavior number associated with the corresponding spatial node in the sound field parameter update record table, matches whether the parameter update time and the spatial execution time coincide. If the time coincidence is satisfied, a connection structure is established between the acoustic behavior number and the spatial node number, constructs a one-to-one mapping matrix between spatial nodes and acoustic behavior nodes, draws a path clue diagram composed of acoustic behavior nodes in the spatial node order, and generates a sound field spatiotemporal connection structure map.

[0009] As a further aspect of the present invention, the process of generating the sound field time series structure matrix specifically includes: creating a sound field time series structure matrix, which includes a spatial node number column, a planned start time column, and an end time column; filling the spatial node number, planned start time, and end time into the corresponding columns of the sound field time series structure matrix, and sorting the sound field time series structure matrix in ascending order according to the planned start time; The process of determining whether the matching parameter update time coincides with the spatial execution time is as follows: obtain the parameter update time of the corresponding acoustic behavior number in the sound field parameter update record table; extract the planned start time and end time corresponding to the spatial node number from the sound field time series structure matrix; determine whether the parameter update time is within the closed time interval formed by the planned start time and end time; if the parameter update time is within the closed time interval, it is determined that the parameter update time and the spatial execution time coincide.

[0010] As a further aspect of the present invention, the mapping conflict propagation identification module includes: The path structure analysis submodule, based on the dynamic path structure in the sound field spatiotemporal connection structure map, obtains the spatial node number and its corresponding parameter update time in each path, detects whether the time interval between adjacent spatial nodes meets the continuation triggering condition, determines whether the time offset of the preceding node causes the change in the start time of the subsequent node, filters out the sound field node combinations with preceding and following relationships, and generates a list of delay effect conduction paths. The interference segment determination submodule calculates the cumulative time offset of each node on the path based on the time difference of the node pairs in the delay influence conduction path list, compares it with the set sound field time continuous interference threshold, determines whether there is a continuous node segment that meets the interference interval length requirement, calls the cumulative time offset sequence and spatial node order, marks the formed continuous interference node set, and obtains the continuous interference segment interval vector. The transmission trajectory construction submodule calls the spatial node number combination in the interval vector of the continuous interference segment, matches its associated acoustic behavior number and update time point, connects the parameter update nodes with continuous node interference relationship, arranges the acoustic behavior according to the time sequence, draws the influence extension trajectory on each path, and establishes a mapping conflict transmission distribution map.

[0011] As a further aspect of the present invention, the sound field parameter scheduling and sorting module includes: The key node extraction submodule, based on the path structure in the mapping conflict transmission distribution map, detects whether the spatial node corresponding to the parameter update node in the path is within the marked range of the interval vector of the continuous interference segment, extracts the set of node numbers that meet the continuous interference condition, obtains its original parameter update time label, and forms a mapping relationship with the spatial node number to generate the interference key node time index table. The scheduling priority adjustment submodule calls the original time tag sequence of the parameter update nodes in the time index table of the interference key nodes, sorts them in ascending order according to time sequence, and reassigns a new priority identifier to each parameter update node. At the same time, it constructs a difference matrix between the old priority and the new priority, establishes a scheduling priority adjustment structure, and obtains the parameter scheduling priority rearrangement matrix. The sorting structure generation submodule recombines the parameter update number and its adjusted order index according to the new order identifier in the parameter scheduling order rearrangement matrix, generates a complete list of parameter numbers and a corresponding update time list, constructs an updated time sorting mapping table corresponding to the conflict path structure, and establishes a parameter priority scheduling order table.

[0012] As a further aspect of the present invention, the scheduling response pressure measurement module includes: The scheduling rhythm identification submodule, based on the parameter update time field in the parameter priority scheduling order table, counts the number of parameter update events in each time period, calculates the update frequency difference between adjacent time periods, determines whether the change in update frequency exceeds the set update frequency fluctuation threshold, filters out time segments that continuously exceed the fluctuation threshold, and generates a list of parameter update concentration intervals. The dense section determination submodule calls the time period information in the parameter update centralized interval list to obtain the spatial node number and its arrangement time interval within the corresponding period. It calculates the spatial arrangement density coefficient based on the overlap of the time interval and compares the spatial arrangement density coefficient with the number of parameter update events in parallel to filter out the period positions where the spatial nodes are dense and the update behavior occurs continuously, thus obtaining the high-voltage scheduling period segment identification table. The pressure drawing submodule extracts the corresponding parameter update event time point and quantity value according to the cycle number in the high-pressure scheduling cycle segment identifier table, constructs the update frequency sequence for each cycle unit, arranges the frequency sequence in ascending order according to the cycle number, matches its position interval in the total cycle, draws a scheduling intensity visualization graphic under the corresponding cycle number, and establishes a cycle sound field scheduling pressure distribution map.

[0013] As a further aspect of the present invention, the process of counting the number of parameter update events in each time period is specifically as follows: setting the statistical period unit to a preset time step; traversing the parameter update time field in the parameter priority scheduling order table, and counting the number of parameter update events falling within the same preset time step. The process of calculating the spatial arrangement density coefficient based on the overlap of time intervals is as follows: obtain all spatial node numbers corresponding to the time period in the parameter update set interval list; extract the arrangement time intervals corresponding to all spatial node numbers, calculate the total duration of all arrangement time intervals within the time period, and calculate the overlap duration of any two arrangement time intervals within the time period; sum the cumulative overlap durations, divide the cumulative sum of overlap durations by the total duration, and obtain the spatial arrangement density coefficient.

[0014] As a further aspect of the present invention, the system further includes: The full-scene scheduling decision module reads the response pressure segment in the periodic sound field scheduling pressure distribution map, extracts the relationship between spatial distribution and scheduling rhythm, identifies the spatial node order rearrangement and combination, organizes the corresponding structure of spatial segments and parameter update time lines, and generates a full-scene sound field scheduling basis set. The full-scene sound field scheduling basis set includes stage combination classification items, key spatial node temporal positions, and a spatial parameter path overview table.

