Communication method, apparatus, device, and storage medium

Abstract

The application discloses a communication method, device, equipment and storage medium, the communication method is applied to the intelligent surface, the method comprises the steps that the communication content sent by a first terminal based on a terminal native communication function is acquired; the communication content is identified and converted into a first communication instruction; a task execution result is obtained based on the task of the first communication instruction executed by an intelligent agent; and terminal communication associated with the task execution result. The application makes the native communication function of the first terminal have AI processing capability, compared with the terminal native communication function of the prior art, the terminal native communication function of the application can process the demand of the terminal user through AI intelligence, and can provide convenience for the user.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a communication method, apparatus, device and storage medium. Background Technology

[0002] With the improvement of 5G network infrastructure and the planning of 6G networks, traditional operators' basic voice and SMS services are undergoing a historic reshaping. 5G messaging and new voice services, as benchmark applications in this transformative period, have been established as core strategic priorities for operators.

[0003] With the gradual development of AI in recent years, seizing the AI ​​entry point on the terminal has become a core competitive point for major applications. As the native messaging and voice entry points on terminals, 5G messaging and new calls also need to have AI capabilities to enhance user stickiness, increase users' use of traditional messaging and voice entry points, and thus expand the overall business volume of 5G messaging and new calls.

[0004] Currently, how to leverage AI capabilities to provide users with more service functions or enhance existing service functions within the native communication functions of terminals is an urgent problem that needs to be solved. Summary of the Invention

[0005] The main purpose of this application is to provide a communication method, apparatus, device and storage medium, which aims to provide AI services to end users based on the existing native communication functions of the terminal.

[0006] To achieve the above objectives, this application proposes a communication method applied to an intelligent surface, the method comprising: Obtain the communication content sent by the first terminal based on the terminal's native communication functions; Identify the communication content and convert the communication content into a first communication instruction; Based on the task executed by the intelligent agent using the first communication instruction, the task execution result is obtained; Based on the task execution result, terminal communication associated with the task execution result.

[0007] Furthermore, to achieve the above objectives, this application also proposes a communication method applied to a first terminal, the method comprising: The terminal sends communication content to the smart surface based on its native communication function. The smart surface recognizes the communication content and converts it into a first communication instruction. The smart agent executes the task based on the first communication instruction and obtains the task execution result. Receive communication data sent by the intelligent surface based on the task execution result.

[0008] Furthermore, to achieve the above objectives, this application also proposes a communication method applied to a second terminal, the method comprising: The system receives communication data sent by the intelligent surface based on the task execution result, obtains the communication content sent by the first terminal based on the terminal's native communication function, identifies the communication content and converts the communication content into a first communication instruction, executes the task based on the first communication instruction, and obtains the task execution result.

[0009] Furthermore, to achieve the above objectives, this application also proposes a communication method applied to a messaging platform, the method comprising: Receive communication content sent by the first terminal based on the terminal's native communication functions; Identify whether the communication content is sent to the AI ​​messaging assistant; When it is recognized that the communication content is sent to the AI ​​message assistant, the communication content is sent to the intelligent surface, which recognizes the communication content and converts it into a first communication instruction. The intelligent agent executes the task based on the first communication instruction to obtain the task execution result, and the terminal communication is associated with the task execution result.

[0010] Furthermore, to achieve the above objectives, this application also proposes a communication method applied to a call service control platform, the method comprising: Receive communication content initiated by the first terminal based on the terminal's native communication functions; Identify whether the first terminal has enabled call AI processing permissions; If it is recognized that the first terminal has enabled call AI processing permission, the communication content is sent to the intelligent surface, which recognizes the communication content and converts it into a first communication instruction. The intelligent agent then executes the task based on the first communication instruction to obtain the task execution result and the terminal communication associated with the task execution result.

[0011] In addition, to achieve the above objectives, this application also proposes a communication device, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the communication method described above.

[0012] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and which, when executed by a processor, implements the steps of the communication method described above.

[0013] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the communication method described above.

[0014] One or more technical solutions proposed in this application have at least the following technical effects: Since the smart surface receives the communication content sent by the first terminal based on the native communication function, it identifies the communication content and converts it into a first communication instruction that the smart agent can process. The smart agent executes the task of the first communication instruction to obtain the task execution result, and communicates with the first terminal and / or the second terminal associated with the task execution result based on the task execution result. Thus, the native communication function of the first terminal has AI processing capabilities. Compared with the native communication function of the terminal in the prior art, the native communication function of the terminal in this application can intelligently process the needs of the terminal user through the smart agent on the smart surface, which can provide convenience to the user. Attached Figure Description

[0015] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a structural block diagram of an embodiment of an existing 5G messaging system; Figure 2 This is a structural block diagram of an embodiment of an existing 5G new voice communication system; Figure 3 This is a schematic diagram of the structure of an embodiment of the intelligent surface of the communication method of this application; Figure 4 This is a flowchart illustrating an embodiment of the communication method of this application. Figure 5 This is a flowchart illustrating the second embodiment of the communication method of this application. Figure 6 This is a flowchart illustrating the communication method of Embodiment 3 of this application; Figure 7 This is a flowchart illustrating the communication method of Embodiment 4 of this application; Figure 8 This is a flowchart illustrating Embodiment 5 of the communication method of this application; Figure 9 This is a flowchart illustrating Embodiment Six of the communication method of this application; Figure 10 This is a flowchart illustrating the communication method of Embodiment Seven of this application. Figure 11 This is a flowchart illustrating the communication method of embodiment eight of this application. Figure 12 This is a flowchart illustrating an embodiment of step S402 in Embodiment Eight of the Communication Method of this Application; Figure 13 This is a flowchart illustrating an embodiment of step S403 in Embodiment Eight of the Communication Method of this Application; Figure 14 This is a flowchart illustrating Embodiment Nine of the communication method of this application; Figure 15 This is a flowchart illustrating the communication method of Embodiment 10 of this application; Figure 16 This is a flowchart illustrating the communication method of embodiment eleven of this application. Figure 17 This is a flowchart illustrating the communication method of embodiment 12 of this application. Figure 18 This is a flowchart illustrating the communication method of embodiment thirteen of this application. Figure 19 This is a flowchart illustrating the communication method of embodiment fourteen of this application. Figure 20 This is a flowchart illustrating Embodiment Fifteen of the communication method of this application; Figure 21 This is a flowchart illustrating the communication method of Embodiment Sixteen of this application; Figure 22 This is a flowchart illustrating Embodiment Seventeen of the communication method of this application; Figures 23-28 These are schematic diagrams illustrating different interactions in the communication system of this application, where communication services are subscribed via native terminal messages. Figures 29-34 These are schematic diagrams illustrating different interactions in the communication system of this application for scheduling a teleconference via native terminal messages. Figure 35 This is a schematic diagram of the module structure of the communication device according to an embodiment of this application; Figure 36 This is a schematic diagram of the device structure of the hardware operating environment involved in the communication method in the embodiments of this application.

[0018] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0019] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0020] To make this application easier to understand, the technical terms involved in the various embodiments of this application are explained below. It should be noted that these explanations should not be regarded as limiting the scope of protection claimed in this application.

[0021] The technical terms used in this application include: I. Terminal The terminals in this application include physical communication devices with wireless communication methods such as 4G, 5G, or 6G, such as mobile phones and tablets, which will not be listed here.

[0022] II. Messaging Platform The messaging platform in this application is a core capability open platform connecting enterprise / industry customers with operator messaging centers. It is also a key network element for realizing "B2C industry messaging" and "Chatbot (hereinafter referred to as personal messaging assistant) interaction" and serves as an intermediary bridge between operators, enterprises, and mobile terminals.

[0023] In this application, the MaaP platform (Message as a Platform) in a 5G messaging system is used as an example to illustrate the messaging platform. For instance... Figure 1 As shown, the MaaP platform is deployed on top of the 5G Messaging Center (5GMC system), providing standardized HTTP API interfaces to enterprise IT systems / Chatbots at the top and connecting to the 5G Messaging Center at the bottom to complete message routing and delivery. It allows enterprises to send rich media messages to users and receive user interactions in the form of a Chatbot without developing the underlying RCS protocol.

[0024] III. Call Service Control Platform The function of the call service control platform in this application is to identify call services and execute corresponding logical processing during the call process. All call value-added services are driven and executed by the call service control platform.

[0025] In this application, the application server (AS platform) in a 5G new calling system is used as an example as the calling service control platform. Figure 2 As shown, the AS platform is deployed on top of the VoNR+ capability network element. The VoNR+ capability network element is the capability platform and signaling / media control bridge between the IMS core network and service applications. The AS platform is the logical implementation and content decision center for specific new call services.

[0026] IV. Intelligent Face The smart surface in this application can be a physical device or a virtual server.

[0027] It should be noted that the intelligent face does not communicate directly with the terminal, but communicates with the terminal through a messaging platform or a call service control platform.

[0028] Please refer to Figure 3 , Figure 3 This is a structural schematic diagram of one embodiment of the intelligent surface. For example... Figure 3 As shown, the intelligent surface includes a first message conversion module, a second message conversion module, a message access module, an intelligent agent, a user session message module, and a task processing module. The intelligent agent invokes the task processing module through its skills to handle various tasks. Specifically, the first message conversion module communicates with the MaaP platform, and the second message conversion module communicates with the AS platform. The message access module serves as a bridge for data interaction between the intelligent agent and external communication modules and task processing modules.

