system

Abstract

Provide a system. A means for registering a request for an increase in electricity rates; A means for calculating appropriate electricity unit prices for each region; a means for notifying a user of a fair electricity rate; a means for providing data for price negotiation; a means of providing standard metrics data to external clients; A system including:

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Due to the recent rise in electricity prices, base station owners are increasingly requesting higher electricity rates. Furthermore, when installing new stations, there is a need to quickly determine the appropriate unit price for each region. Furthermore, a data infrastructure that can be used in future price negotiations is necessary, and there is a growing demand for a system that provides standard indicators nationwide. However, there is no integrated system that can meet these demands. [Means for solving the problem]

[0005] The present invention provides a system including a means for registering requests for electricity rate increases, a means for calculating appropriate electricity unit prices for each region, a means for notifying users of the appropriate electricity unit prices, a means for providing data for price reduction negotiations, and a means for providing standard index data to external clients. This system makes it possible to respond quickly and efficiently to electricity rate increases, to build a data base for calculating appropriate unit prices when new stations are installed, and for future price reduction negotiations, and to provide standard indexes nationwide.

[0006] A "request for an increase in electricity rates" is a request submitted by a base station owner or other user who wishes to increase the current electricity rates.

[0007] "Appropriate electricity unit price for each region" refers to the appropriate electricity unit price calculated based on past price history and market fluctuation data in a specific region.

[0008] A "database" is a system or location for systematically storing, managing, and retrieving information.

[0009] An "algorithm" is a specific procedure that defines a series of calculation procedures or rules and solves a problem.

[0010] A "visual report" is a report that presents data in an easy-to-understand manner using visual elements such as graphs and tables.

[0011] An "external client" is a third party who is not a user of the system but uses the data and functions provided by the system.

[0012] "API" stands for Application Programming Interface, an interface that allows different software systems to communicate with each other.

[0013] A "dashboard" is an interface that intuitively displays a visual summary of data and key metrics. [Brief explanation of the drawings]

[0014] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0015] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0018] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0019] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0020] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple 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), etc.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] 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 a "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).

[0026] 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, and the camera 42 are also connected to the bus 52.

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A 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, the specific processing unit 290 acquires the data indicating the user input.

[0028] 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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process 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.

[0032] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0034] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0035] The present invention is an integrated system for registering requests for electricity rate increases, quickly calculating appropriate unit prices for each region, and providing data that can be used in price negotiations. A specific embodiment of the present invention will be described below.

[0036] System Configuration

[0037] This system mainly consists of the following components:

[0038] 1. User terminal: A device through which base station owners and other users enter information and view relevant data.

[0039] 2. Server: A central computing device that processes, stores, and analyzes data.

[0040] 3. Database: Data storage for saving electricity tariff information, request information, historical data, fair unit prices, etc.

[0041] Program Processing Overview

[0042] The programs in this system have the following functions:

[0043] Registering a request for an increase in electricity rates

[0044] The user uses the user terminal to input the required information (e.g., base station location, current electricity rate, desired rate) into a web form or application. This information is first validated by the terminal and then sent to the server. The server registers the received data in a database, enabling request management.

[0045] Calculation of appropriate unit prices for each region

[0046] The server accesses the database of each local power supplier to obtain past electricity rate history and market fluctuation data. The obtained data is analyzed within the server using an algorithm to calculate the appropriate unit price, and the calculation results are saved in the database and updated as needed.

[0047] User notification of fair unit price

[0048] Once the calculation of the appropriate unit price is complete, the server notifies the terminal of the result, which is displayed to the user. For example, if the appropriate unit price for base station A is calculated to be "4,500 yen / month," this information is displayed on the user's screen.

[0049] Providing data for price negotiations

[0050] A user logs into the system and requests data for negotiating price increases. The device forwards this request to the server, which extracts relevant information from the database (e.g., electricity rates for nearby base stations, historical rate fluctuations, and local market trends) and generates a visual report. This report is sent to the device and displayed to the user.

[0051] Providing standard metrics data to external clients

[0052] The server collects electricity bill data from across the country and periodically analyzes it. It then runs the applied algorithms to generate standard index data. This data is packaged and provided to external clients via APIs and dashboards. External clients can use the provided data to set their own rates and negotiate discounts.

[0053] Specific examples

[0054] For example, suppose a base station owner in one of Tokyo's 23 wards inputs a request through the system saying, "I would like to raise my current electricity rate from 3,000 yen / month to 5,000 yen / month." This information is validated on the terminal, then sent to the server and registered in the database.

[0055] Next, the server retrieves data from electricity suppliers in Tokyo's 23 wards and calculates the appropriate unit price based on past price history and market trends. In this case, the appropriate unit price of 4,500 yen / month is calculated and notified to the user.

[0056] Finally, users can log into the system and view detailed reports including nearby cell tower pricing data and market trends, and use this information to negotiate discounts with their power company.

[0057] In this way, the system efficiently manages requests for electricity rate increases and supports the calculation of appropriate unit prices and the provision of data for price negotiations when installing new stations.

[0058] The processing flow will be explained below.

[0059] Step 1:

[0060] Users input their electricity rate increase request using a dedicated web form or application, specifically by entering information such as the base station location, current electricity rate, and desired rate.

[0061] Step 2:

[0062] The terminal receives the data entered by the user and performs initial validation, which checks for required fields and the data format.

[0063] Step 3:

[0064] The terminal transmits the successfully validated data to the server.

[0065] Step 4:

[0066] The server stores the received electricity rate increase request in a database, including the base station location, current electricity rate, and desired rate.

[0067] Step 5:

[0068] The server accesses the database of local power supply companies to obtain electricity rate history and market trend data for the specified area.

[0069] Step 6:

[0070] The server runs an algorithm based on the acquired data to calculate the appropriate electricity unit price, taking into account past price history, local market fluctuations, and future market forecasts.

[0071] Step 7:

[0072] The server stores the calculated fair unit price in a database and simultaneously notifies the terminal.

[0073] Step 8:

[0074] The terminal displays the appropriate unit price to the user, who then checks the appropriate electricity unit price of the base station.

[0075] Step 9:

[0076] A user logs into the system and makes a request for the data needed to negotiate a price increase.

[0077] Step 10:

[0078] The terminal transmits the user's request to the server.

[0079] Step 11:

[0080] The server extracts relevant information from the database (e.g., electricity rate data for nearby base stations, historical rate fluctuation data, and local market trend data).

[0081] Step 12:

[0082] The server formats the extracted data into visual reports, converting the data into graphs and tables.

[0083] Step 13:

[0084] The server transmits the generated report to the terminal.

[0085] Step 14:

[0086] The terminal displays a visual report to the user, who can then use this report to negotiate discounts with the power company.

[0087] Step 15:

[0088] The server periodically collects and analyzes nationwide electricity price data, which it then runs an algorithm to generate standard index data.

[0089] Step 16:

[0090] The server packages the generated metrics data and prepares APIs and dashboards to provide to external clients.

[0091] Step 17:

[0092] External clients can use the provided APIs and dashboards to obtain standard metrics and use them to set their own prices and negotiate discounts.

[0093] Example 1

[0094] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0095] In the conventional system, registering requests for electricity rate increases and calculating appropriate unit prices were often time-consuming and difficult to execute efficiently. Furthermore, there was a lack of effective means to provide the necessary information for users to negotiate discounts. Furthermore, there was a need for a comprehensive and rapid response in collecting electricity rate data nationwide and providing standard index data.

[0096] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0097] In this invention, the server includes means for registering requests for an electricity rate increase, means for calculating an appropriate electricity unit price for each region, means for notifying users of the appropriate electricity unit price, means for providing data for discount negotiations, means for providing standard index data to external clients, means for validating information on the requested electricity rate increase, means for accessing a rate database for each region, means for executing an algorithm for calculating the appropriate unit price, means for structuring the request information and registering it in the database, and means for extracting related information in response to user requests and generating visual reports. This enables efficient registration of requests for an electricity rate increase, rapid calculation of the appropriate unit price, and provision of useful data to users and external clients.

[0098] "Means for registering requests for an increase in electricity rates" refers to a function that allows a user to input a request for an increase in electricity rates and record it in the system.

[0099] "Means for calculating appropriate electricity unit prices for each region" refers to a function for calculating appropriate electricity unit prices for each region based on power supply companies and market data from different regions.

[0100] "Means for notifying the user of the appropriate electricity unit price" refers to a function for notifying the user of the calculated appropriate electricity unit price on the user's terminal so that the user can check it.

[0101] The "means for providing data for price negotiation" refers to a function for providing a user with data and information required for negotiating a price reduction for electricity charges.

[0102] "Means of providing standard index data to external clients" refers to APIs, dashboards, etc. for providing standard electricity rates and market index data to external client companies.

[0103] "Means for validating electricity rate increase request information" refers to a function for verifying and confirming the accuracy and completeness of the rate increase request information entered by the user.

[0104] "Means for accessing a regional fee database" refers to a function for accessing a database that stores fee data for a specific region and obtaining the required information.

[0105] "Means for executing an algorithm for calculating a fair unit price" refers to a function for executing an analytical algorithm for calculating a fair unit price for electricity based on a variety of data.

[0106] "Means for structuring request information and registering it in a database" refers to a function for organizing request information submitted by users and efficiently storing it in a database.

[0107] "Means for extracting relevant information in response to a user request and generating a visual report" refers to a function for extracting information requested by a user from a database and generating a report in an easy-to-read format.

