Teaching data transmission method, device, server and system and storage medium

Abstract

The invention provides a teaching data transmission method and device, a server, a system and a storage medium, and the method comprises the steps that an edge server carries out the first data analysis processing of teaching data in a teaching environment based on an artificial intelligence analysis algorithm, and obtains initial teaching data; performing encryption processing on the initial teaching data to obtain target teaching data; sending the target teaching data to a cloud server; and receiving a teaching analysis report returned by the cloud server, wherein the teaching analysis report is obtained by analyzing the target teaching data. According to the technical scheme, the data security of the teaching data can be improved.

Description

Technical Field

[0001] The present application relates to the field of Internet teaching technology, and in particular to a teaching data transmission method, device, server, system and storage medium. Background Art

[0002] With the continuous development of teaching technology, teaching aids such as multimedia classrooms, Internet teaching platforms, and teaching data transmission systems are also constantly being updated and iterated. Among them, the teaching data transmission system is mainly implemented based on cloud servers. It is necessary to upload the audio and video data, student learning data, homework data, etc. collected in the teaching environment to the cloud server for analysis by the cloud server. However, the data collected during the teaching process often involves the privacy of students. Cloud servers are usually provided by third parties, which are prone to the risk of privacy leakage. Summary of the invention

[0003] The present application provides a teaching data transmission method, device, server, system and storage medium to solve the technical problem in the prior art that uploading teaching data to a cloud server easily causes the risk of privacy leakage.

[0004] In a first aspect, a teaching data transmission method is provided, which is applied to an edge server, and the method includes: performing a first data analysis process on the teaching data in the teaching environment based on an artificial intelligence analysis algorithm to obtain initial teaching data; encrypting the initial teaching data to obtain target teaching data; sending the target teaching data to a cloud server; and receiving a teaching analysis report returned by the cloud server, wherein the teaching analysis report is obtained based on the analysis of the target teaching data.

[0005] In combination with the first aspect, in a possible implementation method, the first data analysis and processing of the teaching data in the teaching environment based on the artificial intelligence analysis algorithm, before obtaining the initial teaching data, also includes: receiving the teaching data in the teaching environment collected by the recording device, the teaching data in the teaching environment at least includes: audio and video data in the teaching environment, students' learning situation data, and homework data.

[0006] In combination with the first aspect, in a possible implementation method, a first data analysis and processing is performed on the teaching data in the teaching environment based on an artificial intelligence analysis algorithm to obtain initial teaching data, including: extracting first audio and video data and first homework data of each student based on the student's learning situation data; performing a first data analysis and processing on the first audio and video data and the first homework data based on an artificial intelligence analysis algorithm to obtain initial behavior data of each student; and associating the initial behavior data of each student with the corresponding learning situation data to obtain initial teaching data.

[0007] In combination with the first aspect, in a possible implementation method, the teaching data in the teaching environment is subjected to a first data analysis and processing based on an artificial intelligence analysis algorithm to obtain initial teaching data, including: extracting second audio and video data and second homework data of each classroom based on the students' learning situation data; performing a second data analysis and processing on the second audio and video data and second homework data based on an artificial intelligence analysis algorithm to obtain initial interaction data of each classroom; and associating the initial interaction data of each classroom with the corresponding learning situation data to obtain initial teaching data.

[0008] In combination with the first aspect, in a possible implementation method, encrypting the initial teaching data to obtain target teaching data includes: encrypting the initial teaching data based on a homomorphic encryption algorithm to obtain target teaching data.

[0009] In a second aspect, a teaching data transmission method is provided, which is applied to a cloud server, and the method includes: receiving target teaching data sent by an edge server, wherein the target teaching data is teaching data processed based on a homomorphic encryption algorithm; performing a third data analysis process based on the target teaching data to obtain a teaching analysis report; and returning the teaching analysis report to the edge server.

[0010] In combination with the second aspect, in a possible implementation method, the third data analysis and processing is performed on the target teaching data to obtain a teaching analysis report, including: after decrypting the target teaching data based on a private key of a homomorphic encryption algorithm, the third data analysis and processing is performed on the target teaching data to obtain a teaching analysis report.

