Information processing method, information processing system, computer equipment and storage medium

Abstract

The invention relates to an information processing method, an information processing system, computer equipment and a storage medium. The method comprises the following steps: for a target scene in a target time interval, acquiring audio and video information for recording the target scene and associated information associated with the target scene in the target time interval; the target scene comprises a target object; based on the audio and video information and the associated information, performing action recognition on the target object to obtain corresponding recognition information; the identification information is an identification result set about the behavior action; based on the identification information, performing event analysis on the target object to obtain a corresponding analysis result report; and the event analysis is used for analyzing a context relationship among the behavior actions in the recognition result set so as to determine a behavior event generated by the target object in the target scene. By adopting the method, the efficiency and accuracy of information processing can be effectively improved, and subsequent reference and optimization of interactive behaviors are facilitated.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to an information processing method, an information processing system, a computer device, a storage medium and a computer program product. Background Art

[0002] Currently, in many interactive scenarios regarding on-site behavioral activities (for example, interactive scenarios regarding teaching behaviors between teachers and students, interactive scenarios regarding business handling between tellers and visiting customers, etc.), it is necessary to record and analyze the interactive behaviors between the two parties in order to draw corresponding analysis conclusions, so as to make reference and optimize subsequent interactive behaviors based on the analysis conclusions.

[0003] In current interactive scenarios, the behavioral information of active objects is recorded manually or the audio and video of active objects are collected through smart terminals such as cameras and microphones, so as to manually analyze the behavioral events generated by active objects in interactive scenarios and draw corresponding analysis conclusions. However, the above methods mainly rely on manual professional experience and meticulous analysis operations, resulting in low efficiency and accuracy of information processing, which is not conducive to the reference and optimization of subsequent interactive behaviors. Summary of the invention

[0004] Based on this, it is necessary to provide an information processing method, information processing system, computer equipment, storage medium and computer program product that can improve the efficiency and accuracy of information processing in response to the above technical problems.

[0005] In a first aspect, the present application provides an information processing method. The method comprises:

[0006] For a target scene within a target time interval, obtain audio and video information recorded for the target scene, and associated information associated with the target scene within the target time interval; wherein the target scene includes a target object;

[0007] Based on the audio and video information and the associated information, the target object is subjected to action recognition to obtain corresponding identification information; the action recognition is used to identify the behavior actions generated by the audio and video information and the associated information about the target object from multiple modal dimensions, and the identification information is a set of identification results about the behavior actions;

[0008] Based on the recognition information, event analysis is performed on the target object to obtain a corresponding analysis result report; the event analysis is used to analyze the contextual relationship between each behavioral action in the recognition result set to determine the behavioral event generated by the target object in the target scene.

[0009] In one embodiment, the step of obtaining audio and video information recorded for the target scene includes:

[0010] In the target time interval, based on a preset audio and video processing program, a camera device preset in the target scene is controlled to record the target scene to obtain a corresponding audio and video stream;

[0011] The audio and video streams are collected and converted to obtain corresponding audio and video information.

[0012] In one embodiment, obtaining the associated information associated with the target scene within the target time interval includes:

[0013] Within the target time interval, the IoT terminal device placed in the target scene is connected based on a preset IoT control platform;

[0014] Based on the control instruction, the IoT terminal device is controlled to perform corresponding functional operations to obtain corresponding association information.

[0015] In one embodiment, obtaining the associated information associated with the target scene within the target time interval includes:

[0016] In the target time interval, the associated resources used by the target object in the target scene are extracted from the storage medium based on a preset resource storage platform to obtain corresponding associated information.

[0017] In one embodiment, the step of performing action recognition on the target object based on the audio and video information and the associated information to obtain corresponding recognition information includes:

[0018] Based on a preset algorithm engine, the audio and video information and the associated information are input into a pre-trained neural network algorithm to perform action recognition on the target object to obtain corresponding recognition information; the neural network algorithm includes at least a visual algorithm, a speech algorithm and a language algorithm;

[0019] The identification information is non-structural information data, and the non-structural information data is based on the target object, action occurrence time and behavior action representation of the symbolic connection.

[0020] In one embodiment, the event analysis is performed on the target object based on the identification information to obtain a corresponding analysis result report, including:

[0021] Based on a preset event analysis platform, the identification information is input into a state machine to perform event analysis on the target object using preset event analysis rules to obtain a corresponding analysis result report;

[0022] The event analysis rules include at least facial expression analysis rules, tone type analysis rules and dialogue text analysis rules for the target object.

[0023] In one embodiment, the method further comprises:

[0024] Obtaining a target hash code generated during the execution of information processing; the target hash code includes a hash code for a program version corresponding to the audio and video processing program, a hash code for the photographic device, a hash code for the audio and video information, a hash code for a platform version corresponding to the IoT control platform, a hash code for the IoT terminal device, a hash code for the functional operation, a hash code for the associated resource, a hash code for an algorithm version corresponding to the algorithm engine, a hash code for the identification information, a hash code for a platform version corresponding to the event analysis platform, and a hash code for the analysis result report;

[0025] Verifying the target hash code to obtain corresponding credential information;

[0026] The credential information is uploaded to the blockchain.

[0027] In a second aspect, the present application also provides an information processing system. The system comprises:

[0028] An information acquisition module, for acquiring, for a target scene within a target time interval, audio and video information recorded for the target scene, and associated information associated with the target scene within the target time interval; wherein the target scene includes a target object;

[0029] An action recognition module is used to perform action recognition on the target object based on the audio and video information and the associated information to obtain corresponding recognition information; the action recognition is used to recognize the action behavior generated by the target object in the audio and video information and the associated information from multiple modal dimensions, and the recognition information is a set of recognition results about the action behavior;

[0030] An event analysis module is used to perform event analysis on the target object based on the recognition information to obtain a corresponding analysis result report; the event analysis is used to analyze the contextual relationship between each action behavior in the recognition result set to determine the behavioral event generated by the target object in the target scene.