[0108] The present invention is an integrated system for registering requests for electricity rate increases, quickly calculating appropriate unit prices for each region, and providing data that can be used in price negotiations. The following describes in detail an embodiment of the present invention.

[0109] System Configuration

[0110] This system mainly consists of the following components:

[0111] 1. User terminal: A device through which base station owners and other users enter information and view relevant data.

[0112] 2. Server: A central computing device that processes, stores, and analyzes data.

[0113] 3. Database: Data storage for saving electricity tariff information, request information, historical data, fair unit prices, etc.

[0114] 4. API: An interface for providing data to external clients.

[0115] Registering a request for an increase in electricity rates

[0116] The user uses a user terminal to enter the required information (e.g., base station location, current electricity rate, desired rate) into a web form or application. This information is validated in real time by the terminal. For example, if a required field is missing or an invalid value is entered, an error message is displayed to the user. Data that has been successfully validated is sent to the server using HTTPS. The server registers the received data in a database, enabling request management.

[0117] Calculation of appropriate unit prices for each region

[0118] The server accesses the API of the local power supply company to obtain the necessary data. For example, data may be obtained through the API of Tokyo Electric Power Company. In addition, past electricity rate history and market fluctuation data are retrieved from the database. This data is analyzed by the server's appropriate unit price calculation algorithm, and the appropriate electricity unit price is calculated. The calculation results are stored in the database and updated as needed.

[0119] User notification of fair unit price

[0120] Once the calculation of the appropriate unit price has been completed, the server calls an API to notify the device of the results. Some notifications may use WebSocket technology. The device receives the results and displays a specific message on the user's screen, such as "The appropriate unit price for your base station is 4,500 yen / month."

[0121] Providing data for price negotiations

[0122] A user logs into the system and requests data for price increase negotiations. The request can be made with a simple button press. The device forwards this request to the server via HTTPS. The server extracts relevant information from the database, such as "electricity rates of nearby base stations," "past price fluctuations," and "local market trends." The server generates a visual report from the extracted data using a BI tool (e.g., Tableau). The generated report is sent to the device as a PDF or Excel file, and the device displays it to the user.

[0123] Providing standard metrics data to external clients

[0124] The server periodically collects data from each regional electricity supplier in order to centralize nationwide electricity rate data. The server analyzes the collected data at regular intervals (e.g., once a month) and also analyzes long-term market trends. It generates standard indicators using specific algorithms (e.g., moving average method) and packages them in JSON format or similar. It provides the generated standard indicator data to external clients via APIs or dedicated dashboards. External clients download this data and apply it to their own business.

[0125] Examples and prompts

[0126] For example, if a base station owner in Tokyo's 23 wards submits a request through the system saying, "I want to raise my current electricity rate from 3,000 yen / month to 5,000 yen / month," the request would be:

[0127] The user enters information into a web form and submits it.

[0128] The device performs validation and sends the data to the server.

[0129] The server registers the data and accesses TEPCO's API to retrieve the necessary data.

[0130] The server uses past pricing data to calculate the appropriate unit price and comes up with the result "4,500 yen / month."

[0131] The server communicates this information to the terminal, which displays the results to the user.

[0132] Users can request detailed reports and receive reports that include neighboring cell tower data and market trends.

[0133] To operate this system, the prompts sent to the generative AI model are as follows:

[0134] "A base station owner in Tokyo's 23 wards has entered a request to raise their current electricity rate from 3,000 yen / month to 5,000 yen / month. Please explain the detailed process flow, step by step, for calculating the appropriate electricity rate based on this information and notifying the user."

[0135] This prompt sentence enables the generative AI model to generate a specific processing flow for calculating the appropriate unit price and notifying the user.

[0136] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0137] Step 1:

[0138] Input and registration of electricity rate increase requests

[0139] The user uses the user terminal to input the required information into a web form or application. The input information includes the location of the base station, the current electricity rate, and the desired electricity rate. When the user clicks the "Submit" button, the terminal validates the input data (e.g., checking for missing fields or incorrect data format). Data that passes validation is sent to the server via HTTPS. The server structures the received data and registers it in a database along with a timestamp and user ID. The input to the server is the requested information sent from the user terminal, and the output is the structured data registered in the database.

[0140] Step 2:

[0141] Obtaining data on electricity supply companies by region

[0142] The server accesses the power supply company's API to obtain past electricity rate history and market fluctuation data for the specified region. For example, the server obtains data through Tokyo Electric Power Company's API. At this time, the server temporarily stores the obtained data in memory and then also stores it in a database for further analysis. The input is the region-specified request data, and the output is the obtained power supply data.

[0143] Step 3:

[0144] Calculation of appropriate electricity unit price

[0145] The server runs an algorithm to calculate the appropriate electricity unit price based on the historical electricity rate history for each region and market fluctuation data obtained from the database. This algorithm includes, for example, the past average value and the moving average method. The server calculates the appropriate unit price based on the analysis results and saves the result in the database. The input is the obtained power supply data and past rate history, and the output is the calculated appropriate unit price.

[0146] Step 4:

[0147] Notification of fair unit price

[0148] Once the server has calculated the appropriate unit price, it calls an API to notify the user device of the result. The server composes the content of the notification and sends it to the user device in real time using WebSocket technology. Based on the notification received, the device displays details of the appropriate unit price (e.g., 4,500 yen / month) on the user's screen. The input is the calculated appropriate unit price, and the output is a notification message to the user.

[0149] Step 5:

[0150] Requesting and providing price negotiation data

[0151] A user logs into the system and requests data for price negotiation. This request is sent from the user's terminal to the server. The server extracts relevant information based on the request from the database. This information may include "electricity rates of nearby base stations," "past price fluctuations," and "market trends." The server uses a BI tool (e.g., Tableau) to generate a visual report. This report is saved in PDF or Excel format and sent from the server to the user's terminal. The user can view the report on their terminal and use it in negotiations. The input is the user's request, and the output is the generated visual report.

[0152] Step 6:

[0153] Providing standard indicator data

[0154] The server periodically collects data from each regional power supply company in order to centralize nationwide electricity rate data. The server analyzes the collected data at regular intervals and also analyzes long-term market trends. It generates standard indicators using specific algorithms and packages them in formats such as JSON or CSV. These data packages are provided to external clients via APIs or dedicated dashboards. External clients can download this data and use it to set their own rates and negotiate discounts. The input is the collected electricity rate data, and the output is standard indicator data.

[0155] (Application example 1)

[0156] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0157] Because logistics centers consume large amounts of energy, proper management of electricity rates and negotiation of price increases are extremely important. However, current systems have difficulty quickly collecting and analyzing regional electricity rate data and market fluctuation data, calculating appropriate unit prices, and notifying them in real time. Furthermore, the provision of data for price negotiation is insufficient, resulting in inefficient energy management. The purpose of this invention is to provide an integrated system that solves these problems.

[0158] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0159] In this invention, the server includes: means for registering requests for an electricity rate increase; means for calculating an appropriate electricity unit price for each region; means for notifying users of the appropriate electricity unit price; means for providing data for discount negotiations; means for providing standard index data to external clients; means for calculating an appropriate energy unit price based on energy consumption data and supporting energy management at logistics centers; means for including an algorithm for calculating an average appropriate unit price based on past rate data; and means for notifying users of the appropriate unit price in real time to their terminals. This enables prompt and appropriate management of electricity rates and makes it possible to improve the efficiency of energy management at logistics centers by providing data useful for discount negotiations.

[0160] The "means for registering a request for an increase in electricity rates" is a function that allows the user to input and save the current electricity rate and the desired rate.

[0161] The "means for calculating appropriate electricity unit prices for each region" is a function for calculating fair electricity unit prices for each region based on past rate data and market fluctuation data.

[0162] The "means for notifying the user of the appropriate electricity unit price" is a function that transmits the calculated appropriate electricity unit price to the user terminal in real time.

[0163] The "means for providing data for price negotiation" is a function that provides past price data and market information necessary to support the user in price negotiation.

[0164] "Means for providing standard index data to external clients" refers to an API or dashboard that provides unified electricity rate index data to external users.

[0165] "A means to support energy management at logistics centers by calculating appropriate energy rates based on energy consumption data" is a function that supports energy management by collecting and analyzing energy consumption data at logistics centers and calculating fair energy rates.

[0166] The "algorithm for calculating the average fair price based on past rate data" is a calculation method that uses past electricity rate data to find the average value and derive the fair price.

[0167] "Means for notifying the user of the fair unit price in real time" is a function that immediately transmits the calculated fair unit price to the user's device.

[0168] System Configuration

[0169] The present invention is realized by providing a number of components, including a user terminal, a server, a database, and the like.

[0170] 1. User Device

[0171] The user terminal is a device used by the energy manager at the logistics center to input information and check related data. Smartphones, tablets, PCs, etc. are used as user terminals.

[0172] 2. Server

[0173] The server is a central computing device that processes, stores, and analyzes data. The server receives information sent from user devices, calculates appropriate energy rates, and notifies the results to users.

[0174] 3. Database

[0175] The system includes data storage for storing electricity bill information, energy consumption data, billing history data, fair unit prices, etc.

[0176] Program Processing Overview

[0177] Registering a request for an increase in electricity rates

[0178] The user uses the user terminal to input the required information (for example, current electricity bill, desired rate) into a web form or application. This information is first validated by the terminal and then sent to the server. The server registers the received data in a database, enabling request management.