[0011] In a third aspect, a teaching data transmission device is provided, and the teaching data transmission device includes: a first processing module, which is used to perform a first data analysis process on the teaching data in the teaching environment based on an artificial intelligence analysis algorithm to obtain initial teaching data; the first processing module is also used to encrypt the initial teaching data to obtain target teaching data; a first communication module is used to send the target teaching data to a cloud server; the first communication module is also used to receive a teaching analysis report returned by the cloud server, and the teaching analysis report is obtained based on the analysis of the target teaching data.

[0012] In a fourth aspect, a teaching data transmission device is provided, which includes: a second communication module, used to receive target teaching data sent by an edge server, wherein the target teaching data is teaching data processed based on a homomorphic encryption algorithm; a second processing module, used to perform a third data analysis and processing based on the target teaching data to obtain a teaching analysis report; the second communication module is also used to return the teaching analysis report to the edge server.

[0013] In a fifth aspect, an edge server is provided, comprising a memory, a processor and a transceiver, wherein the memory and the transceiver are connected to the processor, the transceiver is used to send or receive data, and the processor is used to execute one or more computer programs stored in the memory. When the processor executes the one or more computer programs, the edge server implements the method described in the first aspect.

[0014] In a sixth aspect, a cloud server is provided, comprising a memory, a processor and a transceiver, wherein the memory and the transceiver are connected to the processor, the transceiver is used to send or receive data, and the processor is used to execute one or more computer programs stored in the memory. When the processor executes the one or more computer programs, the edge server implements the method described in the second aspect.

[0015] In a seventh aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor executes the teaching data transmission method of the first aspect or the second aspect.

[0016] In an eighth aspect, a teaching data transmission system is provided, comprising an edge server and a cloud server, wherein the edge server and the cloud server are connected via the Internet, the edge server is used to execute the method described in the first aspect, and the cloud server is used to execute the method described in the second aspect.

[0017] This application can achieve the following technical effects: the edge server performs a first data analysis on the teaching data in the teaching environment based on an artificial intelligence analysis algorithm to obtain initial teaching data, and then encrypts the initial teaching data to obtain target teaching data, and sends the target teaching data to the cloud server for the cloud server to generate a teaching analysis report. This application introduces an edge server, places the teaching data on the edge server for preliminary data analysis and encryption, and then uploads the data to the cloud. While fully utilizing the analysis capabilities of the cloud server, it also ensures that the teaching data is not leaked, thereby improving data security. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a schematic diagram of the architecture of an existing teaching data transmission system;

[0019] Figure 2 A schematic diagram of the architecture of a teaching data transmission system provided in an embodiment of the present application;

[0020] Figure 3A schematic diagram of the architecture of another teaching data transmission system provided in an embodiment of the present application;

[0021] Figure 4 A flow chart of a teaching data transmission method provided in an embodiment of the present application;

[0022] Figure 5 A display effect diagram of a teaching analysis report provided in an embodiment of the present application;

[0023] Figure 6 Another display effect diagram of a teaching analysis report provided in an embodiment of the present application;

[0024] Figure 7 A structural diagram of a teaching analysis device provided in an embodiment of the present application;

[0025] Figure 8 A structural schematic diagram of another teaching analysis device provided in an embodiment of the present application;

[0026] Fig. 9 A schematic diagram of the structure of an edge server provided in an embodiment of the present application;

[0027] Fig.10 A schematic diagram of the structure of a cloud server provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical scheme and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0029] It should be noted that, if there is no conflict, the various features in the embodiments of the present invention can be combined with each other, and all are within the scope of protection of the present invention. In addition, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in a different order from the module division in the device or the flow chart. Furthermore, the words "first", "second", "third", etc. used in the present invention do not limit the data and execution order, but only distinguish the same items or similar items with basically the same functions and effects.

[0030] To describe the present application in more detail, an existing teaching data transmission system is first introduced. Figure 1 , which is a schematic diagram of the architecture of an existing teaching data transmission system. Figure 1The teaching data transmission system 10 shown includes: a data acquisition device 101 and a cloud server 102. When the teaching data transmission system 10 performs teaching data transmission and analysis, the steps including classroom recording, data uploading, cloud data processing and analysis, and result feedback can be implemented through the above devices.