[0031] In one embodiment, the information acquisition module includes:

[0032] An audio and video recording unit, configured to control a camera preset in the target scene to record the target scene within the target time interval based on a preset audio and video processing program, and obtain a corresponding audio and video stream;

[0033] An audio and video processing unit is used to use the received control instructions to instruct the photographic device to start or stop recording the target scene, and to collect and convert the audio and video streams to obtain corresponding audio and video information; and to generate a hash code for the program version corresponding to the audio and video processing program, a hash code for the photographic device, and a hash code for the audio and video information.

[0034] In one embodiment, the information acquisition module includes:

[0035] The IoT control platform unit is used to connect the IoT terminal device placed in the target scene based on a preset IoT control platform within the target time interval; and control the IoT terminal device based on control instructions to perform corresponding functional operations to obtain corresponding association information; and generate a hash code for the corresponding platform version of the IoT control platform, a hash code of the IoT terminal device and a hash code of the functional operation.

[0036] In one embodiment, the information acquisition module includes:

[0037] The resource storage platform unit is used to extract the associated resources used by the target object in the target scene from the storage medium based on the preset resource storage platform within the target time interval to obtain corresponding associated information; and generate a hash code for the associated resources.

[0038] In one embodiment, the action recognition module includes:

[0039] An algorithm engine unit is used to input the audio and video information and the associated information into a pre-trained neural network algorithm based on a preset algorithm engine to perform action recognition on the target object and obtain corresponding recognition information; the neural network algorithm at least includes a visual algorithm, a speech algorithm and a language algorithm; wherein the recognition information is unstructured information data, and the unstructured information data is based on symbolically connected target objects, action occurrence time and behavioral action representations; and generate a hash code for the algorithm version corresponding to the algorithm engine and a hash code for the recognition information.

[0040] In one embodiment, the event analysis module includes:

[0041] An event analysis unit is used to input the identification information into a state machine based on a preset event analysis platform, so as to perform event analysis on the target object using preset event analysis rules to obtain a corresponding analysis result report; wherein the event analysis rules at least include facial expression analysis rules, tone type analysis rules and dialogue text analysis rules for the target object; and generate a hash code for the platform version corresponding to the event analysis platform and a hash code for the analysis result report.

[0042] In one embodiment, the information analysis system further includes a blockchain module, and the blockchain module includes:

[0043] The on-chain credential unit is used to obtain the target hash code generated in the process of executing information processing; the target hash code includes a hash code for the program version corresponding to the audio and video processing program, a hash code for the photographic device, a hash code for the audio and video information, a hash code for the platform version corresponding to the IoT control platform, a hash code for the IoT terminal device, a hash code for the functional operation, a hash code for the associated resource, a hash code for the algorithm version corresponding to the algorithm engine, a hash code for the identification information, a hash code for the platform version corresponding to the event analysis platform, and a hash code for the analysis result report; and the target hash code is verified to obtain the corresponding credential information; and the credential information is uploaded to the blockchain.

[0044] In a third aspect, the present application further provides a computer device, including:

[0045] processor;

[0046] a memory for storing executable instructions for the processor;

[0047] The processor is configured to execute the executable instructions to implement the information processing method as described above.

[0048] In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium includes program data, and is characterized in that when the program data is executed, the above-mentioned information processing method is implemented.

[0049] In a fifth aspect, the present application further provides a computer program product, wherein the computer program product includes program instructions, and when the program instructions are executed, the above-mentioned information processing method is implemented.

[0050] The above-mentioned information processing method, information processing system, computer device, storage medium and computer program product, on the one hand, in a manner different from the prior art, perform action recognition on the target object through audio and video information and related information to obtain corresponding recognition information, and then perform event analysis on the target object through the recognition information to obtain a corresponding analysis result report, thereby optimizing the information processing process, effectively improving the efficiency of analyzing the behavioral events generated by the target object in the target scene, and reducing the consumption of manpower and material resources; on the other hand, this scheme identifies the recognition result set of the action behavior generated by the target object in the audio and video information and related information from multiple modal dimensions, and then analyzes the contextual relationship between each action behavior in the recognition result set to determine the behavioral event generated by the target object in the target scene, effectively improving the efficiency and accuracy of information processing, and facilitating the subsequent reference and optimization of interactive behaviors. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description are used to explain the principles of the present disclosure, and do not constitute improper limitations on the present disclosure.

[0052] Figure 1 The present invention is a diagram showing an application environment of an information processing method according to an exemplary embodiment.

[0053] Figure 2 The invention is a flowchart of an information processing method according to an exemplary embodiment.

[0054] Figure 3 It is a flowchart showing the steps of processing a hash code on-chain credential according to an exemplary embodiment.

[0055] Figure 4 The present invention is a flowchart showing steps of performing authentication and verification on a user according to an exemplary embodiment.

[0056] Figure 5 is a block diagram of a first information processing system according to an exemplary embodiment.

[0057] Figure 6 is a block diagram of a second information processing system according to an exemplary embodiment.

[0058] Figure 7 is a block diagram of a third information processing system according to an exemplary embodiment.

[0059] Figure 8 The invention is a block diagram of a computer device for information processing according to another exemplary embodiment. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application 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 application and are not used to limit the present application.

[0061] The terms "first", "second", etc. in this application are used to distinguish different objects, rather than to describe a specific order. In addition, although the terms "first", "second", etc. are used many times to describe various operations (or various thresholds or various applications or various instructions or various elements), etc., these operations (or thresholds or applications or instructions or elements) should not be limited by these terms. These terms are only used to distinguish one operation (or threshold or application or instruction or element) from another operation (or threshold or application or instruction or element).

[0062] The information processing system method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown, the terminal 102 communicates with the server 104 via a communication network. The data storage system can store data that the server 104 needs to process. The data storage system can be integrated on the server 104, or placed on the cloud or other network servers.