[0029] V. AI Messaging Assistant The AI ​​messaging assistants in this application include: enterprise chatbots or personal AI messaging assistants. Enterprise chatbots provide enterprise-level business services, such as 10086 for managing phone bills, weather forecast robots for managing weather forecasts, and cultural tourism robots for providing cultural tourism information. Personal AI messaging assistants refer to customized AI messaging assistants provided by telecom operators. For example, if an individual has subscribed to AI messaging services with a telecom operator, they can send messages to the personal AI messaging assistant to obtain AI services.

[0030] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0031] The main solution of this application embodiment is: to obtain the communication content sent by the first terminal based on the terminal's native communication function; to identify the communication content and convert the communication content into a first communication instruction; to execute the task based on the intelligent agent using the first communication instruction, and to obtain the task execution result; Terminal communication associated with the result of the task execution.

[0032] In this embodiment, for ease of description, the following explanation will focus on the intelligent surface as the execution subject.

[0033] This is due to the technical problem that existing terminal devices lack AI capabilities in their native communication functions.

[0034] This application provides a solution including an intelligent face, a first terminal, a messaging platform, and a call service control platform. The first terminal sends communication content based on its native communication functions. The messaging platform or call service control platform receives the communication content, identifies it, and determines whether to send it to the intelligent face. The intelligent face identifies the communication content and converts it into a first communication command. An intelligent agent executes the task based on the first communication command to obtain a task execution result. Terminal communication is associated with the task execution result. This application uses the terminal's native voice and messaging entry points as AI entry points, allowing users to use AI capabilities without pre-installing any additional applications. This facilitates operators in quickly seizing user AI entry points in the AI ​​era, enhancing user stickiness to traditional messaging and voice applications, and increasing the business activity of both products.

[0035] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a physical server device, a virtual server, or an electronic device or smart face capable of performing the above functions. The following description uses a smart face as an example to illustrate this embodiment and the subsequent embodiments.

[0036] Based on this, the embodiments of this application provide a communication method, please refer to... Figure 4 , Figure 4 This is a flowchart illustrating the first embodiment of the communication method of this application.

[0037] In this embodiment, the communication method is applied to a smart surface, and the communication method includes steps S10~S40: S10: Obtain the communication content sent by the first terminal based on the terminal's native communication function; Native communication functions on a device include native messaging and native calling functions. Understandably, native messaging functions include SMS and phone calls.

[0038] It should be noted that the intelligent face receives communication content sent by the first terminal through the message platform on the message link or the call service control platform on the call link.

[0039] The following examples of 5G SMS and 5G new calls illustrate how this step works.

[0040] When the intelligent surface receives communication content through the message platform on the message chain, please refer to... Figure 3 The first terminal sends a 5G message to the AI ​​message assistant based on the terminal's native messaging function. During the uplink process of sending the 5G message, when the MaaP platform recognizes that the recipient of this 5G message is the AI ​​message assistant, it sends the 5G message to the smart face, so that the smart face can obtain the 5G message.

[0041] When the intelligent face receives communication content through the call service control platform on the call link, please refer to... Figure 3 The first terminal initiates a 5G call to the second terminal based on its native call function. During the transmission of 5G call data, when the AS platform recognizes that the first terminal and / or the second terminal have enabled call AI processing permissions, it sends the 5G call content to the smart face according to the requirements corresponding to the call AI processing permissions, thereby enabling the smart face to obtain the 5G call content. For example, if the call AI processing permission is to save call records, the call records between the first terminal and the second terminal can be sent to the smart face for further processing.

[0042] S20: Identify the communication content and convert the communication content into a first communication instruction; First, determine whether the communication content needs to be sent to the Smart Face. If it is determined that the communication content needs to be sent to the Smart Face, proceed to the next step; otherwise, do not proceed to the next step.

[0043] Since the agent cannot directly process the communication content sent directly from the message link or the call link, the communication content needs to be converted through protocol conversion into the first communication instruction that the agent can process.

[0044] S30: Based on the intelligent agent executing the task of the first communication instruction, the task execution result is obtained; The first step is task parsing. After receiving the first communication instruction, the agent parses the task to be processed from it.

[0045] The intelligent agent performs natural language semantic understanding based on the instructions in the first communication command, and performs task recognition operations such as user intent recognition, entity extraction, disambiguation and completion of missing information, and constraint extraction. If the task is identified as simple, it is executed directly; if the task is identified as complex, it is broken down into multiple sub-tasks.

[0046] The second step is task processing. The agent matches its available capabilities against the task at hand, identifying the agent skills that correspond to the task. The selected agent skills are then used to process the task, generating the task execution result.

[0047] S40: Terminal communication associated with the result of the task execution.

[0048] After processing the task, the intelligent agent outputs the task execution result. The terminals associated with the task execution result may include only the first terminal; or only the second terminal; or only the third terminal; or both the first and second terminals; or the first, second, and third terminals; or the first, second, and third terminals, along with multiple other terminals. It should be noted that the number of terminals associated with the task execution result is not limited here.

[0049] The intelligent surface converts the task execution result through a protocol and sends it to the terminal associated with the task execution result via a downlink.

[0050] It should be noted that the task execution result is sent to the terminal via the message platform on the message chain or the call service control platform on the call chain. For example: Please refer to... Figure 3 The result of the task execution is sent to the terminal via the MaaP platform on the message link or the AS platform on the call link, which sends a 5G message to the terminal or initiates a new call.

[0051] In this embodiment, the intelligent face receives communication content sent by the first terminal based on its native communication function. After recognizing the communication content, it converts it into a first communication instruction that the intelligent agent can process. The intelligent agent executes the task of the first communication instruction to obtain the task execution result, and based on the task execution result and the terminal communication associated with the task execution result, the native communication function of the first terminal is equipped with AI processing capabilities. Compared with the native communication function of the terminal in the prior art, the native communication function of the terminal in this embodiment can intelligently process the needs of terminal users, provide convenience to users, and thus stimulate the number of users using the native communication function of the terminal, which is conducive to the business growth of operators.

[0052] To more clearly describe the structure of the intelligent surface of this application, which allows for the sharing of message and call links, a second embodiment of this application is proposed. Based on the first embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description and will not be repeated hereafter. Based on this, please refer to... Figure 5 , Figure 5 and Figure 4 The difference is that step S10 includes step S1A, and step S40 includes step S4A. For example... Figure 5 As shown, this embodiment includes the following steps: Step S1A: Obtain the communication content sent by the first terminal based on the message link; This message link includes 4G, 5G, and 6G message links, which are not limited here. This message link includes the aforementioned message platform, which forwards the communication content sent by the first terminal to the smart face.

[0053] Taking 5G messaging links as an example, such as Figure 3 As shown, the first terminal sends a 5G message to the AI ​​message assistant based on the terminal's native messaging function. During the uplink process of sending the 5G message, when the MaaP platform recognizes that the recipient of this 5G message is the AI ​​message assistant, it sends the 5G message to the smart face, so that the smart face can obtain the 5G message.

[0054] Step S20: Identify the communication content and convert the communication content into a first communication instruction; Step S20 has been described in detail in Embodiment 1 and will not be repeated here.

[0055] Step S30: Based on the intelligent agent executing the task of the first communication instruction, obtain the task execution result; Step S30 has been described in detail in Embodiment 1 and will not be repeated here.

[0056] Step S4A: Conduct a call with the terminal associated with the task execution result through the call link.

[0057] The call link includes 4G, 5G, and 6G call links, which are not limited here. The call link includes the aforementioned call service control platform. The intelligent facet converts the task execution result into a call task result, and the call service control platform initiates a call to the terminal associated with the task execution result based on this call task result.

[0058] One application scenario of this embodiment is as follows: A first terminal sends an uplink message with a teleconference booking task instruction to a personal AI message assistant. During the uplink transmission, the message is forwarded to the intelligent surface by the message platform. After receiving the uplink message, the intelligent surface performs task processing based on the intelligent agent and generates a call task result. For example, the call task result is to initiate a conference booking notification to a second terminal and a third terminal. In this way, the call service control platform initiates a call to the second terminal and the third terminal based on the call task result and initiates a teleconference booking to the second terminal and the third terminal.

[0059] In this embodiment, the intelligent surface obtains the communication content sent by the first terminal based on the message link, processes the communication content based on the intelligent agent to generate a task execution result, and then initiates a call with the terminal associated with the task execution and result through a call link based on the task execution result. In this way, the terminal user can initiate calls to other terminals using native messaging functions.

[0060] To more clearly describe the structure of the intelligent surface of this application, which allows for the sharing of message and call links, a third embodiment of this application is proposed. Based on the first embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description and will not be repeated hereafter. Based on this, please refer to... Figure 6 , Figure 6 and Figure 4 The difference is that step S10 includes step S1B, and step S40 includes step S4B. For example... Figure 6 As shown, this embodiment includes the following steps: Step S1B: Obtain the communication content sent by the first terminal based on the call link; The call link includes 4G, 5G, and 6G call links, which are not limited here. The call link includes the aforementioned call service control platform. When the first terminal initiates a call to the second terminal through this call link, the call service control platform will receive the call content. If the call service control platform recognizes that the first terminal or the second terminal has enabled call AI processing permissions, it will send the call content to the smart face.