[0031] In the classroom recording step, the data acquisition device 101 can collect audio and video information during classroom teaching. In the data uploading step, the data acquisition device 101 can be connected to the Internet, and the data acquisition device 101 uploads the collected teaching data (such as classroom real-time audio and video data, classroom interaction data, student moral education data, homework data, etc.) to the cloud server in real time through the Internet. In the cloud data processing and analysis step, after the cloud server 102 receives the teaching data, it processes and analyzes the teaching data. In the result feedback step, the cloud server can be connected to the user through the Internet, and the analysis results are fed back to the user based on the Internet.

[0032] It can be seen from the process of teaching data transmission and analysis performed by the above-mentioned existing teaching data transmission system 10 that the classroom real-time audio and video data, student learning data, homework data, etc. generated in the school classroom must be sent to the cloud server for analysis. However, the cloud server is usually provided by a third party, and in order to ensure the multi-dimensionality of the teaching data, it is usually necessary for multiple equipment manufacturers to collect data. If all these teaching data are uploaded to the cloud server at the same time, the multi-dimensional teaching data is very likely to have the risk of student privacy leakage, and the data security of data storage and analysis is low.

[0033] In view of this, this application proposes a teaching data transmission method, device, server, system and storage medium, which can improve the data security of teaching data and avoid privacy leakage. Figure 2 , is a schematic diagram of the architecture of a data transmission system provided in an embodiment of the present application, Figure 2 The teaching data transmission system 20 shown includes: an edge server 201, a cloud server 202, and a recording device 203, wherein the edge server 201 and the cloud server 202 perform data transmission via the Internet.

[0034] In one embodiment, the edge server 201 is a computing device located in an edge computing network for processing data and performing computing tasks. Among them, edge computing is a distributed computing model that aims to process and store data as close as possible to where the data is generated. By using edge servers for edge computing, data transmission delays and network bandwidth consumption can be reduced. As a feasible implementation method, the edge server 201 can be deployed locally, such as in a school, or in a place close to a teaching environment such as a classroom.

[0035] In one embodiment, the cloud server 202 is a virtual server based on cloud computing technology, which may not rely on specific physical hardware, but runs in the data center of a cloud service provider. Users can access and manage the cloud server 202 through the Internet.

[0036] In one embodiment, the recording device 203 includes a fixed device and / or a mobile device deployed in a teaching environment. For example, the fixed device deployed in the teaching environment can be a camera, a microphone, etc. deployed in a classroom, and the mobile device can be a camera and a microphone on a tablet computer or a mobile phone, etc. In order to capture the teaching content more comprehensively, the camera can be deployed in a position that can cover the entire teaching environment, such as the front and side of the classroom, etc., and the microphone can be deployed in a position that can receive the voices of teachers and students, such as a teacher's podium, a student's seat, etc. At the same time, the student's homework data, the student's learning data, etc. can also be collected by a mobile device and sent to the edge server 201.

[0037] In one embodiment, the teaching data transmission system 20 may further include a user terminal for receiving and viewing the teaching analysis report. The user terminal may be deployed in a browser or a dedicated application access server, and may include a teacher user terminal, an educational institution user terminal, and a student user terminal.

[0038] As an example of the teaching data transmission system 20, please refer to Figure 3 , is a teaching data transmission system 30 provided in an embodiment of the present application. According to different data transmission communication modes, the teaching data transmission system 30 can be divided into an intranet part and an Internet part. Among them, the intranet shown in the intranet part can be a local area network deployed in the teaching place (such as a school), which is limited to transmitting data within a fixed physical distance range, while the Internet part is not limited by the physical distance and can transmit data anywhere there is an Internet network.

[0039] The intranet part includes an edge server, a classroom observation system, and an operation system, and the Internet part includes a cloud server, on which a classroom analysis system can be deployed. Among them, multiple recording devices can be deployed in the classroom observation system and the operation system to collect teaching data. In some embodiments, corresponding processors such as computers can also be configured in the classroom observation system and the operation system. In some feasible implementations, the recording device can also be used as a processor.

[0040] For example, the homework system can collect students' homework data and students' learning data, and send them to the classroom observation system. The classroom observation system can collect audio and video data during the teaching process, and send the students' homework data, students' learning data and the audio and video data to the edge server for preliminary analysis and processing. After the edge server performs preliminary analysis and processing, the processed data is sent to the cloud server via the Internet. The cloud server can provide the classroom analysis system with multi-dimensional data analysis to generate a classroom analysis report.