[0179] Calculation of appropriate unit prices for each region

[0180] The server accesses the database of each local power supplier to obtain past electricity rate history and market fluctuation data. The obtained data is analyzed within the server using an algorithm to calculate the appropriate unit price, and the calculation results are saved in the database and updated as needed.

[0181] User notification of fair unit price

[0182] Once the calculation of the appropriate unit price is complete, the server notifies the user of the result and displays it to the user. For example, if the appropriate unit price for logistics center A is calculated to be "4,500 yen / month," this information is displayed on the user's screen.

[0183] Providing data for price negotiations

[0184] A user logs into the system and requests data for negotiating price increases. The terminal forwards this request to the server, which extracts relevant information from the database (e.g., electricity rates for nearby logistics depots, historical rate fluctuations, and local market trends) and generates a visual report. This report is sent to the terminal and displayed to the user.

[0185] Providing standard metrics data to external clients

[0186] The server collects electricity bill data from across the country and periodically analyzes it. It then runs the applied algorithms to generate standard index data. This data is packaged and provided to external clients via APIs and dashboards. External clients can use the provided data to set their own rates and negotiate discounts.

[0187] Adding specific examples

[0188] For example, suppose a logistics center manager in one of Tokyo's 23 wards inputs a request through the system saying, "I would like to raise the current electricity rate from 3,000 yen / month to 5,000 yen / month." This information is validated on the terminal, then sent to the server and registered in the database.

[0189] Next, the server retrieves data from electricity suppliers in Tokyo's 23 wards and calculates the appropriate unit price based on past price history and market trends. In this case, the appropriate unit price of 4,500 yen / month is calculated and notified to the user.

[0190] Finally, users can log into the system and view detailed reports including pricing data from nearby logistics depots and market trends, which they can use to negotiate discounts with their energy provider.

[0191] Prompt Sentence Examples

[0192] "I have entered a request to raise the electricity bill for my logistics center in Tokyo's 23 wards from 3,500 yen / month to 5,000 yen / month. Please calculate the appropriate unit price based on past billing history and generate an analysis report."

[0193] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0194] Step 1:

[0195] The user uses a user terminal to enter desired information such as the current electricity rate, desired rate, and base station location into a web form or application. This input information is validated (format checked) by the terminal and then sent to the server. If the validation results are correct, the system proceeds to the next step.

[0196] Step 2:

[0197] The server receives the electricity rate request data sent from the terminal and registers the data in the database. Specific input data includes user identification information, base station location, current electricity rate, desired rate, etc. This allows for request management.

[0198] Step 3:

[0199] The server accesses the databases of local power suppliers to retrieve historical electricity rates and market trend data. The server then executes appropriate database queries based on the local information. The retrieved data is then used as input data for calculating the appropriate unit price within the server.

[0200] Step 4:

[0201] The server uses the acquired historical electricity rate data and market fluctuation data to execute an algorithm to calculate the appropriate unit price. For example, it calculates the average electricity rate for each region over the past five years to calculate the appropriate unit price. The calculation results are stored in a database and are notified to the user in the next step.

[0202] Step 5:

[0203] After the calculated fair unit price is saved in the database, the server sends the fair unit price information via the communication dispatch system to notify the result to the user terminal. The user terminal receives this and displays it on the screen. For example, if the fair unit price for base station A is calculated to be "4,500 yen / month," this information will be displayed on the user's screen.

[0204] Step 6:

[0205] A user logs into the system and requests data for negotiating price increases. The request includes relevant data (electricity rates from nearby base stations, historical price fluctuations, local market trends, etc.). The device then sends this request to the server.

[0206] Step 7:

[0207] The server extracts the requested relevant data from the database and generates a visual report, specifically, visualizing the relevant data as graphs and charts, and then generates a report summarizing the data. The generated report is then transmitted to the user's device.

[0208] Step 8:

[0209] Users can view the report on their device and use it to negotiate discounts with their power company. The report displays nearby base station fee data and market trends, and users can use this information as a basis for negotiations.

[0210] Step 9:

[0211] The server periodically collects nationwide electricity price data and uses algorithms to generate standard index data, including data processing to analyze average prices by region and historical price trends. The generated index data is then made available to external clients via APIs and dashboards.

[0212] Step 10:

[0213] External clients can use the standard metrics provided to them to set their own prices and negotiate discounts, while data obtained via APIs can be integrated into their own systems to help inform strategic decision-making.

[0214] In this way, the system of the present invention efficiently carries out a series of processes related to energy management, and realizes appropriate calculation of electricity charges and user support.

[0215] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0216] The present invention combines an emotion engine that recognizes the emotions of users with an integrated system that registers requests for electricity rate increases, calculates appropriate unit prices for each region, and provides data that can be used in price negotiations. A specific embodiment of the present invention will be described below.

[0217] System Configuration

[0218] This system mainly consists of the following components:

[0219] 1. User terminal: A device through which base station owners and other users enter information and view relevant data.

[0220] 2. Server: A central computing device that processes, stores, and analyzes data.

[0221] 3. Database: Data storage for saving electricity tariff information, request information, historical data, fair unit prices, etc.

[0222] 4. Emotion engine: A system that analyzes user input data and recognizes the user's emotions.

[0223] Program Processing Overview

[0224] The programs in this system have the following functions:

[0225] Registering a request for an increase in electricity rates

[0226] The user uses a terminal to input the required information (e.g., base station location, current electricity rate, desired rate) into a web form or application. This information is first validated by the terminal and then sent to the server. The server registers the received data in a database, enabling request management.

[0227] Calculation of appropriate unit prices for each region

[0228] The server accesses the database of each local power supplier to obtain electricity rate history and market trend data for the specified area. The obtained data is analyzed within the server using an algorithm to calculate the appropriate unit price, and the calculation results are saved in the database and updated as necessary.

[0229] User Notifications and Emotion Recognition

[0230] Once the calculation of the appropriate unit price is complete, the server notifies the terminal of the result, which is displayed to the user. Furthermore, at this time, the emotion engine analyzes the user's input data (e.g., text input content and past behavioral history) and recognizes the user's emotional state (e.g., satisfaction, dissatisfaction, excitement, etc.). Based on the recognized emotion, the server adjusts the wording of the notification message and provides adaptive feedback to the user.

[0231] Providing data for price negotiations

[0232] A user logs into the system and requests the data needed to negotiate a price increase. The device forwards this request to the server, which extracts relevant information from the database (e.g., electricity rates for nearby base stations, historical price fluctuations, and local market trends) and generates a visual report. This report is sent to the device and displayed to the user.

[0233] Providing standard metrics data to external clients

[0234] The server collects electricity bill data from across the country and periodically analyzes it. It then runs the applied algorithms to generate standard index data. This data is packaged and provided to external clients via APIs and dashboards. External clients can use the provided data to set their own rates and negotiate discounts.

[0235] Specific examples

[0236] For example, suppose a base station owner in one of Tokyo's 23 wards inputs a request through the system saying, "I would like to raise my current electricity rate from 3,000 yen / month to 5,000 yen / month." This information is validated on the terminal, then sent to the server and registered in the database.

[0237] Next, the server retrieves data from electricity suppliers in Tokyo's 23 wards and calculates the appropriate unit price based on past price history and market trends. In this case, the appropriate unit price of 4,500 yen / month is calculated and notified to the user.

[0238] Furthermore, the emotion engine analyzes the user's input and recognizes emotions such as "I'm dissatisfied with the results." Based on the recognized emotion, the server adjusts the notification message to "We will propose a more optimal plan to bring you closer to your needs," and displays it to the user.

[0239] In this way, this system efficiently manages requests for electricity rate increases, supports the calculation of appropriate unit prices when installing new stations, and provides data for price negotiations. It also recognizes user emotions and responds adaptively to provide a better user experience.

[0240] The processing flow will be explained below.

[0241] Step 1:

[0242] Users input their electricity rate increase request using a dedicated web form or application, specifically by entering information such as the base station location, current electricity rate, and desired rate.

[0243] Step 2:

[0244] The terminal receives the data entered by the user and performs initial validation, which checks for required fields and the data format.

[0245] Step 3:

[0246] The terminal transmits the successfully validated data to the server.

[0247] Step 4:

[0248] The server stores the received electricity rate increase request in a database, including the base station location, current electricity rate, and desired rate.

[0249] Step 5:

[0250] The server accesses the database of local power supply companies to obtain electricity rate history and market trend data for the specified area.

[0251] Step 6:

[0252] The server runs an algorithm based on the acquired data to calculate the appropriate electricity unit price, taking into account past price history, local market fluctuations, and future market forecasts.

[0253] Step 7:

[0254] The server stores the calculated fair unit price in a database and simultaneously notifies the terminal.

[0255] Step 8:

[0256] The terminal displays the appropriate unit price to the user, who then checks the appropriate electricity unit price of the base station.

[0257] Step 9:

[0258] The emotion engine analyzes the user's input data and past behavioral history to recognize the user's emotional state. For example, it extracts emotions such as "satisfied" or "dissatisfied" from text content and click patterns.

[0259] Step 10:

[0260] The terminal transmits the user's emotional state recognized by the emotion engine to the server.

[0261] Step 11:

[0262] The server tailors the notification message based on the emotional state received from the emotion engine, for example by including a message offering further information or support to a frustrated user.