[0061] Step S20: Identify the communication content and convert the communication content into a first communication instruction; Step S20 has been described in detail in Embodiment 1 and will not be repeated here.

[0062] Step S30: Based on the intelligent agent executing the task of the first communication instruction, obtain the task execution result; Step S30 has been described in detail in Embodiment 1 and will not be repeated here.

[0063] Step S4B: Send a message to the terminal associated with the task execution result via the message link.

[0064] This message link includes 4G, 5G, and 6G message links, which are not limited here. This message link includes the aforementioned message platform. The intelligent facet converts the task execution result into a message task result, and the message platform sends a message to the first terminal and / or a second terminal associated with the task execution result based on this message task result.

[0065] One application scenario of this embodiment is as follows: A first terminal makes a call to a second terminal using the terminal's native call function. During the call, if the call service control platform recognizes that either the first or second terminal has enabled call AI processing permissions, it sends the call content to the intelligent surface. The intelligent agent on the intelligent surface processes the call content, generates a call record, and sends the call record to either the first or second terminal via a message link.

[0066] In this embodiment, the intelligent face obtains the communication content sent by the first terminal based on the call link, processes the communication content based on the intelligent agent to generate a task execution result, and sends a message to the terminal associated with the task execution result through a message link based on the task execution result. In this way, the terminal user can send messages to the terminal associated with the task execution result when using the native call function.

[0067] To better illustrate the specific implementation method of step S10, a fourth embodiment of this application is proposed. Based on the first embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description and will not be repeated hereafter. Based on this, please refer to... Figure 7 , Figure 7 and Figure 4 The difference is that step S10 includes step S1C. For example... Figure 7 As shown, this embodiment includes the following steps: Step S1C: Receive message content sent by the messaging platform, wherein the message content is sent by the first terminal to the AI ​​message assistant via the messaging platform; or The system receives the call content between the first terminal and the second terminal from the call service control platform, and the first terminal or the second terminal has enabled call AI processing permissions.

[0068] In step S10, the intelligent surface primarily obtains communication content through two channels: message link or call link. When the intelligent surface obtains communication content via message link, it retrieves the message content from the message platform. When the intelligent surface obtains communication content via call link, it retrieves the call content from the call service control platform.

[0069] When the first terminal sends a message to the AI ​​message assistant, the messaging platform recognizes that the message is intended for the AI ​​message assistant and forwards it to the Smart Surface. Understandably, if the first terminal sends a message to another terminal—that is, a message not intended for the AI ​​message assistant—the messaging platform will not forward the message to the Smart Surface.

[0070] When the first terminal initiates a call to the second terminal, the call service control platform, upon recognizing that either the first or second terminal has enabled call AI processing permissions, forwards the call content between the first and second terminals to the intelligent surface. Understandably, if neither the first nor the second terminal has enabled call AI processing permissions, the call service control platform will not forward the call content to the intelligent surface.

[0071] In this embodiment, the intelligent surface primarily obtains communication content through a messaging platform or a call service control platform, which already exists in existing communication systems. Therefore, the communication method in this embodiment is based on existing communication systems and does not require the addition of new communication facilities. This embodiment provides a method for a call system and a messaging system to share the intelligent surface, allowing the call system and the messaging system to share AI capabilities.

[0072] Since the intelligent agent does not communicate directly with the communication link, it needs to identify the communication content sent by the communication link and convert the communication content into communication instructions that the intelligent agent can process. Therefore, a fifth embodiment of this application is proposed. Based on the first embodiment of this application, the content that is the same as or similar to the first embodiment described above can be referred to the above description and will not be repeated hereafter. Based on this, please refer to Figure 8 , Figure 8 and Figure 4 The difference is that step S20 includes steps S201 to S204.

[0073] Step S201: Identify whether the communication content conforms to a preset communication protocol; The intelligent surface includes a message conversion module. After receiving the communication content sent by the first terminal from the communication link, the message conversion module identifies whether the message type identifier conforms to the preset communication protocol identifier.

[0074] Specifically, such as Figure 3 As shown, the message conversion module includes a first message conversion module and a second message conversion module.

[0075] The first message conversion module is used to receive messages from the message platform and identify whether the message conforms to the preset first communication protocol. If it conforms, the message is processed in step S202; if it does not conform, the message is discarded and no further processing is performed.

[0076] The second message conversion module is used to receive call content from the call service control platform and identify whether the call content conforms to the preset second communication protocol. If it conforms, the process in step S202 is performed; if it does not conform, the call content is discarded and no further processing is performed.

[0077] Step S202: In response to the communication content conforming to the preset communication protocol, the communication content is converted into a second communication instruction; The aforementioned message conversion module extracts the payload and control signaling from the communication content and converts the communication content into a second communication instruction.

[0078] Specifically, the first message conversion module converts the message received from the message platform into the second communication instruction, and the second message conversion module converts the call content received from the call service control platform into the second communication instruction.

[0079] Step S203: Identify the second communication instruction using a rule engine or classification model; like Figure 3 As shown, the intelligent surface also includes a message access module, which serves as the unified message access entry point and unified message distribution exit point for the intelligent surface. The message conversion module converts the communication content into the second communication command and sends the second communication command to the message access module for processing.

[0080] Since the message access module receives not only second communication commands from the message conversion module and communication data from the large model and third-party applications, but also communication data from agents, it needs to identify the received communication data to determine whether it belongs to the agent processing link, the large model processing link, the third-party application processing link, the message processing link, or the call processing link.

[0081] The second communication instruction is identified by a rule engine or classification model to determine whether the second communication instruction belongs to the agent processing link.

[0082] The rule engine includes rules for multiple preset message formats. For example, the first rule is a rule for setting the message header format, the second rule is a rule for setting keywords, and the third rule is a rule for setting media types.

[0083] The classification model can be a machine learning model or a deep learning model.

[0084] Step S204: In response to the fact that the second communication instruction belongs to the agent processing link, the second communication instruction is converted into the first communication instruction.

[0085] After determining that the second communication instruction belongs to the agent processing link, the message access module converts the second communication instruction into the first communication instruction suitable for agent processing.

[0086] In this embodiment, the communication content sent by the communication link is identified and converted into communication instructions that the intelligent agent can process. This allows the intelligent agent to process the communication content sent by the communication link. Since the intelligent agent does not need to communicate directly with the communication link, it does not need to perform invalid tasks, which also improves the processing efficiency of the intelligent agent.

[0087] To meet the diverse user needs of the first terminal user, various types of tasks need to be processed on the intelligent surface. Therefore, a sixth embodiment of this application is proposed. Based on the first embodiment of this application, the content in this sixth embodiment that is the same as or similar to that in the first embodiment described above can be referred to the above description and will not be repeated hereafter. Based on this, please refer to... Figure 9 , Figure 9 and Figure 4 The difference is that step S30 includes steps S301 to S302.

[0088] Step S301: Parse the first communication instruction based on the user session message to obtain the structured user intent and task execution sequence, wherein the user session message includes the historical session records of the first terminal; The historical session records of the first terminal include the session records of the first terminal's last or several interactions with the intelligent agent. Specifically, such as... Figure 3 As shown, historical session records are stored in the user session message module of the intelligent surface. When the intelligent agent reads the historical session record of the first terminal from the user message session module for the first time, it can save the historical session record in the cache for easy access later.

[0089] By combining the historical session records and the first communication command, the intelligent agent can accurately parse out the structured user intent and task execution sequence. This task execution sequence may include multiple tasks to be executed.

[0090] The structured user intent can take various forms, such as key-value pairs, JSON format, hierarchical tree structure, and tuple structured intents. The tasks in the task execution sequence correspond to the user intents in the structured user intent. For example, if the structured user intent includes "book a flight," the tasks in the task execution sequence might include: "Book a flight from location A to location B on June 12, 2026," and "Book a flight from location B back to location C on June 15, 2026."

[0091] Step S302: Invoke the preset intelligent agent skill according to the structured user intent, and input the task execution sequence of the task to the task execution module based on the intelligent agent skill to obtain the task execution result.

[0092] The task execution module includes API call interfaces for large models, and / or API call interfaces for third-party application modules, and / or scheduled task processing modules, as well as other types of task execution modules.

[0093] Large-scale models can utilize existing large language models, such as Doubao, Yuanbao, and Qianwen. Third-party application modules include popular websites providing servers in various niche sectors, such as Meituan, Ctrip, and Taobao.

[0094] The scheduled task processing module is a fundamental component for unified management of periodic and delayed-triggered tasks, replacing manual polling and hard-coded sleep logic, and automatically executing preset task logic according to preset time rules.

[0095] The intelligent agent in this application includes multiple preset intelligent agent skills. Based on the structured user intent generated in step S301, a target skill is matched from these preset intelligent agent skills, and the task execution sequence is executed based on the target skill. The target skill selects a suitable task execution module, and the task execution sequence is input into the selected task execution module to obtain the task execution result.