[0041] The teaching data transmission method involved in the present application is described in detail below. The teaching data transmission method can be implemented by the teaching data transmission systems 20 and 30 mentioned above. Figure 4 , Figure 4 The teaching data transmission method shown may specifically include the following steps:

[0042] S401, the recording device sends the teaching data in the teaching environment to the edge server.

[0043] It should be noted that the recording device collects the teaching data in the teaching environment and sends the teaching data in the teaching environment to the edge server. The edge server receives the teaching data in the teaching environment and performs the following processing in S402.

[0044] In a feasible implementation manner, the teaching data in the teaching environment at least includes: audio and video data in the teaching environment, students' learning data, and homework data.

[0045] As a feasible implementation, the user can directly start recording the audio and video data in the teaching environment through the recording device. For example, when the recording device is a mobile device such as a tablet computer in the classroom, the tablet computer can be configured with a recording module, and the user can directly call the camera and microphone of the tablet computer through the recording module to start recording the audio and video data in the teaching environment.

[0046] As a feasible implementation, the recording device can be turned on before the teaching starts and turned off after the teaching ends. The recording device can also be adjusted according to the actual teaching situation, for example, the camera can be adjusted according to the movement of the teacher, and the microphone can be adjusted according to the volume of the speech.

[0047] As a feasible implementation method, when the recording device is a mobile device such as a tablet computer, the mobile device can also serve as a user terminal. The user can do homework, fill in or select academic data (such as personal name, class, student number, course identification, etc.) on the mobile device. The recording device can generate homework data and student academic data based on the user's operations, and upload them to the edge server.

[0048] S402. The edge server performs a first data analysis on the teaching data in the teaching environment based on an artificial intelligence analysis algorithm to obtain initial teaching data.

[0049] It is agreed in this article that the initial teaching data described in this application refers to the preliminary structured data obtained after processing the teaching data in the teaching environment based on an artificial intelligence analysis algorithm.

[0050] It should be noted that structured data refers to data that is organized and stored according to certain rules and formats, usually presented in the form of tables or databases, where each data item has specific fields and values. This type of data is easy to query, analyze and process because the data structure is clear and can be easily indexed and sorted by rows and columns.

[0051] In one embodiment, the teaching data in the teaching environment sent by the recording device may be unstructured data, which is presented in the form of text, images, audio, etc. After receiving the teaching data, the edge server may process it based on the artificial intelligence analysis algorithm to generate structured data, which is easier to use for data encryption, data analysis, and other processing.

[0052] In a feasible implementation, the artificial intelligence analysis algorithm may include a convolutional neural network (CNN) algorithm, target detection models yolov4, yolov6, yolov7, and residual network Resnet18, etc. For example, the Resnet18 can be specifically used to analyze the learning data in the teaching data for target detection, and the target detection model can be specifically used to analyze the audio and video data and homework data in the teaching data for behavior detection.

[0053] In a feasible implementation, the student's academic data may include the student's personal name, class, student number, course ID, as well as the student's biometric information such as facial information, fingerprint information, and voice information.

[0054] In one embodiment, the S402 step may include: extracting first audio and video data and first homework data of each student based on the student's learning situation data; performing first data analysis processing on the first audio and video data and first homework data based on an artificial intelligence analysis algorithm to obtain initial behavior data of each student; and associating the initial behavior data of each student with the corresponding learning situation data to obtain initial teaching data.

[0055] For example, the edge server can extract the first audio and video data containing the student based on the student's biological information, and can extract the student's homework data based on the student's personal name, student number and other information. Then, the first data analysis and processing can be performed on the first audio and video data and the first homework data based on the target detection model, residual network Resnet 18 and other artificial intelligence analysis algorithms to obtain the initial behavior data of each student, which is used to characterize the performance of the corresponding student in classroom learning. Finally, the edge server can associate the obtained initial behavior data of each student with the corresponding learning situation data to obtain the initial teaching data.

[0056] For another example, the initial behavior data can be the comprehensive mastery of a student's knowledge points in class, such as student A's knowledge point interaction (raising hands\answering) score of a point, knowledge point classroom exercise score of b points, and knowledge point homework mastery of c points.