[0263] Step 12:

[0264] The server then sends the adjusted notification message to the terminal and displays it to the user, who receives feedback according to their emotional state.

[0265] Step 13:

[0266] A user logs into the system and requests the data needed to negotiate a price increase.

[0267] Step 14:

[0268] The terminal transmits the user's request to the server.

[0269] Step 15:

[0270] The server extracts relevant information from the database (e.g., electricity rate data for nearby base stations, historical rate fluctuation data, and local market trend data).

[0271] Step 16:

[0272] The server formats the extracted data into visual reports, converting the data into graphs and tables.

[0273] Step 17:

[0274] The server sends the generated report to the terminal, where it is displayed to the user.

[0275] Step 18:

[0276] The terminal displays a visual report to the user, who can then use this report to negotiate discounts with the power company.

[0277] Step 19:

[0278] The server periodically collects and analyzes nationwide electricity price data, which it then runs an algorithm to generate standard index data.

[0279] Step 20:

[0280] The server packages the generated metrics data and prepares APIs and dashboards to provide to external clients.

[0281] Step 21:

[0282] External clients can use the provided APIs and dashboards to obtain standard metrics and use them to set their own prices and negotiate discounts.

[0283] Example 2

[0284] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0285] The current system has difficulty effectively registering and managing requests for electricity rate increases and quickly and accurately calculating appropriate electricity unit prices for each region. It also lacks the ability to recognize user emotions and appropriately adjust notification messages accordingly, making it difficult to improve the user experience. Furthermore, there are issues with the efficiency of providing data required for price negotiations and rate setting to external clients. A system that solves these problems is needed.

[0286] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0287] In this invention, the server includes means for registering requests for electricity rate increases, means for calculating appropriate electricity unit prices for each region, means for notifying the user and recognizing their emotional state, means for adjusting the notification message based on the emotional state, means for providing data for price negotiations, and means for providing standard index data to external clients. This makes it possible to effectively manage requests for electricity rate increases and adaptively calculate and notify appropriate unit prices, thereby improving the user experience and providing efficient data.

[0288] An "electricity bill" is the fee that ordinary households and businesses pay to electric power companies for energy consumption.

[0289] A "price increase request" refers to a user expressing to the system a request to increase the current electricity rate.

[0290] A "fair electricity unit price" is a unit price of electricity that is considered reasonable in a particular area, calculated based on market trends and past price history.

[0291] "User" refers to an individual or corporation that uses the system to manage electricity charges or request rate increases.

[0292] An "emotion engine" is a system component that analyzes a user's input and behavioral history and recognizes their emotional state (e.g., satisfaction, dissatisfaction, excitement, etc.).

[0293] A "notification message" is an information message sent from the system to the user, and includes information such as the appropriate unit price and system update information.

[0294] "Discount negotiation data" refers to relevant information required when a user negotiates a discount with an electric power company.

[0295] "Standard index data" is reference data that indicates pricing and market trends, generated by analyzing electricity rate data nationwide.

[0296] "External Client" means a third-party individual or entity that uses standard indicator data provided by the System.

[0297] A "database" refers to data storage that regularly stores and manages information within a system.

[0298] "Validation" is the process of checking the accuracy and validity of entered data.

[0299] An "algorithm" is a set of computational steps that a system executes to solve a particular problem.

[0300] "API" refers to an interface that allows a system to exchange data with external clients.

[0301] A "dashboard" is a user interface that visually displays system usage status and important indicators.

[0302] A "visual report" is a report that organizes data in a visually easy-to-understand manner in the form of graphs, charts, etc.

[0303] The present invention is an integrated system that registers requests for electricity rate increases, calculates appropriate unit prices for each region, and provides data that can be used in price negotiations, and is combined with an emotion engine that recognizes user emotions. Detailed embodiments of the present invention are described below.

[0304] System Configuration

[0305] The system consists of the following main components:

[0306] 1. User terminal: A device on which a user inputs information and checks related data. Examples include smartphones, tablets, and PCs.

[0307] 2. Server: A central computing device that processes, stores, and analyzes data. In this invention, a high-performance cloud server is recommended.

[0308] 3. Database: This is data storage for saving electricity rate information, request information, historical data, fair unit prices, etc. For example, a database management system such as MySQL (registered trademark) or PostgreSQL is used.

[0309] 4. Emotion engine: A system that analyzes user input data and recognizes the user's emotions. Specifically, it uses emotion analysis software that uses natural language processing (NLP) technology.

[0310] Program Processing Overview

[0311] The system has the following main processing functions:

[0312] Registering a request for an increase in electricity rates

[0313] The user uses a terminal to input the required information (e.g., base station location, current electricity rate, desired rate) into a web form or application. This information is first validated by the terminal and then sent to the server. The server registers the received data in a database, enabling request management.

[0314] Calculation of appropriate unit prices for each region

[0315] The server accesses the database of each local power supplier to obtain electricity rate history and market trend data for the specified area. The obtained data is analyzed within the server using an algorithm to calculate the appropriate unit price, and the calculation results are saved in the database and updated as necessary.

[0316] User Notifications and Emotion Recognition

[0317] Once the calculation of the appropriate unit price is complete, the server notifies the terminal of the result, which is displayed to the user. Furthermore, at this time, the emotion engine analyzes the user's input data (e.g., text input content and past behavioral history) and recognizes the user's emotional state (e.g., satisfaction, dissatisfaction, excitement, etc.). Based on the recognized emotion, the server adjusts the wording of the notification message and provides adaptive feedback to the user.

[0318] Providing data for price negotiations

[0319] A user logs into the system and requests the data needed to negotiate a price increase. The device forwards this request to the server, which extracts relevant information from the database (e.g., electricity rates for nearby base stations, historical price fluctuations, and local market trends) and generates a visual report. This report is sent to the device and displayed to the user.

[0320] Providing standard metrics data to external clients

[0321] The server collects electricity bill data from across the country and periodically analyzes it. It then runs the applied algorithms to generate standard index data. This data is packaged and provided to external clients via APIs and dashboards. External clients can use the provided data to set their own rates and negotiate discounts.

[0322] Specific examples

[0323] For example, suppose a base station owner in one of Tokyo's 23 wards inputs a request through the system saying, "I would like to raise my current electricity rate from 3,000 yen / month to 5,000 yen / month." This information is validated on the terminal, then sent to the server and registered in the database.

[0324] Next, the server retrieves data from electricity suppliers in Tokyo's 23 wards and calculates the appropriate unit price based on past price history and market trends. In this case, the appropriate unit price of 4,500 yen / month is calculated and notified to the user.

[0325] Furthermore, the emotion engine analyzes the user's input and recognizes emotions such as "I'm dissatisfied with the results." Based on the recognized emotion, the server adjusts the notification message to "We will propose a more optimal plan to bring you closer to your needs," and displays it to the user.

[0326] Prompt Sentence Examples

[0327] An example of a prompt to input to a generative AI model is as follows:

[0328] "As a base station owner within Tokyo's 23 wards, I would like to raise my current electricity bill from 3,000 yen / month to 5,000 yen / month. Please calculate the appropriate electricity unit price and provide data for price negotiation based on the results. Also, please create a system that recognizes user emotions and provides adaptive feedback."

[0329] Using this prompt, the generative AI model can understand the specific instructions and generate an appropriate response.

[0330] The system of the present invention effectively manages requests for electricity rate increases, supports calculation of appropriate unit prices for new base stations, and provides data for price negotiations. Furthermore, it can provide a better user experience by recognizing user emotions and responding adaptively.

[0331] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0332] Step 1:

[0333] The user enters a request

[0334] The user uses the terminal to input the required information (e.g., base station location, current electricity price, desired price) into the web form or application. The input data is entered in the following format:

[0335] Input: Base station location (e.g., "Shinagawa-ku, Tokyo"), current electricity rate (e.g., "3,000 yen / month"), desired rate (e.g., "5,000 yen / month")

[0336] When the terminal receives this, it formats the data internally and proceeds to the next step.

[0337] Step 2:

[0338] The terminal validates the data

[0339] The terminal validates the input data, specifically performing the following data manipulations and calculations:

[0340] Check whether the base station location is in a real area (e.g., verify whether "Shinagawa Ward, Tokyo" is a valid area).

[0341] Check that your current electricity rate and desired rate are numerical values.

[0342] Input: Information entered by the user

[0343] Output: Valid data (e.g., "Shinagawa-ku, Tokyo", "3000 yen / month", "5000 yen / month")

[0344] If the validation is successful, the terminal transmits the data to the server.

[0345] Step 3:

[0346] The server receives the data and registers it in the database

[0347] The server receives the data sent from the device. The received data is stored in the following format:

[0348] Input: Valid data from the device (e.g., "Shinagawa-ku, Tokyo", "3000 yen / month", "5000 yen / month")

[0349] The server registers this in a database, enabling request management.

[0350] Output: Add a new record to the database (e.g., add the current electricity rate and desired rate to the "Shinagawa Ward, Tokyo" field)

[0351] Step 4:

[0352] The server obtains data to calculate the appropriate unit price for each region.

[0353] The server accesses the power supplier's database to obtain electricity rate history and market trend data for the specified area.

[0354] Input: Area information (e.g. "Shinagawa-ku, Tokyo")

[0355] Output: Electricity rate history by region, market trend data (e.g., "Price history for the past year", "Market trend data")

[0356] The acquired data is used in the next step.

