Virtual space interaction data management and storage system and method thereof

Abstract

A virtual space interaction data management and storage system and a method thereof are provided, by connecting a data acquisition device and an arithmetic device, the data acquisition device senses the operation of a user in a virtual space in real time to generate virtual space interaction data, and then the arithmetic device performs data preprocessing and event stream processing on the virtual space interaction data to obtain virtual space interaction data. And the obtained preprocessed data is stored in a corresponding database according to data attributes, so that instant retrieval and operation of a virtual space operation engine are provided, and the technical effects of improving the processing efficiency and operation instantaneity of heterogeneous data are achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to a data management and storage system and method thereof, in particular, a virtual space interactive data management and storage system and method thereof. BACKGROUND

[0002] In recent years, with the popularity and vigorous development of virtual reality (VR) and augmented reality (AR) technology, various virtual space applications have emerged like mushrooms after rain, among which, multi-person real-time interaction and high-fidelity simulation are the most eye-catching.

[0003] Generally speaking, the conventional virtual space data management technology usually uses a single structured database to store user interaction data and virtual object states. However, when facing huge, high-speed, and heterogeneous data generated from different elements, devices, and sensors, this approach is prone to have low data storage efficiency, query delay, and other problems due to different data types. Therefore, the conventional data management approach has the problems of being difficult to integrate, classify, and efficiently utilize heterogeneous data in real time.

[0004] In view of this, some manufacturers have proposed a distributed database technology, which uses a distributed architecture to improve the data processing performance of virtual space. However, this approach cannot effectively manage multiple data types and simultaneously meet the demand for real-time response, so it is still insufficient to solve the problems of poor processing performance of heterogeneous data and insufficient computational immediacy in virtual space.

[0005] In summary, it can be seen that there has been a problem of poor processing performance of heterogeneous data and insufficient computational immediacy for a long time in the prior art, so it is necessary to propose an improved technical means to solve this problem. SUMMARY

[0006] The present application discloses a virtual space interactive data management and storage system and method thereof.

[0007] First, the present application discloses a virtual space interaction data management and storage system, which comprises a data acquisition device and a computing device. The data acquisition device is used to generate virtual space interaction data by instantaneously sensing user operations in a virtual space through sensors, wherein the virtual space interaction data comprises virtual object state data generated when a user operates a virtual object in a virtual space. Then, the computing device is connected to the data acquisition device and receives the virtual space interaction data, and comprises a data preprocessing module, a hybrid data storage module, and an instant query and calculation module. The data preprocessing module is used to perform data preprocessing and event stream processing (ESP), and converts the virtual space interaction data into preprocessed data by selecting one or any combination of format standardization, noise removal, data filtering conversion, and timestamp integration, wherein the preprocessed data comprises one or any combination of time series data, interaction connection data, and unstructured data. The hybrid data storage module is connected to the data preprocessing module and comprises a time series database, a graph database, and a file database, and is used to store the preprocessed data identified as time series data in the time series database, store the preprocessed data identified as interaction connection data in the graph database, and store the preprocessed data identified as unstructured data in the file database. The instant query and calculation module is connected to the hybrid data storage module and has an application programming interface (API) unit, which is used to receive a query request from a virtual space running engine, and according to the data attributes of the query request, select one or any combination of the time series database, the graph database, and the file database to query the preprocessed data that meets the query request to perform statistical analysis, so that the virtual space running engine performs operations according to the queried preprocessed data and the results of statistical analysis.

[0008] In addition, the present application also discloses a virtual space interactive data management and storage method, which comprises the following steps: connecting a data acquisition device and a computing device, wherein the data acquisition device instantaneously senses user operations in a virtual space through a sensor to generate virtual space interactive data, the virtual space interactive data comprising virtual object state data generated when a user operates a virtual object in the virtual space; the computing device receives the virtual space interactive data from the data acquisition device, and performs data preprocessing and event stream processing, and converts the virtual space interactive data into preprocessed data by selecting one or any combination of format standardization, noise removal, data filtering conversion, and timestamp integration, wherein the preprocessed data comprises one or any combination of time series data, interactive connection data, and unstructured data; the computing device stores the preprocessed data identified as time series data in a time series database, stores the preprocessed data identified as interactive connection data in a graph database, and stores the preprocessed data identified as unstructured data in a file database; and the computing device has an application program interface unit for receiving query requests issued by a virtual space running engine, and according to the data attributes of the query requests, queries the preprocessed data that meets the query requests from one or any combination of the time series database, the graph database, and the file database to perform statistical analysis, so that the virtual space running engine performs operations according to the preprocessed data and the results of the statistical analysis.