[0063] In some embodiments, reference Figure 1 First, the server 104 obtains the audio and video information recorded for the target scene and the associated information associated with the target scene in the target time interval for the target scene in the target time interval; wherein the target scene includes a target object; then, the server 104 performs action recognition on the target object based on the audio and video information and the associated information to obtain corresponding recognition information; wherein the action recognition is used to identify the action behaviors generated by the target object in the audio and video information and the associated information from multiple modal dimensions, and the recognition information is a recognition result set about the action behaviors; finally, the server 104 performs event analysis on the target object based on the recognition information to obtain a corresponding analysis result report; wherein the event analysis is used to analyze the contextual relationship between each action behavior in the recognition result set to determine the behavior event generated by the target object in the target scene.

[0064] In some embodiments, the terminal 102 (such as a mobile terminal, a fixed terminal) can be implemented in various forms. The terminal 102 can be a mobile terminal including a mobile phone, a smart phone, a laptop, a portable handheld device, a personal digital assistant (PDA), a tablet computer (PAD), etc. The terminal 102 can also be a fixed terminal such as an automated teller machine (ATM), an automatic all-in-one machine, a digital TV, a desktop computer, a fixed computer, etc.

[0065] In the following, it is assumed that the terminal 102 is a fixed terminal. However, it will be understood by those skilled in the art that the configuration according to the embodiments disclosed in the present application can also be applied to a mobile type terminal 102 if there are operations or elements specifically for mobile purposes.

[0066] In some embodiments, the data processing component running on the server 104 may load any of a variety of additional server applications and / or middle-tier applications being executed, such as HTTP (Hypertext Transfer Protocol), FTP (File Transfer Protocol), CGI (Common Gateway Interface), RDBMS (Relational Database Management System), etc.

[0067] In some embodiments, the server 104 may be implemented as an independent server or a server cluster consisting of multiple servers. The server 104 may be suitable for running one or more application services or software components that provide the terminal 102 described in the above disclosure.

[0068] In some embodiments, the application service may include a service interface for providing information processing to users, and corresponding program services, etc. Among them, the software component may include an application program (SDK) or a client (APP) that performs the root cause positioning function.

[0069] In some embodiments, the application or client with information processing function provided by server 104 includes a portal port that provides one-to-one application services to users in the foreground and multiple business systems located in the background for information processing, so as to extend the application of information processing function to APP or client, so that users can use and access information processing functions at any time and any place.

[0070] In some embodiments, the user can input corresponding code data or control parameters to the APP or client through a preset input device or automatic control program to execute the application service of the computer program in the server 104 and display the application service in the user interface.

[0071] In some embodiments, the operating system running on the APP or client may include various versions of Microsoft Windows®, Apple Macintosh® and / or Linux operating systems, various commercial or UNIX®-like operating systems (including but not limited to various GNU / Linux operating systems, Google Chrome® OS, etc.) and / or mobile operating systems, such as iOS®, Windows® Phone, Android® OS, BlackBerry® OS, Palm® OS operating systems, and other online operating systems or offline operating systems, without specific limitations here.

[0072] In some embodiments, Figure 2 As shown, an information processing method is provided, which is applied to Figure 1 Taking the server 104 in the example as an example, the method includes the following steps:

[0073] Step S11, for a target scene within a target time interval, obtaining audio and video information recorded for the target scene, and associated information associated with the target scene within the target time interval.

[0074] In one embodiment, the target scene is the application scene in the embodiment of the present application, the target time interval is a time range corresponding to the application scene, and the target scene includes a target object, wherein the target object is a multilateral object that performs interactive behavior in the application scene.

[0075] As an example, the application scenario may be a scenario in which a teacher teaches students in a classroom, the corresponding target objects are the teacher and the students, and the corresponding target time interval is the time range in which the teacher teaches the students; or, the application scenario may be a scenario in which a bank teller handles business for a customer at a counter, the corresponding target objects are the bank teller and the customer, and the corresponding target time interval is the time range in which the bank teller handles business for the customer.

[0076] Furthermore, the target scenario may also be a selection scenario selected by the user account from multiple application scenarios, and the target time interval may be a selection range selected by the user account from multiple time ranges corresponding to the selection scenario.

[0077] As an example, for an education platform, a display interface displays multiple candidate classrooms (including classroom A, classroom B, and classroom C) as candidate scenarios, as well as the course schedules corresponding to each candidate classroom, and each course schedule displays corresponding course information (including course 1, course 2, and course 3 for classroom A; course 4, course 5, and course 6 for classroom B; course 7, course 8, and course 9 for classroom C). Therefore, the user account selects classroom B and course 5 in the course schedule corresponding to classroom B in the display interface, so that classroom B is the target scenario selected by the user account, and the time range of the course corresponding to course 5 is the target time interval selected by the user account.

[0078] Step S12: Based on the audio and video information and the associated information, the target object is subjected to action recognition to obtain corresponding recognition information.

[0079] In one embodiment, action recognition is used to identify behavioral actions generated about a target object in audio and video information and related information from multiple modal dimensions, and the recognition information is a set of recognition results about the behavioral actions.

[0080] Among them, the modality dimension includes at least visual modality, speech modality and language text modality.

[0081] Specifically, the server can input the audio and video information and related information into a pre-trained neural network algorithm based on a preset algorithm engine to perform action recognition on the target object and obtain corresponding recognition information.

[0082] Among them, the neural network algorithm at least includes a visual algorithm, a speech algorithm and a language algorithm.

[0083] In some embodiments, the server inputs the audio and video information and related information into the pre-trained visual algorithm model, speech algorithm model and language algorithm model respectively to perform action recognition on the information about the visual modality, speech modality and language text modality of the target object in the audio and video information and related information to obtain corresponding recognition information.

[0084] In one embodiment, the identification information is non-structural information data, which is based on the target object, the action occurrence time and the identification action representation of the symbolic connection. For example, an identification information is (object S-time T-action P).