[0096] When the task execution module is a third-party application module, such as calling the API interface of the Ctrip website, the task execution result can be: "A flight from location A to location B at 7:30 on June 12, 2026 has been booked, with flight number G687."

[0097] When the task execution module is a large language model, such as Doubao, the task execution result can be a text dialogue result, such as: "On June 12, 2026, there are several flights from location A to location B... Which flight would you like to choose?"

[0098] In this embodiment, the first communication command is parsed based on the historical session records of the first terminal, making the generated user intent more accurate. Furthermore, this embodiment includes various types of task execution modules to meet the diverse needs of the first terminal user.

[0099] To process the next communication content of the first terminal user, a seventh embodiment of this application is proposed. Based on the sixth embodiment of this application, the content that is the same as or similar to that of the sixth embodiment described above in this seventh embodiment can be referred to the above description and will not be repeated hereafter. Based on this, please refer to... Figure 10 , Figure 10 and Figure 9 The difference is that after step S30, step S50 is also included.

[0100] Step S50: Based on the unique identifier of the first terminal, save the communication content and the task execution result as a session record to the user session message.

[0101] This unique identifier can be a serial number (SN) or an IMEI number. Preferably, the user session messages are stored in a database within the user message session module.

[0102] In this embodiment, the communication content and the task execution result are saved as the user session message of the first terminal as the session record. In this way, when the first terminal initiates the next communication, the user session message can be used as context information to identify user intent.

[0103] This embodiment deploys intelligent agents on the intelligent surface and caches users' private data (such as voice and message data) with user authorization, ensuring the privacy of remotely stored user privacy through dedicated personnel and domains. In this embodiment, user data is cached in a shared space, and the call system and messages can directly access each other's content through user information, providing a consistent AI application experience for the same application scenario through two entry points.

[0104] After the task execution result is generated, it needs to be returned to the terminal associated with the task execution result. Therefore, the eighth embodiment of this application is introduced. Based on the first embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description and will not be repeated hereafter. Please refer to the following... Figures 11-13 , Figure 11 and Figure 4 The difference is that step S40 also includes steps S401 to S403.

[0105] Step S401: Identify the routing links of the task execution results; Since the routing chain for the task execution result includes two scenarios: a message link and a call link, it is necessary to identify whether the task execution result is sent to the message link or the call link.

[0106] Specifically, such as Figure 3 As shown, when the message access module receives the task execution result sent by the agent, it will identify the task execution result through a rule engine or classification model to determine whether the task execution result is sent to a message link or a call link.

[0107] The working method of the rule engine or classification model has been described in detail in Example 5, and will not be repeated here.

[0108] Step S402: If the routing link is a message link, convert the task execution result into a message result that is compatible with the communication standard adopted by the first terminal, and send the message result to the terminal associated with the task execution result; Understandably, the message result needs to be compatible with the communication standard used by the first terminal; otherwise, the first terminal will not be able to receive the message result.

[0109] If the first terminal uses a 5G communication standard, the task execution result is converted into a 5G message result adapted to 5G. If the first terminal uses a 4G communication standard, the task execution result is converted into a 4G message result adapted to 4G.

[0110] The intelligent interface sends the message result to the messaging platform, which then sends the message result to the terminal associated with the task execution result.

[0111] In one feasible implementation, please refer to Figure 12 Step S402 may include steps S4021 to S4022: Step S4021: If the routing link is a 5G message link, convert the task execution result into a 5G message result adapted to 5G messages. Specifically, such as Figure 3 As shown, the message access module sends the task execution result to the first message conversion module, which converts the task execution result into a message result that is compatible with 5G messages.

[0112] Step S4022: Send the 5G message result to the Message as Platform, and then send the 5G message result to the terminal associated with the task execution result through the Message as Platform.

[0113] Specifically, such as Figure 3 As shown, the first message conversion module sends the 5G message result to the MaaP platform (Chinese name: Message as Platform), and the Message as Platform sends the 5G message result to the terminal associated with the task execution result.

[0114] In this embodiment, the task execution result is sent to the terminal associated with the task execution result through the message platform in the 5G messaging system, thus solving the problem of how to return the task execution result to the terminal associated with the task execution result through the message link.

[0115] Step S403: If the routing link is a call link, the task execution result is converted into a call result that is compatible with the communication standard used by the first terminal, and a call is initiated to the terminal associated with the task execution result.

[0116] Understandably, the call result needs to be compatible with the communication standard used by the first terminal; otherwise, the first terminal will not be able to receive the call result.

[0117] If the first terminal uses a 5G communication standard, the task execution result is converted into a 5G call result compatible with 5G. If the first terminal uses a 4G communication standard, the task execution result is converted into a 4G call result compatible with 4G.

[0118] In one feasible implementation, please refer to Figure 13 Step S403 may include steps S4031 to S4032: Step S4031: If the routing link is a 5G new call link, then the task execution result is converted into a new call result adapted to the new call. Specifically, such as Figure 3 As shown, the message access module sends the task execution result to the second message conversion module, and the second message conversion module converts the task execution result into a 5G new call result adapted to the new call.

[0119] Step S4032: Send the new call result to the application server platform, and initiate a new call to the terminal associated with the task execution result through the application server platform.

[0120] Specifically, such as Figure 3 As shown, the second message conversion module sends the new call result to the AS platform (Chinese name: application server platform), and the AS platform initiates a new call to the terminal associated with the task execution result based on the new call result.

[0121] In this embodiment, the task execution result is sent to the terminal associated with the task execution result through the application server platform of the 5G call system, thus solving the problem of how to return the task execution result to the terminal associated with the task execution result through the call link.

[0122] In this embodiment, the routing link of the task execution result is identified. According to the type of routing link, the task execution result is converted into a message result or call result that is compatible with the communication standard adopted by the first terminal. The message result is sent to the terminal associated with the task execution result through the message link, and the call result is sent to the terminal associated with the task execution result through the call link.

[0123] Furthermore, this embodiment enhances the intelligence (AI) level of traditional messaging and voice channels, opening up new directions for channel business expansion. In the future, 5G messaging can empower more enterprise chatbots with AI, thereby attracting more enterprises to join.

[0124] Furthermore, in traditional messaging, short messages are often merely a presentation of the message, and users typically need to complete subsequent processes through other means after receiving a 5G message. This application, through built-in AI capabilities, bridges the "last mile" of the user's subsequent processes, providing an intelligent, one-stop solution based on the user's messaging scenario.

[0125] To enable access to the historical call records of the same user via a message link, a ninth embodiment of this application is proposed. Based on the sixth embodiment of this application, the content that is the same as or similar to that in the sixth embodiment described above can be referred to the above description and will not be repeated hereafter. Please refer to [the relevant documentation / reference]. Figure 14 , Figure 14 and Figure 9 The difference is that step S40 is followed by steps S6A to S6B.

[0126] S6A: Receive the call recording of the first terminal or the second terminal; It should be noted that receiving conference call recordings from terminals requires that the terminal has enabled call AI processing permissions. If the first terminal has enabled call AI processing permissions, then the system will receive conference call recordings from conversations between the first terminal and other terminals. If the second terminal has enabled call AI processing permissions, then the system will receive conference call recordings from conversations between the second terminal and other terminals.

[0127] S6B: Based on the unique identifier of the first terminal or the second terminal, save the conference call record to the user session message of the first terminal or the second terminal.

[0128] The method for saving user session messages in this step is the same as in step S50.

[0129] The unique identifier can be a serial number (SN) or an IMEI number. Preferably, the call recordings are stored in a database within the user message session module.

[0130] After the conference call records of the first terminal are saved in the user message session module, the first terminal can access the conference call records of the first terminal through the message link by accessing the user message session module.

[0131] In this embodiment, the call recordings of the first terminal or the second terminal are stored in the user message session module of the smart surface. The first terminal or the second terminal can access the call recordings by accessing the user message session module through a message link. This allows users to access their historical call records via a message link.

[0132] To enable the querying of a user's historical user session messages, a tenth embodiment of this application is introduced. Based on the sixth embodiment of this application, the content that is the same as or similar to that in the sixth embodiment described above can be referred to the above description and will not be repeated hereafter. Based on this, please... Figure 15 , Figure 15 and Figure 9 The difference is that step S40 is followed by steps S7A to S7C.

[0133] S7A: Obtain the query communication content of the user session message sent by the first terminal or the second terminal to query the first terminal; It should be noted that this step refers to the first terminal or the second terminal sending a query message to the AI ​​message assistant based on the terminal's native messaging function to inquire about the user session of the first terminal.

[0134] For example, the first terminal sends a 5G message to the personal AI message assistant to query the first terminal's call records from 10:00 to 12:00 yesterday.

[0135] S7B: If the query communication content is initiated by the first terminal, send the user session message of the first terminal to the first terminal; The intelligent agent receives the query content through the message platform, the first message conversion module, and the message access module.

[0136] After receiving the query content, the intelligent agent determines whether the user initiating the query communication content matches the query communication content. If it is the first terminal querying the user session message of the first terminal, it searches for the user session message corresponding to the query content in the user message session module, and then returns the user session message corresponding to the query communication content through the message access module, the first message conversion module, and the message platform.