[0057] In another embodiment, the S402 step may include: the edge server extracts the second audio and video data and the second homework data of each class according to the student's learning data; performs a second data analysis on the second audio and video data and the second homework data based on an artificial intelligence analysis algorithm to obtain the initial interaction data of each class; and associates the initial interaction data of each class with the corresponding learning data to obtain initial teaching data.

[0058] For another example, the edge server can extract the second audio and video data corresponding to the classroom identifier and the second homework data of each student in the corresponding classroom according to the classroom identifier in the learning information. Then, the second audio and video data and the second homework data can be subjected to second data analysis based on the target detection model, residual network Resnet 18 and other artificial intelligence analysis algorithms to obtain the initial interaction data of each classroom, which is used to characterize the interaction between teachers and students in the classroom. Finally, the edge server can associate the obtained initial interaction data of each classroom with the corresponding learning data to obtain the initial teaching data.

[0059] S403: The edge server encrypts the initial teaching data to obtain target teaching data.

[0060] In one embodiment, the step S403 may include:

[0061] S4031: The edge server encrypts the initial teaching data based on a homomorphic encryption algorithm to obtain target teaching data.

[0062] This article stipulates that the target teaching data refers to the data sent by the edge server to the cloud server for data analysis.

[0063] It should be noted that the homomorphic encryption algorithm is a special type of encryption algorithm that allows some computing operations to be performed in an encrypted state without decrypting the data. This feature enables homomorphic encryption to perform privacy computing while protecting data privacy, thereby performing a series of operations on encrypted data, making it easier for subsequent cloud servers to perform data analysis and processing to avoid privacy leaks. The homomorphic encryption algorithm of the embodiment of the present application may be a Paillier homomorphic encryption algorithm.

[0064] For example, when the initial teaching data is teaching data for students, the edge server can obtain the comprehensive mastery of a student's knowledge points based on the initial teaching data, such as extracting the knowledge point interaction (raising hands\answering) score a, the knowledge point classroom exercise score b, and the knowledge point homework mastery score c of the student identified as student A from the learning situation data in the initial teaching data; the Paillier homomorphic encryption algorithm is performed on the knowledge point interaction (raising hands\answering) score a, the knowledge point classroom exercise score b, and the knowledge point homework mastery score c of student A to obtain E(a), E(b), E(c) and the calculation function PP.

[0065] S404: The edge server sends the target teaching data to the cloud server.

[0066] As a feasible implementation method, the edge server can send the target teaching data to the cloud server via the Internet.

[0067] S405. The cloud server receives target teaching data sent by the edge server, where the target teaching data is teaching data processed based on a homomorphic encryption algorithm.

[0068] S406. The cloud server performs a third data analysis process based on the target teaching data to obtain a teaching analysis report.

[0069] This article stipulates that the private key based on the homomorphic encryption algorithm refers to the private key corresponding to the homomorphic encryption processing of the initial teaching data by the edge server.

[0070] It should be noted that after the cloud server receives the target teaching data, it can decrypt the target teaching data based on the private key of the homomorphic encryption algorithm, and perform comprehensive calculation and analysis on the target teaching data to obtain a teaching analysis report.

[0071] In one embodiment, the third data analysis and processing is performed on the target teaching data to obtain a teaching analysis report, including: after decrypting the target teaching data with a private key based on a homomorphic encryption algorithm, the target teaching data is subjected to a second data analysis and processing to obtain a teaching analysis report.

[0072] As a feasible implementation method, the teaching analysis report may include at least one or more of the classroom interaction between students and teachers, students' mastery of knowledge points, students' behavior analysis, and classroom teaching situation analysis.

[0073] For example, Figure 5 and Figure 6 The figure shows the effects of two teaching analysis reports provided in the embodiment of the present application. Figure 5 It shows the classroom interaction between students and teachers, including the number of questions and answers, the duration of the questions and answers, speech records, speech data analysis, etc. Figure 6 It shows the classroom teaching situation, including the allocation of teaching time, as well as the time series and proportion analysis of teacher teaching data, teacher-student interaction data, and classroom exercise data.

