Data medium station management system and centralized data processing method

Abstract

The invention discloses a data center management system and a centralized data processing method.The system is arranged between a cloud server and local equipment and comprises a cloud synchronization module, an equipment management module, a data exchange layer and a core controller, the cloud synchronization module is used for encrypting and backing up data of local equipment to a cloud server according to a preset time interval; the equipment management module is used for controlling the state and data output of local equipment through a remote issuing mode or a local control mode; the data exchange layer is used for carrying out data exchange on a cloud server and local equipment through any one communication protocol of TCP, WebSocket, MQTT and HTTP; and the core controller is used for receiving data of the cloud server and the local equipment and carrying out data processing and protocol conversion according to communication protocols of different data sources. According to the scheme, the data interaction efficiency and the real-time performance of terminal equipment control can be improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a data center management system, a centralized data processing method, a computing device and a storage medium. Background Art

[0002] In the campus AI sports application scenario, the deep integration of artificial intelligence vision and sports education can realize large-scale testing of student sports through IoT terminals, AI sports vision algorithms, and AI sports computing platforms. With the increase in the number of IoT terminals (such as AI smart runway, AI sit-ups, AI standing long jump, AI skipping, long-distance running sign-in machines, etc.), the demand for centralized control of local data is also growing.

[0003] In order to utilize big data technology and integrate data assets through global planning, data middle platform came into being. However, the existing data middle platform system has problems such as low data interaction efficiency, inflexible device control, and poor real-time performance. Summary of the invention

[0004] In view of the above technical problems, the present invention provides a data middle-end management system and a centralized data processing method, which completes data exchange and real-time synchronization between local devices and cloud servers through conversion of multiple communication protocols, thereby improving data interaction efficiency and real-time control of terminal devices.

[0005] According to a first aspect of the present invention, there is provided a data middle-office management system, which is arranged between a local device and a cloud server, and includes a cloud synchronization module, a device management module, a data exchange layer and a core controller, wherein the cloud synchronization module is used to encrypt and back up the data of the local device to the cloud server at a preset time interval; the device management module is used to control the status and data output of the local device through a remote delivery mode or a local control mode; the data exchange layer is used to exchange data between the cloud server and the local device through any one of the communication protocols including TCP, WebSocket, MQTT, and HTTP; the core controller is used to receive data from the cloud server and the local device, and perform data processing and protocol conversion according to the communication protocols of different data sources.

[0006] By adopting the above technical solutions, the data exchange layer supports multiple communication protocols such as TCP, WebSocket, MQTT, HTTP, etc., so that the system can adapt to different network environments and equipment requirements and enhance compatibility. The core controller can process data and convert protocols according to the communication protocols of different data sources, simplifying the data processing process, responding to and processing various data sources in real time, and improving the efficiency and accuracy of data exchange.

[0007] Optionally, in the data middle-station management system provided by the present invention, the device management module integrates control protocols of multiple local devices, and the local devices include cameras and algorithm boxes. The cameras are used to collect motion videos of people in real time, and the algorithm boxes are used to perform facial image quality evaluation on the video data stream collected by the cameras, and transmit facial images with image quality that meets preset standards to the core controller.

[0008] The above technical solution integrates the control protocols of multiple local devices, enabling the system to uniformly manage multiple devices. The algorithm box performs facial image quality assessment on the video data stream collected by the camera. Only facial images that meet the image quality assessment standards are transmitted to the core controller. This screening mechanism can reduce unnecessary data transmission, improve data transmission efficiency, and reduce the demand for network bandwidth.

[0009] Optionally, in the data middle-office management system provided by the present invention, the core controller has a built-in face recognition module for receiving face images transmitted by the algorithm box, receiving face data sent by the cloud server through a long connection communication protocol, extracting face features in the face image based on the face recognition algorithm, and comparing the extracted face features with the face data sent by the cloud server, obtaining face matching results based on a preset similarity threshold, determining personnel identity information based on the face matching results, and synchronizing the personnel identity information to the cloud server after protocol conversion.

[0010] In the above technical solution, the face recognition module built into the core controller can receive the face image transmitted by the algorithm box in real time, and promptly receive and process the face data sent by the cloud server through the long connection communication protocol. This real-time response capability enables the system to complete face feature extraction and comparison in the shortest time, thereby quickly confirming the identity information of the person.

[0011] Optionally, in the data middle-station management system provided by the present invention, the algorithm box is also used to detect and judge the movement posture of people in the video data stream, generate detection data on whether the people have abnormal movements, and transmit the detection data to the core controller.