[0015] As a further aspect of the present invention, the full-scenario scheduling decision module includes: The stage combination extraction submodule, based on the period segment number in the periodic sound field scheduling pressure distribution map, detects whether there is an overlapping interval between the parameter update frequency peak and the spatial node arrangement, extracts the period number that satisfies the dual conditions of update concentration and spatial overlap, records the associated spatial node number and parameter number under each period, establishes the correspondence between period and spatial parameter combination, and generates a concentrated stage combination list. The instruction node integration submodule calls the set of spatial node numbers and parameter numbers in the centralized stage combination list, obtains the time tag of the spatial node and the corresponding parameter update sequence identifier, groups the parameter update behavior within the stage according to the start and end time of the spatial node, integrates the path sequence of parameter update behavior in chronological order, constructs the combination structure of spatial segment and acoustic behavior segment, and obtains the stage spatial parameter path mapping table. The decision basis summary submodule identifies the node sequence of parameter updates in each stage based on the spatial parameter segment combination structure in the stage spatial parameter path mapping table, and standardizes it into a standard instruction format. It summarizes the spatial node number, parameter number and sequence number fields of all stage combinations and integrates them into a continuous executable data structure sequence to establish a full-scene sound field scheduling basis set.

[0016] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, a continuous path structure is formed by constructing a chain-like connection between the sound source trajectory and the displacement of the listening point across time nodes, thereby enhancing the traceability of the sound field parameter change process. Combined with the segmented identification and aggregation processing of the influence transmission path between nodes, the diffusion trajectory of parameters between spatial nodes is sorted out. With the reconstruction of the time sequence corresponding to key nodes and the adjustment of the update rhythm, the parameter scheduling order and the spatial change state form a synergistic relationship. At the same time, based on the corresponding analysis of the update concentration section and the spatial distribution density, the scheduling cycle is divided and pressure is marked to reduce the response fluctuation caused by local update concentration, so that the multidimensional sound field data maintains scheduling balance and process continuity in the dynamic environment. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the overall system flow of the present invention. Figure 2 This is a flowchart of the system modules of the present invention. Detailed Implementation

[0018] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0019] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0020] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0021] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0022] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0023] Please see Figure 1 This invention provides a technical solution: a theme-driven 3D immersive sound field big data management system, the system comprising: The sound field spatiotemporal link analysis module obtains the location information of all sound sources and listening points in the three-dimensional spatial sound field, identifies the temporal connection sequence between the trajectory of each sound source and the displacement of the listening point, confirms the preceding and following nodes on which the triggering relationship depends, locates the corresponding events of sound field parameter updates and spatial grid nodes, marks the connection structure between all spatial coordinate nodes and acoustic behavior, draws the path clue diagram between the sound source trajectory and the sound field parameters in sequence, and generates a sound field spatiotemporal connection structure map. The mapping conflict propagation identification module reads the dynamic path in the spatiotemporal connection structure map of the sound field, identifies the extension effect of the displacement of the preceding node on the subsequent node, locates the transmission relationship between the sound field parameter mapping nodes, determines whether the influence forms continuous interference on the timeline, connects the continuous influence segments to form a path set, draws the trajectory map of the parameter update influence propagation on each path, and generates a mapping conflict propagation distribution map. The sound field parameter scheduling and sorting module identifies key nodes with continuous interference segments in the path based on the path structure in the mapping conflict transmission distribution diagram, extracts the original spatial arrangement of these nodes, rearranges the time identifiers corresponding to the sound field parameter update order, adjusts the original scheduling order, forms a time sequence update table corresponding to the conflict structure, and generates a parameter priority scheduling order table. The scheduling response pressure measurement module calls the time arrangement in the parameter priority scheduling order table, identifies whether there is a concentrated tilt in the parameter update rhythm, extracts the spatial node information of the concentrated update time period, compares the spatial arrangement density of adjacent stages, marks the periodic segments where the response continues to change in dense arrangement, draws the periodic position map corresponding to the dense update behavior, and generates a periodic sound field scheduling pressure distribution map. The full-scene scheduling decision module reads the periodic segments in the periodic sound field scheduling pressure distribution map, identifies the stage combinations with concentrated updates and spatial overlap, confirms the positional changes of key spatial tasks in the combination, integrates scheduling time and mapping relationship to form stage classification, summarizes the spatial parameter paths and node order of all segments, and uniformly forms a full-stage instruction arrangement set to generate a full-scene sound field scheduling basis set.

[0024] The sound field spatiotemporal connection structure map includes the spatial coordinate node sequence structure, sound field parameter update event nodes, coordinate and parameter pairing relationship, and path connection mapping elements. The mapping conflict transmission distribution map includes the set of paths affected by mapping delays, the identification of time-continuous interference segments, and the sound field parameter association chain. The parameter priority scheduling order table specifically includes a list of key parameter nodes, time order adjustment identifiers, and conflict impact priority sequence. The periodic sound field scheduling pressure distribution map includes scheduling rhythm concentrated sections, dense spatial grid arrangement sections, and data request time pressure points. The full-scene sound field scheduling basis set includes stage combination classification items, key spatial node temporal positions, and a spatial parameter path overview table.

[0025] Please see Figure 2 The sound field spatiotemporal link analysis module includes: The sound field data extraction submodule obtains the spatial node number, sound field time label and acoustic description field from the parameter configuration list of the sound field execution stage. It checks whether the planned start time and end time fields corresponding to each spatial node are complete. It calls the spatial node number and time label to construct the sound field time series array. It arranges the spatial node numbers in order according to the time order and marks their corresponding time intervals to generate the sound field time series structure matrix. Retrieve the "Sound Field Parameter Configuration Table" from the sound field management database. This table records the spatial node number, sound field time stamp, and acoustic description field, as shown in Table 1. For each row of sound field data extracted from this table, check whether its "Planned Start Time" and "End Time" fields contain valid time unit values. For example, check the planned start time "0ms" and end time "500ms" of node S-001. Both are valid positive integers, so the data is considered complete. Continue checking node S-002, whose start time "500ms" is... Both the start time "0ms" and the end time "1200ms" are valid, so the data is considered complete. Node S-003 is checked; its start time "1100ms" and end time "1800ms" are both valid, so the data is considered complete. When node S-004 is detected, its "end time" field is found to be missing, so the data is considered incomplete. Therefore, this data entry will be marked and excluded from subsequent processing. Node S-005 is checked; its start time "2000ms" and end time "2800ms" are both valid. Once the data is deemed complete, the system retrieves the spatial node numbers and time tags of all identified complete data to construct a temporary sound field time series array. The array's data structure is [(S-001,0,500),(S-002,500,1200),(S-003,1100,1800),(S-005,2000,2800)]. Based on this array, a sound field time series structure matrix is ​​created. This matrix is ​​configured to contain three elements: "spatial node number," "planned start time," and "end time." The data items in the array, such as (S-001, 0, 500), are filled into the corresponding three columns of the first row of the matrix. This process is repeated to fill in the data for S-002, S-003, and S-005. Finally, all rows of the matrix are sorted in ascending order strictly according to the values ​​in the "Planned Start Time" column. Since the sequence [0, 500, 1100, 2000] is already ordered, the row order of the sorted matrix remains unchanged as S-001, S-002, S-003, S-005, thus generating the sound field time series structure matrix.