[0074] For example, assuming that the cloud server needs to analyze a student's comprehensive mastery of a knowledge point, the cloud server can extract the knowledge point interaction (raising hands\answering) situation E(a), the knowledge point classroom exercise score E(b), the knowledge point homework mastery situation c score E(c) and the calculation function PP of the student identified as student A from the target teaching data. The cloud server calculates E(a)+E(b)+E(c)=E(a+b+c), and decrypts the data using the private key of the homomorphic encryption algorithm to obtain the value of the data a+b+c, that is, the comprehensive mastery of the knowledge point by student A.

[0075] S407: The cloud server returns the teaching analysis report to the edge server.

[0076] In a feasible implementation, the cloud server can feed back the teaching analysis report to the edge server via the Internet.

[0077] In one embodiment, when the user needs to view the teaching analysis report, he can request the edge server to view it through the user terminal. After receiving the request, the edge server can send the teaching analysis report to the user terminal after verifying that the request is legal.

[0078] For example, when the user terminal and the edge server are in the same local area network, the edge server can send the teaching analysis report to the user terminal through the local area network; when the user terminal and the edge server are not in the same local area network, the edge server can send the teaching analysis report to the user terminal through the Internet.

[0079] It can be seen that the teaching data transmission method shown in the embodiment of the present application introduces an edge server, performs artificial intelligence analysis on the teaching data based on the edge server to form initial teaching data, and then encrypts the initial teaching data through a homomorphic encryption algorithm to obtain target teaching data, which is sent to the cloud server. The cloud server combines the multi-dimensional target teaching data to calculate the classroom analysis report and returns it to the edge server. This not only makes use of the computing power resources of the cloud server to ensure the multi-dimensional analysis and display of the classroom analysis report, but also realizes the "data is available but invisible" on the cloud server, effectively protects privacy data from being leaked, and improves data security.

[0080] The method of the present application is introduced above, and the device of the present application is introduced below.

[0081] See also Figure 7 , Figure 7 is a structural diagram of a teaching data transmission device provided in an embodiment of the present application, which is applied to an edge server, such as Figure 7 As shown, the teaching data transmission device 70 includes:

[0082] The first processing module 701 is used to perform a first data analysis process on the teaching data in the teaching environment based on an artificial intelligence analysis algorithm to obtain initial teaching data.

[0083] The first processing module 701 is further used to encrypt the initial teaching data to obtain target teaching data.

[0084] The first communication module 702 is used to send the target teaching data to the cloud server.

[0085] The first communication module 702 is also used to receive the teaching analysis report returned by the cloud server, and the teaching analysis report is obtained based on the analysis of the target teaching data.

[0086] In a possible design, the first communication module 702 is also used to receive teaching data in a teaching environment collected by a recording device, where the teaching data in the teaching environment at least includes audio and video data in the teaching environment, students' learning data, and homework data.

[0087] In one possible design, the first processing module 701, when used to perform a first data analysis and processing on the teaching data in the teaching environment based on an artificial intelligence analysis algorithm to obtain initial teaching data, is specifically used to: extract the first audio and video data and the first homework data of each student based on the student's learning data; perform a first data analysis and processing on the first audio and video data and the first homework data based on the artificial intelligence analysis algorithm to obtain the initial behavior data of each student; and associate the initial behavior data of each student with the corresponding learning data to obtain initial teaching data.

[0088] In one possible design, the first processing module 701, when used to perform a first data analysis and processing on the teaching data in the teaching environment based on an artificial intelligence analysis algorithm to obtain initial teaching data, is specifically used to: extract second audio and video data and second homework data of each classroom based on the students' learning situation data; perform a second data analysis and processing on the second audio and video data and second homework data based on the artificial intelligence analysis algorithm to obtain initial interaction data of each classroom; and associate the initial interaction data of each classroom with the corresponding learning situation data to obtain initial teaching data.

[0089] In a possible design, when the first processing module 701 is used to encrypt the initial teaching data to obtain target teaching data, it is specifically used to: encrypt the initial teaching data based on a homomorphic encryption algorithm to obtain target teaching data.

[0090] It can be seen that the teaching data transmission device shown in the embodiment of the present application performs artificial intelligence analysis on the teaching data to form initial teaching data, and then encrypts the initial teaching data through a homomorphic encryption algorithm to obtain target teaching data, and sends it to the cloud server. The teaching data can be uploaded to the cloud after preliminary data analysis and encryption processing. While making full use of the analysis capabilities of the cloud server, it also ensures that the teaching data is not leaked, thereby improving data security.