[0012] In the above technical solution, the detection data generated by the algorithm box can be effectively transmitted to the core controller and integrated and analyzed with the data generated by the face recognition module, so that the system can comprehensively consider multiple data sources and improve the ability to judge and respond to security incidents.

[0013] Optionally, in the data middle station management system provided by the present invention, the local device also includes an IP sound column, and the core controller is used to generate a sound column playback instruction according to the detection data of the algorithm box or control the corresponding IP sound column to broadcast or stop broadcasting according to the sound column playback instruction remotely issued by the cloud server.

[0014] In the above technical solution, the core controller serves as the center of the system, centrally managing and controlling the playback behavior of all sound columns. Through a unified control interface, it can effectively manage the broadcasting actions of multiple sound columns to ensure the consistency and synchronization of the broadcasting instructions.

[0015] Optionally, in the data middle-station management system provided by the present invention, the data exchange layer is used to receive data from the cloud synchronization module and the device management module, decode and verify the integrity of the data, and encode the verified data according to the protocol of the target device and send it to the target device.

[0016] The above technical solution can effectively prevent data from being tampered with or damaged through the verification mechanism, thereby improving the reliability of data transmission.

[0017] Optionally, in the data middle-office management system provided by the present invention, the system reserves a peripheral device interface for configuring peripheral data processing and interaction functions by importing a new device docking protocol, and exchanging data between the cloud server and the functional modules connected to the peripheral device interface.

[0018] The above technical solutions can quickly and flexibly expand the functions and capabilities of the system, support the access of more types of peripheral devices, and thus meet the ever-changing business needs.

[0019] According to a second aspect of the present invention, a centralized data processing method is provided, which is suitable for execution in the data middle station management system described in the first aspect of the present invention, comprising: Receive facial data and control instructions sent by the cloud server through any communication protocol including TCP, WebSocket, MQTT, and HTTP; convert the control instructions sent by the cloud server into a protocol and send them to the corresponding local device; receive facial images collected by the local device through the device docking protocol, compare the facial images with the facial data, and obtain facial matching results; convert the facial matching results and the detection data of the local device into a protocol and report them to the cloud server.

[0020] The above technical solution effectively connects cloud control with data collection, processing and feedback of local devices, and realizes centralized data processing and management through unified data management and protocol conversion.

[0021] The present invention also provides a computing device, comprising: at least one processor and a memory storing program instructions, wherein the program instructions are configured to be suitable for execution by the at least one processor, and the program instructions include instructions for executing the above-mentioned centralized data processing method.

[0022] The present invention also provides a readable storage medium storing program instructions. When the program instructions are read and executed by a computing device, the computing device executes the above-mentioned centralized data processing method.

[0023] The data middle station management system and centralized data processing method provided by the present invention can at least achieve the following technical effects: 1. By integrating the control protocols of multiple local devices, the core controller can uniformly receive and process data from cloud servers and local devices, and perform data processing and protocol conversion according to different communication protocols, ensuring the consistency and efficiency of data processing; 2. The system can respond to and process data from multiple data sources in real time, improving data interaction efficiency and real-time control of terminal devices.

[0024] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings: Figure 1 A schematic diagram of the structure of a data center management system according to an embodiment of the present invention is shown; Figure 2 A schematic flow chart of a centralized data processing method 200 according to an embodiment of the present invention is shown; Figure 3 FIG. 1 shows a structural diagram of a computing device 100 according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to build a highly integrated AI sports management system, this solution connects local devices and cloud servers through a local area network to achieve real-time monitoring and data management of sports items.

[0027] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0028] The data middle-office management system is set up between local devices and cloud servers, and cameras, algorithm boxes, sound columns and other devices are deployed in the local area network to ensure seamless data interaction between them through corresponding protocols. Figure 1 FIG. 1 shows a schematic diagram of the structure of a data center management system according to an embodiment of the present invention. Figure 1 As shown, the data middle-end management system includes a cloud synchronization module, a device management module, a data exchange layer and a core controller.

[0029] The cloud synchronization module is used to encrypt and back up the data of the local device to the cloud server at a preset time interval. The cloud synchronization module can achieve data synchronization and consistency between the cloud server and the local device. For example, the cloud synchronization module can regularly back up local data to the cloud to deal with local data loss or system failure.

