system

Abstract

We provide the system. [Solution] The present invention relates to a system that enables telecommunications service retailers to quickly and accurately create, propose, contract, and manage billing for optimal new pricing plans for each customer. The system comprises a customer request acquisition unit, an optimal plan generation unit, a profit determination unit, a new plan creation unit, and a billing monitoring unit. By making essential use of generation AI in each unit, the system automates the entire process from the automatic generation of optimal plan specifications based on diverse and complex customer requests, to the automatic determination of profit criteria, plan registration, and monitoring of billing and payment information and anomaly detection. This simultaneously achieves individual optimization, operational efficiency, profit securing, and trouble prevention, which were difficult with conventional manual or rule-based processing.

Description

Technical Field

[0001] The technology of the present disclosure relates to a system.

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method executed by at least one processor, the method comprising the steps of: receiving a user utterance; adding the user utterance to a prompt including an instruction sentence associated with a description relating to a character of the chatbot; encoding the prompt; and inputting the encoded prompt into a language model to generate a chatbot utterance that responds to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] The problems that this invention aims to solve are: when telecommunications service retailers propose the most suitable pricing plan to customers, the variety and complexity of existing brands and pricing plans means that conventional plan combinations cannot adequately meet the diverse needs and specific requests of each customer, resulting in decreased customer satisfaction, lost sales opportunities, and difficulty in securing company profits; in addition, it is practically difficult for retailers to manually design, calculate profits, register internally, and manage billing for new plans tailored to individual requests, increasing the risk of human error, increased workload, and problems in billing and payment management; and furthermore, there is a need for an efficient and highly accurate system that can quickly and accurately create and propose new plans optimized for each customer, automatically determine whether they meet profit criteria, and automatically monitor billing and payment status after the contract is signed to detect anomalies early. [Means for solving the problem]

[0005] The means for solving the problems according to the present invention is to configure a system comprising a customer request acquisition unit, an optimal plan generation unit, a profit determination unit, a new plan creation unit, and a billing monitoring unit. The customer request acquisition unit acquires various request information from customers via in-store sales staff, such as data communication capacity, whether or not voice calls are made, desired monthly fee, contract period, and optional services. The optimal plan generation unit uses a generation AI to automatically generate an optimal pricing plan specification for the customer that cannot be achieved with combinations of existing pricing plans, using the customer request information as input. The profit determination unit uses a generation AI to determine whether or not the company's profit criteria are met based on the optimal pricing plan specification. If the profit criteria are met, the new plan creation unit uses a generation AI to create a new pricing plan with a unique plan identifier based on the optimal pricing plan specification. The billing monitoring unit uses a generation AI to monitor billing and payment information related to the new pricing plan and automatically detects anomalies in payment status and billing amounts. This automates the rapid and accurate creation, proposal, contract, and billing management of new pricing plans optimized for each customer, reducing the risk of human error, increased workload, and problems in billing and payment management, while simultaneously improving customer satisfaction and company profits. [Brief explanation of the drawing]

[0006] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0007] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0008] First, let's explain the terminology used in the following explanation.

[0009] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), and APU (Accelerated Processing Unit).

[0010] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0011] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include a flash memory (SSD (Solid State Drive)), a magnetic disk (for example, a hard disk), a magnetic tape, or the like.

[0012] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. The communication I / F governs communication between a plurality of computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), and the like.

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Further, in the present specification, when three or more matters are connected and expressed by "and / or", the same concept as that of "A and / or B" is applied.

[0014] [First Embodiment]

[0015] FIG. 1 illustrates an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] As shown in FIG. 1, the data processing system 10 includes a data processing apparatus 12 and a smart device 14. An example of the data processing apparatus 12 is a server.

[0017] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of the "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0018] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, the camera 42, and the communication I / F 44 are also connected to the bus 52.

[0019] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A receives user input via contact of an indicator by detecting the contact of the indicator (for example, a pen, a finger, or the like). The microphone 38B receives voice-based user input by detecting the user's voice. A control unit 46A in the processor 46 transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, a specific processing unit 290 acquires the data indicating the user input.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0021] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0022] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0024] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0025] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0026] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0027] (Example 1)

[0028] The flow of a specific process in Example 1 will now be described. Each part of the system described below is implemented by a data processing device 12 and a smart device 14. The data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0029] (Embodiments for carrying out the present invention)

[0030] Embodiments of the present invention will be described in more detail. The system of the present invention mainly consists of a server and a terminal, and is configured such that a terminal operated by a retail salesperson and a server responsible for various AI processing and data management are linked via a network. The configuration and functions of each part, methods for utilizing generative AI, and the division of roles between the server and the terminal will be described comprehensively with many specific examples below.

[0031] First, the customer request acquisition function is implemented on a tablet, laptop, or smartphone operated by the sales staff at the store. The sales staff, for example, while interacting with the customer across the counter, enters the customer's requests into a dedicated input screen on the terminal. The input fields are wide-ranging, allowing for comprehensive input of diverse customer requests and detailed conditions, such as "I need 50 gigabytes of monthly data," "I want unlimited voice calls both domestically and internationally," "The monthly fee should be within 8,000 yen," "The contract period should be 24 months," "I want to pay for the device in installments," "I want to apply for a family discount," "I want to add options for video streaming services and music streaming services," "I want to use international roaming," "I want to contract for multiple lines as a corporate contract," "I want to apply for student or senior discounts," "I want to add a device warranty service," "I want to increase my data capacity for a short period," and "I want to eliminate data consumption when using a specific app." Furthermore, it is also possible to input the customer's past usage history, contract history, family structure, occupation, age, residential area, current device model, and preferred payment method. This information is transmitted from the terminal to the server in real time.

[0032] Next, the optimal plan generation unit is implemented on the server. The server receives customer request information sent from the terminal and automatically generates the optimal pricing plan specifications using a generative AI. As the generative AI, large-scale language models, generative neural networks, reinforcement learning models, and hybrid types with rule-based AI can be used. For example, if a customer inputs complex and diverse requests such as "I need 30 gigabytes of data communication per month, but I want to increase it to 50 gigabytes in the summer," "Unlimited voice calls are fine only between family members," "I only want to use the video streaming service for six months," "I don't need terminal insurance," "I want to contract 10 lines together under a corporate contract," and "The monthly fee should be within 6,000 yen per line," the generative AI understands these requests through natural language processing and outputs a new pricing plan specification tailored to the customer that cannot be achieved with combinations of existing pricing plans. For example, it automatically generates specific plan specifications such as, "The basic plan has a data capacity of 30 gigabytes, which automatically increases to 50 gigabytes in the summer, calls between family members are unlimited, the video streaming service is free for the first 6 months, then costs 500 yen per month, with a corporate discount of 5800 yen per line per month, and there is no device warranty." Furthermore, the generation AI also refers to big data such as the usage history and contract trends of similar past customers, seasonal fluctuations, regional characteristics, popularity trends of device models, usage rates of optional services, churn rates, and payment delay rates, enabling it to generate dynamically optimized plans such as, "Data usage increases during the new student life season, so increase data capacity only in the spring," "Propose a plan that prioritizes voice calls to senior citizens," "Apply a discount for multiple lines in corporate contracts," and "Include the option as standard in areas where video streaming services are frequently used."

[0033] The profit determination unit is also implemented on the server. The generation AI is used to determine whether the new pricing plan specifications generated by the optimal plan generation unit meet the company's profit criteria. The generation AI comprehensively evaluates multiple parameters, including the monthly fee of the plan, expected communication costs, the cost of optional services, profit reduction due to discounts, customer acquisition costs, future churn risk, payment delay risk, impact on cash flow due to terminal installment payments, and profit compression due to lump-sum discounts for corporate contracts. For example, it automatically performs complex profit determinations such as, "This plan can be offered for 5,800 yen per month, but after deducting communication costs and option costs, the profit is 1,100 yen, which exceeds the company standard of 1,000 yen, so it is acceptable," "If 10 lines are contracted together under a corporate contract, the profit per line after applying discounts will be 900 yen, which does not meet the standard, so it is unacceptable," and "There is a high risk of cash flow deterioration due to terminal installment payments, so an additional deposit needs to be set." Furthermore, the generative AI also takes into account the revenue performance of similar past plans, customer payment delay history, churn rate, and retention rate of optional services. If profits are unstable, it can reject the plan for "not meeting profit criteria" or propose changes to the terms.

[0034] The new plan creation unit is implemented on the server. If the profitability evaluation unit determines it is acceptable, the new plan creation unit uses a generation AI to formally create a new pricing plan based on the optimal plan specifications. The generation AI automatically converts the plan content into the internal system's database format and registers it with a unique plan identifier (e.g., "CUSTOM20240601001"). Furthermore, the generation AI automatically generates plan descriptions, contract terms, notes, detailed explanations of optional services, discount application conditions, points to note when paying for terminal installments, and special notes for corporate contracts, and outputs them to sales staff terminals and customer materials. For example, it automatically generates specific descriptions such as, "This plan allows 30 gigabytes of data communication per month, automatically increases to 50 gigabytes in the summer, unlimited calls between family members, video streaming service is free for the first 6 months, then 500 yen per month, 5800 yen per line per month with corporate discount, no terminal warranty," and displays them on the sales staff terminal. Furthermore, the generative AI will automatically generate a complete set of necessary documents, including contracts, application forms, terms of service for optional services, and device installment payment agreements, and will also support electronic signatures and electronic applications.