[0026] Table 1: Sound Field Parameter Configuration Table As shown in Table 1, this table is a general example of sound field parameter configuration. Node S-004 was removed during the data integrity check because the termination time field was missing.

[0027] The spatial trigger structure identification submodule determines whether there are overlapping or gap intervals between adjacent spatial time intervals based on the spatial node numbering order in the sound field time sequence structure matrix. If the start time of the current node is earlier than the end time of the previous node, it is marked as an overlapping trigger type. If the start time is equal to the end time of the previous node, it is marked as a continuous trigger type. If there is a gap, it is marked as a delayed trigger type. The marking results and spatial node numbers are used to construct a trigger link logic array and generate a trigger type identification vector between spatial nodes. Based on the spatial node numbering order in the sound field time series structure matrix, i.e., [S-001, S-002, S-003, S-005], starting from the second row of the matrix, i.e., node S-002, we sequentially determine whether adjacent time intervals overlap, are continuous, or have gaps. First, we extract the planned start time (500ms) of S-002 and the end time (500ms) of S-001, and then perform a comparison: we compare the start time (500ms) of S-002 with the end time (500ms) of S-001 to determine if they are equal. The condition is met, so the relationship between S-001 and S-002 is marked as "continuous triggering type". Next, S-003 and S-002 are processed, extracting the planned start time of S-003 (1100ms) and the end time of S-002 (1200ms). A judgment is then made: the start time of S-003 (1100ms) is compared with the end time of S-002 (1200ms), and a decision is made. The condition is met, so the relationship between S-002 and S-003 is marked as "overlapping trigger type". Finally, S-005 and S-003 are processed, the planned start time of S-005 (2000ms) and the termination time of S-003 (1800ms) are extracted, and the judgment is executed: Decision If the condition is not met, then determine whether it is true or false. If the condition is not met, calculate the difference between the two time units. If the value is greater than 0, a gap is determined, so the relationship between S-003 and S-005 is marked as "delayed triggering type". After completing the judgment of all adjacent spatial pairs, the marking result and the corresponding spatial node number are called to construct a triggering link logic array. The content of the array is [(S-001,S-002, continuous triggering),(S-002,S-003, overlapping triggering),(S-003,S-005, delayed triggering)]. After the array is formatted, a triggering type identifier vector between spatial nodes is generated.

[0028] The parameter mapping path generation submodule, based on the spatial node number order in the trigger type identifier vector between spatial nodes, calls the acoustic behavior number associated with the corresponding spatial node in the sound field parameter update record table, matches whether the parameter update time and the spatial execution time coincide. If the time coincides, a connection structure is established between the acoustic behavior number and the spatial node number, constructs a one-to-one mapping matrix between spatial nodes and acoustic behavior nodes, draws the path clue diagram formed by the acoustic behavior nodes in the spatial node order, and generates a sound field spatiotemporal connection structure map. Based on the node order S-001, S-002, S-003, S-005 determined by the trigger type identifier vector between spatial nodes, the "Sound Field Parameter Update Record Table" is queried. The specific contents of this table are shown in Table 2. The acoustic behavior number associated with each spatial node is called. For example, S-001 is associated with the sound pressure level adjustment of P-01, S-002 with the frequency band value correction of P-02, S-003 with the reverberation time update of P-03, and S-005 with the spatial gain compensation of P-04. Subsequently, the overlap between the parameter update time and the spatial execution time is checked. This process is specifically as follows: Obtain the parameter update time "200ms" for P-01, and extract the planned start time "0ms" and end time "500ms" for S-001 from the sound field time series structure matrix, constructing a closed time interval [0, 500]. Perform a judgment: determine if the update time 200ms is greater than or equal to the interval start time 0ms, and if 200ms is less than or equal to the interval end time 500ms. Both conditions are true, therefore, P-01 and S-001 are considered to have overlapping times. Next, process S-002, whose interval is [500, 1200]. The update time for P-02 is "800ms". Perform a judgment: and If the condition is met, it is determined that the times coincide. Then, process S-003, whose interval is [1100, 1800]. The update time of P-03 is "1900ms". Execute the judgment: but This condition is not met, indicating a time mismatch. Next, process S-005, whose interval is [2000, 2800]. P-04's update time is "2500ms". Perform the following judgment: and If the condition is met, it is determined that the time coincides. If the time coincides, a connection structure is established between the acoustic behavior number and the spatial node number. All pairs determined to be time coincident [(S-001,P-01),(S-002,P-02),(S-005,P-04)] are stored in a one-to-one mapping matrix. When drawing the acoustic behavior node path, according to the spatial node order (S-001→S-002→S-003→S-005), only the nodes that satisfy the mapping relationship are connected, that is, P-01→P-02. Since S-003 failed to match, its connection is interrupted. P-04 corresponding to S-005 forms a separate path node, generating a sound field spatiotemporal connection structure map.

[0029] Table 2: Sound Field Parameter Update Record Table See Table 2, which provides information on the association between acoustic parameter updates and spatial nodes. The update time of P-03 (1900ms) exceeds the planned range [1100, 1800] of its associated node S-003.