[0137] S7C: If the query communication content is initiated by the second terminal, send a query failure result to the second terminal.

[0138] After receiving the query content, the intelligent agent determines whether the user who initiated the query communication content matches the query communication content. If it is a second terminal or other terminal querying the user session message of the first terminal, the agent returns a query failure result through the message link.

[0139] In this embodiment, a single terminal can query the terminal's historical user session messages through the message chain, while other terminals cannot query the terminal's historical user session messages. This ensures the security of terminal querying historical user session messages.

[0140] This application also provides a communication method, please refer to... Figure 16 , Figure 16 This is a flowchart illustrating the eleventh embodiment of the communication method of this application. Figure 16 As shown, the communication method is applied to the first terminal, and the communication method includes steps SA1 to SA2.

[0141] Step SA1: Send communication content to the smart surface based on the terminal's native communication function. The smart surface recognizes the communication content and converts it into a first communication instruction. The smart agent executes the task based on the first communication instruction to obtain the task execution result. Specifically, the working method of the first terminal and the smart face in this embodiment has been described in detail in Embodiments 1 to 7, 9 and 10, and will not be repeated here.

[0142] Step SA2: Receive communication data sent by the intelligent surface based on the task execution result.

[0143] After generating a task execution result based on the intelligent agent, the intelligent surface sends the task execution result to the first terminal, and the first terminal receives the communication data sent by the intelligent surface based on the task execution result. Specifically, the method by which the intelligent surface sends the communication data to the first terminal has been described in detail in Embodiment 8, and will not be repeated here.

[0144] In this embodiment, the first terminal sends communication content to the intelligent surface based on its native communication function. The intelligent surface processes the communication content based on the intelligent agent, generates a task execution result, and sends communication data generated based on the task execution result to the first terminal. The first terminal receives the communication data. This enables the first terminal's native communication function to have AI processing capabilities.

[0145] To better illustrate the working method of step SA1, a twelfth embodiment of this application is proposed. Based on the eleventh embodiment of this application, the content that is the same as or similar to that in the eleventh embodiment can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 17 , Figure 17 and Figure 16 The difference is that step SA1 includes step SA11.

[0146] Step SA11: Send the communication content to the AI ​​message assistant through the messaging platform; or, with call AI processing permissions enabled, send the communication content through the application server platform to make a call with the second terminal.

[0147] Specifically, the working method of step SA11 has been described in detail in Examples 2 to 4, and will not be repeated here.

[0148] In this embodiment, the first terminal sends the communication content to the AI ​​message assistant through a messaging platform; or, with AI call processing permissions enabled, it sends the communication content to the second terminal through an application server platform. The messaging platform and application server platform already exist in existing communication systems. Therefore, the communication method in this embodiment is based on existing communication systems and does not require the addition of new communication facilities.

[0149] This application also provides a communication method, please refer to... Figure 18 , Figure 18 This is a flowchart illustrating the thirteenth embodiment of the communication method of this application. Figure 18 As shown, the communication method is applied to the second terminal, and the communication method includes step SB1.

[0150] Step SB1: Receive communication data sent by the intelligent surface based on the task execution result; obtain the communication content sent by the first terminal based on the terminal's native communication function; identify the communication content and convert it into a first communication instruction; execute the task based on the first communication instruction to obtain the task execution result.

[0151] The second terminal can obtain the communication data based on a message link or a call link.

[0152] Specifically, the working methods of the second terminal, the first terminal, and the smart surface have been described in detail in Embodiments 1 to 10, and will not be repeated here.

[0153] In this embodiment, the second terminal can receive communication data sent by the smart terminal, so that the first terminal can initiate smart tasks such as teleconferences to the second terminal or other terminals based on the terminal's native communication functions.

[0154] This application also provides a communication method, please refer to... Figure 19 , Figure 19 This is a flowchart illustrating the fourteenth embodiment of the communication method of this application. Figure 19 As shown, the communication method is applied to a messaging platform, and the communication method includes steps SC1 to SC3.

[0155] Step SC1: Receive communication content sent by the first terminal based on the terminal's native communication function; Specifically, the working methods of the messaging platform and the first terminal have been described in detail in Embodiments 1 to 4, and will not be repeated here.

[0156] Step SC2: Identify whether the communication content has been sent to the AI ​​message assistant; Specifically, the messaging platform can identify whether the communication content is sent to the AI ​​messaging assistant by information such as keywords contained in the communication content or characters at fixed positions in the communication frame.

[0157] Step SC3: When it is recognized that the communication content is sent to the AI ​​message assistant, the communication content is sent to the smart face, the smart face recognizes the communication content and converts the communication content into a first communication instruction, the smart agent executes the task based on the first communication instruction, obtains the task execution result, and the terminal communication associated with the task execution result.

[0158] Specifically, the working methods of the messaging platform, the smart face, the first terminal, and the second terminal have been described in detail in Embodiments 1 to 10, and will not be repeated here.

[0159] In this embodiment, the communication content of the first terminal is sent uplink to the smart surface via a messaging platform. The messaging platform already exists in existing communication systems. Therefore, the communication method in this embodiment is based on existing communication systems and does not require the addition of new communication facilities.

[0160] The messaging platform can also receive downlink communication data from the smart face, for which the fifteenth embodiment of this application is proposed. Based on the fourteenth embodiment of this application, the content that is the same as or similar to the fourteenth embodiment described above in the fifteenth embodiment will not be repeated hereafter. Please refer to... Figure 20 , Figure 20 This is a flowchart illustrating the fifteenth embodiment of the communication method of this application. Figure 20 As shown, Figure 20 and Figure 19 The difference is that the communication method further includes steps SC4 to SC5.

[0161] SC4: Receive a message result from the intelligent surface based on the task execution result; The intelligent surface sends the message result to the message platform via the message link. Specifically, please refer to Example 8 for the working method of the intelligent surface and the message platform in this step.

[0162] SC5: Send the message result to the terminal associated with the task execution result.

[0163] The messaging platform receives the message result, identifies the message result, and sends the message result to the terminal associated with the task execution result based on the identification result.

[0164] In this embodiment, the message result of intelligent surface processing is sent downlink to the terminal associated with the task execution result via a messaging platform. The messaging platform already exists in existing communication systems. Therefore, the communication method in this embodiment is based on existing communication systems and does not require the addition of new communication facilities.

[0165] This application also provides a communication method, please refer to... Figure 21 , Figure 21 This is a flowchart illustrating the sixteenth embodiment of the communication method of this application. Figure 21 As shown, the communication method is applied to the call service control platform, and the communication method includes steps SD1 to SD3.

[0166] SD1: Receives communication content initiated by the first terminal based on the terminal's native communication function; Specifically, the working methods of the call service control platform and the first terminal have been described in detail in Embodiments 1 to 4, and will not be repeated here.

[0167] SD2: Identify whether the first terminal has enabled call AI processing permissions; SD3: When it is recognized that the first terminal has enabled call AI processing permission, the communication content is sent to the intelligent surface, the intelligent surface recognizes the communication content and converts the communication content into a first communication instruction, and executes the task of the first communication instruction based on the intelligent agent to obtain the task execution result, and the terminal communication is associated with the task execution result.

[0168] Specifically, the working methods of the call service control platform, the smart face, the first terminal, and the second terminal have been described in detail in Embodiments 1 to 10, and will not be repeated here.

[0169] In this embodiment, the call service control platform sends the communication content of the first terminal to the smart surface via an uplink. The call service control platform already exists in existing communication systems. Therefore, the communication method in this embodiment is based on existing communication systems and does not require the addition of new communication facilities.

[0170] The call service control platform can also receive downlink communication data from the smart face, for which the seventeenth embodiment of this application is proposed. Based on the sixteenth embodiment of this application, the content that is the same as or similar to that in the sixteenth embodiment described above can be referred to the above description and will not be repeated hereafter. Please refer to... Figure 22 , Figure 22 This is a flowchart illustrating the seventeenth embodiment of the communication method of this application. Figure 22 As shown, Figure 22 and Figure 21 The difference is that the communication method further includes steps SD4 to SD5.

[0171] SD4: Receive the call result from the smart surface based on the task execution result; The intelligent face sends the message result to the call service control platform via the call link. Specifically, please refer to Embodiment Eight for the working methods of the intelligent face and the call service control platform in this step.

[0172] SD5: Initiate a call to the terminal associated with the task execution result based on the call result.

[0173] The call service control platform receives the call result, identifies the call result, and initiates a call to the terminal associated with the task execution result based on the identification result.

[0174] In this embodiment, the call result of the intelligent face processing is sent down to the terminal associated with the task execution result via a call service control platform to initiate a call. The call service control platform already exists in existing communication systems. Therefore, the communication method in this embodiment is based on existing communication systems and does not require the addition of new communication facilities.

[0175] This application also provides a communication system, which includes the aforementioned smart face, first terminal, second terminal, messaging platform, and call service control platform.