[0357] Step 5:

[0358] The server calculates the appropriate unit price

[0359] The server uses the acquired data to apply an algorithm to calculate the appropriate unit price for each region. Specifically, the following data calculations are performed:

[0360] Calculate the average price from past price history

[0361] Applying predictive models based on market trend data

[0362] Input: Electricity rate history by region, market trend data

[0363] Output: Fair price (e.g. "4500 yen / month")

[0364] The calculation results are stored in a database.

[0365] Step 6:

[0366] The server notifies the device of the results, and the emotion engine recognizes the user's emotions.

[0367] The server notifies the terminal of the calculated fair price and displays it to the user. Based on the displayed result, the emotion engine analyzes the user's input data (e.g., text input content and past behavior history) and recognizes the user's emotional state.

[0368] Input: Fair unit price result (e.g. "4500 yen / month"), user input data

[0369] Output: User's emotional state (e.g. "unhappy")

[0370] The result of the fair unit price being fair will evoke feelings of satisfaction, dissatisfaction, excitement, etc. in the user.

[0371] Step 7:

[0372] The server adjusts notification messages based on emotional state.

[0373] The server adjusts the notification message based on the recognized emotion and provides adaptive feedback to the user. Specifically, it works as follows:

[0374] Select an appropriate feedback message from templates stored on the server for the recognized emotion (e.g., "unhappy").

[0375] Input: User's emotional state

[0376] Output: Optimized notification message (e.g. "We will propose a more optimal plan to meet your needs")

[0377] This provides feedback according to the user's emotions.

[0378] Step 8:

[0379] The user requests data for price negotiation, and the server generates and serves the report.

[0380] Users log into the system and request the data they need to negotiate a price increase. The device forwards this request to the server, which extracts the relevant information from the database and generates a visual report.

[0381] Input: User request (e.g. "Request for price negotiation data")

[0382] Output: Visual report (e.g. "PDF report")

[0383] The report is sent to the terminal and displayed to the user.

[0384] Step 9:

[0385] The server collects and analyzes electricity rate data nationwide to provide standard index data.

[0386] The server periodically collects electricity bill data from across the country and applies algorithms to generate standard index data, which is then provided to external clients via APIs and dashboards.

[0387] Input: Nationwide electricity rate data

[0388] Output: Standard indicator data (e.g., "national average, standard deviation")

[0389] External clients can use this information to set their own prices and negotiate discounts.

[0390] Through these steps, the system can improve the user experience while efficiently managing requests for electricity rate increases and providing data for calculating fair unit prices and negotiating discounts.

[0391] (Application example 2)

[0392] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0393] Conventional electricity rate management systems lack the ability to respond to user needs with detailed consideration, making it difficult to improve user satisfaction. Furthermore, it is difficult to provide the appropriate data required for price negotiations, resulting in a low success rate for negotiations. The present invention aims to solve these problems and support improved user satisfaction and efficient price negotiations.

[0394] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0395] In this invention, the server includes a means for registering requests for an increase in electricity rates, a means for calculating appropriate electricity unit prices for each region, a means for notifying the user of the appropriate electricity unit price, a means for recognizing the user's emotions and adjusting the notification message, and a means for generating a visual report including nearby prices and trend information during price negotiations. This enables a detailed response that takes the user's emotions into consideration, improves the success rate of negotiations, and increases user satisfaction.

[0396] The "means for registering a request for an increase in electricity rates" is a function that allows a user to input a request for an increase in electricity rates into the system and register that information in the database.

[0397] The "means for calculating appropriate electricity unit prices for each region" is a function that calculates appropriate electricity unit prices based on past price history and market trend data in a specific region.

[0398] The "means for notifying the user of the appropriate electricity unit price" is a function for notifying the user of the calculated appropriate electricity unit price.

[0399] The "means for providing data for price negotiation" is a function for providing relevant data necessary when a user negotiates a price.

[0400] The "means for recognizing the user's emotions and adjusting the notification message" is a function that uses an emotion engine to analyze the user's emotions and adaptively adjusts the notification message in accordance with those emotions.

[0401] "Means for generating visual reports including nearby price and trend information during price negotiations" refers to a function for generating reports that visually display nearby prices and market trend information to assist in negotiations.

[0402] "Means for providing standard index data to external clients" refers to a function for collecting and analyzing nationwide electricity rate data, generating standard indexes, and providing them to external clients.

[0403] The "means for managing requests for an increase in electricity rates and storing the same in a database" is a function for efficiently managing requests for an increase in electricity rates from users and storing the data in a database.

[0404] "Means for automatically calculating appropriate unit prices based on past rate history and market fluctuation data" is a function that automatically calculates appropriate electricity unit prices based on past electricity rate history and market fluctuation data.

[0405] "Means for recognizing emotions by analyzing user input data and past behavioral history" is a function for analyzing and recognizing emotions based on user input data and past behavioral history.

[0406] "Means for extracting relevant data in response to a user request and providing it as a visual report" refers to a function that extracts necessary data in response to a user request and provides that data as a visually displayed report.

[0407] "Means for collecting and analyzing electricity rate data nationwide" is a function for analyzing electricity rate data collected from across the country.

[0408] The "means for executing an algorithm for generating a standard index" is a function for executing a specific algorithm for generating a standard index.

[0409] The "means for generating an adaptive notification message based on the user's emotion" is a function for generating an adaptive notification message based on the user's emotion analyzed by the emotion engine.

[0410] "Means for providing an API or dashboard for providing index data to external clients" refers to a function for setting up an API or dashboard for providing index data to external clients.

[0411] This is an integrated system that manages requests for electricity rate increases, calculates appropriate electricity unit prices for each region, notifies users of these prices, and provides adaptive notification messages through emotion recognition. It also generates visual reports including nearby prices and trend information during price negotiations, and provides standard index data to external clients.

[0412] System configuration

[0413] This system consists of the following components:

[0414] 1. User terminal: A device on which a user inputs their request for an increase in electricity rates and checks related data. This is often a smartphone or tablet.

[0415] 2. Server: The central computing device that processes, stores, and analyzes data, and performs fair pricing and emotion recognition.

[0416] 3. Database: Data storage for saving electricity rate information, user request information, historical data, appropriate unit prices for each region, etc.

[0417] 4. Emotion Engine: A system that analyzes user input data and recognizes user emotions. It uses the BERT model and other emotion recognition algorithms.

[0418] Program Processing Overview

[0419] 1. Request registration

[0420] A user uses a user terminal to input required information into a web form or application, including location, current electricity rate, and desired rate.

[0421] The entered information is validated in real time and then sent to the server, which registers the received data in a database and manages requests.

[0422] 2. Calculating the appropriate unit price

[0423] The server retrieves past electricity rate history and market trend data from the database and calculates the appropriate unit price. The system calculates the appropriate unit price using data analysis libraries such as Pandas and Scikit-learn.

[0424] The calculated fair unit price is stored in a database and updated as necessary.

[0425] 3. Emotion Recognition and Notification

[0426] The server notifies the user of the calculated fair price. When notifying the user, the emotion engine analyzes the user's input data and recognizes the user's emotion.

[0427] Generative AI models such as the BERT model are used for emotion recognition. An example prompt is as follows:

[0428] python

[0429] import transformers

[0430] Loading the model

[0431] model_name = "nlptown / bert-base-multilingual-uncased-sentiment"

[0432] tokenizer = transformers.AutoTokenizer.from_pretrained(model_name)

[0433] model = transformers.AutoModelForSequenceClassification.from_pretrained(model_name)

[0434] text = "I am extremely dissatisfied with this service."

[0435] inputs = tokenizer.encode_plus(

[0436] text,

[0437] add_special_tokens=True,

[0438] return_tensors="pt"

[0439] )

[0440] Model prediction

[0441] outputs = model(inputs)

[0442] prediction = torch.argmax(outputs.logits, dim=1).item()

[0443] Emotion-based response message generation

[0444] if prediction == 0:

[0445] response_message = "We apologize for the inconvenience. We will look into resolving this issue immediately."

[0446] elif prediction == 1:

[0447] response_message = "We appreciate your feedback."

[0448] else:

[0449] response_message = "Thank you for using our service. We look forward to working with you in the future."

[0450] print(response_message)

[0451] Based on the recognized emotion, the server adjusts the wording of the notification message and provides adaptive feedback to the user.

[0452] 4. Providing discount negotiation data

[0453] When a user logs into the system and requests the data needed to negotiate a price, the server extracts the relevant information from the database and uses libraries (Matplotlib and Seaborn) to generate visual reports.

[0454] The generated report is sent to the user terminal and displayed to the user.

[0455] 5. Providing standard indicator data to external clients

[0456] The server periodically collects electricity bill data from across the country and runs data analysis algorithms such as Pandas and Scikit-learn.

[0457] The generated standard metrics data is provided to external clients via APIs and dashboards.

[0458] In this way, the system efficiently manages requests for electricity rate increases, improves the user experience by providing notification messages that reflect the user's feelings, and increases the user's success rate in negotiating discounts by providing necessary data for price negotiations.

[0459] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0460] Step 1:

[0461] Register your request

[0462] The user uses a terminal to open a web form or application and input a request for an increase in electricity rates. The information entered includes location, current electricity rate, and desired rate. This input data is validated in real time and, if there are no problems, is sent to the server. The server registers the received data in a database and manages the request.

[0463] Input: User's request for rate increase (location, current electricity rate, desired rate)

[0464] Output: Request information registered in the database

[0465] Processing operation: The server validates the input data and saves it in the database.