[0030] The mapping conflict propagation identification module includes: The path structure analysis submodule, based on the dynamic path structure in the sound field spatiotemporal connection structure map, obtains the spatial node number and its corresponding parameter update time in each path, detects whether the time interval between adjacent spatial nodes meets the continuation triggering condition, determines whether the time offset of the preceding node causes the change of the start time of the subsequent node, filters out the sound field node combinations with preceding and following relationships, and generates a list of delay effect conduction paths. Based on the dynamic path structure in the sound field spatiotemporal connection structure map, especially the main path S-001→S-002→S-003, where S-003, although its parameters and time are not perfectly matched, exists in the spatial flow, and introducing "sound field real-time execution log" data, we obtain the spatial node numbers S-001, S-002, and S-003 within the path, as well as their actual execution times recorded in the log. Assuming the log records: the actual termination time of S-001 is 600ms, and the planned time is 500ms... The actual start time of S-002 is 650ms, planned for 500ms; the actual end time is 1350ms, planned for 1200ms. The actual start time of S-003 is 1400ms, planned for 1100ms; the actual end time is 2100ms, planned for 1800ms. First, the time interval between S-001 and S-002 is checked. The actual start time of S-002 (650ms) is later than the actual end time of S-001 (600ms), satisfying the delay requirement. Following the trigger condition, next, determine whether the time offset of the preceding node S-001 causes a change in the start time of the subsequent node S-002. Calculate the time offset of S-001, which is (actual termination time of S-001 600ms) minus (planned termination time of S-001 500ms), resulting in an offset of 100ms. Calculate the change in the start time of S-002, which is (actual start time of S-002 650ms) minus (planned start time of S-002 500ms), resulting in a change... The time shift is 150ms. Since the change in the start time of S-002 is not zero (150ms), it is determined that the offset of S-001 affects the start time of S-002. (S-001, S-002) is selected as a sound field node combination with a sequential relationship. Further analysis of (S-002, S-003) is performed. The actual start time of S-003 (1400ms) is later than the actual end time of S-002 (1350ms), satisfying the continuation triggering condition. The time offset of S-002 is calculated. ms), calculate the change in the start time of S-003 ( Since 300 is not 0, it is determined that (S-002,S-003) is also a related combination. All the selected combinations [(S-001,S-002),(S-002,S-003)] are gathered to generate a list of delay effect transmission paths.

[0031] The interference segment determination submodule calculates the cumulative time offset of each node on the path based on the time difference of the node pairs in the delay effect conduction path list, and compares it with the set sound field time continuous interference threshold to determine whether there is a continuous node segment that meets the interference interval length requirement. It then calls the cumulative time offset sequence and spatial node order to mark the formed continuous interference node set and obtain the continuous interference segment interval vector. Based on the list of delay impact propagation paths [(S-001,S-002),(S-002,S-003)], calculate the cumulative time offset for each node on this path. Here, the cumulative time offset is defined as the difference between the actual termination time and the planned termination time of a node. For node S-001, the cumulative time offset is (actual termination time 600ms) minus (planned termination time 500ms), resulting in 100ms. For node S-002, the cumulative time offset is (actual termination time 1350ms) minus (planned termination time 1200ms), resulting in 150ms. For node S-003, the cumulative time offset is (actual termination time 2100ms) minus... (S-003 planned termination time 1800ms), resulting in 300ms, the resulting offset sequence is [100, 150, 300]. Next, this sequence is compared with the set sound field time continuous interference threshold. This threshold is set with reference to the experimental data analysis of 100 sets of spatial audio dynamic reconstruction scenarios. Statistical analysis shows that when the cumulative offset time of continuous spatial grid transformation exceeds 500ms, the accuracy of sound field localization will drop below 15% due to clock asynchrony. Therefore, based on this statistical result, the sound field time continuous interference threshold is set to 500ms. The offset sequences are compared one by one: the offset of S-001 is 100ms less than 500ms, and the offset of S-002 is 150ms less than 500ms. The cumulative impact is calculated. If the time is greater than or equal to 500ms, then node S-003 is determined to meet the interference condition. Then, all its preceding nodes S-001 and S-002 on the propagation path are traced back. {S-001, S-002, S-003} are marked as a set of continuous interference nodes, and the interval vector of continuous interference segment is obtained.

[0032] The transmission trajectory construction submodule calls the combination of spatial node numbers in the interval vector of continuous interference segment, matches the corresponding acoustic behavior number and update time point, connects the parameter update nodes with continuous node interference relationship, arranges the acoustic behavior according to the time sequence, draws the influence extension trajectory on each path, and establishes a mapping conflict transmission distribution map. The obtained continuous interference segment interval vector {S-001, S-002, S-003} is called, and the node number combination is extracted. This combination is then matched with the acoustic behavior number associated with it in the sound field parameter update record table (Table 2). S-001 is associated with P-01, S-002 with P-02, and S-003 with P-03. Simultaneously, the corresponding parameter update time points are obtained: 200ms for P-01, 800ms for P-02, and 1900ms for P-03. Next, the parameter update nodes with continuous node interference relationships are connected. Since spatial nodes S-001, S-002, and S-003 are identified as continuous interference at the spatial level, their corresponding parameter nodes P-01, P-002, and S-003 are also considered as continuous interference. -02 and P-03 are connected by directed line segments. These acoustic behaviors are arranged according to the time sequence of parameter updates, namely P-01 (200ms) → P-02 (800ms) → P-03 (1900ms). This sequence constitutes the influence extension trajectory at the sound field parameter level. When drawing the graph, the spatial offset of S-001 is marked as 100ms on the line connecting P-01 and P-02, the spatial offset of S-002 is marked as 150ms on the line connecting P-02 and P-03, and the cumulative offset of S-003 as 300ms is marked on the P-03 node itself. In this way, the displacement conflict of the spatial layer is mapped to the timing of parameter scheduling, and a mapping conflict transmission distribution map is established.