[0035] The billing monitoring unit is implemented on a server. After a new pricing plan is contracted, the billing monitoring unit uses a generative AI to monitor billing and payment information related to that plan in real time or periodically. For example, the generative AI automatically checks whether the monthly billing amount is calculated correctly, whether additional charges are being incurred based on the usage of optional services, whether customer payments are completed by the due date, whether there are any overcharges or undercharges, whether the remaining balance of terminal installment payments is being managed accurately, and whether lump-sum billing for corporate contracts is being processed correctly. Furthermore, the generative AI learns from past billing trouble cases and customer payment trends, and can make predictions such as "This customer has had many payment delays in the past, so there is a high risk of delay this month as well" or "Since the lump-sum billing amount is large for corporate contracts, we will focus on monitoring payment confirmation," and can send alert notifications to sales staff terminals and administrator terminals. Furthermore, the generation AI automatically audits complex billing conditions, such as "whether customers were not notified in advance when automatic billing began after the free trial period for optional services ended," "whether the conditions for applying family discounts were met," "whether the remaining balance on device installment payments was paid in full," and "whether the billing amount was correctly recalculated when the number of lines in a corporate contract changed midway through the contract."

[0036] Furthermore, if a customer later requests additional information or changes, such as "I want to temporarily increase my data allowance for this month only," "I want to cancel an optional service midway through the contract," "I want to change my device model midway through the contract," "I want to add more lines to my corporate contract," or "I want to change the family discount eligibility," the salesperson's terminal can send the request to the server, and the generative AI will immediately redesign the plan, perform profit calculations and billing conditions recalculations, and even automatically renew the contract. For example, regarding a temporary increase in data allowance, the generative AI will automatically determine, "We will provide an additional 10 gigabytes for 1,000 yen for this month only, setting an additional charge to meet the profit criteria," and immediately reflect the contract details and billing amount. Regarding the cancellation of an optional service midway through the contract, the AI ​​will automatically calculate complex conditions such as "No penalty fee because it is canceled during the free period" or "Refund will be calculated on a pro-rata basis because it is canceled during the paid period," and will also automatically generate explanatory text for the customer.

[0037] In this way, the system of the present invention implements the customer request acquisition unit on a terminal, and the optimal plan generation unit, profit determination unit, new plan creation unit, and billing monitoring unit on a server, and by making essential use of a generational AI in each unit, it simultaneously achieves customer-specific optimization, automation, and high accuracy, which were difficult to achieve with conventional manual or rule-based processing. A store salesperson simply inputs the customer request on the terminal, and the generational AI on the server side automatically performs complex plan design, profit calculation, and billing monitoring, and the final proposed plan, contract procedure screen, and billing status alerts are displayed on the salesperson's terminal in real time. Furthermore, it can respond flexibly and quickly to changes and additional requests after the contract is signed, so it can comprehensively achieve improved customer satisfaction, operational efficiency, profit maximization, and trouble risk reduction.

[0038] (System Configuration)

[0039] The system according to this embodiment includes a customer request acquisition unit, an optimal plan generation unit, a profit determination unit, a new plan creation unit, and a billing monitoring unit. The customer request acquisition unit has the function of acquiring various request information from customers through a user interface such as a tablet terminal, laptop terminal, or smartphone terminal operated by a salesperson at the store. For example, customers can comprehensively input a wide range of requests and detailed conditions, such as "I need 50 gigabytes of monthly data communication capacity," "I want unlimited voice calls both domestically and internationally," "The monthly fee should be within 8,000 yen," "The contract period should be 24 months," "I would like to pay for the terminal in installments," "I would like to apply for a family discount," "I would like to add options for video streaming services and music streaming services," "I would like to use international roaming," "I would like to contract for multiple lines as a corporate contract," "I would like to apply for a student discount or senior discount," "I would like to add a terminal warranty service," "I would like to increase my data capacity for a short period," or "I would like to make data consumption zero when using a specific app." Furthermore, the customer can also input their past usage history, contract history, family structure, occupation, age, residential area, current terminal model, and preferred payment method, and this information is transmitted from the terminal to the server in real time.

[0040] The optimal plan generation unit is implemented on a server and has the function of receiving customer request information sent from the customer request acquisition unit and automatically generating the optimal pricing plan specifications using a generation AI. For example, if a customer inputs complex and diverse requests such as "I need 30 gigabytes of data communication per month, but I want to increase it to 50 gigabytes in the summer," "Unlimited voice calls are fine only between family members," "I only want to use the video streaming service for six months," "I don't need a device warranty," "I want to contract 10 lines together under a corporate contract," and "The monthly fee should be within 6,000 yen per line," the generation AI will understand these requests through natural language processing and output a new pricing plan specification tailored to the customer that cannot be achieved with combinations of existing pricing plans. Furthermore, the generating AI also references big data such as past usage history and contract trends of similar customers, seasonal fluctuations, regional characteristics, popularity trends of device models, usage rates of optional services, churn rates, and payment delay rates. This allows it to generate dynamic and individually optimized plans, such as "increasing data capacity only in the spring because data usage increases during the new student life season," "proposing a voice call-focused plan for senior citizens," "applying discounts for multiple lines in corporate contracts," and "providing optional services as standard in areas with high video streaming service usage." Specific examples of prompts to be fed into the generating AI include: "The customer wants 50 gigabytes of monthly data, unlimited voice calls, a monthly fee of 8,000 yen or less, a 24-month contract, installment payments for the device, a family discount, the addition of video streaming services, international roaming, a corporate contract with 10 lines bundled, a student discount, device warranty service, increased data capacity for a short period, and zero data consumption when using specific apps. Generate the optimal new pricing plan specifications that meet these requirements."

[0041] The profit determination unit has the function of using a generating AI to determine whether the new pricing plan specifications generated by the optimal plan generation unit meet the company's profit criteria. The generating AI comprehensively evaluates multiple parameters, such as the monthly fee of the plan, expected communication costs, the cost of optional services, profit reduction due to discounts, customer acquisition costs, future churn risk, payment delay risk, impact on cash flow due to terminal installment payments, and profit reduction due to lump-sum discounts for corporate contracts. For example, it automatically performs complex profit determinations such as, "This plan can be offered for 5,800 yen per month, but after deducting communication costs and option costs, the profit is 1,100 yen, which exceeds the company standard of 1,000 yen, so it is acceptable," "If 10 lines are contracted together under a corporate contract, the profit after applying discounts will be 900 yen per line, which does not meet the standard, so it is unacceptable," "There is a high risk of cash flow deterioration due to terminal installment payments, so an additional deposit needs to be set," and "The profit reduction when applying student discounts is large, so shorten the free period for optional services to secure profits." Specific examples of prompts to be fed into the generating AI include: "Comprehensively evaluate the following new pricing plan specifications, including monthly fees, communication costs, option costs, discount application, customer acquisition costs, churn risk, payment delay risk, device installment payment risk, and corporate contract discounts, and determine whether it meets the profit criteria. If it does not meet the profit criteria, suggest which conditions need to be changed to meet the criteria."

[0042] The new plan creation unit has the function of formally creating a new pricing plan based on the optimal plan specifications using a generation AI, provided that the profit evaluation unit determines it is acceptable. The generation AI automatically converts the plan content into the internal system's database format, assigns a unique plan identifier, and registers it. Furthermore, the generation AI automatically generates plan descriptions, contract terms, notes, detailed explanations of optional services, discount application conditions, points to note when paying for terminal installments, and special notes for corporate contracts, and outputs them as sales staff terminals and customer materials. For example, it automatically generates a specific description such as, "This plan allows 30 gigabytes of data communication per month, automatically increases to 50 gigabytes in the summer, unlimited calls between family members, video streaming service is free for the first 6 months, then 500 yen per month, 5800 yen per line per month with corporate discount, no terminal warranty," and displays it on the sales staff terminal. In addition, the generation AI automatically generates a complete set of necessary documents, such as contract documents, application forms, terms of use for optional services, and terminal installment payment agreements, and supports electronic signatures and electronic applications. Specific examples of prompts to be fed into the generation AI include: "Based on the following new pricing plan specifications, automatically generate the data format for internal system registration, plan description for customer explanation, contract terms, notes, details of optional services, discount application conditions, points to note regarding terminal installment payments, special notes for corporate contracts, and a complete set of contract documents."