[0466] Step 2:

[0467] Calculating the appropriate unit price

[0468] The server retrieves historical electricity rates and market trend data from the database. Based on the retrieved data, the server calculates the appropriate unit price using data analysis libraries such as Pandas and Scikit-learn. The calculated appropriate unit price is saved in the database and updated as necessary.

[0469] Input: Past electricity rate history and market trend data obtained from the database

[0470] Output: Fair unit price stored in the database

[0471] Processing operation: The server analyzes the data using the data analysis library and calculates the appropriate unit price.

[0472] Step 3:

[0473] Emotion Recognition and Notification

[0474] The server notifies the user device of the calculated fair price. When this notification is sent, the emotion engine analyzes the user's input data and recognizes the user's emotions. Emotion recognition uses a generative AI model such as the BERT model.

[0475] Example prompt sentence:

[0476] python

[0477] import transformers

[0478] Loading the model

[0479] model_name = "nlptown / bert-base-multilingual-uncased-sentiment"

[0480] tokenizer = transformers.AutoTokenizer.from_pretrained(model_name)

[0481] model = transformers.AutoModelForSequenceClassification.from_pretrained(model_name)

[0482] text = "I am extremely dissatisfied with this service."

[0483] inputs = tokenizer.encode_plus(

[0484] text,

[0485] add_special_tokens=True,

[0486] return_tensors="pt"

[0487] )

[0488] Model prediction

[0489] outputs = model(inputs)

[0490] prediction = torch.argmax(outputs.logits, dim=1).item()

[0491] Emotion-based response message generation

[0492] if prediction == 0:

[0493] response_message = "We apologize for the inconvenience. We will look into resolving this issue immediately."

[0494] elif prediction == 1:

[0495] response_message = "We appreciate your feedback."

[0496] else:

[0497] response_message = "Thank you for using our service. We look forward to working with you in the future."

[0498] print(response_message)

[0499] Input: User-entered data

[0500] Output: Adaptive notification message based on emotions

[0501] Processing operation: The server analyzes the user's emotions using the emotion engine, adjusts the text of the notification message, and notifies the user.

[0502] Step 4:

[0503] Providing discount negotiation data

[0504] When a user logs in to the system and requests data for price negotiation, the server extracts nearby prices and market trend information from the database and generates a visual report using libraries such as Matplotlib and Seaborn. The generated report is sent to the user's terminal and displayed for the user.

[0505] Input: User requests and data extracted from the database

[0506] Output: Data displayed as a visual report

[0507] Processing operations: The server extracts and analyzes the data, generates a visual report and sends it to the user.

[0508] Step 5:

[0509] Providing standard metrics data to external clients

[0510] The server periodically collects electricity rate data from across the country and runs data analysis algorithms such as Pandas and Scikit-learn to generate standard indicator data, which is then provided to external clients via APIs and dashboards.

[0511] Input: Nationwide electricity rate data

[0512] Output: Standard metrics data provided to external clients

[0513] Processing operations: The server analyzes the collected data and provides the generated standard metrics data to external clients via APIs and dashboards.

[0514] The specific processing unit 290 transmits the result of the specific processing 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0515] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0516] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0517] [Second embodiment]

[0518] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0519] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0520] 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 a "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).

[0521] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, 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 microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0522] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0523] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0524] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0525] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0526] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0527] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0528] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0529] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0530] The present invention is an integrated system for registering requests for electricity rate increases, quickly calculating appropriate unit prices for each region, and providing data that can be used in price negotiations. A specific embodiment of the present invention will be described below.

[0531] System Configuration

[0532] This system mainly consists of the following components:

[0533] 1. User terminal: A device through which base station owners and other users enter information and view relevant data.

[0534] 2. Server: A central computing device that processes, stores, and analyzes data.

[0535] 3. Database: Data storage for saving electricity tariff information, request information, historical data, fair unit prices, etc.

[0536] Program Processing Overview

[0537] The programs in this system have the following functions:

[0538] Registering a request for an increase in electricity rates

[0539] The user uses the user terminal to input the required information (e.g., base station location, current electricity rate, desired rate) into a web form or application. This information is first validated by the terminal and then sent to the server. The server registers the received data in a database, enabling request management.

[0540] Calculation of appropriate unit prices for each region

[0541] The server accesses the database of each local power supplier to obtain past electricity rate history and market fluctuation data. The obtained data is analyzed within the server using an algorithm to calculate the appropriate unit price, and the calculation results are saved in the database and updated as needed.

[0542] User notification of fair unit price

[0543] Once the calculation of the appropriate unit price is complete, the server notifies the terminal of the result, which is displayed to the user. For example, if the appropriate unit price for base station A is calculated to be "4,500 yen / month," this information is displayed on the user's screen.

[0544] Providing data for price negotiations

[0545] A user logs into the system and requests data for negotiating price increases. The device forwards this request to the server, which extracts relevant information from the database (e.g., electricity rates for nearby base stations, historical rate fluctuations, and local market trends) and generates a visual report. This report is sent to the device and displayed to the user.

[0546] Providing standard metrics data to external clients

[0547] The server collects electricity bill data from across the country and periodically analyzes it. It then runs the applied algorithms to generate standard index data. This data is packaged and provided to external clients via APIs and dashboards. External clients can use the provided data to set their own rates and negotiate discounts.

[0548] Specific examples

[0549] For example, suppose a base station owner in one of Tokyo's 23 wards inputs a request through the system saying, "I would like to raise my current electricity rate from 3,000 yen / month to 5,000 yen / month." This information is validated on the terminal, then sent to the server and registered in the database.

[0550] Next, the server retrieves data from electricity suppliers in Tokyo's 23 wards and calculates the appropriate unit price based on past price history and market trends. In this case, the appropriate unit price of 4,500 yen / month is calculated and notified to the user.

[0551] Finally, users can log into the system and view detailed reports including nearby cell tower pricing data and market trends, and use this information to negotiate discounts with their power company.

[0552] In this way, the system efficiently manages requests for electricity rate increases and supports the calculation of appropriate unit prices and the provision of data for price negotiations when installing new stations.

[0553] The processing flow will be explained below.

[0554] Step 1:

[0555] Users input their electricity rate increase request using a dedicated web form or application, specifically by entering information such as the base station location, current electricity rate, and desired rate.

[0556] Step 2:

[0557] The terminal receives the data entered by the user and performs initial validation, which checks for required fields and the data format.

[0558] Step 3:

[0559] The terminal transmits the successfully validated data to the server.

[0560] Step 4:

[0561] The server stores the received electricity rate increase request in a database, including the base station location, current electricity rate, and desired rate.

[0562] Step 5:

[0563] The server accesses the database of local power supply companies to obtain electricity rate history and market trend data for the specified area.

[0564] Step 6:

[0565] The server runs an algorithm based on the acquired data to calculate the appropriate electricity unit price, taking into account past price history, local market fluctuations, and future market forecasts.

[0566] Step 7:

[0567] The server stores the calculated fair unit price in a database and simultaneously notifies the terminal.

[0568] Step 8:

[0569] The terminal displays the appropriate unit price to the user, who then checks the appropriate electricity unit price of the base station.

[0570] Step 9:

[0571] A user logs into the system and makes a request for the data needed to negotiate a price increase.

[0572] Step 10:

[0573] The terminal transmits the user's request to the server.

[0574] Step 11:

[0575] The server extracts relevant information from the database (e.g., electricity rate data for nearby base stations, historical rate fluctuation data, and local market trend data).

[0576] Step 12:

[0577] The server formats the extracted data into visual reports, converting the data into graphs and tables.

[0578] Step 13:

[0579] The server transmits the generated report to the terminal.

[0580] Step 14:

[0581] The terminal displays a visual report to the user, who can then use this report to negotiate discounts with the power company.

[0582] Step 15:

[0583] The server periodically collects and analyzes nationwide electricity price data, which it then runs an algorithm to generate standard index data.

[0584] Step 16:

[0585] The server packages the generated metrics data and prepares APIs and dashboards to provide to external clients.

[0586] Step 17:

[0587] External clients can use the provided APIs and dashboards to obtain standard metrics and use them to set their own prices and negotiate discounts.

[0588] Example 1

[0589] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0590] In the conventional system, registering requests for electricity rate increases and calculating appropriate unit prices were often time-consuming and difficult to execute efficiently. Furthermore, there was a lack of effective means to provide the necessary information for users to negotiate discounts. Furthermore, there was a need for a comprehensive and rapid response in collecting electricity rate data nationwide and providing standard index data.

[0591] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0592] In this invention, the server includes means for registering requests for an electricity rate increase, means for calculating an appropriate electricity unit price for each region, means for notifying users of the appropriate electricity unit price, means for providing data for discount negotiations, means for providing standard index data to external clients, means for validating information on the requested electricity rate increase, means for accessing a rate database for each region, means for executing an algorithm for calculating the appropriate unit price, means for structuring the request information and registering it in the database, and means for extracting related information in response to user requests and generating visual reports. This enables efficient registration of requests for an electricity rate increase, rapid calculation of the appropriate unit price, and provision of useful data to users and external clients.

[0593] "Means for registering requests for an increase in electricity rates" refers to a function that allows a user to input a request for an increase in electricity rates and record it in the system.

[0594] "Means for calculating appropriate electricity unit prices for each region" refers to a function for calculating appropriate electricity unit prices for each region based on power supply companies and market data from different regions.