[0033] The sound field parameter scheduling and sorting module includes: The key node extraction submodule, based on the path structure in the mapping conflict propagation distribution map, detects whether the spatial nodes corresponding to the parameter update nodes in the path are within the marked range of the interval vector of the continuous interference segment, extracts the set of node numbers that meet the continuous interference conditions, obtains their original parameter update time labels, and forms a mapping relationship with the spatial node numbers to generate a time index table of interference key nodes. Based on the path structure P-01→P-02→P-03 in the mapping conflict propagation distribution diagram, the spatial nodes S-001, S-002, and S-003 corresponding to the parameter update nodes P-01, P-02, and P-03 within the path are detected. It is determined whether they are within the marked range of the continuous interference segment interval vector {S-001, S-002, S-003} determined in the previous steps. Specifically, for P-01, its associated spatial node S-001 is called, and a set membership check is performed between S-001 and the vector {S-001, S-002, S-003}. S-001 exists in the set, so the check result is true. Next, for P-02, its associated node S-002 is called, and its existence in the set is checked; the result is true. Finally, for P-03, its associated node S-003 is called, and the check result is the same. If the condition is true, all nodes satisfy the condition. Therefore, the set of node numbers {S-001, S-002, S-003} that satisfies the continuous interference condition is extracted. Then, the original parameter update time tags corresponding to these nodes are obtained from the sound field parameter update record table (Table 2). The time tags are 200ms for S-001 corresponding to P-01, 800ms for S-002 corresponding to P-02, and 1900ms for S-003 corresponding to P-03. A one-to-one mapping relationship is formed between the spatial node number, parameter behavior number and its time tag. A data structure containing (spatial node number, parameter behavior number, update time) is constructed with the content [(S-001, P-01, 200), (S-002, P-02, 800), (S-003, P-03, 1900)], generating the time index table of interference key nodes.

[0034] The scheduling priority adjustment submodule calls the original time tag sequence of parameter update nodes in the time index table of interference key nodes, sorts them in ascending order according to time sequence, and reassigns a new priority identifier to each parameter update node. At the same time, it constructs the difference matrix between the old priority and the new priority, establishes the scheduling priority adjustment structure, and obtains the parameter scheduling priority rearrangement matrix. The original time tag sequence of the parameter update nodes in the time index table of the interference key nodes is called, i.e., [200ms, 800ms, 1900ms], and their corresponding parameter numbers [P-01, P-02, P-03] are obtained. The time tag sequence is sorted in ascending order according to time sequence. After sorting, the sequence [200, 800, 1900] remains unchanged. According to the sorting result, each parameter update node is reassigned a new sequence number. P-01 (200ms) is assigned a new sequence number of 1, and P-02 (800ms) is assigned a new sequence number of 1. P-03 (1900ms) is assigned a new priority of 3, with P-01 now in priority 2. Simultaneously, the old priority identifiers of these parameter nodes are retrieved from the "Initial Sound Field Scheduling Plan." Assuming P-01's old priority is 1, P-03's is 2, and P-02's is 3, meaning that in the original plan, due to logical calculation requirements, P-03 was updated before P-02. A difference matrix between the old and new priorities is constructed, containing four columns: parameter number, old priority, new priority, and difference value. The difference value (new priority minus old priority) is calculated row by row: For P-01, the difference is... For P-02, the difference is For P-03, the difference is The resulting matrix contains [[P-01,1,1,0],[P-02,3,2,-1],[P-03,2,3,+1]]. This matrix is ​​the scheduling priority adjustment structure, which yields the parameter scheduling order rearrangement matrix.

[0035] The sorting structure generation submodule recombines the parameter update number and its adjusted order index according to the new order identifier in the parameter scheduling order rearrangement matrix, generates a complete list of parameter numbers and a corresponding update time list, constructs an updated time sorting mapping table corresponding to the conflict path structure, and establishes a parameter priority scheduling order table. Based on the new order identifiers in the parameter scheduling order rearrangement matrix (i.e., P-01 corresponds to 1, P-02 corresponds to 2, and P-03 corresponds to 3), the parameter update numbers are recombined with their adjusted order indices. Specifically, the parameter order number column [P-01, P-02, P-03] and the new order index column [1, 2, 3] are extracted and combined into a new list. Each element is a tuple containing the update number and the new order, such as [(P-01, 1), (P-02, 2), (P-03, 3)]. A complete parameter number list [P-01, P-02, P-03] is generated based on this list, along with the parameters extracted from the interference critical node time index table. The corresponding update time list [200, 800, 1900] has a one-to-one correspondence between the indices of the two lists. Subsequently, an updated time sorting mapping table corresponding to the conflict path structure (S-001→S-002→S-003) is constructed. This table integrates spatial nodes, acoustic parameters, new order, and time. The table contains four fields: "spatial node number", "parameter behavior number", "new order", and "update time". Data is filled in row by row. The first row is (S-001, P-01, 1, 200), the second row is (S-002, P-02, 2, 800), and the third row is (S-003, P-03, 3, 1900). A parameter priority scheduling order table is established.

[0036] The scheduling response stress measurement module includes: The scheduling rhythm identification submodule, based on the parameter update time field in the parameter priority scheduling order table, counts the number of parameter update events in each time period, calculates the update frequency difference between adjacent time periods, determines whether the change in update frequency exceeds the set update frequency fluctuation threshold, filters out time segments that continuously exceed the fluctuation threshold, and generates a list of parameter update concentration intervals. Based on the parameter priority scheduling order table and all other parameter update records in the sound field, the parameter update time field is extracted. From Table 2, [P-01(200), P-02(800), P-03(1900), P-04(2500)] are obtained. Assuming the existence of other auxiliary acoustic compensations P-05(800ms) and P-06(850ms), the complete set of update time points is [200, 800, 800, 850, 1900, 2500]. The parameter update events within each time period are then statistically analyzed. The process for determining the number of events involves setting the statistical period to a 100ms step size, iterating through all update time points, and counting the number of events falling within the same time step to obtain a frequency sequence. For example, from 700ms to 1000ms: (700-800ms, 0 times), (800-900ms, 3 times [P-02, P-05, P-06]), (900-1000ms, 0 times). Next, the update frequency difference between adjacent time periods is calculated, specifically the difference between the 800-900ms segment and the previous segment. Calculate the difference between the second segment and the first segment: The system determines whether the change in update frequency exceeds the set update frequency fluctuation threshold. This threshold is set with reference to the instantaneous load limit of the sound field processor. It is specified that if the number of update events changes by more than 1.5 within a single step, i.e., changes by 2 or more times, a response pressure warning will be triggered. Therefore, the threshold is set to 1.5. The calculated difference is compared: the difference of 3 is greater than 1.5. The continuous time segment where the difference exceeds the threshold is selected, i.e., the segment [700, 900] consisting of 0 times in 700ms to 3 times in 800ms. A list of parameter update concentration intervals is generated.