[0043] The billing monitoring unit has the function of monitoring billing and payment information related to a new pricing plan in real time or periodically using a generating AI after the plan has been contracted. For example, the generating AI automatically checks whether the monthly billing amount is calculated correctly, whether additional charges are being incurred based on the usage of optional services, whether payments from customers are completed by the due date, whether there are any overcharges or undercharges, whether the remaining balance of device installment payments is being managed accurately, and whether lump-sum billing for corporate contracts is being processed correctly. Furthermore, the generating AI learns from past billing trouble cases and customer payment trends and can make predictions such as "This customer has had many payment delays in the past, so there is a high risk of delay this month as well" or "Since the lump-sum billing amount is large for corporate contracts, we will focus on monitoring payment confirmation," and can send alert notifications to sales staff terminals and administrator terminals. The generating AI also automatically audits complex billing conditions such as "whether customers were not notified in advance when automatic billing started after the free period of optional services ended," "whether the conditions for applying family discounts were met," "whether the remaining balance of device installment payments was paid in full," and "whether the billing amount was correctly recalculated when the number of lines for corporate contracts changed midway through the contract." Specific examples of prompt messages to be fed into the generating AI include: "Based on the billing and payment information for the following new rate plan contract, comprehensively audit the validity of the billing amount, whether there are any additional charges, the risk of payment delays, whether there are any overcharges or undercharges, the management of remaining balances on device installment payments, the accuracy of consolidated billing for corporate contracts, the billing conditions for optional services, and the conditions for applying family discounts. If any abnormalities are found, generate an alert notification message."

[0044] As described above, the system according to this embodiment includes a customer request acquisition unit, an optimal plan generation unit, a profit determination unit, a new plan creation unit, and a billing monitoring unit. Each unit makes essential use of the generation AI, enabling the system to consistently automate and highly accurately optimize new pricing plans based on diverse and complex customer requests, ensure profits, handle contract procedures, manage billing, and prevent problems.

[0045] (Implementation Steps)

[0046] Step 1: Obtain detailed customer requirements This step involves obtaining detailed customer request information using user interfaces such as tablet devices, laptops, and smartphones operated by in-store sales staff. For example, customers can comprehensively input a wide range of requests and specific conditions, such as "I need 50 gigabytes of monthly data," "I want unlimited voice calls both domestically and internationally," "My monthly fee should be under 8,000 yen," "The contract period should be 24 months," "I want to pay for the device in installments," "I want to apply for a family discount," "I want to add options for video and music streaming services," "I want to use international roaming," "I want to contract for multiple lines as a corporate contract," "I want to apply for student or senior discounts," "I want a device warranty service," "I want to increase my data capacity for a short period," or "I want to eliminate data consumption when using specific apps." Furthermore, it is possible to input the customer's past usage history, contract history, family structure, occupation, age, residential area, current device model, and preferred payment method, and this information is transmitted from the device to the server in real time.

[0047] Step 2: Automatic generation of optimal plan specifications using AI. This step involves receiving customer request information sent from the customer request acquisition unit on the server and automatically generating the optimal pricing plan specifications using a generation AI. The generation AI uses a hybrid approach, including large-scale language models, generative neural networks, reinforcement learning models, and rule-based AI, to understand customer requests through natural language processing and output new pricing plan specifications tailored to the customer that cannot be achieved with combinations of existing pricing plans. For example, it automatically generates specific plan specifications such as, "Basic plan includes 30 gigabytes of data, automatically increased to 50 gigabytes in the summer, unlimited calls between family members, video streaming service free for the first 6 months, then 500 yen per month thereafter, 5800 yen per line per month with corporate discount applied, no device warranty." Specific examples of prompt messages to be fed into the generating AI include: "The customer wants 50 gigabytes of monthly data, unlimited voice calls, a monthly fee of 8,000 yen or less, a 24-month contract, installment payments for the device, a family discount, the addition of a video streaming service, international roaming, a corporate contract with 10 lines bundled together, a student discount, device warranty service, a short-term data allowance increase, and zero data consumption when using a specific app. Generate the optimal new pricing plan specifications that meet these requirements."

[0048] Step 3: Profit criteria determination by generating AI This step involves using a generating AI to determine whether the new pricing plan specifications generated by the optimal plan generation unit meet the company's profit criteria. The generating AI comprehensively evaluates multiple parameters, including the monthly fee of the plan, expected communication costs, the cost of optional services, profit reduction due to discounts, customer acquisition costs, future churn risk, payment delay risk, impact on cash flow due to terminal installment payments, and profit reduction due to lump-sum discounts for corporate contracts. For example, it automatically performs complex profit assessments such as, "This plan can be offered for 5,800 yen per month, but after deducting communication costs and option costs, the profit is 1,100 yen, which exceeds the company standard of 1,000 yen, so it is acceptable," "If 10 lines are contracted together under a corporate contract, the profit per line after applying discounts will be 900 yen, which does not meet the standard, so it is unacceptable," and "There is a high risk of cash flow deterioration due to terminal installment payments, so an additional deposit needs to be set." Specific examples of prompts to be fed into the generating AI include: "Comprehensively evaluate the following new pricing plan specifications, including monthly fees, communication costs, option costs, discount application, customer acquisition costs, churn risk, payment delay risk, device installment payment risk, and corporate contract discounts, and determine whether it meets the profit criteria. If it does not meet the profit criteria, suggest which conditions need to be changed to meet the criteria."

[0049] Step 4: Formal creation and registration of the new plan using the generation AI. If the profit assessment unit determines it is acceptable, the next step is to use the generation AI to formally create a new pricing plan based on the optimal plan specifications and register it in the internal system. The generation AI automatically converts the plan content into the internal system's database format, assigns a unique plan identifier, and registers it. Furthermore, the generation AI automatically generates a plan description, contract terms, precautions, detailed explanations of optional services, discount application conditions, points to note when paying for terminals in installments, and special notes for corporate contracts, and outputs them as sales staff terminals and customer materials. For example, it automatically generates a specific description such as, "This plan allows 30 gigabytes of data communication per month, automatically increases to 50 gigabytes in the summer, unlimited calls between family members, video streaming service is free for the first 6 months, then 500 yen per month, 5800 yen per line per month with corporate discount applied, no terminal warranty," and displays it on the sales staff terminal. Specific examples of prompts to be fed into the generation AI include: "Based on the following new pricing plan specifications, automatically generate the data format for internal system registration, plan description for customer explanation, contract terms, notes, details of optional services, discount application conditions, points to note regarding terminal installment payments, special notes for corporate contracts, and a complete set of contract documents."

[0050] Step 5: AI-generated monitoring and alert notifications for billing and payment information. This step involves using a generating AI to monitor billing and payment information related to a new pricing plan in real time or periodically after the plan has been contracted, and to send alert notifications if any anomalies are detected. For example, the generating AI automatically checks whether the monthly billing amount is calculated correctly, whether additional charges are being incurred based on the usage of optional services, whether customer payments are completed by the due date, whether there are any overcharges or undercharges, whether the remaining balance of device installment payments is being managed accurately, and whether lump-sum billing for corporate contracts is being processed correctly. Furthermore, the generating AI learns from past billing trouble cases and customer payment trends, and can make predictions such as "This customer has had many payment delays in the past, so there is a high risk of delay this month as well" or "Since the lump-sum billing amount is large for corporate contracts, we will focus on monitoring payment confirmation," and can send alert notifications to sales staff terminals and administrator terminals. Specific examples of prompt messages to be fed into the generating AI include: "Based on the billing and payment information for the following new rate plan contract, comprehensively audit the validity of the billing amount, whether there are any additional charges, the risk of payment delays, whether there are any overcharges or undercharges, the management of remaining balances on device installment payments, the accuracy of consolidated billing for corporate contracts, the billing conditions for optional services, and the conditions for applying family discounts. If any abnormalities are found, generate an alert notification message."

[0051] (Specific use cases)

[0052] For example, when a salesperson in a store uses a tablet to obtain detailed requests from a customer, the customer may present multiple requests such as "I need 40 gigabytes of monthly data," "I want unlimited voice calls both domestically and internationally," "The monthly fee should be under 7,000 yen," "The contract period should be 12 months," "I would like to pay for the device in installments," "I would like to apply for a family discount," "I would like to add a video streaming service option," "I would like to use international roaming," "I would like to apply for a student discount," "I would like to add a device warranty service," and "I would like to have zero data consumption when using specific apps." The salesperson enters these requests into a dedicated input screen on the device, along with the customer's past usage history, contract history, family structure, occupation, age, residential area, current device model, and preferred payment method. This information is transmitted to the server in real time.

[0053] The optimal plan generation unit on the server automatically generates the optimal pricing plan specifications using a generation AI based on the received customer request information. The generation AI takes a prompt message such as, "The customer wants 40 gigabytes of monthly data, unlimited voice calls, a monthly fee of 7,000 yen or less, a contract period of 12 months, installment payments for the device, family discounts, the addition of video streaming services, international roaming, student discounts, device warranty services, and zero data consumption when using specific apps. Generate the optimal new pricing plan specifications that satisfy these requests," and outputs new pricing plan specifications tailored to the customer that cannot be achieved with combinations of existing pricing plans. For example, the generating AI automatically creates specific plan specifications such as: "The basic plan includes 40 gigabytes of data, unlimited voice calls, a monthly fee of 6,800 yen, a 12-month contract period, installment payments for the device are available, a family discount applies for an additional 500 yen off per month, the video streaming service is free for the first three months, then 600 yen per month, international roaming is 980 yen per day, the first month is free with the student discount, the device warranty service is 400 yen per month, and the option for zero data consumption when using specific apps is 300 yen per month."