[0030] It can also achieve data synchronization between multiple local devices. For example, after a user creates or modifies data on one device, the cloud synchronization module will synchronize these data changes to other devices, ensuring that users can access the latest data on any device and avoid information deviation due to data lag. At the same time, in order to improve data security, the cloud synchronization module encrypts and stores data, and only authorized users can access and modify the data.

[0031] The device management module is used to control the status and data output of local devices through remote delivery mode or local control mode. Since local devices, such as sound columns and cameras, have different control interfaces, the device management module integrates a variety of control protocols for local devices. For example, local devices include IP sound columns, cameras, algorithm boxes, etc. The algorithm box and the core controller use the TCP protocol for data docking, and the camera and the core controller interact with each other through the SDK.

[0032] In the remote sending mode, the device management module can forward the control instructions issued by the cloud server to the target device to realize remote control of the local device. In the local control mode, the device management module can directly interact with the local device for data, for example, receiving the operating status and sensor data returned by the device.

[0033] The data exchange layer is used to exchange data between the cloud server and the local device through any of the communication protocols TCP, WebSocket, MQTT, and HTTP. The system can select the appropriate protocol to optimize the efficiency and stability of data exchange according to different application requirements and network environments. For example, for scenarios that require real-time data updates and low latency, you can use the WebSocket or MQTT protocol; and for applications that transfer files or ensure data reliability, you can use the TCP protocol. Therefore, the data exchange layer can realize the rapid verification, data exchange, and control command issuance of data transmitted between the cloud server and the local device, ensuring that the system can respond to and manage information from multiple data sources and devices in a timely manner.

[0034] The core controller is used to receive data from cloud servers and local devices, and perform data processing and protocol conversion according to the communication protocols of different data sources. For example, the core controller can convert hexadecimal data into JSON format, and perform operations such as data decryption and field conversion. According to the communication protocol requirements of different devices or systems, protocol conversion and unified processing can ensure data consistency and availability.

[0035] According to an embodiment of the present invention, the local device includes an IP sound column, a camera, an algorithm box, etc. The IP sound column can remind athletes to prepare for the game and issue instructions for the start of the game through voice. The camera is used to collect sports videos of people in real time for face recognition and motion detection. The algorithm box is used to evaluate the face image quality of the video data stream collected by the camera, and transmit the face image that meets the preset image quality standard to the core controller.

[0036] The core controller has a built-in face recognition module, which is used to receive face images transmitted by the algorithm box, receive face data sent by the cloud server through a long connection communication protocol, extract face features in the face image based on the face recognition algorithm, and compare the extracted face features with the face data sent by the cloud server. The face matching result is obtained according to the preset similarity threshold, and the identity information of the person is determined based on the face matching result. The identity information of the person is synchronized to the cloud server after protocol conversion.

[0037] The algorithm box can also detect and judge the movement posture of people in the video data stream, generate detection data of whether people have abnormal movements (whether they cross the line), and transmit the detection data to the core controller. The core controller generates a sound column playback instruction based on the detection data of the algorithm box, or controls the corresponding IP sound column to broadcast or stop broadcasting according to the sound column playback instruction sent remotely by the cloud server.

[0038] For example, in the AI ​​running test project, first install and deploy hardware devices such as cameras, algorithm boxes, and sound columns in the local area network. Then send instructions to local devices through the cloud server, such as voice prompts athletes to start running, and the algorithm box calls the camera to obtain real-time video streams, detect the athlete's face and posture, identify the athlete's information, and determine whether the line is crossed. After the athlete finishes running, the algorithm box reports the facial information and running completion time to the core controller. The core controller synchronizes data such as facial information, running time, and captured images during exercise to the cloud server for storage and backup, so as to facilitate subsequent data query and statistical analysis.

[0039] For the sound column control instructions sent from the cloud or the control instructions of the local algorithm box, camera, and core controller to the sound column, adaptive data conversion can be performed according to the source of the control instructions, and the instructions that need to be controlled output can be sent to the corresponding sound column. After unified data conversion and synchronous processing of different docking protocols of the system, it can ensure that all data and control instructions are accurately transmitted between different modules.

[0040] In addition, the core controller is highly scalable and configurable. Figure 1 As shown, the data middle-end system has reserved an application peripheral device interface, which can import new data docking protocols, configure peripheral data processing and interaction functions, and exchange data between the cloud server and the functional modules connected to the peripheral device interface.