[0085] As an example, a target scene is classroom A. The server inputs the audio and video files of Class 1 corresponding to classroom A, the associated information of the intelligent terminal device, and the associated information of the associated resources into the pre-trained visual algorithm model, voice algorithm model, and language algorithm model, respectively, to perform action recognition on the information of the teacher and students in terms of visual modality, voice modality, and language text modality, and obtain the corresponding recognition information. Among them, the recognition information includes: (Teacher-10:00-Writing on the blackboard) and (Student-10:30-Raising hands). Among them, (Teacher-10:00-Writing on the blackboard) represents that the teacher writes on the blackboard at 10:00; (Student-10:30-Raising hands) represents that the student raises his hand in the classroom at 10:30.

[0086] In some embodiments, the algorithm engine may also calculate a hash code of the algorithm version corresponding to its algorithm engine and a hash code of identification information, so as to upload these hash codes to the blockchain for subsequent processing.

[0087] Step S13: Based on the identification information, an event analysis is performed on the target object to obtain a corresponding analysis result report.

[0088] In one embodiment, event analysis is used to analyze the contextual relationship between each behavior action in the recognition result set to determine the behavior event generated by the target object in the target scene.

[0089] In some embodiments, the behavior event is a target event preset by the server, that is, the server determines whether the target object generates a predetermined target event in the target scene by analyzing the contextual relationship between each behavior action in the recognition result set.

[0090] Specifically, the server can input the recognition information into the state machine based on the preset event analysis platform to perform event analysis on the target object using the preset event analysis rules to obtain a corresponding analysis result report. The event analysis rules at least include facial expression analysis rules, tone type analysis rules, and dialogue text analysis rules for the target object.

[0091] As an example, for a scenario in which a teacher is teaching students in a classroom, the state machine uses dialogue text analysis rules to analyze the contextual relationship between each behavior action in the recognition result set for the teacher, so as to determine whether the teacher has taught the important and difficult knowledge in the syllabus during the teaching process.

[0092] As another example, for a scenario in which a teacher is teaching students in a classroom, the state machine uses tone type analysis rules and conversation text analysis rules to analyze the contextual relationship between each behavior action in the recognition result set for the teacher and the student, thereby determining whether the teacher asks questions to the students during the lecture and whether the students answer the questions.

[0093] As another example, for a scenario in which a teacher is teaching students in a classroom, the state machine uses facial expression analysis rules, tone type analysis rules, and conversation text analysis rules to analyze the contextual relationship between each behavioral action in the recognition result set for the students, thereby determining whether students have conducted group discussions among themselves during the class.

[0094] In some embodiments, the event analysis platform may also calculate a hash code of its corresponding platform version and a hash code of the analysis result report to upload these hash codes to the blockchain for subsequent processing.

[0095] The above-mentioned information processing system first obtains the audio and video information recorded for the target scene within the target time interval, as well as the associated information associated with the target scene within the target time interval; wherein the target scene includes a target object; then, based on the audio and video information and the associated information, the target object is subjected to action recognition to obtain corresponding recognition information; action recognition is used to identify the behavioral actions generated about the target object in the audio and video information and the associated information from multiple modal dimensions, and the recognition information is a set of recognition results about the behavioral actions; finally, based on the recognition information, event analysis is performed on the target object to obtain a corresponding analysis result report; event analysis is used to analyze the contextual relationship between each behavioral action in the recognition result set to determine the behavioral event generated by the target object in the target scene. In this way, on the one hand, in a manner different from the prior art, the action of the target object is recognized through audio and video information and related information to obtain corresponding recognition information, and then event analysis is performed on the target object through the recognition information to obtain a corresponding analysis result report, thereby optimizing the information processing process, effectively improving the efficiency of analyzing the behavioral events generated by the target object in the target scene, and reducing the consumption of manpower and material resources; on the other hand, this solution identifies the recognition result set of the action behaviors generated by the target object in the audio and video information and related information from multiple modal dimensions, and then analyzes the contextual relationship between each action behavior in the recognition result set to determine the behavioral events generated by the target object in the target scene, effectively improving the efficiency and accuracy of information processing, and facilitating the subsequent reference and optimization of interactive behaviors.

[0096] Those skilled in the art can understand that in the above method of specific implementation, the disclosed method can be implemented in a more specific manner. For example, the above described implementation in which the server performs event analysis on the target object based on the identification information and obtains the corresponding analysis result report is only illustrative.

[0097] Exemplarily, the way in which the server obtains audio and video information recorded for the target scene; or, the way in which the server obtains associated information related to the target scene within a target time interval, etc., is merely a collection method, and there may be other division methods in actual implementation. For example, the audio and video information recorded for the target scene and the associated information related to the target scene can be combined or collected into another system, or some features can be ignored or not executed.

[0098] In one embodiment, the server obtains audio and video information recorded for the target scene, including: first, within a target time interval, based on a preset audio and video processing program, controlling a photographic device preset in the target scene to record the target scene to obtain a corresponding audio and video stream; then, the audio and video stream is collected and converted to obtain corresponding audio and video information.

[0099] In some embodiments, at least one camera is pre-installed in the target scene to record the audio and video stream of the target scene. For example, a camera is installed on each side of the classroom to record the audio and video stream of the teacher teaching the students.

[0100] In some embodiments, the audio and video processing program is used to send control instructions to the photographic device via broadcast messages to control the photographic device to start or stop recording the audio and video streams within a target time interval; and is used to collect, transmit and convert the real-time recorded audio and video streams in sequence to obtain corresponding audio and video files, i.e., audio and video information.

[0101] In some embodiments, the audio and video processing program can also calculate the hash code of its program version, the hash code of the converted audio and video information, and the hash code of the photographic device, so as to upload these hash codes to the blockchain for subsequent processing.

[0102] Among them, the hash code is an integer value used to quickly determine the equality of objects. In Java, each object has a default hashCode() method, which is used to return the hash code of the object. The hash code is calculated based on the internal state of the object (for example, audio and video processing programs, audio and video files, photographic equipment, etc.), usually calculated based on the attribute values ​​of the object to obtain the hash code. Objects with the same attribute values ​​usually generate the same hash code, but objects with different attribute values ​​may generate different hash codes.