[0054] The profit determination unit uses a generation AI to comprehensively evaluate the new pricing plan specifications, considering factors such as monthly fees, communication costs, the cost of optional services, profit reduction due to discounts, customer acquisition costs, future churn risk, payment delay risk, and the impact of terminal installment payments on cash flow, and determines whether or not it meets the profit criteria. For example, it might determine, "This plan can be offered for 6,800 yen per month, but after deducting communication costs and option costs, the profit is 1,200 yen, which exceeds the company standard of 1,000 yen, so it is acceptable." A specific example of a prompt message to be fed into the generation AI is, "Comprehensively evaluate the following new pricing plan specifications, considering factors such as monthly fees, communication costs, option costs, discounts, customer acquisition costs, churn risk, payment delay risk, and terminal installment payment risk, and determine whether it meets the profit criteria. If it does not meet the profit criteria, suggest which conditions should be changed to meet the criteria."

[0055] If the profit criteria are met, the new plan creation department uses a generation AI to formally create a new pricing plan based on the optimal plan specifications and register it in the internal system. The generation AI automatically converts the plan content into the internal system's database format, assigns a unique plan identifier, and registers it. Furthermore, the generation AI automatically generates the plan description, contract terms, notes, detailed explanations of optional services, discount application conditions, points to note when paying for terminal installments, student discount application conditions, terms of use for terminal warranty services, and details of the zero data consumption option when using specific applications, and outputs these as sales staff terminals and customer materials. A specific example of a prompt message to be fed into the generation AI is: "Based on the following new pricing plan specifications, automatically generate the data format for internal system registration, the plan description for customer explanation, contract terms, notes, details of optional services, discount application conditions, points to note when paying for terminal installments, special notes on student discounts, terms of use for terminal warranty services, details of the zero data consumption option when using specific applications, and a complete set of contract documents."

[0056] The billing monitoring unit uses a generating AI to monitor billing and payment information related to the plan in real time or periodically, automatically checking whether the monthly billing amount is calculated correctly, whether additional charges are being incurred based on the usage of optional services, whether customer payments are completed by the due date, whether there are any overcharges or undercharges, whether the remaining balance of device installment payments is being managed accurately, whether the eligibility requirements for student and family discounts are being met, and whether the zero data consumption option for using specific apps is being applied correctly. Furthermore, the generating AI learns from past billing trouble cases and customer payment trends, and can make predictions such as "This customer has had many payment delays in the past, so there is a high risk of delay this month as well" or "The eligibility requirements for the family discount have changed, so recalculation is necessary," and can send alert notifications to sales staff terminals and administrator terminals. A specific example of a prompt message to be fed into the generating AI is: "Based on the billing and payment information for the following new rate plan contract, comprehensively audit the legitimacy of the billing amount, whether there are any additional charges, the risk of payment delays, whether there are any overcharges or undercharges, the management of remaining balances on device installment payments, the eligibility requirements for student and family discounts, and the application status of the zero data consumption option when using specific apps. If any abnormalities are found, generate an alert notification message."

[0057] Thus, the system of the present invention can automatically generate optimal new pricing plans using generation AI to meet the diverse and complex needs of each customer, and can consistently and efficiently perform profit assessment, formal registration, and billing monitoring with high accuracy.

[0058] (Application Example 1) The flow of a specific process in Application Example 1 will be explained below. Each part of the system described below is implemented by a data processing device 12 and a smart device 14. The data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0059] (Embodiments for carrying out the present invention)

[0060] Embodiments of the present invention will be described in more detail with greater specificity. The system of the present invention is centered on a user request acquisition unit, an optimal plan generation unit, a profit determination unit, a new plan registration unit, and a billing monitoring unit, which operate cooperatively on the server and user terminal. The functions of each unit, methods of utilizing the generation AI, specific processing examples, operation scenarios, handling of abnormalities, handling of additional requests, data linkage, security, and measures to improve the user experience will be described in depth from multiple perspectives.

[0061] The user request acquisition function is implemented on the user interface of the website or application. For example, users can access it from various devices such as smartphones, tablets, PCs, smart TVs, and game consoles, and specify their desired content genre (anime, movies, documentaries, sports, kids' content, music concerts, news, variety shows, education, hobbies, language learning, business, self-improvement, e-sports, live streaming, foreign dramas, etc.), monthly budget (1,000 yen, 1,500 yen, 2,000 yen, 2,500 yen, 3,000 yen, etc.), and number of simultaneous viewing devices (1, 2, 3, 4, 5, 6, 8, etc.). , whether you want to watch offline (watching while out and about, using during commutes, using while traveling, using on airplanes, using when data limits are reached, etc.), whether you want ads (prefer no ads, want a discount with ads, tolerate some ads, allow ads only for specific genres, etc.), maximum monthly viewing time (30 hours, 50 hours, 100 hours, 200 hours, unlimited, etc.), past viewing history (recently watched titles, frequently watched genres, viewing frequency, viewing trends by day of the week and time of day, continued viewing of specific series, history of shared viewing with family, past Users can input and select details such as their usage history of options, family structure (using with a family of four, using with two children, living with a senior, using alone, sharing with a friend, requesting parental controls, etc.), age group (teens, 20s, 30s, 40s, 50s, 60s and over, preschoolers, elementary school students, junior and senior high school students, university students, working adults, seniors, etc.), type of device used (smartphone, tablet, PC, smart TV, game console, set-top box, in-car terminal, wearable device, etc.), payment method (credit card, electronic payment service, prepaid card, carrier billing, bank transfer, point payment, gift code, etc.), and other usage requests (student discount, family discount, corporate contract, limited-time option addition, zero data consumption when using specific apps, multiple account management, setting viewing history to private, automatic subtitle / dubbing switching, audio guide, barrier-free access, mode for the visually impaired, subtitles for the hearing impaired, language switching, overseas use, VPN support, region-specific content unlocking, temporary data increase during specific events, etc.).This information is transmitted in real time from the user's terminal to the server via encrypted communication, with full consideration given to privacy protection and security.

[0062] The optimal plan generation unit is implemented on a server and receives diverse and detailed user information sent from the user request acquisition unit, automatically generating the optimal subscription plan specifications using generative AI. The generative AI utilizes large-scale language models, generative neural networks, reinforcement learning models, and hybrid rule-based AI, and also refers to natural language processing, pattern recognition, historical data analysis, prediction of similar user behavior, demand forecasting during seasonal fluctuations and events, usage trend analysis for each device, content consumption trends based on family structure and age group, usage rate of optional services, churn rate, payment delay rate, regional characteristics, trend analysis, and buzz on social media. For example, "Since it will be used by a family of four, simultaneous viewing on 4 devices, including kids' content," "Since I am a student, apply the student discount and keep the monthly fee down to 1200 yen," "I only want to watch movies and sports, so..." It can generate dynamic and individually optimized plans, such as "reducing costs by excluding other genres," "including more news and health programs for seniors," "optimizing available genres by day of the week, as users tend to watch more news and documentaries on weekdays and movies and anime on weekends," "enabling offline viewing only during travel periods," "automatically applying parental controls during children's viewing times," "temporarily increasing viewing time limits only during live streaming events," "separating and managing viewing history across multiple accounts," "equipping automatic subtitle / dubbing switching as standard," and "unlocking region-specific content via VPN when used overseas." Furthermore, the generation AI analyzes users' past reasons for cancellation, customer support history, survey responses, and feedback on social media, enabling detailed customization such as "prioritizing ad-free plans for users who previously canceled due to ads," "proposing privacy-enhanced plans for users who requested privacy of their viewing history," and "automatically generating barrier-free plans for users who frequently use subtitles and audio guides."

[0063] The profit determination unit uses a generation AI to determine the profit criteria for the new subscription plan specifications generated by the optimal plan generation unit. For example, for a monthly fee of 1500 yen, the unit considers the following costs: distribution costs per genre (100 yen per hour for anime, 200 yen per movie, 300 yen per match for live sports streaming, 400 yen per event for music concerts, 150 yen per series for variety shows, etc.), the cost of offline functionality (100 yen per device per month, increasing by 50 yen for each additional device), the reduction in advertising revenue due to ad removal (200 yen reduction per month compared to when ads are displayed, 100 yen reduction if ads are only displayed for specific genres), and additional costs due to increased simultaneous viewership (50 yen per device per month, increased server load). The system comprehensively calculates multiple parameters, such as the cost of additional services (an additional 30 yen is added for each additional hour), minimum profit criteria (e.g., securing a profit of 200 yen or more per month), the cost of optional services (e.g., automatic subtitle / dubbing switching is 30 yen per month, barrier-free access is 50 yen per month, VPN support is 40 yen per month, overseas use is 100 yen per month, temporary bonuses during events are 80 yen per month for every 10 hours), profit reduction due to family or student discounts, profit compression due to bulk discounts for corporate contracts, cancellation risk and payment delay risk, impact on cash flow due to additional devices, and operational costs due to managing multiple accounts, to determine whether profit can be secured. For example, it might say, "This plan can be offered for 1500 yen per month, but the total cost is 1200 yen and the profit is 300 yen, which meets the criteria, so it's OK," or "If the number of simultaneous viewers is increased to 4, the profit will be 100 yen, which does not meet the criteria, so it's OK," or "If you want to remove ads, the monthly fee needs to be increased to 1700 yen," or "Limiting the number of offline viewing devices to 2 will meet the profit criteria." The system automatically makes complex profit judgments and proposes changes to conditions. Furthermore, the generative AI also takes into account factors such as past revenue performance of similar plans, user payment delay history, churn rate, retention rate of optional services, risk of temporary cost increases during events, regional cost differences, and the impact of promotional measures. If profits are unstable, it can reject the plan as "not meeting profit criteria" or propose changes to the terms.