[0009] The system and method disclosed by the present application are different from the prior art in that the present application connects a data acquisition device and a computing device, instantaneously senses user operations in a virtual space through the data acquisition device to generate virtual space interactive data, and then performs data preprocessing and event stream processing on the virtual space interactive data by the computing device, and stores the obtained preprocessed data in corresponding databases according to data attributes, so as to provide the virtual space running engine with instant retrieval and operation.

[0010] Through the above technical means, the present application can achieve the technical effects of improving the processing efficiency of heterogeneous data and the instantaneity of operations. BRIEF DESCRIPTION OF DRAWINGS

[0011] Figure 1 A system block diagram of the virtual space interactive data management and storage system of the present application.

[0012] Figures 2A-2C A method flowchart of the virtual space interactive data management and storage method of the present application.

[0013] Figure 3 A schematic diagram of the application of the present application in a virtual conference field.

[0014] Figure 4Fig. 1 is a schematic diagram of the hardware architecture of the computing device of the present application.

[0015] Reference numerals:

[0016] 110, 310: data acquisition device

[0017] 120, 320: computing device

[0018] 121, 321: data preprocessing module

[0019] 122, 322: hybrid data storage module

[0020] 122a, 322a: time-series database

[0021] 122b, 322b: graph database

[0022] 122c, 322c: file database

[0023] 123, 324: instant query and computation module

[0024] 323: data synchronization and compression module

[0025] 325: security and access control module

[0026] 400: computing device

[0027] 411: hardware processor

[0028] 412: memory

[0029] 413: network interface device

[0030] 414: network

[0031] 415: display device

[0032] 416: graphical user interface

[0033] 417: input device

[0034] 418: data storage device

[0035] 419: bus

[0036] Step 210: connecting a data acquisition device and a computing device, wherein the data acquisition device instantaneously senses user operations in a virtual space through sensors to generate virtual space interaction data, the virtual space interaction data comprising at least one virtual object state data generated when a user operates at least one virtual object in the virtual space

[0037] Step 220: The operation device receives the virtual space interaction data from the data acquisition device, and performs data preprocessing and event stream processing, and selects one or any combination of format standardization, noise removal, data filtering conversion and timestamp integration to convert the virtual space interaction data into preprocessed data, wherein the preprocessed data includes one or any combination of time series data, interaction connection data and unstructured data

[0038] Step 230: The operation device stores the preprocessed data identified as the time series data to a time series database, stores the preprocessed data identified as the interaction connection data to a graph database, and stores the preprocessed data identified as the unstructured data to a file database

[0039] Step 240: The operation device has an application program interface unit to receive a query request issued from a virtual space running engine, and according to the data attributes of the query request, selects one or any combination of the time series database, the graph database and the file database to query the preprocessed data that meets the query request to perform statistical analysis, so that the virtual space running engine performs operation according to the preprocessed data queried out and the result of the statistical analysis DETAILED DESCRIPTION

[0040] The embodiments of the present application will be described in detail with reference to the drawings and examples, so that the implementation process of how the present application applies technical means to solve technical problems and achieve technical effects can be fully understood and implemented.

[0041] Please refer to Figure 1 , Figure 1 is a system block diagram of a virtual space interaction data management and storage system of the present application, which includes a data acquisition device 110 and an operation device 120. The data acquisition device 110 generates virtual space interaction data by instantaneously sensing user operations in a virtual space through sensors, and the virtual space interaction data includes virtual object state data generated when a user operates a virtual object in a virtual space. In actual implementation, the virtual space interaction data can include one or any combination of gestures, eye movements, voice instructions, controller inputs and spatial movement trajectories. In addition, the virtual object state data can include one or any combination of position, rotation, scaling and collision state. In other words, the virtual space interaction data refers to data generated by sensors (such as sensing elements provided in a head-mounted display, gesture trackers, voice microphones, controllers, etc.) for instant sensing, such as gesture data, eye movement parameters, voice instruction content, controller trigger state and spatial coordinate trajectory, etc. original data.