[0041] Taking AI sports in smart campus as an example, by installing and deploying the data middle platform system in the local area network, configuring the hardware equipment information in AI sports, such as cameras, algorithm boxes, sound columns, etc., and selecting the corresponding protocol for data interaction. The cloud server sends control commands or reports local data to achieve control and status monitoring of the equipment, thereby realizing sports test related to AI sports.

[0042] If you need to access the physical measurement function module, you can configure the peripheral data interaction function in the system, configure the service or client, set the connection mode and the corresponding data instructions. After the physical measurement function module communicates with the core controller, the physical measurement end tells the controller which customized functions are needed and which data processing to perform, such as calling the face interface and returning parameters. The received data is hexadecimal data, which can be converted through scripts, and finally output to the server or controller in json format.

[0043] By sending voice prompts to the sound column, athletes are reminded to prepare for the game. By sending instructions to the algorithm box, the athlete's sports video data stream captured by the camera is called to perform face recognition, sports posture recognition, track recognition, and judgment of whether the line is crossed.

[0044] The sound column announces the names of the athletes on each track and issues the start running command. During the exercise, the algorithm box records the athlete's track, running start time, end time, running results and other competition data, uploads the captured pictures and videos to the core controller synchronously, and saves the data to the cloud server for subsequent data query and statistics. After the run is completed, the sound column broadcasts the running results of the athletes on each track in real time.

[0045] Figure 2 FIG. 2 is a flow chart of a centralized data processing method 200 according to an embodiment of the present invention. Figure 2 As shown, in step S210, the face data and control instructions sent by the cloud server are received through any one of the communication protocols including TCP, WebSocket, MQTT, and HTTP.

[0046] Then in step S220, the control instruction protocol sent by the cloud server is converted and sent to the corresponding local device.

[0047] For example, the algorithm box and the core controller use the TCP protocol for data connection, the camera and the core controller interact with each other through the SDK, and the core controller interacts with the cloud server through the WebSocket protocol. Therefore, the WebSocket protocol control instructions sent by the cloud server can be converted into the SDK format and sent to the camera, and the WebSocket protocol control instructions sent by the cloud server can be converted into the TCP format and sent to the algorithm box.

[0048] In step S230, a facial image collected by a local device is received through a device docking protocol, and the facial image is compared with the facial data to obtain a facial matching result.

[0049] Since the local device contains a variety of AI sports test equipment, such as AI sit-ups, AI running tracks, AI pull-ups, AI rope skipping, AI standing long jump, sign-in machines, etc., face recognition of the tester is required. In order to centrally manage and control the test data of each AI sports test equipment, face image quality assessment and personnel information comparison can be performed in the core controller of the data middle station management system to obtain relevant attribute information of the matching personnel. This is crucial for athlete identification and monitoring in AI sports test projects, and can ensure the fairness of the event and the accuracy of the data.

[0050] Finally, in step S240, the face matching result and the detection data of the local device are converted into a protocol and then uploaded to the cloud server.

[0051] Different local devices send data to the core controller through their own control protocols. The core controller converts and adapts the data of local devices to ensure the uniformity and availability of data formats. Using protocols such as TCP, WebSocket, MQTT or HTTP, the adapted data is transmitted to the cloud server, which ensures that the system can perform efficient data transmission and device control in different scenarios.

[0052] Figure 3 FIG. 1 shows a block diagram of a computing device 100 according to an embodiment of the present invention. Figure 3 As shown, computing device 100 may include memory 106 and processor 104. Memory bus 108 may be used for communication between processor 104 and system memory 106.

[0053] Memory 106 may include operating system 120, applications 122, and program data 124. Applications 122 may be arranged to be executed on the operating system by one or more processors 104 using program data 124. Applications 122 include program instructions for implementing various user desired functions.

[0054] When the computing device 100 starts running, the processor 104 reads and executes the program instructions of the operating system 120 from the memory 106. The application 122 runs on the operating system 120 and uses the interfaces provided by the operating system 120 and the underlying hardware to implement various functions desired by the user. When the user starts the application 122, the application 122 is loaded into the memory 106, and the processor 104 reads and executes the program instructions of the application 122 from the memory 106.

[0055] The computing device 100 also includes a storage device 132 and an output device 142 connected to a storage interface bus 134. An interface bus 140 facilitates communication from various interface devices (eg, output device 142, peripheral interface 144, and communication device 146) via the bus / interface controller 130.