[0064] If the profit evaluation unit determines that a new plan is acceptable, the new plan registration unit uses a generative AI to formally create a new subscription plan based on the optimal plan specifications and registers it in the internal system. For example, the generative AI automatically converts the plan content into the internal system's database format and registers it with a unique plan identifier (e.g., CUST20240701001, FAMILY20240701002, STUDENT20240701003). Furthermore, the generative AI automatically generates user-facing plan descriptions ("This plan offers unlimited access to anime and documentaries for ¥1500 per month, simultaneous viewing on 3 devices, offline viewing available, no ads, and up to 50 hours of use per month"), contract terms ("Student ID required for student discounts," "Family discounts are limited to family members at the same address," "Offline viewing is limited to a maximum of 2 devices," "Ad-free option is an additional ¥200 per month"), notes ("Additional charges apply for exceeding viewing time," "Prorated refunds for option cancellations," "Discounts apply from the following month if family structure changes"), details of optional services ("Automatic subtitle / dubbing switching is standard," "Accessibility support is an additional ¥50 per month," "VPN support is an additional ¥40 per month"), discount eligibility conditions, terms of service, parental control explanations, offline viewing instructions, ad-free viewing precautions, electronic signature documents, and electronic application data, and displays them on the user and administrator screens. In addition, it automatically generates contract documents, application forms, terms of service for optional services, and electronic signature documents, enabling support for electronic applications and electronic signatures.

[0065] The billing monitoring department uses generative AI to monitor billing and payment information in real time or periodically after a new subscription plan is signed. For example, it automatically checks whether the monthly billing amount is calculated correctly, whether additional charges are incurred based on the usage of optional services, whether payments from users are completed by the due date, whether there are any overcharges or undercharges, whether the limits on simultaneous viewers or viewing time are not exceeded, whether ad-free and offline viewing features are applied correctly, whether discount application conditions are met, whether parental controls are working properly, whether bulk billing for corporate contracts is processed correctly, whether additional charges due to multiple account management are reflected correctly, whether the usage of region-specific content matches the contract conditions, whether temporary increases during events are charged correctly, whether the setting to hide viewing history is reflected correctly, and whether the usage of accessibility options is managed correctly. For example, the AI ​​automatically audits complex billing conditions and usage statuses, such as "Additional charges will be incurred this month because viewing time has exceeded the limit," "Usage restrictions will be automatically applied because the number of offline viewing devices has exceeded the limit," "Recalculation is required because the eligibility conditions for the family discount have changed," "An alert notification has been sent because the billing for the ad-free option was missed," "Is the billing amount correctly recalculated when the number of lines for a corporate contract changes midway through the year?", and "Does the usage status when managing multiple accounts comply with the contract conditions?". If an anomaly is detected, an alert notification is sent to the administrator terminal and user terminal.

[0066] Furthermore, if a user makes additional requests or changes, such as "I want to temporarily increase my viewing time for this month only," "I want to cancel an optional service midway through the contract," "My family structure has changed, so I want to change the discount conditions," "I want to add a device," "I want to lower the monthly fee in exchange for allowing some ads," "I want to add automatic switching between subtitles and dubbing," "I want to add accessibility features," "I want to temporarily enable overseas use," "I want to temporarily increase the viewing time limit only during events," or "I want to enable the setting to hide my viewing history," the user can send the request from their device to the server, and the generative AI will immediately redesign the plan, perform profit assessments and recalculates billing conditions, and even automatically renew the contract. For example, the app automatically handles detailed changes to conditions and recalculations of fees, such as "additional viewing time incurs an additional 300 yen per month for every 10 hours," "refunds are calculated on a pro-rata basis upon cancellation of options," "changes to family discount eligibility take effect from the following month," "additional devices incur an additional 100 yen per month," "a 200 yen monthly discount if you allow ads to be displayed," "automatic subtitle / dubbing switching incurs an additional 30 yen per month," "barrier-free access incurs an additional 50 yen per month," "overseas use incurs an additional 100 yen per month for every week," "temporary bonuses during events incur an additional 80 yen per month for every 10 hours," and "setting viewing history to private is free and reflected immediately."

[0067] Regarding data integration, the system comprehensively manages user viewing history, usage status, option usage history, payment history, customer support history, survey responses, and feedback on social media. Generative AI learns and analyzes this data in real time to enable personalized recommendations, anomaly detection, trouble prevention, optimization of promotional strategies, and automation of customer support. In terms of security, all communications are encrypted, personal and payment information is strictly managed, and access control, multi-factor authentication, anomaly detection, data tampering prevention, and anonymization processing for privacy protection are incorporated.

[0068] Thus, the system of the present invention comprises a user request acquisition unit, an optimal plan generation unit, a profit determination unit, a new plan registration unit, and a billing monitoring unit. Each unit makes essential use of generational AI, resulting in an extremely comprehensive and advanced configuration that can consistently automate and highly accurately optimize new subscription plans based on diverse and complex user requests, ensure profits, handle contract procedures, manage billing, prevent problems, respond to additional requests, link data, enhance security, and improve the user experience.

[0069] (System Configuration)

[0070] The system according to this embodiment includes a user request acquisition unit, an optimal plan generation unit, a profit determination unit, a new plan registration unit, and a billing monitoring unit. The user request acquisition unit is implemented on the user interface of a website or application, and users can access it from various devices such as smartphones, tablets, PCs, smart TVs, and game consoles to input and select extremely diverse and detailed usage requests and attribute information, such as desired content genre, monthly budget, number of simultaneous viewing devices, whether or not offline viewing is desired, whether or not advertisements are displayed, maximum monthly viewing time, past viewing history, family structure, age group, type of device used, payment method, student discounts and family discounts, corporate contracts, limited-time option additions, zero data consumption when using specific apps, multiple account management, setting viewing history to be private, automatic subtitle / dubbing switching, audio guidance, barrier-free support, mode for the visually impaired, subtitles for the hearing impaired, language switching, overseas use, VPN support, region-specific content unlocking, and temporary data increase during specific events. For example, a user can simultaneously enter multiple requests such as "Focus on anime and documentaries, under 1500 yen per month, simultaneous viewing on 3 devices, offline viewing available, no ads, up to 50 hours of viewing per month, for use by a family of 4, student discount desired, automatic subtitle switching desired, overseas use also being considered." This information is transmitted in real time from the user's device to the server via encrypted communication.

[0071] The optimal plan generation unit is implemented on a server and receives diverse and detailed user information sent from the user request acquisition unit, automatically generating the optimal subscription plan specifications using a generation AI. The optimal plan generation unit utilizes large-scale language models, generative neural networks, reinforcement learning models, and a hybrid of rule-based AI, and also refers to natural language processing, pattern recognition, historical data analysis, prediction of similar user behavior, demand forecasting during seasonal fluctuations and events, usage trend analysis for each device, content consumption trends based on family structure and age group, usage rate of optional services, churn rate, payment delay rate, regional characteristics, trend analysis, and topicality on social media, for example, "For use by a family of four, simultaneous viewing on 4 devices, including kids' content," "As a student, apply student discount and keep the monthly fee down to 1200 yen," "I only want to watch movies and sports." It is possible to generate dynamic and individually optimized plans such as: "Exclude other genres to reduce costs," "Include more news and health programs for seniors," "Optimize available genres by day of the week, as people tend to watch more news and documentaries on weekdays and movies and anime on weekends," "Enable offline viewing only during travel periods," "Automatically apply parental controls during children's viewing times," "Temporarily increase viewing time limits only during live streaming events," "Manage viewing history separately for multiple accounts," "Include automatic subtitle / dubbing switching as standard," and "Release region-restricted content via VPN when used overseas." A specific example of a prompt to be fed into the generating AI is: "The user wants to watch mainly anime and documentaries, for under 1500 yen per month, with simultaneous viewing on 3 devices, offline viewing available, no ads, a maximum of 50 hours of viewing per month, for use by a family of 4, student discount desired, automatic subtitle switching desired, and overseas use also being considered. Generate the optimal new subscription plan specifications that meet these requirements and profit criteria."