[0103] Among them, hash codes are mainly used in hash tables in data structures, such as HashMap, HashSet, etc. Hash tables use hash codes to determine the storage location of objects in the table, thereby achieving fast search, insertion, and deletion operations.

[0104] In one embodiment, the server obtains associated information associated with the target scene within the target time interval, including: within the target time interval, based on a preset resource storage platform, extracting associated resources used by the target object in the target scene from a storage medium to obtain corresponding associated information.

[0105] In some embodiments, the storage medium of the resource storage platform stores associated resources used in the target scenario.

[0106] As an example, a target scene is classroom A, and the target time interval is the time range corresponding to course 1 in the curriculum of classroom A. Thus, the server can extract the teaching resources (including courseware, lesson plans, exercises, etc.) used by the teacher in course 1 of classroom A from the storage medium of the resource storage platform.

[0107] In some embodiments, the resource storage platform may also calculate hash codes of its corresponding associated resources to upload these hash codes to the blockchain for subsequent processing.

[0108] In one embodiment, the server obtains association information associated with the target scene within the target time interval, and also includes: first, within the target time interval, based on a preset IoT control platform, connecting the IoT terminal device placed in the target scene; then, based on the control instruction, controlling the IoT terminal device to perform corresponding functional operations to obtain corresponding association information.

[0109] In some embodiments, at least one IoT terminal device (eg, a projector, a speaker, a computer, etc.) is pre-installed in the target scene.

[0110] In some embodiments, the IoT control platform is used to connect to the IoT terminal device in the target scene, and send control instructions to the IoT terminal device through the operation behavior of the user object within the target time interval to control the IoT terminal device to perform corresponding functional operations and obtain corresponding associated information. The associated information is the record information about the corresponding functional operations of the IoT terminal device. For example, it records when the projector is turned on and off, and what content is played, etc.

[0111] In some embodiments, the IoT control platform may also calculate the hash code of its platform version, the hash code of the connected IoT terminal device, and the hash code of the recorded associated information, so as to upload these hash codes to the blockchain for subsequent processing.

[0112] In some embodiments, the server needs to process the hash codes produced by the IoT control platform, audio and video processing program, event analysis platform and algorithm engine on the chain to ensure the accuracy of data information and prevent tampering, and ensure that the data is reliable and traceable.

[0113] In an exemplary embodiment, see Figure 3 , Figure 3 This is a flow chart of processing the hash code on-chain credentials in this application. In steps S11-S13, the server can also specifically perform the following methods:

[0114] Step a1: Obtain a target hash code generated during information processing.

[0115] Among them, the target hash code includes the hash code of the platform version corresponding to the IoT control platform, the hash code of the connected IoT terminal device, and the hash code of the recorded associated information; as well as the hash code of the program version corresponding to the audio and video processing program, the hash code of the converted audio and video information, and the hash code of the photographic equipment; as well as the hash code of the platform version corresponding to the event analysis platform and the hash code of the analysis result report; as well as the hash code of the algorithm version corresponding to the algorithm engine and the hash code of the identification information; and the hash code of the associated resources corresponding to the resource storage platform.

[0116] Step a2: Verify the target hash code to obtain the corresponding credential information.

[0117] Step a3: Upload the credential information to the blockchain.

[0118] Specifically, the server verifies and uploads the target hash code (i.e., on-chain credential processing) in turn, thereby encrypting, hashing, and timestamping the information data corresponding to the target hash code, and solidifying the authenticity and integrity of the information data on the blockchain. Therefore, once the information data is on the chain, it cannot be tampered with or deleted, and a traceable and tamper-proof record can be provided. At the same time, the on-chain credential can also achieve data transparency and automatic execution through the consensus mechanism and smart contracts of the blockchain.

[0119] In other embodiments, after the server obtains the corresponding analysis result report through the event analysis platform analysis, and after the hash codes of various information data are chained as credentials, the server can also: obtain the analysis result report and the credential information involved in the analysis result report; then, display the analysis result report and the credential information in the client for the user to view and analyze, so as to refer to and optimize the subsequent interactive behaviors of the target application scenario.

[0120] In some embodiments, the server needs to authenticate various institutions or platforms that users log in to, so that information data generated by user objects can only be viewed by other users after authorization, ensuring the security of user data.

[0121] In an exemplary embodiment, see Figure 4 , Figure 4This is a flow chart of the user authentication process in this application. In steps S11-S13, the server can also specifically perform the following methods:

[0122] Step b1: Obtain user information input by the user for login authentication.

[0123] Specifically, the user information includes the account number and account password of the user account entered by the user, so that the server performs login authentication on the user's identity based on the user information to verify whether the information entered by the user is accurate, and logs in to the user account in the user interface if the information entered by the user is accurate (i.e., the user's identity authentication is accurate).

[0124] Step b2: If the login is successful, the user account is authenticated based on the user information.

[0125] Step b3: If the authentication is successful, the corresponding functional permissions are developed for the user account.

[0126] In one embodiment, the server matches the user information with a rights management table for the user account stored in a storage medium to authenticate the user account.

[0127] Among them, the functional permissions of the user account are recorded in the permission management table, including displaying analysis result reports of certain accounts and credential information to the user account.

[0128] The above scheme, on the one hand, uses audio and video information and related information to perform action recognition on the target object in a manner different from the prior art to obtain corresponding recognition information, and then uses the recognition information to perform event analysis on the target object to obtain a corresponding analysis result report, thereby optimizing the information processing process, effectively improving the efficiency of analyzing the behavioral events generated by the target object in the target scene, and reducing the consumption of manpower and material resources; on the other hand, this scheme identifies the recognition result set of the action behaviors generated by the target object in the audio and video information and related information from multiple modal dimensions, and then analyzes the contextual relationship between each action behavior in the recognition result set to determine the behavioral events generated by the target object in the target scene, effectively improving the efficiency and accuracy of information processing, and facilitating the subsequent reference and optimization of interactive behaviors.