[0056] The peripheral interface 144 may include a serial interface controller 154 and a parallel interface controller 156, which may be configured to facilitate communication with external devices such as input devices (e.g., keyboards, mice, pens, voice input devices, touch input devices) or other peripherals (e.g., printers, scanners, etc.) via one or more I / O ports 158. The communication device 146 may include a network controller 160, which may be arranged to facilitate communication with one or more other computing devices 162 via a network communication link via one or more communication ports 164. In the computing device 100 according to the present invention, the application 122 includes instructions for executing the centralized data processing method 200 of the present invention.

[0057] The data middle station management system and centralized data processing method provided by the present invention can at least achieve the following technical effects: 1. By integrating the control protocols of multiple local devices, the core controller can uniformly receive and process data from cloud servers and local devices, and perform data processing and protocol conversion according to different communication protocols, ensuring the consistency and efficiency of data processing; 2. The system can respond to and process data from multiple data sources in real time, improving data interaction efficiency and real-time control of terminal devices.

[0058] In the description provided herein, a large number of specific details are described. However, it is understood that embodiments of the present invention can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0059] As used herein, unless otherwise specified, the use of ordinal numbers "first," "second," "third," etc. to describe common objects merely indicates that different instances of similar objects are involved, and is not intended to imply that the objects so described must have a given order in time, space, order, or in any other manner.

Claims

1. A data middle-end management system, arranged between a cloud server and a local device, characterized in that: include: A cloud synchronization module, a device management module, a data exchange layer and a core controller, wherein the cloud synchronization module is used to encrypt and back up the data of the local device to the cloud server at preset time intervals; The device management module is used to control the status and data output of the local device through a remote sending mode or a local control mode; the data exchange layer is used to exchange data between the cloud server and the local device through any one of the communication protocols including TCP, WebSocket, MQTT, and HTTP; the core controller is used to receive data from the cloud server and the local device, and perform data processing and protocol conversion according to the communication protocols of different data sources.

2. The data middle station management system according to claim 1 is characterized in that: The device management module integrates control protocols of multiple local devices, and the local devices include cameras and algorithm boxes. The cameras are used to collect motion videos of people in real time, and the algorithm boxes are used to evaluate the facial image quality of the video data stream collected by the cameras, and transmit facial images whose image quality meets preset standards to the core controller.

3. The data middle station management system according to claim 2 is characterized in that: The core controller has a built-in face recognition module, which is used to receive face images transmitted by the algorithm box, receive face data sent by the cloud server through a long connection communication protocol, extract face features in the face image based on the face recognition algorithm, and compare the extracted face features with the face data sent by the cloud server, obtain face matching results based on a preset similarity threshold, determine person identity information based on the face matching results, and synchronize the person identity information to the cloud server after protocol conversion.

4. The data middle station management system according to claim 2 is characterized in that: The algorithm box is also used to detect and judge the motion posture of people in the video data stream, generate detection data of whether the people have abnormal movements, and transmit the detection data to the core controller.

5. The data middle station management system according to claim 4 is characterized in that: The local device also includes an IP sound column, and the core controller is used to generate a sound column playing instruction according to the detection data of the algorithm box or control the corresponding IP sound column to broadcast or stop broadcasting according to the sound column playing instruction remotely issued by the cloud server.

6. The data middle station management system according to claim 1 is characterized in that: The data exchange layer is used to receive data from the cloud synchronization module and the device management module, decode and verify the integrity of the data, and encode the verified data according to the protocol of the target device and send it to the target device.

7. The data middle station management system according to claim 1 is characterized in that: The system reserves a peripheral device interface for configuring peripheral data processing and interaction functions by importing a new device docking protocol, and performing data exchange between a cloud server and a functional module connected to the peripheral device interface.

8. A centralized data processing method, suitable for execution in the data middle station management system described in any one of claims 1 to 7, characterized in that: include: Receive facial data and control instructions sent by the cloud server through any communication protocol including TCP, WebSocket, MQTT, and HTTP; The control instructions sent by the cloud server are converted into protocols and sent to the corresponding local devices; Receiving a facial image collected by a local device through a device docking protocol, comparing the facial image with the facial data, and obtaining a facial matching result; The face matching result and the detection data of the local device are converted into a protocol and then reported to the cloud server.

9. A computing device, characterized in that include: At least one processor; a memory storing program instructions, wherein the program instructions are configured to be suitable for execution by the at least one processor, and the program instructions include instructions for executing the centralized data processing method as claimed in claim 8.

10. A readable storage medium storing program instructions, characterized in that: When the program instructions are read and executed by a computing device, the computing device is caused to execute the centralized data processing method as claimed in claim 8.

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