[0042] Then, at a portion of the computing device 120, which is connected to the data acquisition device 110 and receives the virtual space interaction data, the computing device 120 includes a data preprocessing module 121, a hybrid data storage module 122, and an instant query and calculation module 123. The data preprocessing module 121 is used to perform data preprocessing and event stream processing, and converts the virtual space interaction data into preprocessed data by selecting one or any combination of format standardization (e.g., uniformly converting data from different sensors into a common data format), noise removal (e.g., filtering out redundant detection noise or outliers to improve data accuracy), data filtering conversion (e.g., retaining only interaction data of specific time ranges or specific object operations), and timestamp integration (e.g., synchronizing and comparing each item of data according to time to establish correct time sequence correlation). The preprocessed data includes one or any combination of time series data (e.g., continuous recording of user eye movement trajectories), interaction connection data (e.g., association information between multiple user interaction operations), and unstructured data (e.g., voice files of voice instructions or text descriptions of virtual objects). For example, in the case of format standardization, the data can be converted into a uniform encoding, such as UTF-8. In the case of noise removal, median filtering, Chi-Square Test, etc. can be used. In the case of data filtering conversion, a threshold can be set to filter out invalid operations. In the case of timestamp integration, cross-device synchronization can be performed through the Network Time Protocol (NTP). In addition, the event stream processing can be performed using a processing unit with hardware event detection function, such as ESP32, or using an industry common event stream platform, such as Apache Kafka, Flink, etc., to perform instant data distribution and aggregation to achieve event stream processing.

[0043] The hybrid data storage module 122 is connected to the data preprocessing module 121 and contains a time-series database 122a, a graph database 122b, and a file database 122c, to store the preprocessed data identified as time-series data to the time-series database 122a, the preprocessed data identified as interactive connection data to the graph database 122b, and the preprocessed data identified as unstructured data to the file database 122c. In practice, the time-series database 122a (e.g., InfluxDB, TimescaleDB) is used to store the time-series data of user interactions and object states; the graph database 122b (e.g., Neo4j) is used to store the interactive relationships and social connections between users and virtual objects; and the file database 122c (e.g., MongoDB) is used to store complex virtual object attributes and unstructured description data. For example, when a user performs a gesture operation in a virtual space, the hand coordinates and time information can be stored as time-series data; if multiple users pass virtual objects to each other in a collaborative work platform, the interactive associations will be stored in a graph structure; and voice content, photographic images are stored in unstructured format in the file database 122c. In fact, the hybrid data storage module 122 will identify data with timestamps as time-series data, data with source nodes and destination nodes as interactive connection data, and data containing free text or multimedia files as unstructured data.

[0044] The instant query and calculation module 123 is connected to the hybrid data storage module 122 and has an application program interface unit to receive query requests from the virtual space running engine and select one or any combination of the time series database 122a, the graph database 122b and the file database 122c according to the data attributes of the query request to query the preprocessed data that meets the query request to perform statistical analysis, so that the virtual space running engine performs operation according to the preprocessed data and the result of the statistical analysis. In actual implementation, the statistical analysis can include one or any combination of user hotspot analysis (e.g. calculating the most frequently gazed or operated area in the virtual space), user behavior pattern prediction (e.g. predicting subsequent actions according to historical operation trends) and load balancing operation (e.g. automatically adjusting data processing resources according to the distribution of users), and in the process of statistical analysis, one or any combination of graph analysis (e.g. social network correlation strength calculation) and time series data aggregation technology (e.g. calculating user interaction frequency according to time interval) is allowed. In fact, the application program interface unit can use RESTful architecture design and support HTTP POST / GET query, and the return format is preset as JSON. When data query error occurs (e.g. database offline, no data found, etc.), the corresponding error code and information can be returned to provide front-end or engine for exception handling. It is particularly pointed out that although the time series data aggregation technology is illustrated above, the application is not limited thereto, and any technology for summarizing and calculating data arranged in time sequence (e.g. statistical data of a specific time interval) is within the application scope of the application.