[0129] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0130] Based on the same inventive concept, the embodiment of the present application also provides an information processing system corresponding to the information processing method involved above. The implementation scheme for solving the problem provided by the information processing system is similar to the implementation scheme recorded in the above method, so the specific limitations of one or more unit embodiments provided below can refer to the limitations of the information processing method above, and will not be repeated here.

[0131] In one embodiment, Figure 5 As shown, an information processing system 10 is provided, including: an information acquisition module 11, an action recognition module 12, and an event analysis module 13, wherein:

[0132] The information acquisition module 11 is used to acquire, for a target scene within a target time interval, audio and video information recorded for the target scene, and associated information associated with the target scene within the target time interval; wherein the target scene includes a target object;

[0133] The action recognition module 12 is used to perform action recognition on the target object based on the audio and video information and the associated information to obtain corresponding recognition information; the action recognition is used to recognize the action behavior generated by the target object in the audio and video information and the associated information from multiple modal dimensions, and the recognition information is a set of recognition results about the action behavior;

[0134] The event analysis module 13 is used to perform event analysis on the target object based on the recognition information to obtain a corresponding analysis result report; the event analysis is used to analyze the contextual relationship between each action behavior in the recognition result set to determine the behavior event generated by the target object in the target scene.

[0135] In another embodiment, Figure 6As shown, another information processing system 20 is provided, including: an information acquisition module 21, an action recognition module 22, and an event analysis module 23.

[0136] In some embodiments, the action recognition module 22 includes:

[0137] The algorithm engine unit 221 is used to input the audio and video information and the associated information into a pre-trained neural network algorithm based on a preset algorithm engine to perform action recognition on the target object to obtain corresponding recognition information; the neural network algorithm includes at least a visual algorithm, a speech algorithm and a language algorithm; wherein the recognition information is unstructured information data, and the unstructured information data is based on symbolically connected target objects, action occurrence time and behavioral action representations; and, generate a hash code for the algorithm version corresponding to the algorithm engine and a hash code for the recognition information.

[0138] In some embodiments, the event analysis module 23 includes:

[0139] The event analysis unit 231 is used to input the identification information into the state machine based on a preset event analysis platform, so as to perform event analysis on the target object using preset event analysis rules to obtain a corresponding analysis result report; wherein the event analysis rules at least include facial expression analysis rules, tone type analysis rules and dialogue text analysis rules for the target object; and generate a hash code for the corresponding platform version of the event analysis platform and a hash code for the analysis result report.

[0140] In some embodiments, the information acquisition module 21 includes:

[0141] The audio and video recording unit 211 is used to control the camera preset in the target scene to record the target scene within the target time interval based on the preset audio and video processing program to obtain the corresponding audio and video stream;

[0142] The audio and video processing unit 212 is used to use the received control instructions to instruct the photographic device to start or stop recording the target scene, and to collect and convert the audio and video streams to obtain corresponding audio and video information; and to generate a hash code for the program version corresponding to the audio and video processing program, a hash code for the photographic device, and a hash code for the audio and video information.

[0143] In some embodiments, the information acquisition module 21 includes:

[0144] The IoT control platform unit 213 is used to connect the IoT terminal device placed in the target scene based on a preset IoT control platform within the target time interval; and control the IoT terminal device based on a control instruction to perform corresponding functional operations to obtain corresponding association information; and generate a hash code for the corresponding platform version of the IoT control platform, a hash code of the IoT terminal device and a hash code of the functional operation.

[0145] In some embodiments, the information acquisition module 21 includes:

[0146] The resource storage platform unit 214 is used to extract the associated resources used by the target object in the target scene from the storage medium based on the preset resource storage platform within the target time interval to obtain corresponding associated information; and generate a hash code for the associated resources.

[0147] In some embodiments, the information analysis system 20 further includes a blockchain module 24, and the blockchain module 24 includes:

[0148] The on-chain credential unit 241 is used to obtain the target hash code generated during the execution of information processing; the target hash code includes a hash code for the program version corresponding to the audio and video processing program, a hash code for the photographic device, a hash code for the audio and video information, a hash code for the platform version corresponding to the IoT control platform, a hash code for the IoT terminal device, a hash code for the functional operation, a hash code for the associated resource, a hash code for the algorithm version corresponding to the algorithm engine, a hash code for the identification information, a hash code for the platform version corresponding to the event analysis platform, and a hash code for the analysis result report; and the target hash code is verified to obtain the corresponding credential information; and the credential information is uploaded to the blockchain.

[0149] In another embodiment, Figure 7 As shown, another information processing system 30 is provided, comprising:

[0150] The teacher's mobile terminal p is used to: ① connect to the IoT platform c.

[0151] Classroom s is used to: ① install two cameras at the front and back of the classroom to record audio and video in real time; ② connect the audio and video server d and the IoT platform c.

[0152] The audio and video server d is used to: ① transmit the signaling message indicating turning on / off audio and video recording through broadcasting; ② collect, transmit and convert the real-time recorded audio and video; ③ calculate the hash code of the service version, the hash code of the audio and video file, and the hash code of the video recording device; ④ based on the blockchain server f, the calculated hash code is chained as a certificate; ⑤ chain the service version certificate, loT device certificate information, hash code certificate of audio and video files and other certificate information to the blockchain server f.

[0153] The IoT platform c is used to: ① connect the IoT terminal to the classroom s; ② send control instructions to the control device to control the control device; ③ calculate the hash code of (the collected data of the smart device), the hash code of the control device position, and the hash code of the IoT terminal service; ④ based on the blockchain server f, the calculated hash code is chained as a certificate; ⑤ the device fingerprint certificate, IoT terminal service version certificate and other certificate information are chained to the blockchain server f.

[0154] The algorithm engine e is used to: ①According to the classroom s and the class schedule, obtain the current teaching resource information in the teaching resource platform g, the information of the IoT terminal bound to the classroom s, and the current audio and video in the classroom s; ②Through vision, voice, and NLP algorithms, conduct multimodal analysis of the current teaching resource information, IoT terminal information, and current audio and video on classroom teaching behavior to obtain the analyzed unstructured data; ③Calculate the hash code of the algorithm version, the hash code of the current audio and video, and the hash code of the unstructured data; ④Based on the blockchain server f, upload the calculated hash code to the chain certificate; ⑤Upload the algorithm version certificate, input video certificate, output unstructured information certificate and other certificate information to the blockchain server f.