[0072] The profit determination unit uses a generating AI to determine the profit criteria for the new subscription plan specifications generated by the optimal plan generation unit. The profit determination unit considers the monthly fee, distribution costs per genre (e.g., 100 yen per hour for anime, 200 yen per movie, 300 yen per match for live sports streaming, 400 yen per event for music concerts, 150 yen per series for variety shows), the cost of offline functions (100 yen per device per month, increasing by 50 yen for each additional device), the decrease in advertising revenue due to ad removal (a decrease of 200 yen per month compared to when ads are displayed, a decrease of 100 yen if ads are only displayed for specific genres), and additional costs due to increased simultaneous viewership (50 yen per device per month, and when server load increases...). The system comprehensively calculates multiple parameters, such as an additional 30 yen, minimum profit criteria (e.g., securing a profit of 200 yen or more per month), the cost of optional services (e.g., automatic subtitle / dubbing switching is 30 yen per month, barrier-free access is 50 yen per month, VPN support is 40 yen per month, overseas use is 100 yen per month, temporary bonuses during events are 80 yen per month for every 10 hours), profit reduction due to family or student discounts, profit compression due to bulk discounts for corporate contracts, cancellation risk and payment delay risk, impact on cash flow due to additional devices, and operational costs due to managing multiple accounts, to determine whether profit can be secured. For example, it might say, "This plan can be offered for 1500 yen per month, but the total cost is 1200 yen and the profit is 300 yen, which meets the criteria, so it's OK," "If the number of simultaneous viewers is increased to 4, the profit will be 100 yen, which does not meet the criteria, so it's OK," "If you want to remove ads, the monthly fee needs to be increased to 1700 yen," or "Limiting the number of offline viewing devices to 2 will meet the profit criteria." The system automatically makes complex profit judgments and proposes changes to conditions. A concrete example of a prompt message to be fed into the generating AI is: "For the following new subscription plan specifications, comprehensively evaluate the monthly fee, distribution costs per genre, offline functionality costs, reduction in advertising revenue due to ad removal, additional costs due to increased concurrent viewership, minimum profit criteria, costs of optional services, reduction in profit due to discounts, churn risk, payment delay risk, impact on cash flow due to additional devices, and operational costs due to managing multiple accounts, and determine whether the profit criteria are met. If the profit criteria are not met, also suggest which conditions should be changed to meet the criteria."" is one example.

[0073] If the profit evaluation unit determines that the new plan registration is acceptable, the new plan registration unit uses a generation AI to formally create a new subscription plan based on the optimal plan specifications and registers it in the internal system. The new plan registration unit automatically converts the plan content into the internal system's database format and registers it with a unique plan identifier (e.g., CUST20240701001, FAMILY20240701002, STUDENT20240701003). Furthermore, the generating AI automatically creates and displays user-facing plan descriptions ("This plan offers unlimited access to anime and documentaries for ¥1500 per month, simultaneous viewing on 3 devices, offline viewing available, no ads, and up to 50 hours of use per month"), contract terms ("Student ID required for student discounts," "Family discounts are limited to family members at the same address," "Offline viewing is limited to a maximum of 2 devices," "Ad-free option is an additional ¥200 per month"), notes ("Additional charges apply for exceeding viewing time," "Prorated refunds for option cancellations," "Discounts apply from the following month if family structure changes"), details of optional services ("Automatic subtitle / dubbing switching is standard," "Accessibility support is an additional ¥50 per month," "VPN support is an additional ¥40 per month"), discount eligibility conditions, terms of service, parental control explanations, instructions for using offline viewing, notes on ad-free viewing, documents for electronic signatures, and data for electronic applications. A specific example of a prompt message to be fed into the generation AI is: "Based on the following new subscription plan specifications, automatically generate the data format for internal system registration, plan description for user explanation, contract terms, notes, details of optional services, discount application conditions, terms of service, parental control explanation, offline viewing usage instructions, notes on ad-free viewing, documents for electronic signature, and data for electronic application."

[0074] The billing monitoring department uses generated AI to monitor billing and payment information in real time or periodically after a new subscription plan is signed. The billing monitoring department automatically checks whether the monthly billing amount is calculated correctly, whether additional charges are incurred based on the usage of optional services, whether payments from users are completed by the due date, whether there are any overcharges or undercharges, whether the limits on simultaneous viewers or viewing time are not exceeded, whether ad-free and offline viewing features are applied correctly, whether discount application conditions are met, whether parental controls are working properly, whether bulk billing for corporate contracts is processed correctly, whether additional charges due to multiple account management are reflected correctly, whether the usage of region-specific content matches the contract conditions, whether temporary increases during events are billed correctly, whether the setting to hide viewing history is reflected correctly, and whether the usage of accessibility options is managed correctly. For example, the AI ​​automatically audits complex billing conditions and usage statuses, such as "Additional charges will be incurred this month because viewing time has exceeded the limit," "Usage restrictions will be automatically applied because the number of offline viewing devices has exceeded the limit," "Recalculation is required because the eligibility conditions for the family discount have changed," "An alert notification has been sent because the billing for the ad-free option was missed," "Is the billing amount correctly recalculated when the number of lines for a corporate contract changes midway through the year?", and "Does the usage status when managing multiple accounts comply with the contract conditions?". If an anomaly is detected, an alert notification is sent to the administrator terminal and user terminal. A concrete example of a prompt message to be fed into the generating AI is: "Based on the billing and payment information for the following new subscription plan contract, comprehensively audit the validity of the billing amount, whether there are any additional charges, the risk of payment delays, whether there are any overcharges or undercharges, whether the limits for simultaneous viewing or viewing time have been exceeded, whether ad-free and offline viewing features have been applied, whether the conditions for discount application have been met, whether parental controls are working, the accuracy of consolidated billing for corporate contracts, whether additional charges due to multiple account management have been reflected, the usage status of region-specific content, the status of temporary data increase charges during events, the reflection of the private viewing history setting, and the management status of accessibility options. If any abnormalities are found, generate an alert notification message."

[0075] Thus, the system according to this embodiment includes a user request acquisition unit, an optimal plan generation unit, a profit determination unit, a new plan registration unit, and a billing monitoring unit. Each unit makes essential use of generation AI, resulting in an extremely comprehensive and advanced configuration that can consistently automate and highly accurately perform tasks ranging from optimizing new subscription plans based on diverse and complex user requests, ensuring profits, contract procedures, billing management, trouble prevention, handling additional requests, data linkage, security enhancement, and improving the user experience.

[0076] (Implementation Steps)

[0077] Step 1: Obtain detailed user request information. The user request acquisition department gathers user requests through the website or application interface, specifying desired content genres (anime, movies, documentaries, sports, kids' content, music concerts, news, variety shows, education, hobbies, language learning, business, self-improvement, esports, live streaming, foreign dramas, etc.), monthly budget (1,000 yen, 1,500 yen, 2,000 yen, 2,500 yen, 3,000 yen, etc.), number of simultaneous viewing devices (1, 2, 3, 4, 5, 6, 8, etc.), and preference for offline viewing. Whether or not you use it (viewing while out and about, using it during your commute, using it while traveling, using it on an airplane, using it when data limits are reached, etc.), whether or not you want ads (prefer no ads, want a discount with ads, tolerate some ads, allow ads only for specific genres, etc.), maximum monthly viewing time (30 hours, 50 hours, 100 hours, 200 hours, unlimited, etc.), past viewing history (recently watched titles, frequently watched genres, viewing frequency, viewing trends by day of the week / time of day, continued viewing of a specific series, history of shared viewing with family, past option usage history, etc.), Users can input and select extremely diverse and detailed usage requests and attribute information, such as family structure (using with a family of four, using with two children, living with a senior, using alone, sharing with a friend, requesting parental controls, etc.), age group (teens, 20s, 30s, 40s, 50s, 60s and over, preschoolers, elementary school students, junior and senior high school students, university students, working adults, seniors, etc.), type of device used (smartphone, tablet, PC, smart TV, game console, set-top box, in-car terminal, wearable device, etc.), payment method (credit card, electronic payment service, prepaid card, carrier billing, bank transfer, point payment, gift code, etc.), student discount, family discount, corporate contract, limited-time option addition, zero data consumption when using specific apps, multiple account management, setting viewing history to private, automatic subtitle / dubbing switching, audio guide, barrier-free access, mode for the visually impaired, subtitles for the hearing impaired, language switching, overseas use, VPN support, region-specific content access, temporary data increase during specific events, etc., and this information is sent to the server in real time.

[0078] Step 2: Automatic generation of optimal plan specifications using AI. The optimal plan generation unit receives diverse and detailed user information sent from the user request acquisition unit and automatically generates the optimal subscription plan specifications using a generation AI. The generation AI utilizes large-scale language models, generative neural networks, reinforcement learning models, and hybrid rule-based AIs, and also references natural language processing, pattern recognition, historical data analysis, prediction of similar user behavior, demand forecasting during seasonal fluctuations and events, usage trend analysis for each device, content consumption trends based on family structure and age group, usage rates of optional services, churn rates, payment delay rates, regional characteristics, trend analysis, and buzz on social media to generate dynamically and individually optimized plans. A specific example of a prompt statement to be fed into the generation AI is: "The user wants to watch mainly anime and documentaries, with a monthly fee of 1500 yen or less, simultaneous viewing on 3 devices, offline viewing available, no ads, a maximum of 50 hours of viewing per month, use by a family of 4, student discount desired, automatic subtitle switching desired, and overseas use also being considered. Generate the optimal new subscription plan specifications that meet these requirements and also meet profit criteria."

[0079] Step 3: Profit criteria determination by generating AI The profit determination unit uses the generation AI to determine the profit criteria for the new subscription plan specifications generated by the optimal plan generation unit. The profit determination unit comprehensively calculates multiple parameters, such as monthly fees, distribution costs per genre, costs of offline functions, reduction in advertising revenue due to ad removal, additional costs due to increased concurrent viewers, minimum profit criteria, costs of optional services, profit reduction due to discounts, churn risk, payment delay risk, impact on cash flow due to additional devices, and operational costs due to managing multiple accounts, to determine whether profit can be secured. A specific example of a prompt message to be fed into the generation AI is: "For the following new subscription plan specifications, comprehensively evaluate the monthly fees, distribution costs per genre, costs of offline functions, reduction in advertising revenue due to ad removal, additional costs due to increased concurrent viewers, minimum profit criteria, costs of optional services, profit reduction due to discounts, churn risk, payment delay risk, impact on cash flow due to additional devices, and operational costs due to managing multiple accounts, and determine whether the profit criteria are met. If the profit criteria are not met, suggest which conditions should be changed to meet the criteria."