[0595] "Means for notifying the user of the appropriate electricity unit price" refers to a function for notifying the user of the calculated appropriate electricity unit price on the user's terminal so that the user can check it.

[0596] The "means for providing data for price negotiation" refers to a function for providing a user with data and information required for negotiating a price reduction for electricity charges.

[0597] "Means of providing standard index data to external clients" refers to APIs, dashboards, etc. for providing standard electricity rates and market index data to external client companies.

[0598] "Means for validating electricity rate increase request information" refers to a function for verifying and confirming the accuracy and completeness of the rate increase request information entered by the user.

[0599] "Means for accessing a regional fee database" refers to a function for accessing a database that stores fee data for a specific region and obtaining the required information.

[0600] "Means for executing an algorithm for calculating a fair unit price" refers to a function for executing an analytical algorithm for calculating a fair unit price for electricity based on a variety of data.

[0601] "Means for structuring request information and registering it in a database" refers to a function for organizing request information submitted by users and efficiently storing it in a database.

[0602] "Means for extracting relevant information in response to a user request and generating a visual report" refers to a function for extracting information requested by a user from a database and generating a report in an easy-to-read format.

[0603] The present invention is an integrated system for registering requests for electricity rate increases, quickly calculating appropriate unit prices for each region, and providing data that can be used in price negotiations. The following describes in detail an embodiment of the present invention.

[0604] System Configuration

[0605] This system mainly consists of the following components:

[0606] 1. User terminal: A device through which base station owners and other users enter information and view relevant data.

[0607] 2. Server: A central computing device that processes, stores, and analyzes data.

[0608] 3. Database: Data storage for saving electricity tariff information, request information, historical data, fair unit prices, etc.

[0609] 4. API: An interface for providing data to external clients.

[0610] Registering a request for an increase in electricity rates

[0611] The user uses a user terminal to enter the required information (e.g., base station location, current electricity rate, desired rate) into a web form or application. This information is validated in real time by the terminal. For example, if a required field is missing or an invalid value is entered, an error message is displayed to the user. Data that has been successfully validated is sent to the server using HTTPS. The server registers the received data in a database, enabling request management.

[0612] Calculation of appropriate unit prices for each region

[0613] The server accesses the API of the local power supply company to obtain the necessary data. For example, data may be obtained through the API of Tokyo Electric Power Company. In addition, past electricity rate history and market fluctuation data are retrieved from the database. This data is analyzed by the server's appropriate unit price calculation algorithm, and the appropriate electricity unit price is calculated. The calculation results are stored in the database and updated as needed.

[0614] User notification of fair unit price

[0615] Once the calculation of the appropriate unit price has been completed, the server calls an API to notify the device of the results. Some notifications may use WebSocket technology. The device receives the results and displays a specific message on the user's screen, such as "The appropriate unit price for your base station is 4,500 yen / month."

[0616] Providing data for price negotiations

[0617] A user logs into the system and requests data for price increase negotiations. The request can be made with a simple button press. The device forwards this request to the server via HTTPS. The server extracts relevant information from the database, such as "electricity rates of nearby base stations," "past price fluctuations," and "local market trends." The server generates a visual report from the extracted data using a BI tool (e.g., Tableau). The generated report is sent to the device as a PDF or Excel file, and the device displays it to the user.

[0618] Providing standard metrics data to external clients

[0619] The server periodically collects data from each regional electricity supplier in order to centralize nationwide electricity rate data. The server analyzes the collected data at regular intervals (e.g., once a month) and also analyzes long-term market trends. It generates standard indicators using specific algorithms (e.g., moving average method) and packages them in JSON format or similar. It provides the generated standard indicator data to external clients via APIs or dedicated dashboards. External clients download this data and apply it to their own business.

[0620] Examples and prompts

[0621] For example, if a base station owner in Tokyo's 23 wards submits a request through the system saying, "I want to raise my current electricity rate from 3,000 yen / month to 5,000 yen / month," the request would be:

[0622] The user enters information into a web form and submits it.

[0623] The device performs validation and sends the data to the server.

[0624] The server registers the data and accesses TEPCO's API to retrieve the necessary data.

[0625] The server uses past pricing data to calculate the appropriate unit price and comes up with the result "4,500 yen / month."

[0626] The server communicates this information to the terminal, which displays the results to the user.

[0627] Users can request detailed reports and receive reports that include neighboring cell tower data and market trends.

[0628] To operate this system, the prompts sent to the generative AI model are as follows:

[0629] "A base station owner in Tokyo's 23 wards has entered a request to raise their current electricity rate from 3,000 yen / month to 5,000 yen / month. Please explain the detailed process flow, step by step, for calculating the appropriate electricity rate based on this information and notifying the user."

[0630] This prompt sentence enables the generative AI model to generate a specific processing flow for calculating the appropriate unit price and notifying the user.

[0631] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0632] Step 1:

[0633] Input and registration of electricity rate increase requests

[0634] The user uses the user terminal to input the required information into a web form or application. The input information includes the location of the base station, the current electricity rate, and the desired electricity rate. When the user clicks the "Submit" button, the terminal validates the input data (e.g., checking for missing fields or incorrect data format). Data that passes validation is sent to the server via HTTPS. The server structures the received data and registers it in a database along with a timestamp and user ID. The input to the server is the requested information sent from the user terminal, and the output is the structured data registered in the database.

[0635] Step 2:

[0636] Obtaining data on electricity supply companies by region

[0637] The server accesses the power supply company's API to obtain past electricity rate history and market fluctuation data for the specified region. For example, the server obtains data through Tokyo Electric Power Company's API. At this time, the server temporarily stores the obtained data in memory and then also stores it in a database for further analysis. The input is the region-specified request data, and the output is the obtained power supply data.

[0638] Step 3:

[0639] Calculation of appropriate electricity unit price

[0640] The server runs an algorithm to calculate the appropriate electricity unit price based on the historical electricity rate history for each region and market fluctuation data obtained from the database. This algorithm includes, for example, the past average value and the moving average method. The server calculates the appropriate unit price based on the analysis results and saves the result in the database. The input is the obtained power supply data and past rate history, and the output is the calculated appropriate unit price.

[0641] Step 4:

[0642] Notification of fair unit price

[0643] Once the server has calculated the appropriate unit price, it calls an API to notify the user device of the result. The server composes the content of the notification and sends it to the user device in real time using WebSocket technology. Based on the notification received, the device displays details of the appropriate unit price (e.g., 4,500 yen / month) on the user's screen. The input is the calculated appropriate unit price, and the output is a notification message to the user.

[0644] Step 5:

[0645] Requesting and providing price negotiation data

[0646] A user logs into the system and requests data for price negotiation. This request is sent from the user's terminal to the server. The server extracts relevant information based on the request from the database. This information may include "electricity rates of nearby base stations," "past price fluctuations," and "market trends." The server uses a BI tool (e.g., Tableau) to generate a visual report. This report is saved in PDF or Excel format and sent from the server to the user's terminal. The user can view the report on their terminal and use it in negotiations. The input is the user's request, and the output is the generated visual report.

[0647] Step 6:

[0648] Providing standard indicator data

[0649] The server periodically collects data from each regional power supply company in order to centralize nationwide electricity rate data. The server analyzes the collected data at regular intervals and also analyzes long-term market trends. It generates standard indicators using specific algorithms and packages them in formats such as JSON or CSV. These data packages are provided to external clients via APIs or dedicated dashboards. External clients can download this data and use it to set their own rates and negotiate discounts. The input is the collected electricity rate data, and the output is standard indicator data.

[0650] (Application example 1)

[0651] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0652] Because logistics centers consume large amounts of energy, proper management of electricity rates and negotiation of price increases are extremely important. However, current systems have difficulty quickly collecting and analyzing regional electricity rate data and market fluctuation data, calculating appropriate unit prices, and notifying them in real time. Furthermore, the provision of data for price negotiation is insufficient, resulting in inefficient energy management. The purpose of this invention is to provide an integrated system that solves these problems.

[0653] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0654] In this invention, the server includes: means for registering requests for an electricity rate increase; means for calculating an appropriate electricity unit price for each region; means for notifying users of the appropriate electricity unit price; means for providing data for discount negotiations; means for providing standard index data to external clients; means for calculating an appropriate energy unit price based on energy consumption data and supporting energy management at logistics centers; means for including an algorithm for calculating an average appropriate unit price based on past rate data; and means for notifying users of the appropriate unit price in real time to their terminals. This enables prompt and appropriate management of electricity rates and makes it possible to improve the efficiency of energy management at logistics centers by providing data useful for discount negotiations.

[0655] The "means for registering a request for an increase in electricity rates" is a function that allows the user to input and save the current electricity rate and the desired rate.

[0656] The "means for calculating appropriate electricity unit prices for each region" is a function for calculating fair electricity unit prices for each region based on past rate data and market fluctuation data.

[0657] The "means for notifying the user of the appropriate electricity unit price" is a function that transmits the calculated appropriate electricity unit price to the user terminal in real time.

[0658] The "means for providing data for price negotiation" is a function that provides past price data and market information necessary to support the user in price negotiation.

[0659] "Means for providing standard index data to external clients" refers to an API or dashboard that provides unified electricity rate index data to external users.

[0660] "A means to support energy management at logistics centers by calculating appropriate energy rates based on energy consumption data" is a function that supports energy management by collecting and analyzing energy consumption data at logistics centers and calculating fair energy rates.