[0155] The classroom observation server a is used to: ① receive the account and password sent by the teacher's mobile terminal p and log in as a user; ② obtain the current teaching resource information in the teaching resource platform g; ③ obtain the analyzed unstructured data, and analyze the unstructured data through the state machine and behavior rules to obtain the classroom observation digital report (including: standing up, asking questions and answering, group discussion, blackboard writing, inspection, classroom links, key points, etc.), and obtain the traceability information in the classroom observation digital report from the blockchain server f; ④ send the classroom observation digital report and traceability information to the teacher's mobile terminal p for display; ⑤ calculate the hash code of the observation service version, the hash code of the output digital report, and the hash code of the input unstructured data; ⑥ based on the blockchain server f, the calculated hash code is chained; ⑦ the version certificate of the observation service, the input unstructured information, the courseware resource information, the output data report certificate and other certificate information are chained to the blockchain server f.

[0156] The teaching system b is used to: ① obtain the user information (account and password) in the classroom observation server a to authenticate the user login; ② calculate the hash code of the user information and the hash code of the login behavior; ③ based on the blockchain server f, the calculated hash code is chained as a credential; ④ the credential information of teachers, students, etc. is chained to the blockchain server f.

[0157] The teaching resource center g is used to: ① send the teaching resources used in classroom teaching to the algorithm engine e and the classroom observation server a respectively (teaching resources include courseware, lesson plans, exercises); ② upload the courseware, lesson plans, exercises and student answers in classroom teaching to the blockchain server f.

[0158] The blockchain server f is used to: ① connect to the classroom observation server a, store the traceability information involved in the classroom observation digital report (that is, the relevant chain certificates uploaded by various servers), and send the traceability information to the classroom observation server a; ② consensus storage certificate; ③ distributed ID service contract; ④ smart contract management.

[0159] In one embodiment, a computer device is provided. The computer device may be an electronic device or a server according to the program logic to be applied. The internal structure diagram of the computer device may be as follows: Figure 8 The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus.

[0160] The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies.

[0161] The computer program is executed to implement an information processing method. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a key, trackball or touchpad provided on the computer device housing, or an external keyboard, touchpad or mouse.

[0162] Those skilled in the art will understand that Figure 8 The structure shown in the figure is only a block diagram of a part of the structure related to the present application scheme, and does not constitute a limitation on the computer equipment (including servers and electronic devices) to which the present application scheme is applied. The specific computer equipment may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0163] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed, the following steps are implemented:

[0164] For a target scene within a target time interval, obtain audio and video information recorded for the target scene, and associated information associated with the target scene within the target time interval; wherein the target scene includes a target object;

[0165] Based on the audio and video information and the associated information, the target object is subjected to action recognition to obtain corresponding identification information; the action recognition is used to identify the behavior actions generated by the audio and video information and the associated information about the target object from multiple modal dimensions, and the identification information is a set of identification results about the behavior actions;

[0166] Based on the recognition information, event analysis is performed on the target object to obtain a corresponding analysis result report; the event analysis is used to analyze the contextual relationship between each behavioral action in the recognition result set to determine the behavioral event generated by the target object in the target scene.

[0167] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0168] For a target scene within a target time interval, obtain audio and video information recorded for the target scene, and associated information associated with the target scene within the target time interval; wherein the target scene includes a target object;

[0169] Based on the audio and video information and the associated information, the target object is subjected to action recognition to obtain corresponding identification information; the action recognition is used to identify the behavior actions generated by the audio and video information and the associated information about the target object from multiple modal dimensions, and the identification information is a set of identification results about the behavior actions;

[0170] Based on the recognition information, event analysis is performed on the target object to obtain a corresponding analysis result report; the event analysis is used to analyze the contextual relationship between each behavioral action in the recognition result set to determine the behavioral event generated by the target object in the target scene.

[0171] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0172] Those skilled in the art will appreciate that the embodiments of the present application may provide information processing methods, information processing systems, servers, computer equipment, computer-readable storage media, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer program instructions (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0173] The present application is described with reference to the flowcharts and / or block diagrams of the information processing methods, information processing systems, servers, computer devices, computer-readable storage media or computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by a computer program product. These computer program products can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the program instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0174] These computer program products can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the program instructions stored in the computer program product produce a product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0175] These program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the program instructions executed on the computer or other programmable device for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0176] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0177] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0178] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. The present disclosure is intended to cover any variations, uses or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are to be considered exemplary only, and the true scope and spirit of the present disclosure are indicated by the claims.

[0179] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. An information processing method, characterized in that: The method comprises: For a target scene within a target time interval, obtain audio and video information recorded for the target scene, and associated information associated with the target scene within the target time interval; wherein the target scene includes a target object; Based on the audio and video information and the associated information, the target object is subjected to action recognition to obtain corresponding identification information; the action recognition is used to identify the behavior actions generated by the audio and video information and the associated information about the target object from multiple modal dimensions, and the identification information is a set of identification results about the behavior actions; Based on the recognition information, event analysis is performed on the target object to obtain a corresponding analysis result report; the event analysis is used to analyze the contextual relationship between each behavioral action in the recognition result set to determine the behavioral event generated by the target object in the target scene.

2. The method according to claim 1, characterized in that The step of performing action recognition on the target object based on the audio and video information and the associated information to obtain corresponding recognition information includes: Based on a preset algorithm engine, the audio and video information and the associated information are input into a pre-trained neural network algorithm to perform action recognition on the target object to obtain corresponding recognition information; the neural network algorithm includes at least a visual algorithm, a speech algorithm and a language algorithm; The identification information is non-structural information data, and the non-structural information data is based on the target object, action occurrence time and behavior action representation of the symbolic connection.