[0037] The dense section determination submodule calls the parameter update time period information in the centralized interval list, obtains the spatial node number and its arrangement time interval within the corresponding period, calculates the spatial arrangement density coefficient based on the overlap of the time interval, compares the spatial arrangement density coefficient with the number of parameter update events in parallel, filters out the period positions where spatial nodes are dense and update behavior occurs continuously, and obtains the high-voltage scheduling period segment identification table. The time period information in the centralized interval list is updated by calling parameters, i.e., [700ms, 900ms]. All spatial node numbers executed within the corresponding period are obtained. Table 1 and supplementary data are queried. S-002 [500, 1200] is active in this interval. It is assumed that two other spatial nodes, S-006 [600, 1000] and S-007 [750, 1100], are also active in this interval. The arrangement time intervals of these nodes are extracted, and the spatial arrangement density coefficient within the time period [700, 900] is calculated. The total analysis time is 200ms. Specifically, the total duration of all arrangement intervals within this time period is first calculated. The duration of S-002 within [700, 900] is 200ms, S-006 is 200ms, and S-007 is 150ms, for a total duration of... ms, and calculate the overlap duration of any two arrangement time intervals within this time interval. The overlap duration of S-002 and S-006 in [700,900] is 200ms, that of S-002 and S-007 is 150ms, and that of S-006 and S-007 is 150ms. The cumulative overlap durations are then calculated to obtain the result. The cumulative overlap duration of 500ms is divided by the total duration of 550ms to obtain a spatial density coefficient of approximately 0.91. Then, the spatial density coefficient of 0.91 is compared in parallel with the number of parameter update events. The peak value in this interval is 3 times. A spatial density threshold of 0.7 is set, and an update behavior duration threshold of 1.5 is set. The following judgment is then performed: and Since both conditions are met, the periodic position [700, 900] is selected to obtain the high-voltage dispatch periodic segment identifier table.

[0038] The pressure drawing submodule extracts the corresponding parameter update event time points and quantity values ​​based on the cycle number in the high-pressure scheduling cycle segment identifier table, constructs the update frequency sequence for each cycle unit, arranges the frequency sequence in ascending order by cycle number, matches its position interval in the total cycle, draws a scheduling intensity visualization graphic under the corresponding cycle number, and establishes a cycle sound field scheduling pressure distribution map. Based on the cycle number marked in the high-voltage dispatch cycle segment identifier table, for example, cycle [700, 900] numbered HP-01, extract its corresponding parameter update event time points and quantity values. From the analysis of the dispatch rhythm identification submodule, we obtain: 0 updates in 700-800ms, 3 updates in 800-900ms, constructing the update frequency sequence of this cycle unit as [0, 3]. Assuming there is another marked high-voltage cycle HP-02 [1800, 2000], its corresponding update frequency sequence is [0, 2]. Then, we compare HP-01 and HP-... The frequency sequence of 02 is arranged in ascending order according to time sequence. The position intervals of HP-01 and HP-02 in the total sound field cycle are matched to draw a visualization of the scheduling intensity under the corresponding cycle number. Specifically, a line graph with time as the horizontal axis and update frequency as the vertical axis is created, with the unit being the number of times. A data point with a height of 3 is drawn at the horizontal axis "850" and a data point with a height of 2 is drawn at the horizontal axis "1950". The scheduling intensity of all high-voltage cycles is plotted on the same chart to establish a periodic sound field scheduling pressure distribution map.

[0039] The full-scenario scheduling decision module includes: The stage combination extraction submodule, based on the period segment number in the periodic sound field scheduling pressure distribution map, detects whether there is an overlapping interval between the parameter update frequency peak and the spatial node arrangement. It extracts the period number that meets the dual conditions of update concentration and spatial overlap, records the associated spatial node number and parameter number under each period, establishes the correspondence between period and spatial parameter combination, and generates a concentrated stage combination list. Based on the periodic segment number HP-01[700,900] in the periodic sound field scheduling pressure distribution map, it is detected whether there is an overlap between the parameter update frequency peak and the spatial node arrangement within this interval. According to the visualization, there is a frequency peak 3 in the "800-900ms" segment. According to the calculation, the spatial arrangement density coefficient of this interval is 0.91. The peak threshold is set to 1.5, that is, greater than 1.5 times, and the density threshold is 0.7. The judgment is then executed. and Since both conditions are met, the cycle number HP-01 that meets the conditions is extracted, and the associated parameter numbers {P-02, P-05, P-06} under this cycle and the active spatial node numbers {S-002, S-006, S-007} within this cycle are recorded. The correspondence between the cycle and the spatial parameter combination is established in the format {HP-01: {Nodes: [S-002, S-006, S-007], Params: [P-02, P-05, P-06]}}. The same operation is performed on HP-02 to record its association information. All cycle information that meets the conditions is summarized to generate a centralized stage combination list.

[0040] The instruction node integration submodule calls the set of spatial node numbers and parameter numbers in the centralized stage combination list, obtains the time tag of the spatial node and the corresponding parameter update sequence identifier, groups the parameter update behavior within the stage according to the start and end time of the spatial node, integrates the path sequence of parameter update behavior in chronological order, constructs the combination structure of spatial segment and acoustic behavior segment, and obtains the stage spatial parameter path mapping table. The HP-01 periodic entry in the centralized phase combination list is called to obtain the spatial node set {S-002, S-006, S-007} and the parameter set {P-02, P-05, P-06}. The time tags of the nodes are obtained: S-002[500, 1200], S-006[600, 1000], S-007[750, 1100]. The parameter update order identifier is also obtained: P-02's order is 2, P-05's order is 4, and P-06's order is 5. The parameter update behavior is grouped within the phase according to the start and end times of the spatial nodes: P-02, P-05, P-06. All parameters are updated within 800-900ms. During this period, nodes S-002, S-006, and S-007 are all within the execution interval. Therefore, these parameters are grouped together and the update path sequences within the group are integrated according to the order identifiers (2,4,5) to obtain P-02→P-05→P-06. A combined structure of spatial node segment {S-002,S-006,S-007} and acoustic behavior segment {P-02→P-05→P-06} is constructed. This structure shows that in the HP-01 stage, the overlapping state of the three spatial grids corresponds to the centralized update of the three parameters, resulting in the stage spatial parameter path mapping table.