[0080] Step 4: Formal creation and registration of the new plan using the generation AI. If the New Plan Registration Unit is deemed acceptable by the Profit Assessment Unit, it uses the Generation AI to formally create a new subscription plan based on the optimal plan specifications and register it in the internal system. The New Plan Registration Unit automatically converts the plan content into the internal system's database format, assigns a unique plan identifier, and registers it. Furthermore, the Generation AI automatically generates user-facing plan descriptions, contract terms, notes, optional service details, discount application conditions, terms of use, parental control explanations, offline viewing usage instructions, ad-free viewing precautions, electronic signature documents, and electronic application data, and displays them on the user and administrator screens. A specific example of a prompt message to be fed into the Generation AI is: "Based on the following new subscription plan specifications, automatically generate the data format for internal system registration, user-facing plan descriptions, contract terms, notes, optional service details, discount application conditions, terms of use, parental control explanations, offline viewing usage instructions, ad-free viewing precautions, electronic signature documents, and electronic application data."

[0081] Step 5: AI-generated monitoring and alert notifications for billing and payment information. The billing monitoring department uses generated AI to monitor billing and payment information in real time or periodically after a new subscription plan is signed. The billing monitoring department automatically checks whether the monthly billing amount is calculated correctly, whether additional charges are incurred based on the usage of optional services, whether payments from users are completed by the due date, whether there are any overcharges or undercharges, whether the limits on simultaneous viewership or viewing time are not exceeded, whether ad-free and offline viewing features are applied correctly, whether discount application conditions are met, whether parental controls are functioning properly, whether bulk billing for corporate contracts is processed correctly, whether additional charges due to multiple account management are reflected correctly, whether the usage of region-specific content matches the contract conditions, whether temporary increases during events are charged correctly, whether the setting to hide viewing history is reflected correctly, and whether the usage of barrier-free options is managed correctly. If an anomaly is detected, an alert notification is sent to the administrator terminal and the user terminal. A concrete example of a prompt message to be fed into the generating AI is: "Based on the billing and payment information for the following new subscription plan contract, comprehensively audit the validity of the billing amount, whether there are any additional charges, the risk of payment delays, whether there are any overcharges or undercharges, whether the limits for simultaneous viewing or viewing time have been exceeded, whether ad-free and offline viewing features have been applied, whether the conditions for discount application have been met, whether parental controls are working, the accuracy of consolidated billing for corporate contracts, whether additional charges due to multiple account management have been reflected, the usage status of region-specific content, the status of temporary data increase charges during events, the reflection of the private viewing history setting, and the management status of accessibility options. If any abnormalities are found, generate an alert notification message."

[0082] (Specific use cases)

[0083] For example, imagine a scenario where a user accesses a content distribution service's website and simultaneously enters multiple detailed requests on the user request acquisition screen, such as "I want to watch mainly anime and documentaries," "My monthly budget is under 1800 yen," "I can use up to 4 devices simultaneously," "I want offline viewing," "I don't want any ads," "My maximum monthly viewing time is 80 hours," "It will be used by a family of four," "I have elementary school-aged children, so I also value kids' content," "I would like a student discount," "I want to use the automatic subtitle switching function," "I want to use it when traveling abroad," "I want to enable the setting to hide my viewing history," and "I also want accessibility features." The user request acquisition unit sends this diverse information to the server in real time. The optimal plan generation unit uses a generation AI based on the received information to automatically generate a newly optimized subscription plan specification, such as "unlimited anime and documentaries, 1780 yen per month, 4 simultaneous viewing devices, offline viewing available, no ads, maximum 80 hours per month, usable by a family of four, kids' content included as standard, student discount applicable, automatic subtitle switching included as standard, region-specific content can be viewed via VPN when used overseas, viewing history privacy setting supported, accessibility option included." A concrete example of a prompt message to be fed into the generating AI is: "The user primarily watches anime and documentaries, with a monthly fee of 1800 yen or less, simultaneous viewing on 4 devices, offline viewing available, no ads, a maximum of 80 hours per month, use by a family of 4, emphasis on kids' content, desires student discounts, desires automatic subtitle switching, desires overseas use, desires privacy of viewing history, and desires accessibility. Generate the optimal new subscription plan specifications that meet these requirements and also meet profit criteria."

[0084] The profit determination unit uses a generating AI to comprehensively calculate the monthly fee, genre-specific distribution costs, offline functionality costs, advertising revenue reduction due to ad removal, additional costs due to increased simultaneous viewership, additional costs for kids' content, costs for automatic subtitle switching and accessibility features, additional costs for overseas use via VPN, profit reduction due to student discounts, minimum profit criteria, cancellation risk, payment delay risk, and operational costs for managing multiple accounts, and determines whether profit can be secured. A specific example of a prompt message to be fed into the generating AI is: "For the following new subscription plan specifications, comprehensively evaluate the monthly fee, genre-specific distribution costs, offline functionality costs, advertising revenue reduction due to ad removal, additional costs due to increased simultaneous viewership, additional costs for kids' content, costs for automatic subtitle switching and accessibility features, overseas use via VPN, profit reduction due to student discounts, minimum profit criteria, cancellation risk, payment delay risk, and operational costs for managing multiple accounts, and determine whether the profit criteria are met. If the profit criteria are not met, suggest which conditions should be changed to meet the criteria."

[0085] If the profit criteria are met, the new plan registration unit uses a generation AI to formally create a new subscription plan based on the optimal plan specifications and register it in the internal system. The generation AI automatically converts the plan content into the internal system's database format, assigns a unique plan identifier, and registers it. It also automatically generates user-facing plan descriptions, contract terms, notes, optional service details, discount application conditions, terms of use, parental control explanations, offline viewing usage instructions, ad-free viewing notes, electronic signature documents, and electronic application data, and displays them on the user and administrator screens. A specific example of a prompt message to be fed into the generation AI is: "Based on the following new subscription plan specifications, automatically generate data format for internal system registration, user-facing plan descriptions, contract terms, notes, optional service details, discount application conditions, terms of use, parental control explanations, offline viewing usage instructions, ad-free viewing notes, electronic signature documents, and electronic application data."

[0086] The billing monitoring unit uses generated AI to monitor billing and payment information in real time or periodically after a contract is signed. It automatically checks whether the monthly billing amount is calculated correctly, whether additional charges are being incurred based on the usage of optional services, whether payments from users are completed by the due date, whether there are any overcharges or undercharges, whether the limits on the number of simultaneous viewers or viewing time are being exceeded, whether ad-free and offline viewing functions are being applied correctly, whether discount application conditions are being met, whether parental controls are working properly, whether additional charges due to multiple account management are being reflected correctly, whether the usage of region-specific content matches the contract conditions, whether temporary increases during events are being charged correctly, whether the setting to hide viewing history is being reflected correctly, and whether the usage of barrier-free options is being managed correctly. If an anomaly is detected, an alert notification is sent to the administrator terminal and the user terminal. A concrete example of a prompt message to be fed into the generating AI is: "Based on the billing and payment information for the following new subscription plan contract, comprehensively audit the legitimacy of the billing amount, whether there are any additional charges, the risk of payment delays, whether there are any overcharges or undercharges, whether the limits for simultaneous viewing or viewing time have been exceeded, whether ad-free and offline viewing features have been applied, whether the discount application conditions have been met, whether parental controls are working, whether additional charges due to multiple account management have been reflected, whether region-specific content has been used, whether temporary increases in data allowances have been charged during events, whether the setting for hiding viewing history has been applied, and whether the accessibility options have been managed. If any abnormalities are found, generate an alert notification message."

[0087] In this way, by using generative AI to automatically generate optimal new subscription plans based on diverse and complex user needs, and by automating the entire process from profit assessment and formal registration to billing monitoring and anomaly detection, it is possible to simultaneously achieve individual optimization, operational efficiency, profit maximization, trouble risk reduction, and improved user experience in content distribution services.

[0088] The specific processing unit 290 transmits the result of the specific processing obtained in the embodiment 1 or application example 1 described above to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0089] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0090] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0091] For example, the data collection unit is implemented by the control unit 46A of the smart device 14 or the specific processing unit 290 of the data processing device 12. For example, the acquisition unit acquires step count data using the camera 42 and communication I / F 44 of the smart device 14 and processes it with the specific processing unit 290 of the data processing device 12. For example, the analysis unit is implemented by the specific processing unit 290 of the data processing device 12 and analyzes the data from the data collection unit and the acquisition unit. For example, the generation unit is implemented by the specific processing unit 290 of the data processing device 12 and generates a cooking menu using generation AI. For example, the serving unit is implemented by the output device 40 of the smart device 14 or the specific processing unit 290 of the data processing device 12 and provides the generated cooking menu to the user. The correspondence between each unit and the devices and control units is not limited to the examples described above and can be modified in various ways.