[0176] Please refer to the above as well. Figures 23 to 28 , Figures 23 to 28 These are schematic diagrams illustrating different interactions in the communication system of this application, where communication services are subscribed via native terminal messages. For example... Figures 23 to 28 As shown, this communication system is based on the existing 5G communication system and includes a first terminal, a 5GMC (5G Messaging Center), a MaaP platform, a first message conversion module, a chatbot (operator-provided chatbot), a CSP (Communications Service Provider), an intelligent agent, third-party applications, and a scheduled task processing module. For details on the 5GMC message center, MaaP platform, and CSP architecture, please refer to [reference needed]. Figure 1 They are all set up within the existing 5G messaging system. For the architecture of the first message conversion module, intelligent agent, third-party application, and scheduled task processing module, please refer to [reference needed]. Figure 3 They are all located in the smart face.

[0177] In this embodiment, the message types are described as follows: A2P (Application-to-Person): Messages from a chatbot to an end user; P2A (Application-to-Person): Messages from the terminal to the chatbot; P2C (Person-to-Agent): Messages from the terminal to the agent (such as user replies to commands); C2P (Agent-to-Person): Messages from an agent to a terminal (such as an agent pushing results to a user).

[0178] like Figures 23-28 As shown, this process includes the following application scenarios: 1. First-stage traffic reserve notification & triggered check (e.g.) Figure 23 (As shown) 1.1 Request push notification of remaining bandwidth The chatbot sends a request to the CSP to push a notification to the user about the remaining data allowance in their data plan.

[0179] It should be noted that the chatbot mentioned is an enterprise chatbot used by telecom operators.

[0180] 1.2 Send A2P message (data usage remaining notification) The CSP sends an A2P message to the MaaP platform to notify users of their remaining traffic.

[0181] 1.3 Forwarding A2P Messages The MaaP platform sends the A2P message to the 5GMC.

[0182] 1.4 Issue a notification regarding remaining bandwidth The 5GMC sends the A2P message to the first terminal.

[0183] 1.5 Intelligent Analysis Commands The first terminal initiates an intelligent analysis command to the intelligent agent, and then sends the intelligent analysis command to the 5GMC. The intelligent analysis command is a P2C message.

[0184] 1.6 Intelligent Route Analysis Commands 5GMC sends the intelligent analysis instructions to the MaaP platform.

[0185] 1.7 Convert Intelligent Analysis Commands The MaaP platform sends the intelligent analysis command to the first message conversion module.

[0186] 1.7 Routing intelligent analysis instructions to the intelligent agent The first message conversion module sends the intelligent analysis command to the intelligent agent.

[0187] 1.8 Query detailed traffic data After analyzing the intelligent analysis command, the intelligent agent sends a query for detailed traffic data to a third-party application, such as the official website of China Unicom's service platform or the official website of China Mobile's service platform.

[0188] 1.9 Return Traffic Details Third-party applications return traffic details data to the intelligent agent.

[0189] The first stage is suitable for the following application scenarios: The operator's backend monitoring showed that the user had 20GB of remaining data, with only 8 days left before the data plan expired, and predicted that the remaining data would not meet future high data demands. Therefore, a timely notification can be sent to the user, informing them of the risk of insufficient data and potential service limitations. Further immediate solutions can be provided, such as recommending the purchase of a "16GB data package".

[0190] 2. Second-stage intelligent analysis & return solution (e.g.) Figure 24 (As shown) 2.1 Intelligent Analysis The intelligent agent performs intelligent analysis based on the traffic details data returned in step 1.9, such as determining the reason for insufficient traffic, and then generating multiple solutions such as recharging, stopping traffic, or upgrading the plan.

[0191] The intelligent agent generates C2P messages based on the aforementioned multiple solutions.

[0192] 2.2 Sending C2P messages The intelligent agent sends the C2P message to the first message conversion module.

[0193] 2.3 Routing C2P Messages The first message conversion module sends the C2P message to the MaaP platform.

[0194] 2.4 Routing C2P Messages The MaaP platform sends the C2P message to the 5GMC.

[0195] 2.5 Distribute the solution list The 5GMC sends the C2P message to the first terminal.

[0196] The second stage is suitable for the following application scenarios: By using intelligent agents to analyze users' historical consumption habits and current usage data, personalized recommendation strategies can be generated.

[0197] 3. Third-stage automatic recharge (e.g.) Figure 25 (As shown) 3.1 Sending P2C messages The first terminal directly receives the C2P message from step 2.5 and clarifies the selectable operations based on the solution list.

[0198] The first terminal user replies "Select data recharge" on the first terminal, generating a P2C message "Select data recharge".

[0199] The first terminal sends the P2C message to the intelligent agent, and the P2C message is sent to the 5GMC.

[0200] 3.2 Routing P2C Messages 5GMC sends the P2C message to the MaaP platform.

[0201] 3.2 Converting P2C Messages The MaaP platform sends the P2C message to the first message conversion module.

[0202] 3.2 Routing P2C Messages to the Agent The first message conversion module sends the P2C message to the intelligent agent.

[0203] 3.3 Calling the recharge interface The intelligent agent calls the recharge interface of a third-party application to recharge data traffic.

[0204] 3.4 Return recharge result The third-party application returns the recharge result to the smart agent.

[0205] 3.5 Sending C2P Messages The intelligent agent sends a C2P message of the recharge result to the first terminal, and then sends the C2P message to the first message conversion module.

[0206] 3.6 Routing C2P Messages The first message conversion module sends the C2P message to the MaaP platform.

[0207] 3.7 Forwarding C2P Messages The MaaP platform sends the C2P message to the 5GMC.

[0208] 3.7 Issuing recharge results The 5GMC sends the C2P message to the first terminal.

[0209] The third stage is suitable for the following application scenarios: Intelligent agents can be used to perform business functions. For example, when a user clicks to confirm a recharge, the system backend immediately executes the data package subscription instruction without human intervention.

[0210] 4. The fourth stage involves disabling data usage and enabling scheduled tasks (e.g., ...). Figure 26 (As shown) 4.1 Sending P2C messages The first terminal directly receives the C2P message from step 2.5 and clarifies the selectable operations based on the solution list.

[0211] The first terminal user replies "Select Option 4 (Disable Data Traffic + Enable Scheduled Tasks)" on the first terminal, generating a P2C message "Select Option 4 (Disable Data Traffic + Enable Scheduled Tasks)".

[0212] The first terminal sends the P2C message to the intelligent agent, and the P2C message is sent to the 5GMC.

[0213] 4.2 Routing P2C Messages 5GMC sends the P2C message to the MaaP platform.

[0214] 4.2 Converting P2C Messages The MaaP platform sends the P2C message to the first message conversion module.

[0215] 4.2 Routing P2C Messages to the Agent The first message conversion module sends the P2C message to the intelligent agent.

[0216] 4.3 Call the traffic disabling interface The intelligent agent calls the third-party application's disable traffic interface to stop the first terminal's traffic usage function.

[0217] 4.4 Creating Scheduled Tasks The agent invokes the scheduled task processing module to create a scheduled task for "enabling data usage in the next billing cycle".

[0218] 4.5 Scheduled task created successfully The scheduled task processing module sends a notification to the agent that the scheduled task has been successfully created.

[0219] 4.6 Sending C2P messages The intelligent agent sends a C2P message to the first terminal, which reads "Data usage successfully disabled + scheduled task started". The intelligent agent then sends the C2P message to the first message conversion module.

[0220] 4.7 Routing C2P Messages The first message conversion module sends the C2P message to the MaaP platform.

[0221] 4.8 Forwarding C2P Messages The MaaP platform sends the C2P message to the 5GMC.

[0222] 4.8 Issue the deactivation result 5GMC sends the C2P message to the first terminal and returns the result "Successfully disabled traffic + scheduled task started" to the first terminal.

[0223] The fourth stage is suitable for the following application scenarios: Regular checks are performed before the end of the billing cycle to check user balance and data usage status. For example, if the primary card balance is detected to be only 1000MB as of [date], the system will proactively trigger a resource recovery reminder or top-up guidance to ensure service continuity.

[0224] 5. Fifth stage: User habit analysis & authorization application (e.g.) Figure 27 (As shown) 5.1 User habit analysis based on user history The intelligent agent analyzes user habits based on the user's historical operations and generates a C2P message containing "analysis results + scheduled task authorization confirmation request".

[0225] 5.2 Sending C2P messages The intelligent agent sends a C2P message containing "analysis results + timed task authorization confirmation request" to the first terminal, and then sends the C2P message to the first message conversion module.

[0226] 5.3 Routing C2P Messages The first message conversion module sends the C2P message to the MaaP platform.

[0227] 5.4 Forwarding C2P Messages The MaaP platform sends the C2P message to the 5GMC.

[0228] 5.4 Distribute analysis results + authorization request 5GMC sends the C2P message to the first terminal and returns the result of "analysis result + scheduled task authorization confirmation request" to the first terminal.

[0229] 5.5 Sending P2C Messages The first terminal user receives the C2P message from step 5.4, selects to confirm the authorization of the scheduled task, and the first terminal generates a "confirm authorization" P2C message.

[0230] The first terminal sends the P2C message to the intelligent agent, and the P2C message is sent to the 5GMC.

[0231] 5.6 Routing P2C Messages 5GMC sends the P2C message to the MaaP platform.

[0232] 5.6 Converting P2C Messages The MaaP platform sends the P2C message to the first message conversion module.

[0233] 5.6 Routing P2C Messages to the Agent The first message conversion module sends the P2C message to the intelligent agent.