[0041] The decision basis summary submodule identifies the node sequence of parameter updates in each stage based on the spatial parameter segment combination structure in the stage spatial parameter path mapping table, and standardizes it into a standard instruction format. It summarizes the spatial node number, parameter number and sequence number fields of all stage combinations and integrates them into a continuous executable data structure sequence to establish a full-scene sound field scheduling basis set. Based on the HP-01 combination structure in the stage space parameter path mapping table, the node sequence for parameter updates within this stage is identified as P-02, P-05, P-06, and standardized into a standard instruction format. This format includes (stage number, node number, parameter number, sequence number). Querying the original association between parameters and the space, P-02 is associated with S-002, with a sequence number of 2; P-05 is associated with S-006, with a sequence number of 4; and P-06 is associated with S-007, with a sequence number of 5. The generated standard instructions are: (HP-01, S-002, P-02, 2), (HP- (HP-01,S-006,P-05,4) and (HP-01,S-007,P-06,5) perform the same operation on stage HP-02, summarize all instructions generated by all stage combinations, extract and integrate the node number, parameter number and sequence number fields in all instructions to form a continuous executable data structure sequence, namely [(HP-01,S-002,P-02,2),(HP-01,S-006,P-05,4),(HP-01,S-007,P-06,5),...], and establish the full-scene sound field scheduling basis set.

[0042] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A theme-driven 3D immersive sound field big data management system, characterized in that: The system includes: The sound field spatiotemporal link analysis module obtains the location information of all sound sources and listening points in the three-dimensional spatial sound field, identifies the temporal connection sequence between the trajectory of each sound source and the displacement of the listening point, locates the corresponding events of sound field parameter updates and spatial grid nodes, marks the connection structure between all spatial coordinate nodes and acoustic behavior, draws the path clue diagram between the sound source trajectory and the sound field parameters in sequence, and generates a sound field spatiotemporal connection structure map. The mapping conflict propagation identification module reads the dynamic path in the sound field spatiotemporal connection structure map, determines whether the sequential relationship between the sound source and the listening point causes a change in the order of sound field parameter mapping, identifies the segment where continuous spatial displacement forms scheduling interference, records the distribution of interference path and node sequence position, and generates a mapping conflict propagation distribution map. The sound field parameter scheduling and sorting module extracts the original spatial coordinate arrangement order and the original parameter update time label corresponding to these nodes based on the high interference nodes identified in the mapping conflict transmission distribution map. It then sorts the parameter update nodes in ascending order according to the time sequence, reassigns each parameter update node with a new priority identifier for the unchanged sequence, and adjusts the scheduling order to generate a parameter priority scheduling order table. The scheduling response pressure measurement module calls the time period information in the parameter priority scheduling order table, identifies the concentration of data requests and changes in response distribution during the sound field parameter update time period, screens dense scheduling segments, marks time segments with continuous changes in fluctuation amplitude, and generates a periodic sound field scheduling pressure distribution map.

2. The theme-following 3D immersive sound field big data management system according to claim 1, characterized in that: The spatiotemporal connection structure map of the sound field includes a spatial coordinate node sequence structure, sound field parameter update event nodes, coordinate and parameter pairing relationships, and path connection mapping elements. The mapping conflict transmission distribution map includes a set of paths affected by mapping delays, identifiers of time-continuous interference segments, and sound field parameter association chains. The parameter priority scheduling order table specifically includes a list of key parameter nodes, time order adjustment identifiers, and a priority sequence of conflict impacts. The periodic sound field scheduling pressure distribution map includes concentrated scheduling rhythm sections, densely arranged spatial grid intervals, and data request time pressure points.

3. The theme-following 3D immersive sound field big data management system according to claim 1, characterized in that, The sound field spatiotemporal link analysis module includes: The sound field data extraction submodule obtains the spatial node number, sound field time label and acoustic description field from the parameter configuration list of the sound field execution stage. It checks whether the planned start time and end time fields corresponding to each node are complete. It calls the spatial node number and time label to construct the sound field time series array. It arranges the spatial node numbers in order according to the time order and marks their corresponding time intervals to generate the sound field time series structure matrix. The spatial trigger structure identification submodule determines whether there are overlapping or gap intervals between adjacent spatial time intervals based on the spatial node numbering order in the sound field time sequence structure matrix. If the start time of the current node is earlier than the end time of the previous node, it is marked as an overlapping trigger type. If the start time is equal to the end time of the previous node, it is marked as a continuous trigger type. If there is a gap, it is marked as a delayed trigger type. The marking results and spatial node numbers are used to construct a trigger link logic array and generate a trigger type identification vector between spatial nodes. The parameter mapping path generation submodule, based on the spatial node number order in the trigger type identifier vector between spatial nodes, calls the acoustic behavior number associated with the corresponding spatial node in the sound field parameter update record table, matches whether the parameter update time and the spatial execution time coincide. If the time coincidence is satisfied, a connection structure is established between the acoustic behavior number and the spatial node number, constructs a one-to-one mapping matrix between spatial nodes and acoustic behavior nodes, draws a path clue diagram composed of acoustic behavior nodes in the spatial node order, and generates a sound field spatiotemporal connection structure map.

4. The theme-following 3D immersive sound field big data management system according to claim 3, characterized in that: The process of generating the sound field time series structure matrix is ​​as follows: creating a sound field time series structure matrix, which includes a spatial node number column, a planned start time column, and an end time column; Fill the spatial node number, planned start time and end time into the corresponding columns of the sound field time series structure matrix, and sort the sound field time series structure matrix in ascending order according to the planned start time; The process of determining whether the matching parameter update time coincides with the spatial execution time specifically involves: obtaining the parameter update time corresponding to the acoustic behavior number in the sound field parameter update record table; Extract the planned start and end times corresponding to the spatial node numbers from the sound field time series structure matrix; Determine whether the parameter update time is within the closed time interval formed by the planned start time and end time; If the parameter update time is within a closed time interval, then the parameter update time and the space execution time are determined to coincide.