[0045] It is particularly pointed out that, in actual implementation, each module of the present application can be partially or completely realized based on hardware, for example, can be realized through a hardware processor such as an integrated circuit chip, a system on chip (SoC), a complex programmable logic device (CPLD), a field programmable gate array (FPGA), etc. The hardware processor executes a computer program realizing the present application, and the computer program is stored in a computer readable storage medium, i.e., a computer readable storage medium loaded with computer readable program instructions for enabling the hardware processor to realize various aspects of the present application. The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium can be, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the above. More specific examples (a non-exhaustive list) of the computer readable storage medium include a hard disk, a random access memory, a read-only memory, a flash memory, an optical disk, a floppy disk, and any suitable combination of the above. The computer readable storage medium used herein is not to be interpreted as a transitory signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission media (for example, an optical signal propagating through an optical fiber cable), or an electrical signal transmitted through a wire. In addition, the computer readable program instructions described herein can be downloaded from the computer readable storage medium to each computing / processing device, or to an external computer device or an external storage device through a network such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include a copper transmission cable, a fiber optic transmission, a wireless transmission, a router, a firewall, a switch, a hub, and / or a gateway. The network card or network interface in each computing / processing device receives the computer readable program instructions from the network and forwards the computer readable program instructions to the computer readable storage medium stored in each computing / processing device. The computer program instructions for performing the operations of the present application can be combination language instructions, instruction set architecture instructions, machine instructions, machine related instructions, microinstructions, firmware instructions, or original code or object code written in any combination of one or more programming languages, including object-oriented programming languages such as Common Lisp, Python, C++, Objective-C, Smalltalk, Delphi, Java, Swift, C#, Perl, Ruby, and PHP, and conventional procedural programming languages such as C language or similar programming languages.The computer program instructions can execute entirely on the computer, partly on the computer, partly on a client computer, partly on a remote computer or entirely on the remote computer or server.

[0046] Referring to Figures 2A-2C , Figures 2A-2C A method flowchart of a virtual space interactive data management and storage method of the present application includes the following steps: connecting a data acquisition device 110 and a computing device 120, wherein the data acquisition device 110 instantaneously senses user operations in a virtual space through sensors to generate virtual space interactive data, the virtual space interactive data including virtual object state data generated when a user operates a virtual object in a virtual space (step 210); the computing device 120 receives virtual space interactive data from the data acquisition device 110, performs data preprocessing and event stream processing, and converts the virtual space interactive data into preprocessed data by selecting one or any combination of format standardization, noise removal, data filtering conversion, and timestamp integration, wherein the preprocessed data includes one or any combination of time series data, interactive connection data, and unstructured data (step 220); the computing device 120 stores preprocessed data identified as time series data to a time series database 122a, stores preprocessed data identified as interactive connection data to a graph database 122b, and stores preprocessed data identified as unstructured data to a file database 122c (step 230); and the computing device 120 has an application program interface unit to receive query requests issued by a virtual space running engine, and according to the data attributes of the query requests, selects one or any combination of the time series database 122a, the graph database 122b, and the file database 122c to query preprocessed data that meets the query request to perform statistical analysis, so that the virtual space running engine performs operations according to the queried preprocessed data and the results of the statistical analysis (step 240). Through the above steps, the data acquisition device 110 instantaneously senses user operations in a virtual space to generate virtual space interactive data by connecting the data acquisition device 110 and the computing device 120, the computing device 120 performs data preprocessing and event stream processing on the virtual space interactive data, and stores the obtained preprocessed data according to the data attributes to the corresponding database, so as to provide the virtual space running engine with instant retrieval and operation.

[0047] In addition, as shown in FIG. 2B, after step 230, the operation device 120 can perform data synchronization and consistency maintenance on the distributed virtual space through the synchronization controller, and perform data compression algorithm on the pre-processed data stored in the time-series database 122a, the graph database 122b and the file database 122c (step 231). In addition, as shown in FIG. 2B, after step 240, the operation device 120 can perform hierarchical access permission control on the queried pre-processed data according to one or any combination of user identity, data classification and sensitive information, and deploy to the blockchain, so that the queried pre-processed data has tamper resistance (step 250). Figure 2C