[0234] 5.7 Creating Scheduled Tasks After receiving the P2C message, the intelligent agent sends a scheduled task creation instruction to the scheduled task processing module based on the P2C message to create a scheduled task for "periodic detection of traffic / billing status".

[0235] 5.8 Scheduled task created successfully The scheduled task processing module sends a notification to the agent that the scheduled task has been successfully created.

[0236] The fifth stage is suitable for the following application scenarios: Based on user data accumulation (such as recording users' data usage patterns, recharge frequency and preferences), predictive services can be provided. For example, for users with regular recharge habits, promotional information or package suggestions can be pushed in advance when it is expected that they need to recharge.

[0237] 6. Sixth Phase: User Habit Analysis & Authorization Request (e.g.) Figure 28 (As shown) 6.1 Sending a scheduled task execution signal The scheduled task processing module sends a scheduled task to the agent: "Query all business data".

[0238] 6.2 Query all business data The intelligent agent sends a "query full business data" command to a third-party application.

[0239] 6.2 Returning Business Data The third-party application returns the data result of "querying full business data" to the intelligent agent.

[0240] 6.3 Intelligent analysis based on business data The intelligent agent performs intelligent analysis based on business data and generates a C2P message with a "subsidiary card switching suggestion".

[0241] 6.4 Sending C2P Messages The intelligent agent sends a C2P message of "secondary card switching suggestion" to the first terminal, and the intelligent agent sends the C2P message to the first message conversion module.

[0242] 6.5 Routing C2P Messages The first message conversion module sends the C2P message to the MaaP platform.

[0243] 6.6 Forwarding C2P Messages The MaaP platform sends the C2P message to the 5GMC.

[0244] 6.7 Analysis Results of Sub-SIM Card Switching Recommendations The 5GMC sends the C2P message to the first terminal and returns the result of "secondary card switching suggestion" to the first terminal.

[0245] This application example describes a complete process for completing call / data usage reminders and top-ups using a 5G messaging AI assistant. The operator's enterprise chatbot triggers business scenarios via messages. The intelligent agent uses AI to analyze the user's historical consumption habits and current usage data to generate personalized recommendation strategies. Once the user confirms and selects a specific strategy, the service is automatically completed. This application example achieves fully automated management of the entire process from service initiation to completion.

[0246] Please refer to the above as well. Figures 29 to 34 , Figures 29 to 34 These are schematic diagrams illustrating different interactions in the communication system of this application for scheduling a teleconference via native terminal messages. Figures 29 to 34 As shown, this communication system is based on an existing 5G communication system and includes terminal A, a 5G messaging AI assistant, a 5GMC (5G Messaging Center), a MaaP platform, a first message conversion module, an intelligent agent, a scheduled task processing module, an AS platform, terminal B, and terminal C. For the architecture of the 5GMC and MaaP platform, please refer to [reference needed]. Figure 1 They are all set up within the existing 5G messaging system. Please refer to the AS platform architecture for details. Figure 2 and Figure 3 It is installed in the existing 5G new voice system. For the architecture of the first message conversion module, intelligent agent, and scheduled task processing module, please refer to [reference needed]. Figure 3 They are all located in the smart face.

[0247] In this embodiment, the message types are described as follows: A2P (Application-to-Person): Messages from a chatbot to an end user; P2A (Application-to-Person): Messages from the terminal to the chatbot; P2C (Person-to-Agent): Messages from the terminal to the agent (such as user replies to commands); C2P (Agent-to-Person): Messages from an agent to a terminal (such as an agent pushing results to a user).

[0248] like Figures 29-34As shown, this process includes the following application scenarios: 1. Request for booking the first phase of the meeting (e.g.) Figure 29 (As shown) 1.1 Send meeting reservation message Terminal A sends a meeting reservation message to the 5G Messaging AI Assistant. The meeting reservation message includes the participants, time, and meeting topic.

[0249] It should be noted that the 5G messaging AI assistant is a type of personal AI messaging assistant.

[0250] 1.2 Sending uplink messages Terminal A sends the meeting reservation message to 5GMC.

[0251] 1.3 Transferring Meeting Reservation Requests 5GMC sends the meeting reservation message to the MaaP platform.

[0252] 1.4 Identifying Personal Assistant Messages The MaaP platform recognizes that the meeting reservation message is sent to the 5G messaging AI assistant and then sends the meeting reservation message to the first message conversion module of the intelligent surface.

[0253] 1.5 Message Forwarding The first message conversion module forwards the meeting reservation message to the intelligent agent.

[0254] 2. Request for scheduling the second phase of the meeting (e.g.) Figure 30 (As shown) 2.1 Parse and create scheduled tasks The agent invokes preset agent skills to parse the meeting reservation message and generate the scheduled tasks for the meeting.

[0255] 2.2 Scheduled Execution Meeting The agent sends the scheduled tasks for the meeting to the scheduled task processing module.

[0256] 2.3 Send a meeting reservation success response The intelligent agent sends a C2P message to terminal A confirming the successful booking of the meeting.

[0257] 2.4 Send conference messages to terminal B The intelligent agent sends a C2P message for the scheduled meeting to terminal B.

[0258] 2.5 Send conference messages to terminal C The intelligent agent sends a C2P message scheduled for the meeting to terminal C.

[0259] 3. The third stage involves participants confirming / modifying the meeting time (e.g., ...). Figure 31(As shown) 3.1 Terminal B confirms or modifies the meeting time. Terminal B sends a P2C message to the 5G Messaging AI Assistant to confirm or modify the meeting time.

[0260] 3.2 Terminal C confirms or modifies the meeting time. Terminal C sends a P2C message to the 5G Messaging AI Assistant to confirm or modify the meeting time.

[0261] 3.3 Forward confirmation or modify meeting time During the uplink transmission of the aforementioned P2C message to the 5G Message AI Assistant, the P2C message is forwarded to the intelligent agent.

[0262] 3.4 Update meeting information Upon receiving the P2C message, the intelligent agent initiates an update to the meeting information to the scheduled task processing module to modify the meeting's scheduled time.

[0263] 3.5 Change of Notification Time The intelligent agent sends a notification to terminal A about the time change.

[0264] 3.6 Send confirmation result to terminal B The intelligent agent sends a confirmation message to terminal B regarding the rescheduling of the meeting.

[0265] 3.7 Send confirmation result to terminal C The intelligent agent sends a confirmation message to terminal C regarding the rescheduling of the meeting.

[0266] 4. Reminder for the fourth phase of the meeting (e.g.) Figure 32 (As shown) 4.1 Triggering the Meeting The scheduled task processing module sends a meeting reminder to the agent 5 minutes before the meeting starts.

[0267] 4.2 Proactively send reminder notifications to terminal A The intelligent agent proactively sends a C2P message to terminal A to remind the user.

[0268] 4.3 Proactively send reminder notifications to terminal B The intelligent agent proactively sends a C2P message to terminal B to remind the user.

[0269] 4.4 Proactively send reminder notifications to terminal C The intelligent agent proactively sends a C2P message to the terminal C to remind the user.

[0270] 5. The fifth phase of the meeting begins (e.g.) Figure 33 (As shown) 5.1 Meeting Arrival The scheduled task processing module sends a meeting reminder to the agent when the meeting time arrives.

[0271] 5.2 Sending a meeting creation request The agent sends a creation request to the AS platform.

[0272] 5.3 Initiate a conference call to terminal A The AS platform initiates a conference call to terminal A.

[0273] 5.4 Initiate a conference call to terminal B The AS platform initiates a conference call to terminal B.

[0274] 5.5 Initiate a conference call to terminal C The AS platform initiates a conference call to terminal C.

[0275] 5.6 Terminal A connects to the conference Terminal A receives a meeting request from the AS platform.

[0276] 5.7 Terminal B connects to the conference Terminal B accepts the meeting request from the AS platform.

[0277] 5.8 Terminal C connects to the conference Terminal C receives a meeting request from the AS platform.

[0278] 6. Distribution of meeting minutes for the sixth phase (e.g.) Figure 34 (As shown) 6.1 Send meeting minutes The AS platform generates meeting minutes and sends them to the intelligent agent.

[0279] 6.2 Send meeting minutes to terminal A The intelligent agent sends meeting minutes to terminal A.

[0280] 6.3 Send meeting minutes to terminal B The intelligent agent sends meeting minutes to terminal B.

[0281] 6.4 Send meeting minutes to terminal C The intelligent agent sends meeting minutes to terminal C.

[0282] This application example describes a complete intelligent meeting booking and management process based on a 5G messaging AI assistant. End user A initiates a meeting booking through the 5G messaging AI assistant, and the intelligent agent automatically completes a closed-loop operation, including time parsing, participant identification, meeting creation, reminder notifications, meeting initiation, and minutes distribution, achieving fully automated management from meeting invitation to meeting conclusion.

[0283] This application also provides a communication device, please refer to... Figure 35 The communication device is applied to the smart face, and the communication device includes: The communication content acquisition module 10 is used to acquire the communication content sent by the first terminal based on the terminal's native communication function; Communication content conversion module 20 is used to identify the communication content and convert the communication content into a first communication instruction; The communication task execution module 30 is used to execute the task of the first communication instruction based on the intelligent agent and obtain the task execution result; The communication result return module 40 is used for terminal communication associated with the task execution result.