[0092] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0093] [Second Embodiment]

[0094] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0095] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0096] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0097] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and communication interface 44 are also connected to the bus 52.

[0098] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0099] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0100] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0101] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0102] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0103] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0104] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the identification processing unit 290 using these models.

[0105] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. Each part of the system described below is realized by the data processing device 12 and the smart glasses 214. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0106] (Example 1)

[0107] Since the process flow is the same as in Example 1 described in the First Embodiment above, the explanation will be omitted.

[0108] (Application Example 1) Since the process flow is the same as in Application Example 1 described in the first embodiment above, the explanation will be omitted.

[0109] The specific processing unit 290 transmits the result of the specific processing obtained in the embodiment 1 or application example 1 described above to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0110] Furthermore, the processing by the data processing system 10 described above is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0111] For example, the data collection unit is implemented by the control unit 46A of the smart glasses 214 or the specific processing unit 290 of the data processing device 12. For example, the acquisition unit acquires step count data using the camera 42 and communication I / F 44 of the smart glasses 214 and processes it using the specific processing unit 290 of the data processing device 12. For example, the analysis unit is implemented by the specific processing unit 290 of the data processing device 12 and analyzes the data from the data collection unit and the acquisition unit. For example, the generation unit is implemented by the specific processing unit 290 of the data processing device 12 and generates a cooking menu using generation AI. For example, the serving unit is implemented by the speaker 240 of the smart glasses 214 or the specific processing unit 290 of the data processing device 12 and provides the generated cooking menu to the user. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be modified in various ways.

[0112] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0113] [Third Embodiment]

[0114] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0115] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0116] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0117] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, display 343, and communication interface 44 are also connected to the bus 52.

[0118] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0119] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0120] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0121] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0122] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0123] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0124] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0125] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. Each part of the system described below is implemented by the data processing device 12 and the headset terminal 314. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0126] (Example 1) Since the process flow is the same as in Example 1 described in the First Embodiment above, the explanation will be omitted.

[0127] (Application Example 1) Since the process flow is the same as in Application Example 1 described in the first embodiment above, the explanation will be omitted.

[0128] The specific processing unit 290 transmits the result of the specific processing obtained in the embodiment 1 or application example 1 described above to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0129] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0130] For example, the data collection unit is implemented by the control unit 46A of the headset terminal 314 or the specific processing unit 290 of the data processing device 12. For example, the acquisition unit acquires step count data using the camera 42 and communication I / F 44 of the headset terminal 314 and processes it using the specific processing unit 290 of the data processing device 12. For example, the analysis unit is implemented by the specific processing unit 290 of the data processing device 12 and analyzes the data from the data collection unit and the acquisition unit. For example, the generation unit is implemented by the specific processing unit 290 of the data processing device 12 and generates a cooking menu using generation AI. For example, the serving unit is implemented by the speaker 240 and display 343 of the headset terminal 314 or the specific processing unit 290 of the data processing device 12 and provides the generated cooking menu to the user. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be modified in various ways.

[0131] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0132] [Fourth Embodiment]

[0133] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0134] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0135] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0136] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, controlled object 443, and communication interface 44 are also connected to the bus 52.

[0137] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0138] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0139] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0140] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0141] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0142] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0143] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0144] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0145] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. Each part of the system described below is implemented by the data processing device 12 and the robot 414. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0146] (Example 1) Since the process flow is the same as in Example 1 described in the First Embodiment above, the explanation will be omitted.

[0147] (Application Example 1) Since the process flow is the same as in Application Example 1 described in the first embodiment above, the explanation will be omitted.

[0148] The specific processing unit 290 transmits the result of the specific processing obtained in the embodiment 1 or application example 1 described above to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0149] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or external devices, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or external devices.

[0150] For example, the data collection unit is implemented by the control unit 46A of the robot 414 or the specific processing unit 290 of the data processing device 12. For example, the acquisition unit acquires step count data using the camera 42 and communication I / F 44 of the robot 414 and processes it using the specific processing unit 290 of the data processing device 12. For example, the analysis unit is implemented by the specific processing unit 290 of the data processing device 12 and analyzes the data from the data collection unit and the acquisition unit. For example, the generation unit is implemented by the specific processing unit 290 of the data processing device 12 and generates a cooking menu using a generation AI. For example, the serving unit is implemented by the speaker 240 and controlled object 443 of the robot 414 and the specific processing unit 290 of the data processing device 12 and provides the generated cooking menu to the user. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be modified in various ways.

[0151] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0152] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0153] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0154] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0155] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0156] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0157] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0158] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0159] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0160] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0161] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0162] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0163] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0164] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0165] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0166] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0167] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0168] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0169] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0170] Furthermore, the following additional information is disclosed regarding the above explanation.

[0171] (Claim 1)

[0172] A system for content distribution services comprising a user request acquisition unit, an optimal plan generation unit, a profit determination unit, a new plan registration unit, and a billing monitoring unit, wherein the user request acquisition unit acquires diverse and detailed usage requests and attribute information from users through the user interface of a website or application, such as desired genre, monthly budget, number of simultaneous viewing devices, preference for offline viewing, whether or not to display advertisements, maximum monthly viewing time, past viewing history, frequency of use, family structure, age group, type of device used, and payment method; the optimal plan generation unit uses the information acquired by the user request acquisition unit as input and automatically generates a new subscription plan specification for the user that cannot be realized by combinations of existing subscription plans using a generation AI; and the profit determination unit uses the new subscription plan specification generated by the optimal plan generation unit. The system is characterized by using a generative AI to comprehensively evaluate multiple parameters such as monthly fees, distribution costs for each genre, costs of offline and ad-free functions, additional costs due to increased simultaneous viewers, decrease in advertising revenue, and minimum profit standards to determine whether the profit standards are met. If the profit standards are met, the new plan registration unit assigns a unique plan identifier based on the new subscription plan specifications and registers it in the system. The billing monitoring unit uses a generative AI to monitor billing and payment information related to the new subscription plan in real time or periodically, automatically checking the legitimacy of the billing amount, whether there are additional charges, payment delays, overcharging / undercharging, exceeding the limits on simultaneous viewers and viewing time, and the usage status of optional services, and sending alert notifications to administrators and users if there are any abnormalities. (Claim 2)

[0173] The system according to claim 1, characterized in that the optimal plan generation unit uses a generation AI to generate a new subscription plan specification optimized for each user, taking as input multiple parameters such as genre, budget, number of simultaneous viewing devices, preference for offline viewing, whether or not to display advertisements, viewing time, past viewing history, family structure, age group, type of device used, and payment method obtained by the user request acquisition unit, and further, the new plan registration unit automatically assigns a unique plan identifier that can be managed in the internal system based on the new subscription plan specification and registers the new plan, and also automatically generates a plan description for the user, contract terms, precautions, details of optional services, discount application conditions, and terms of use using a generation AI and displays them on the user screen and administrator screen. (Claim 3)

[0174] The system according to claim 1, characterized in that the billing monitoring unit automatically monitors billing information and payment information based on the new subscription plan in real time or at predetermined intervals using a generation AI, comprehensively audits the legitimacy of the monthly billing amount, whether there are additional charges based on the usage of optional services, whether payments from users are completed on time, whether there are any overcharges or undercharges, whether the limits for simultaneous viewing or viewing time have been exceeded, whether ad-free viewing and offline viewing functions have been applied, whether the conditions for discount application have been met, and risk predictions based on past billing trouble cases and payment trends, and sends alert notifications to administrator terminals and user terminals if an anomaly is detected. [Explanation of Symbols]

[0175] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. A system comprising a customer request acquisition unit, an optimal plan generation unit, a profit determination unit, a new plan creation unit, and a billing monitoring unit, wherein the customer request acquisition unit acquires multiple request information from customers via store sales staff, such as data communication capacity, whether or not voice calls are made, desired monthly fee, contract period, and other optional services; the optimal plan generation unit uses a generation AI to automatically generate an optimal pricing plan specification for the customer that cannot be achieved with combinations of existing pricing plans, based on the customer request information acquired by the customer request acquisition unit; the profit determination unit uses a generation AI to determine whether or not the company's profit criteria are met based on the optimal pricing plan specification generated by the optimal plan generation unit; if the profit criteria are met, the new plan creation unit uses a generation AI to create a new pricing plan with a unique plan identifier based on the optimal pricing plan specification; and the billing monitoring unit uses a generation AI to monitor billing information and payment information related to the new pricing plan and automatically detects abnormalities in payment status and billing amounts.

2. The system according to claim 1, characterized in that the optimal plan generation unit generates a new pricing plan specification optimized for each customer using a generation AI, taking as input multiple parameters such as data communication capacity, whether or not voice calls are made, desired monthly fee, contract period, optional services, past usage history, and customer attribute information included in customer request information, and further, the new plan creation unit automatically assigns a unique plan identifier that can be managed in the company's internal system based on the optimized new pricing plan specification and registers the new pricing plan.

3. The system according to claim 1, characterized in that the billing monitoring unit automatically monitors billing information and payment information based on the new pricing plan in real time or at predetermined intervals using a generation AI, and when it detects an anomaly such as payment delay, non-payment, incorrect billing amount, overcharging, undercharging, or customer objections, it sends an alert notification to the salesperson terminal or administrator terminal.

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