[0091] See also Figure 8 , Figure 8 is a structural diagram of another teaching data transmission device provided in an embodiment of the present application, which is applied to an edge server, such as Figure 8 As shown, the teaching data transmission device 80 includes:

[0092] The second communication module 801 is used to receive target teaching data sent by the edge server, where the target teaching data is teaching data processed based on a homomorphic encryption algorithm.

[0093] The second processing module 802 is used to perform a third data analysis process based on the target teaching data to obtain a teaching analysis report.

[0094] The second communication module 801 is further used to return the teaching analysis report to the edge server.

[0095] In one possible design, when the second processing module 802 is used to perform a third data analysis and processing on the target teaching data to obtain a teaching analysis report, it is specifically used to: after decrypting the target teaching data based on a private key of a homomorphic encryption algorithm, perform a third data analysis and processing on the target teaching data to obtain a teaching analysis report.

[0096] It can be seen that the teaching data transmission device shown in the embodiment of the present application performs data analysis on the target teaching data obtained from the edge server, generates a teaching analysis report, and then feeds back the teaching analysis report to the edge server. Since the target teaching data is processed based on the homomorphic encryption algorithm, the security of the teaching data can be fully guaranteed when analyzing based on the teaching data transmission device. Then, based on the ecological teaching analysis of the target teaching data, the analysis capability of the teaching data transmission device can be fully utilized.

[0097] See also Fig. 9 , Fig. 9 1 is a schematic diagram of the structure of an edge server provided in an embodiment of the present application, wherein the edge server 90 includes a processor 901, a memory 902, and a transceiver 903. The memory 902 is connected to the processor 901, for example, via a bus.

[0098] The processor 901 is configured to support the Bluetooth device 90 to perform the corresponding functions in the method in the above method embodiment. The processor 901 can be a central processing unit (CPU), a network processor (NP), a hardware chip or any combination thereof. The above hardware chip can be an application specific integrated circuit (ASIC), a programmable logic device (PLD) or a combination thereof. The above PLD can be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL) or any combination thereof.

[0099] The memory 902 is used to store program codes, etc. The memory 902 may include a volatile memory (VM), such as a random access memory (RAM); the memory 902 may also include a non-volatile memory (NVM), such as a read-only memory (ROM), a flash memory, a hard disk drive (HDD) or a solid-state drive (SSD); the memory 902 may also include a combination of the above-mentioned types of memories.

[0100] The transceiver 903 is used to transmit data.

[0101] The processor 901 may call the program code to perform the following operations:

[0102] Performing a first data analysis and processing on the teaching data in the teaching environment based on an artificial intelligence analysis algorithm to obtain initial teaching data;

[0103] Encrypting the initial teaching data to obtain target teaching data;

[0104] Sending the target teaching data to a cloud server;

[0105] Receive the teaching analysis report returned by the cloud server, where the teaching analysis report is obtained based on the analysis of the target teaching data.

[0106] See also Fig.10 , Fig.10 1 is a schematic diagram of the structure of a cloud server provided in an embodiment of the present application, wherein the cloud server 100 includes a processor 1001, a memory 1002, and a transceiver 1003. The memory 1002 is connected to the processor 1001, for example, via a bus.

[0107] The specific structure of the processor 1001, memory 1002 and transceiver 1003 can be referred to the aforementioned Fig. 9 The corresponding structural description of each component will not be repeated here.

[0108] The processor 1001 may call the program code to perform the following operations:

[0109] Receive target teaching data sent by the edge server, where the target teaching data is teaching data processed based on a homomorphic encryption algorithm;

[0110] Performing a third data analysis process according to the target teaching data to obtain a teaching analysis report;

[0111] The teaching analysis report is returned to the edge server.

[0112] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a computer, the computer executes the method described in the above embodiment.

[0113] A person skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0114] The above disclosure is only the preferred embodiment of the present application, which certainly cannot be used to limit the scope of rights of the present application. Therefore, equivalent changes made according to the claims of the present application are still within the scope covered by the present application.