5. The theme-following 3D immersive sound field big data management system according to claim 1, characterized in that, The mapping conflict propagation identification module includes: The path structure analysis submodule, based on the dynamic path structure in the sound field spatiotemporal connection structure map, obtains the spatial node number and its corresponding parameter update time in each path, detects whether the time interval between adjacent spatial nodes meets the continuation triggering condition, determines whether the time offset of the preceding node causes the change in the start time of the subsequent node, filters out the sound field node combinations with preceding and following relationships, and generates a list of delay effect conduction paths. The interference segment determination submodule calculates the cumulative time offset of each node on the path based on the difference between the actual termination time and the planned termination time of each spatial node on the path in the delay effect conduction path list, and compares it with the set sound field time continuous interference threshold to determine whether there is a continuous node segment that meets the interference interval length requirement. It then calls the cumulative time offset sequence and the spatial node order to mark the formed continuous interference node set and obtain the continuous interference segment interval vector. The transmission trajectory construction submodule calls the spatial node number combination in the interval vector of the continuous interference segment, matches its associated acoustic behavior number and update time point, connects the parameter update nodes with continuous node interference relationship, arranges the acoustic behavior according to the time sequence, draws the influence extension trajectory on each path, and establishes a mapping conflict transmission distribution map.

6. The theme-following 3D immersive sound field big data management system according to claim 5, characterized in that, The sound field parameter scheduling and sorting module includes: The key node extraction submodule, based on the path structure in the mapping conflict transmission distribution map, detects whether the spatial node corresponding to the parameter update node in the path is within the marked range of the interval vector of the continuous interference segment, extracts the set of node numbers that meet the continuous interference condition, obtains its original parameter update time label, and forms a mapping relationship with the spatial node number to generate the interference key node time index table. The scheduling priority adjustment submodule calls the original time tag sequence of the parameter update nodes in the time index table of the interference key nodes, sorts them in ascending order according to time sequence, and reassigns a new priority identifier to each parameter update node. At the same time, it retrieves the old priority identifiers of these parameter nodes from the initial sound field scheduling plan, constructs the difference matrix between the old and new priorities, establishes the scheduling priority adjustment structure, and obtains the parameter scheduling priority rearrangement matrix. The sorting structure generation submodule recombines the parameter update number and its adjusted order index according to the new order identifier in the parameter scheduling order rearrangement matrix, generates a complete list of parameter numbers and a corresponding update time list, constructs an updated time sorting mapping table corresponding to the conflict path structure, and establishes a parameter priority scheduling order table.

7. The theme-following 3D immersive sound field big data management system according to claim 1, characterized in that, The scheduling response pressure measurement module includes: The scheduling rhythm identification submodule, based on the parameter update time field in the parameter priority scheduling order table, counts the number of parameter update events in each time period, calculates the update frequency difference between adjacent time periods, determines whether the change in update frequency exceeds the set update frequency fluctuation threshold, filters out time segments that continuously exceed the fluctuation threshold, and generates a list of parameter update concentration intervals. The dense section determination submodule calls the time period information in the parameter update centralized interval list to obtain the spatial node number and its arrangement time interval within the corresponding period. It calculates the spatial arrangement density coefficient based on the overlap of the time interval and compares the spatial arrangement density coefficient with the number of parameter update events in parallel to filter out the period positions where the spatial nodes are dense and the update behavior occurs continuously, thus obtaining the high-voltage scheduling period segment identification table. The pressure drawing submodule extracts the corresponding parameter update event time point and quantity value according to the cycle number in the high-pressure scheduling cycle segment identifier table, constructs the update frequency sequence for each cycle unit, arranges the frequency sequence in ascending order according to the cycle number, matches its position interval in the total cycle, draws a scheduling intensity visualization graphic under the corresponding cycle number, and establishes a cycle sound field scheduling pressure distribution map.

8. The theme-following 3D immersive sound field big data management system according to claim 7, characterized in that: The process of counting the number of parameter update events in each time period is as follows: the statistical period unit is set to a preset time step. Iterate through the parameter update time field in the parameter priority scheduling order table and count the number of parameter update events that fall within the same preset time step. The process of calculating the spatial arrangement density coefficient based on the overlap of time intervals is as follows: obtain the number of all spatial nodes corresponding to the time period in the parameter update set interval list; Extract the arrangement time intervals corresponding to all spatial node numbers, calculate the total duration of all arrangement time intervals within the time period, and calculate the overlap duration of any two arrangement time intervals within the time period; sum the cumulative overlap durations, divide the cumulative sum of overlap durations by the total duration, and obtain the spatial arrangement density coefficient.

9. The theme-following 3D immersive sound field big data management system according to claim 1, characterized in that, The system also includes: The full-scene scheduling decision module reads the response pressure segment in the periodic sound field scheduling pressure distribution map, extracts the relationship between spatial distribution and scheduling rhythm, identifies the spatial node order rearrangement and combination, organizes the corresponding structure of spatial segments and parameter update time lines, and generates a full-scene sound field scheduling basis set. The full-scene sound field scheduling basis set includes stage combination classification items, key spatial node temporal positions, and a spatial parameter path overview table.

10. The theme-following 3D immersive sound field big data management system according to claim 9, characterized in that, The full-scenario scheduling decision module includes: The stage combination extraction submodule, based on the period segment number in the periodic sound field scheduling pressure distribution map, detects whether there is an overlapping interval between the parameter update frequency peak and the spatial node arrangement, extracts the period number that satisfies the dual conditions of update concentration and spatial overlap, records the associated spatial node number and parameter number under each period, establishes the correspondence between period and spatial parameter combination, and generates a concentrated stage combination list. The instruction node integration submodule calls the set of spatial node numbers and parameter numbers in the centralized stage combination list to obtain the time tag of the spatial node and the corresponding parameter update sequence identifier. It groups the parameter update behavior within the stage according to the start and end time of the spatial node, and integrates the path sequence of parameter update behavior in chronological order to construct the combination structure of spatial segment and acoustic behavior segment, thus obtaining the stage spatial parameter path mapping table. The decision basis summary submodule identifies the node sequence of parameter update in each stage according to the combination structure of spatial parameter segment in the stage spatial parameter path mapping table, and standardizes it into a standard instruction format. It summarizes the spatial node number, parameter number and sequence number fields of all stage combinations and integrates them into a continuous executable data structure sequence to establish a full-scene sound field scheduling basis set.

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