[0048] The following is described by way of example with reference to the accompanying drawings in which: Figure 3 Figure 4 The following is described by way of example with reference to the accompanying drawings in which: Figure 3 Figure 3 is a schematic diagram of applying the present application to the field of virtual meeting. The system of the present application can be applied to a virtual meeting platform, and each participant enters the same virtual space through a device such as a head-mounted display and collaborates. At this time, the data acquisition device 310 can capture the gestures, voice instructions and eye movement information of each participant (or user) in real time through sensors, and generate virtual space interaction data containing state parameters (such as position, rotation, collision, etc.) of virtual objects. Next, the data preprocessing module 321 of the operation device 320 performs data preprocessing and event stream processing on the virtual space interaction data, and can select one or any combination of format standardization, noise removal, data filtering and conversion, and timestamp integration to convert the virtual space interaction data into pre-processed data. Then, the hybrid data storage module 322 can store and classify according to attributes, for example, operation sequences and movement trajectories are stored in the time-series database 322a, inter-user collaborative operation and object interaction association are stored in the graph database 322b, and voice recordings and text annotations are stored in the file database 322c. It is particularly important to note that, unlike the prior art, the present application can perform data preprocessing and event stream processing on the virtual space interaction data in real time, and can perform data compression on the pre-processed data stored in the time-series database 122a, the graph database 122b and the file database 122c, so that the pre-processed data has tamper resistance and can be queried and accessed in a hierarchical manner according to user identity, data classification and sensitive information. Figure 1 ​​​The system block diagram of FIG. 1, in this example, the present application can also include a data synchronization and compression module 323 connected to the hybrid data storage module 322, for performing data synchronization and consistency maintenance on the distributed virtual space by a synchronization controller, and performing data compression algorithm on the pre-processed data stored in the time-series database 322a, the graph database 322b and the file database 322c. In actual implementation, the synchronization controller can use a distributed consensus protocol (such as Paxos, Raft) to ensure the consistency and synchronization of data among the distributed nodes, and to prevent data loss or conflict. In addition, the data compression algorithm can use different data types, such as LZ4 compression (suitable for efficient compression and fast decompression of time-series data), GraphZip algorithm (using dictionary compression algorithm to instantly find structural patterns and repeated subgraphs in graph stream to reduce storage or transmission volume, indirectly achieving similar compression effect), and unstructured file compression algorithm (such as ZIP, GZIP), etc., to improve the overall storage efficiency and query performance.

[0049] Subsequently, when the virtual space running engine generates a query request (such as querying the collaboration hot zone in the past 5 minutes, analyzing all user interactions and participation on virtual objects, or predicting the operation behavior of a user, etc.), the computing device 320 will load the required pre-processed data from the corresponding database according to the data attributes of the query request, and perform hotspot analysis, behavior prediction, load distribution and other statistical analysis on these data, and then return the statistical analysis results and the pre-processed data to the virtual space running engine for operation. In this way, in the multi-user collaboration, object-rich and interactive-intensive virtual space environment, it can effectively deal with the practical scenarios of heterogeneous data instant processing and integrated analysis, and correspond to the appropriate database structure and query mechanism for specific data types, greatly improving the operation efficiency and system instant reaction ability.

[0050] In addition, in this example, the application can also include a security and access control module 325 connected to the instant query and calculation module 324 to perform hierarchical access permission control on the pre-processed data queried out according to one or any combination of user identity, data classification and sensitivity information, and deploy to the blockchain so that the pre-processed data queried out has tamper-proof property. In actual implementation, the security and access control module 325 can integrate a role-based access control (RBAC) mechanism to assign query permissions according to different levels, for example: only high-privilege users can query sensitive interaction behavior data; at the same time, the pre-processed data can be written into the blockchain in a hash value manner by combining the distributed ledger technology (DLT) (such as Ethereum blockchain) to ensure its tamper-proof, traceable, effectively improve data security and credibility. For example, when the data is marked as high sensitivity, only authorized administrators can query in the RBAC system. When the data is written into the blockchain, SHA256 can be used to calculate the hash, and the hash value is written into the Ethereum smart contract. If there is any tampering, the smart contract comparison will be inconsistent, and the administrator will be notified immediately and displayed on the front-end display interface.

[0051] As Figure 4 illustrated, Figure 4 is a schematic diagram of the hardware architecture of the edge server of the application. In the computing device 400, a plurality of computer executable instructions (hereinafter referred to as instructions) are used to drive the machine to execute any one or more methods discussed in the application. In other embodiments, the machine can be connected (for example: network connection) to other machines in a local area network, an internal network, an external network or an Internet network. The machine can run as a server or a client in a client-server network environment, or as a peer machine in a peer-to-peer network environment, and the machine can also act as a network device, a server, a router, a switch or a bridge, an event generator, a distributed node, a centralized system, or any machine capable of executing a set of instructions (whether sequential or other forms) that specify the actions to be taken by the machine. In addition, although only one machine is illustrated, the term "machine" should also be considered to include a collection of any machines (for example: tablet computers) that can individually or jointly execute a set (or multiple sets) of instructions to perform any one or more methods discussed in the application.