Claims

1. A teaching data transmission method, characterized in that: Applied to an edge server, the method comprises: Performing a first data analysis and processing on the teaching data in the teaching environment based on an artificial intelligence analysis algorithm to obtain initial teaching data; Encrypting the initial teaching data to obtain target teaching data; Sending the target teaching data to a cloud server; Receive the teaching analysis report returned by the cloud server, where the teaching analysis report is obtained based on the analysis of the target teaching data.

2. The method according to claim 1, characterized in that Before the first data analysis and processing of the teaching data in the teaching environment is performed based on the artificial intelligence analysis algorithm to obtain the initial teaching data, the method further includes: The teaching data in the teaching environment collected by the recording device is received, and the teaching data in the teaching environment at least includes: audio and video data in the teaching environment, students' learning data, and homework data.

3. The method according to claim 2, characterized in that The first data analysis and processing is performed on the teaching data in the teaching environment based on the artificial intelligence analysis algorithm to obtain initial teaching data, including: Extracting first audio and video data and first homework data of each student according to the student's learning data; Performing a first data analysis process on the first audio and video data and the first homework data based on an artificial intelligence analysis algorithm to obtain initial behavior data of each student; The initial behavior data of each student is associated with the corresponding learning situation data to obtain initial teaching data.

4. The method according to claim 2, characterized in that The first data analysis and processing is performed on the teaching data in the teaching environment based on the artificial intelligence analysis algorithm to obtain initial teaching data, including: Extracting second audio and video data and second homework data of each class according to the student's learning data; Performing a second data analysis process on the second audio and video data and the second homework data based on an artificial intelligence analysis algorithm to obtain initial interaction data of each class; The initial interaction data of each class is associated with the corresponding learning situation data to obtain initial teaching data.

5. The method according to claim 3 or 4, characterized in that The step of encrypting the initial teaching data to obtain target teaching data comprises: The initial teaching data is encrypted based on a homomorphic encryption algorithm to obtain target teaching data.

6. A teaching data transmission method, characterized in that: Applied to a cloud server, the method includes: Receive target teaching data sent by the edge server, where the target teaching data is teaching data processed based on a homomorphic encryption algorithm. Performing a third data analysis process according to the target teaching data to obtain a teaching analysis report; The teaching analysis report is returned to the edge server.

7. The method according to claim 6, characterized in that The third data analysis process is performed according to the target teaching data to obtain a teaching analysis report, including: After decrypting the target teaching data using a private key based on a homomorphic encryption algorithm, the target teaching data is subjected to a third data analysis process to obtain a teaching analysis report.

8. A teaching data transmission device, characterized in that: The teaching data transmission device comprises: A first processing module, used to perform a first data analysis process on the teaching data in the teaching environment based on an artificial intelligence analysis algorithm to obtain initial teaching data; The first processing module is further used to encrypt the initial teaching data to obtain target teaching data; A first communication module, used for sending the target teaching data to a cloud server; The first communication module is also used to receive a teaching analysis report returned by the cloud server, where the teaching analysis report is obtained based on the analysis of the target teaching data.

9. A teaching data transmission device, characterized in that: The teaching data transmission device comprises: A second communication module is used to receive target teaching data sent by the edge server, where the target teaching data is teaching data processed based on a homomorphic encryption algorithm; A second processing module is used to perform a third data analysis process according to the target teaching data to obtain a teaching analysis report; The second communication module is also used to return the teaching analysis report to the edge server.

10. An edge server, characterized in that: The device comprises a memory, a processor and a transceiver, wherein the memory and the transceiver are connected to the processor, the transceiver is used to send or receive data, and the processor is used to execute one or more computer programs stored in the memory. When the processor executes the one or more computer programs, the edge server implements the method according to any one of claims 1 to 5.

11. A cloud server, characterized in that: It includes a memory, a processor and a transceiver, wherein the memory and the transceiver are connected to the processor, the transceiver is used to send or receive data, and the processor is used to execute one or more computer programs stored in the memory. When the processor executes the one or more computer programs, the cloud server implements the method as claimed in claim 6 and / or 7.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which includes program instructions. When the program instructions are executed by a processor, the processor executes the method according to any one of claims 1 to 5 or 6 and / or 7.

13. A teaching data transmission system, characterized in that: It includes an edge server and a cloud server, the edge server and the cloud server are connected via the Internet, the edge server is used to execute the method as described in any one of claims 1-5, and the cloud server is used to execute the method as described in claims 6 and / or 7.

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