[0284] The communication device provided in this application, employing the communication method described in the above embodiments, can solve the technical problem of the lack of AI capabilities in the native communication functions of existing terminals. Compared with the prior art, the beneficial effects of the communication device provided in this application are the same as those of the communication method provided in the above embodiments, and other technical features in the communication device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0285] This application provides a communication device, the communication device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the communication method in Embodiment 1 above.

[0286] The following is for reference. Figure 36 The diagram illustrates a structural schematic of a communication device suitable for implementing embodiments of this application. The communication device in the embodiments of this application may include, but is not limited to, a server. Figure 36 The communication device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0287] like Figure 36As shown, the communication device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the communication device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. Communication device 1009 allows communication devices to exchange data wirelessly or wiredly with other devices. Although communication devices with various systems are shown in the figures, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.

[0288] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0289] The communication device provided in this application, employing the communication method described in the above embodiments, can solve the technical problem of the lack of AI capabilities in the native communication functions of existing terminals. Compared with the prior art, the beneficial effects of the communication device provided in this application are the same as those of the communication method provided in the above embodiments, and other technical features of the communication device are the same as those disclosed in the method of the previous embodiment, and will not be repeated here.

[0290] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0291] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0292] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the communication method in the above embodiments.

[0293] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0294] The aforementioned computer-readable storage medium may be included in the communication device; or it may exist independently and not assembled into the communication device.

[0295] The aforementioned computer-readable storage medium carries one or more programs, which, when executed by a communication device, enable the communication device to intelligently process the needs of end users through AI processing capabilities.

[0296] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0297] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0298] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0299] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described communication method, thereby solving the technical problem that the native communication function of existing terminals lacks AI capabilities. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the communication method provided in the above embodiments, and will not be repeated here.

[0300] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the communication method described above.

[0301] The computer program product provided in this application can solve the technical problem that the native communication function of existing terminals lacks AI capabilities. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the communication method provided in the above embodiments, and will not be repeated here.

[0302] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A communication method, characterized in that, Applied to intelligent surfaces, the communication method includes: Obtain the communication content sent by the first terminal based on the terminal's native communication functions; Identify the communication content and convert the communication content into a first communication instruction; Based on the task executed by the intelligent agent using the first communication instruction, the task execution result is obtained; Terminal communication associated with the result of the task execution.

2. The communication method as described in claim 1, characterized in that, The step of obtaining the communication content sent by the first terminal based on the terminal's native communication function includes: The communication content sent by the first terminal is obtained based on the message chain; The steps of terminal communication associated with the task execution result include: A call is made through a call link to the terminal associated with the task execution result.

3. The communication method as described in claim 1, characterized in that, The step of obtaining the communication content sent by the first terminal based on the terminal's native communication function includes: The communication content sent by the first terminal is obtained based on the call link; The steps of terminal communication associated with the task execution result include: Messages are sent to the terminal associated with the task execution result via a message link.

4. The communication method as described in claim 1, characterized in that, The step of obtaining the communication content sent by the first terminal based on the terminal's native communication function includes: Receive message content sent by the messaging platform, wherein the message content is sent by the first terminal to the AI ​​message assistant via the messaging platform; or The system receives the call content between the first terminal and the second terminal from the call service control platform, and the first terminal or the second terminal has enabled call AI processing permissions.

5. The communication method as described in claim 1, characterized in that, The step of identifying the communication content and converting the communication content into a first communication instruction includes: Identify whether the communication content conforms to a preset communication protocol; In response to the fact that the communication content conforms to the preset communication protocol, the communication content is converted into a second communication instruction; The second communication instruction is identified using a rule engine or classification model; In response to the fact that the second communication instruction belongs to the agent processing link, the second communication instruction is converted into the first communication instruction.

6. The communication method as described in claim 1, characterized in that, The step of obtaining the task execution result based on the intelligent agent executing the first communication instruction includes: The first communication instruction is parsed based on the user session message to obtain the structured user intent and task execution sequence. The user session message includes the historical session records of the first terminal. Based on the structured user intent, a preset intelligent agent skill is invoked, and based on the intelligent agent skill, the task execution sequence is input to the task execution module to obtain the task execution result.

7. The communication method as described in claim 6, characterized in that, After the step of obtaining the task execution result based on the intelligent agent executing the first communication instruction, the method further includes: Based on the unique identifier of the first terminal, the communication content and the task execution result are saved as a session record in the user session message.

8. The communication method as described in claim 1, characterized in that, The steps of terminal communication associated with the task execution result include: Identify the routing links for the task execution results; When the routing link is a message link, the task execution result is converted into a message result adapted to the communication standard adopted by the first terminal, and the message result is sent to the terminal associated with the task execution result; When the routing link is a call link, the task execution result is converted into a call result that is compatible with the communication standard used by the first terminal, and a call is initiated to the terminal associated with the task execution result.

9. The communication method as described in claim 8, characterized in that, When the routing link is a message link, the step of converting the task execution result into a message result adapted to the communication standard adopted by the first terminal, and sending the message result to the terminal associated with the task execution result includes: When the routing link is a 5G messaging link, the task execution result is converted into a 5G messaging result adapted to 5G messaging; The 5G message result is sent to the messaging platform, which then sends the 5G message result to the terminal associated with the task execution result.

10. The communication method as described in claim 8, characterized in that, When the routing link is a call link, the step of converting the task execution result into a call result adapted to the communication standard used by the first terminal, and initiating a call to the terminal associated with the task execution result includes: If the routing link is a 5G new call link, then the task execution result will be converted into a new call result adapted to the new call. The new call result is sent to the application server platform, and the application server platform initiates a new call to the terminal associated with the task execution result.

11. The communication method as described in claim 6 or 7, characterized in that, Following the step of terminal communication associated with the task execution result, the method further includes: Receive the call recordings from the first terminal or the second terminal; Based on the unique identifier of the first terminal or the second terminal, the conference call record is saved to the user session message of the first terminal or the second terminal.

12. The communication method as described in claim 6 or 7, characterized in that, Following the step of terminal communication associated with the task execution result, the method further includes: Obtain the query communication content of the user session message sent by the first terminal or the second terminal to query the first terminal; If the query communication content is initiated by the first terminal, the user session message of the first terminal is sent to the first terminal; If the query communication is initiated by the second terminal, a query failure result is sent to the second terminal.

13. A communication method, characterized in that, Applied to a first terminal, the communication method includes: The terminal sends communication content to the smart surface based on its native communication function. The smart surface recognizes the communication content and converts it into a first communication instruction. The smart agent executes the task based on the first communication instruction and obtains the task execution result. Receive communication data sent by the intelligent surface based on the task execution result.

14. The communication method as described in claim 13, characterized in that, The steps for sending communication content to the intelligent surface based on the terminal's native communication function include: Send the communication content to the AI ​​messaging assistant through the messaging platform; or With AI processing permissions enabled, the communication content is sent to the second terminal via the application server platform.

15. A communication method, characterized in that, Applied to a second terminal, the communication method includes: The system receives communication data sent by the intelligent surface based on the task execution result, obtains the communication content sent by the first terminal based on the terminal's native communication function, identifies the communication content and converts the communication content into a first communication instruction, executes the task based on the first communication instruction, and obtains the task execution result.

16. A communication method, characterized in that, The communication method, applied to a messaging platform, includes: Receive communication content sent by the first terminal based on the terminal's native communication functions; Identify whether the communication content is sent to the AI ​​messaging assistant; When it is recognized that the communication content is sent to the AI ​​message assistant, the communication content is sent to the intelligent surface, which recognizes the communication content and converts it into a first communication instruction. The intelligent agent executes the task based on the first communication instruction to obtain the task execution result, and the terminal communication is associated with the task execution result.

17. The communication method as described in claim 16, characterized in that, Also includes: Receive message results from the intelligent surface based on the task execution result; The message result is sent to the terminal associated with the task execution result.

18. A communication method, characterized in that, The communication method, applied to a call service control platform, includes: Receive communication content initiated by the first terminal based on the terminal's native communication functions; Identify whether the first terminal has enabled call AI processing permissions; If it is recognized that the first terminal has enabled call AI processing permission, the communication content is sent to the intelligent surface, which recognizes the communication content and converts it into a first communication instruction. The intelligent agent then executes the task based on the first communication instruction to obtain the task execution result and the terminal communication associated with the task execution result.

19. The communication method as described in claim 18, characterized in that, Also includes: Receive call results from the smart surface based on the task execution result; Based on the call result, initiate a call to the terminal associated with the task execution result.

20. A communication device, characterized in that, The communication device includes: The communication content acquisition module is used to acquire the communication content sent by the first terminal based on the terminal's native communication function; A communication content conversion module is used to identify the communication content and convert the communication content into a first communication instruction; A communication task execution module is used to execute the task based on the first communication instruction by the intelligent agent and obtain the task execution result; The communication result return module is used for terminal communication associated with the task execution result.

21. A communication device, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the communication method as described in any one of claims 1 to 12.

22. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the communication method as described in any one of claims 1 to 12.

23. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps of the communication method as described in any one of claims 1 to 12.

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