[0052] The computing device 400, such as a desktop computer, a notebook computer, a tablet computer, a server, a smart phone, or the like, includes a hardware processor 411, a memory 412 (e.g., read-only memory, flash memory, dynamic random access memory, non-volatile resistive random access memory, embedded flash memory, or ferroelectric random access memory (FeRAM)), a network interface device 413, a display device 415, an input device 417, and a data storage device 418 (which can include a fixed or removable computer readable storage medium), which are in communication over a bus 419.

[0053] The hardware processor 411 can be a microprocessor, a central processing unit (CPU), or the like. More particularly, the hardware processor 411 can be a complex instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, or a processor implementing other instruction sets or instruction set architectures, or a combination of these. Further, the hardware processor 411 can be a base processor or general purpose processor that implements a plurality of instruction sets or instruction set architectures (ISAs). Still further, the hardware processor 411 can be a special purpose processor, such as a network processor, a communication processor, a media processor, a multi-core processor, or the like. In one embodiment, the hardware processor 411 executes various software elements stored in the memory 412 to perform various functions for the computing device 400. In one embodiment, these software elements include an operating system, a compiler element, and a communication module (or instruction set). The operating system includes various procedures, instructions sets, software elements, and / or drivers for handling general system tasks, and facilitates communication between various hardware and software elements. The compiler is a computer program (or set of programs) that converts source code written in a programming language into another computer language (e.g., an object code, an object language). The communication module can communicate with other devices through the network interface device 413. The network interface device 413 is connected to a network 414 (e.g., a local area network, a wide area network) to communicate with other devices.

[0054] The memory 412 can store program codes and / or data for use by the hardware processor 411. The memory 412 can be implemented using a random access memory (e.g., SRAM, DRAM, DDRAM), a ROM, a magnetic and / or optical storage device, a flash memory, or any combination thereof. The memory 412 can also include a transmission medium to carry information-bearing signals representing instructions or data (which can be modulated signals with or without carrier wave).

[0055] The display device 415, such as a Liquid Crystal Display (LCD), LED, or Cathode Ray Tube (CRT), is connected to the computer system through the display port and the graphic chipset, and provides a Graphic User Interface (GUI) 416 for the user to operate. In actual implementation, the display device 415 can also be a touch screen or similar device with input and display functions. In addition, the input device 417 (such as a keyboard, mouse, touchpad, etc.) can provide user input instructions and generate trigger signals.

[0056] The data storage device 418 can include a machine-readable storage medium (or more specifically, a computer-readable storage medium) that stores one or more instruction sets embodying any one or more of the methods or functions described herein. The disclosed data storage mechanism can be implemented entirely or at least partially in the memory 412. The data storage device 418 and the memory 412 disclosed in the computing device 400 can be configured to implement data storage mechanisms for performing the operations and steps discussed herein.

[0057] In one example, the computing device 400 is an Internet of Things (IoT) device that can be connected (e.g., networked) to other machines in a local area network, a wide area network, or any network. The computing device 400 can be a distributed system including a plurality of interconnected computers. The computers can act as servers or clients in a client-server network environment, or as peer machines in a peer-to-peer (or distributed) network environment.

[0058] In summary, the difference between the present application and the prior art is that the data acquisition device is connected to the computing device, the virtual space interaction data is generated by the data acquisition device in real time to sense the user's operation in the virtual space, the virtual space interaction data is pre-processed and event stream processed by the computing device, and the pre-processed data obtained is stored in the corresponding database according to the data attribute, so as to provide real-time retrieval and operation of the virtual space running engine. Through this technical means, the problems existing in the prior art can be solved, and the technical effects of improving the processing efficiency of heterogeneous data and the real-time operation are achieved.

[0059] Although the present application is disclosed with the above-mentioned embodiments, it is not intended to limit the present application, and any person skilled in the art can make some changes and modifications without departing from the spirit and scope of the present application. Therefore, the patent protection scope of the present application should be subject to the scope defined by the claims attached to the present specification.