3. The method according to claim 2, characterized in that The event analysis is performed on the target object based on the identification information to obtain a corresponding analysis result report, including: Based on a preset event analysis platform, the identification information is input into a state machine to perform event analysis on the target object using preset event analysis rules to obtain a corresponding analysis result report; The event analysis rules include at least facial expression analysis rules, tone type analysis rules and dialogue text analysis rules for the target object.

4. The method according to claim 3, characterized in that The obtaining of audio and video information recorded for the target scene includes: In the target time interval, based on a preset audio and video processing program, a camera device preset in the target scene is controlled to record the target scene to obtain a corresponding audio and video stream; The audio and video streams are collected and converted to obtain corresponding audio and video information.

5. The method according to claim 4, characterized in that Acquiring association information associated with the target scene within the target time interval includes: Within the target time interval, the IoT terminal device placed in the target scene is connected based on a preset IoT control platform; Based on the control instruction, the IoT terminal device is controlled to perform corresponding functional operations to obtain corresponding association information.

6. The method according to claim 5, characterized in that Acquiring association information associated with the target scene within the target time interval includes: In the target time interval, the associated resources used by the target object in the target scene are extracted from the storage medium based on a preset resource storage platform to obtain corresponding associated information.

7. The method according to claim 6, characterized in that The method further comprises: Obtaining a target hash code generated during the execution of information processing; the target hash code includes a hash code for a program version corresponding to the audio and video processing program, a hash code for the photographic device, a hash code for the audio and video information, a hash code for a platform version corresponding to the IoT control platform, a hash code for the IoT terminal device, a hash code for the functional operation, a hash code for the associated resource, a hash code for an algorithm version corresponding to the algorithm engine, a hash code for the identification information, a hash code for a platform version corresponding to the event analysis platform, and a hash code for the analysis result report; Verifying the target hash code to obtain corresponding credential information; The credential information is uploaded to the blockchain.

8. An information processing system, characterized in that: The system comprises: An information acquisition module, for acquiring, for a target scene within a target time interval, audio and video information recorded for the target scene, and associated information associated with the target scene within the target time interval; wherein the target scene includes a target object; An action recognition module is used to perform action recognition on the target object based on the audio and video information and the associated information to obtain corresponding recognition information; the action recognition is used to recognize the action behavior generated by the target object in the audio and video information and the associated information from multiple modal dimensions, and the recognition information is a set of recognition results about the action behavior; An event analysis module is used to perform event analysis on the target object based on the recognition information to obtain a corresponding analysis result report; the event analysis is used to analyze the contextual relationship between each action behavior in the recognition result set to determine the behavioral event generated by the target object in the target scene.

9. The system according to claim 8, characterized in that The action recognition module comprises: An algorithm engine unit is used to input the audio and video information and the associated information into a pre-trained neural network algorithm based on a preset algorithm engine to perform action recognition on the target object and obtain corresponding recognition information; the neural network algorithm at least includes a visual algorithm, a speech algorithm and a language algorithm; wherein the recognition information is unstructured information data, and the unstructured information data is based on symbolically connected target objects, action occurrence time and behavioral action representations; and generate a hash code for the algorithm version corresponding to the algorithm engine and a hash code for the recognition information.

10. The system according to claim 9, characterized in that The event analysis module includes: An event analysis unit is used to input the identification information into a state machine based on a preset event analysis platform, so as to perform event analysis on the target object using preset event analysis rules to obtain a corresponding analysis result report; wherein the event analysis rules at least include facial expression analysis rules, tone type analysis rules and dialogue text analysis rules for the target object; and generate a hash code for the platform version corresponding to the event analysis platform and a hash code for the analysis result report.

11. The system according to claim 10, characterized in that The information acquisition module includes: An audio and video recording unit, configured to control a camera preset in the target scene to record the target scene within the target time interval based on a preset audio and video processing program, and obtain a corresponding audio and video stream; An audio and video processing unit is used to use the received control instructions to instruct the photographic device to start or stop recording the target scene, and to collect and convert the audio and video streams to obtain corresponding audio and video information; and to generate a hash code for the program version corresponding to the audio and video processing program, a hash code for the photographic device, and a hash code for the audio and video information.

12. The system according to claim 11, characterized in that The information acquisition module includes: The IoT control platform unit is used to connect the IoT terminal device placed in the target scene based on a preset IoT control platform within the target time interval; and control the IoT terminal device based on control instructions to perform corresponding functional operations to obtain corresponding association information; and generate a hash code for the corresponding platform version of the IoT control platform, a hash code of the IoT terminal device and a hash code of the functional operation.

13. The system according to claim 12, characterized in that The information acquisition module includes: The resource storage platform unit is used to extract the associated resources used by the target object in the target scene from the storage medium based on the preset resource storage platform within the target time interval to obtain corresponding associated information; and generate a hash code for the associated resources.

14. The system according to claim 13, characterized in that The information analysis system further includes a blockchain module, which includes: The on-chain credential unit is used to obtain the target hash code generated in the process of executing information processing; the target hash code includes a hash code for the program version corresponding to the audio and video processing program, a hash code for the photographic device, a hash code for the audio and video information, a hash code for the platform version corresponding to the IoT control platform, a hash code for the IoT terminal device, a hash code for the functional operation, a hash code for the associated resource, a hash code for the algorithm version corresponding to the algorithm engine, a hash code for the identification information, a hash code for the platform version corresponding to the event analysis platform, and a hash code for the analysis result report; and the target hash code is verified to obtain the corresponding credential information; and the credential information is uploaded to the blockchain.

15. A computer device, characterized in that: include: processor; a memory for storing executable instructions for the processor; The processor is configured to execute the executable instructions to implement the information processing method according to any one of claims 1 to 7.

16. A computer-readable storage medium, the computer-readable storage medium comprising program data, characterized in that: When the program data is executed by a processor of a computer device, the computer device is enabled to execute the information processing method according to any one of claims 1 to 7.

Images