Claims

1. A system for managing and storing virtual space interactive data, the system comprising: A data acquisition device is used to sense user operations in a virtual space in real time through sensors to generate virtual space interaction data, the virtual space interaction data including at least one virtual object status data generated when the user operates at least one virtual object in the virtual space. as well as A computing device, connected to the data acquisition device, and receiving the virtual space interaction data, the computing device comprising: The data preprocessing module performs data preprocessing and event stream processing, and selects one or any combination of format standardization, noise removal, data filtering and transformation, and timestamp integration to convert the virtual space interaction data into preprocessed data. The preprocessed data includes one or any combination of time-series data, interactive connection data, and unstructured data; A hybrid data storage module, connected to the data preprocessing module, includes a time-series database, a graph database, and a file database, for storing the preprocessed data identified as time-series data in the time-series database, storing the preprocessed data identified as interactive connection data in the graph database, and storing the preprocessed data identified as unstructured data in the file database. as well as The real-time query and calculation module, connected to the hybrid data storage module, and having an application programming interface (API), is used to receive query requests from the virtual space operation engine. Based on the data attributes of the query request, it selects one or any combination of the time-series database, the graphics database, and the file database to retrieve the preprocessed data matching the query request for statistical analysis. This allows the virtual space operation engine to perform calculations based on the retrieved preprocessed data and the results of the statistical analysis.

2. The virtual space interactive data management and storage system as described in claim 1, wherein the system further includes a data synchronization and compression module connected to the hybrid data storage module, for performing data synchronization and consistency maintenance on the distributed virtual space through a synchronization controller, and performing data compression algorithms to compress the preprocessed data stored in the time-series database, the graphics database and the file database.

3. The virtual space interactive data management and storage system as described in claim 1, wherein the system further includes a security and access control module connected to the real-time query and calculation module, for performing hierarchical access control on the queried preprocessed data based on one or any combination of user identity, data classification and sensitivity information, and deploying it to the blockchain to make the queried preprocessed data immutable.

4. The virtual space interaction data management and storage system as described in claim 1, wherein the virtual space interaction data includes one or any combination of gestures, eye movements, voice commands, controller inputs, and spatial movement trajectories, and the virtual object state data includes one or any combination of position, rotation, scaling, and collision states.

5. The virtual space interactive data management and storage system as described in claim 1, wherein the statistical analysis includes one or any combination of user hotspot analysis, user behavior pattern prediction and load balancing operation, and allows the simultaneous use of one or any combination of graphical analysis and time series data aggregation technology during the statistical analysis process.

6. A method for managing and storing interactive data in virtual space, comprising the following steps: A data acquisition device and a computing device are connected. The data acquisition device uses a sensor to sense user operations in the virtual space in real time to generate virtual space interaction data. The virtual space interaction data includes at least one virtual object status data generated when the user operates at least one virtual object in the virtual space. The computing device receives the virtual space interaction data from the data acquisition device, and performs data preprocessing and event stream processing. It selects one or any combination of format standardization, noise removal, data filtering and conversion, and timestamp integration to convert the virtual space interaction data into preprocessed data. The preprocessed data includes one or any combination of time-series data, interactive connection data, and unstructured data. The computing device stores the preprocessed data identified as time-series data in a time-series database, stores the preprocessed data identified as interactive connection data in a graphics database, and stores the preprocessed data identified as unstructured data in a file database; and The computing device has an application programming interface (API) unit for receiving query requests from the virtual space operation engine, and then selecting one or any combination of the time-series database, the graphics database, and the file database according to the data attributes of the query request to retrieve the preprocessed data that matches the query request for statistical analysis, so that the virtual space operation engine can perform calculations based on the retrieved preprocessed data and the results of the statistical analysis.

7. The method for managing and storing virtual space interactive data as described in claim 6, wherein the method further comprises performing data synchronization and consistency maintenance on the distributed virtual space through a synchronization controller, and performing a data compression algorithm to compress the preprocessed data stored in the time-series database, the graphics database and the file database.

8. The method for managing and storing virtual space interactive data as described in claim 6, wherein the method further comprises performing hierarchical access control on the queried preprocessed data based on one or any combination of user identity, data classification and sensitivity information, and deploying it to a blockchain to make the queried preprocessed data immutable.

9. The method for managing and storing virtual space interactive data as described in claim 6, wherein the virtual space interactive data includes one or any combination of gestures, eye movements, voice commands, controller inputs, and spatial movement trajectories, and the virtual object state data includes one or any combination of position, rotation, scaling, and collision states.

10. The method for managing and storing virtual space interactive data as described in claim 6, wherein the statistical analysis includes one or any combination of user hotspot analysis, user behavior pattern prediction and load balancing operation, and allows the simultaneous use of one or any combination of graph analysis and time series data aggregation technology during the statistical analysis process.

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