[0661] The "algorithm for calculating the average fair price based on past rate data" is a calculation method that uses past electricity rate data to find the average value and derive the fair price.

[0662] "Means for notifying the user of the fair unit price in real time" is a function that immediately transmits the calculated fair unit price to the user's device.

[0663] System Configuration

[0664] The present invention is realized by providing a number of components, including a user terminal, a server, a database, and the like.

[0665] 1. User Device

[0666] The user terminal is a device used by the energy manager at the logistics center to input information and check related data. Smartphones, tablets, PCs, etc. are used as user terminals.

[0667] 2. Server

[0668] The server is a central computing device that processes, stores, and analyzes data. The server receives information sent from user devices, calculates appropriate energy rates, and notifies the results to users.

[0669] 3. Database

[0670] The system includes data storage for storing electricity bill information, energy consumption data, billing history data, fair unit prices, etc.

[0671] Program Processing Overview

[0672] Registering a request for an increase in electricity rates

[0673] The user uses the user terminal to input the required information (for example, current electricity bill, desired rate) into a web form or application. This information is first validated by the terminal and then sent to the server. The server registers the received data in a database, enabling request management.

[0674] Calculation of appropriate unit prices for each region

[0675] The server accesses the database of each local power supplier to obtain past electricity rate history and market fluctuation data. The obtained data is analyzed within the server using an algorithm to calculate the appropriate unit price, and the calculation results are saved in the database and updated as needed.

[0676] User notification of fair unit price

[0677] Once the calculation of the appropriate unit price is complete, the server notifies the user of the result and displays it to the user. For example, if the appropriate unit price for logistics center A is calculated to be "4,500 yen / month," this information is displayed on the user's screen.

[0678] Providing data for price negotiations

[0679] A user logs into the system and requests data for negotiating price increases. The terminal forwards this request to the server, which extracts relevant information from the database (e.g., electricity rates for nearby logistics depots, historical rate fluctuations, and local market trends) and generates a visual report. This report is sent to the terminal and displayed to the user.

[0680] Providing standard metrics data to external clients

[0681] The server collects electricity bill data from across the country and periodically analyzes it. It then runs the applied algorithms to generate standard index data. This data is packaged and provided to external clients via APIs and dashboards. External clients can use the provided data to set their own rates and negotiate discounts.

[0682] Adding specific examples

[0683] For example, suppose a logistics center manager in one of Tokyo's 23 wards inputs a request through the system saying, "I would like to raise the current electricity rate from 3,000 yen / month to 5,000 yen / month." This information is validated on the terminal, then sent to the server and registered in the database.

[0684] Next, the server retrieves data from electricity suppliers in Tokyo's 23 wards and calculates the appropriate unit price based on past price history and market trends. In this case, the appropriate unit price of 4,500 yen / month is calculated and notified to the user.

[0685] Finally, users can log into the system and view detailed reports including pricing data from nearby logistics depots and market trends, which they can use to negotiate discounts with their energy provider.

[0686] Prompt Sentence Examples

[0687] "I have entered a request to raise the electricity bill for my logistics center in Tokyo's 23 wards from 3,500 yen / month to 5,000 yen / month. Please calculate the appropriate unit price based on past billing history and generate an analysis report."

[0688] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0689] Step 1:

[0690] The user uses a user terminal to enter desired information such as the current electricity rate, desired rate, and base station location into a web form or application. This input information is validated (format checked) by the terminal and then sent to the server. If the validation results are correct, the system proceeds to the next step.

[0691] Step 2:

[0692] The server receives the electricity rate request data sent from the terminal and registers the data in the database. Specific input data includes user identification information, base station location, current electricity rate, desired rate, etc. This allows for request management.

[0693] Step 3:

[0694] The server accesses the databases of local power suppliers to retrieve historical electricity rates and market trend data. The server then executes appropriate database queries based on the local information. The retrieved data is then used as input data for calculating the appropriate unit price within the server.

[0695] Step 4:

[0696] The server uses the acquired historical electricity rate data and market fluctuation data to execute an algorithm to calculate the appropriate unit price. For example, it calculates the average electricity rate for each region over the past five years to calculate the appropriate unit price. The calculation results are stored in a database and are notified to the user in the next step.

[0697] Step 5:

[0698] After the calculated fair unit price is saved in the database, the server sends the fair unit price information via the communication dispatch system to notify the result to the user terminal. The user terminal receives this and displays it on the screen. For example, if the fair unit price for base station A is calculated to be "4,500 yen / month," this information will be displayed on the user's screen.

[0699] Step 6:

[0700] A user logs into the system and requests data for negotiating price increases. The request includes relevant data (electricity rates from nearby base stations, historical price fluctuations, local market trends, etc.). The device then sends this request to the server.

[0701] Step 7:

[0702] The server extracts the requested relevant data from the database and generates a visual report, specifically, visualizing the relevant data as graphs and charts, and then generates a report summarizing the data. The generated report is then transmitted to the user's device.

[0703] Step 8:

[0704] Users can view the report on their device and use it to negotiate discounts with their power company. The report displays nearby base station fee data and market trends, and users can use this information as a basis for negotiations.

[0705] Step 9:

[0706] The server periodically collects nationwide electricity price data and uses algorithms to generate standard index data, including data processing to analyze average prices by region and historical price trends. The generated index data is then made available to external clients via APIs and dashboards.

[0707] Step 10:

[0708] External clients can use the standard metrics provided to them to set their own prices and negotiate discounts, while data obtained via APIs can be integrated into their own systems to help inform strategic decision-making.

[0709] In this way, the system of the present invention efficiently carries out a series of processes related to energy management, and realizes appropriate calculation of electricity charges and user support.

[0710] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0711] The present invention combines an emotion engine that recognizes the emotions of users with an integrated system that registers requests for electricity rate increases, calculates appropriate unit prices for each region, and provides data that can be used in price negotiations. A specific embodiment of the present invention will be described below.

[0712] System Configuration

[0713] This system mainly consists of the following components:

[0714] 1. User terminal: A device through which base station owners and other users enter information and view relevant data.

[0715] 2. Server: A central computing device that processes, stores, and analyzes data.

[0716] 3. Database: Data storage for saving electricity tariff information, request information, historical data, fair unit prices, etc.

[0717] 4. Emotion engine: A system that analyzes user input data and recognizes the user's emotions.

[0718] Program Processing Overview

[0719] The programs in this system have the following functions:

[0720] Registering a request for an increase in electricity rates

[0721] The user uses a terminal to input the required information (e.g., base station location, current electricity rate, desired rate) into a web form or application. This information is first validated by the terminal and then sent to the server. The server registers the received data in a database, enabling request management.

[0722] Calculation of appropriate unit prices for each region

[0723] The server accesses the database of each local power supplier to obtain electricity rate history and market trend data for the specified area. The obtained data is analyzed within the server using an algorithm to calculate the appropriate unit price, and the calculation results are saved in the database and updated as necessary.

[0724] User Notifications and Emotion Recognition

[0725] Once the calculation of the appropriate unit price is complete, the server notifies the terminal of the result, which is displayed to the user. Furthermore, at this time, the emotion engine analyzes the user's input data (e.g., text input content and past behavioral history) and recognizes the user's emotional state (e.g., satisfaction, dissatisfaction, excitement, etc.). Based on the recognized emotion, the server adjusts the wording of the notification message and provides adaptive feedback to the user.

[0726] Providing data for price negotiations

[0727] A user logs into the system and requests the data needed to negotiate a price increase. The device forwards this request to the server, which extracts relevant information from the database (e.g., electricity rates for nearby base stations, historical price fluctuations, and local market trends) and generates a visual report. This report is sent to the device and displayed to the user.

[0728] Providing standard metrics data to external clients

[0729] The server collects electricity bill data from across the country and periodically analyzes it. It then runs the applied algorithms to generate standard index data. This data is packaged and provided to external clients via APIs and dashboards. External clients can use the provided data to set their own rates and negotiate discounts.

[0730] Specific examples

[0731] For example, suppose a base station owner in one of Tokyo's 23 wards inputs a request through the system saying, "I would like to raise my current electricity rate from 3,000 yen / month to 5,000 yen / month." This information is validated on the terminal, then sent to the server and registered in the database.

[0732] Next, the server retrieves data from electricity suppliers in Tokyo's 23 wards and calculates the appropriate unit price based on past price history and market trends. In this case, the appropriate unit price of 4,500 yen / month is calculated and notified to the user.

[0733] Furthermore, the emotion engine analyzes the user's input and recognizes emotions such as "I'm dissatisfied with the results." Based on the recognized emotion, the server adjusts the notification message to "We will propose a more optimal plan to bring you closer to your needs," and displays it to the user.

[0734] In this way, this system efficiently manages requests for electricity rate increases, supports the calculation of appropriate unit prices when installing new stations, and provides data for price negotiations. It also recognizes user emotions and responds adaptively to provide a better user experience.

[0735] The processing flow will be explained below.

[0736] Step 1:

[0737] Users input their electricity rate increase request using a dedicated web form or application, specifically by entering information such as the base station location, current electricity rate, and desired rate.

[0738] Step 2:

[0739] The terminal receives the data entered by the user and performs initial validation, which checks for required fields and the data format.

[0740] Step 3:

[0741] The terminal transmits the successfully validated data to the server.

[0742] Step 4:

[0743] The server stores the received electricity rate increase request in a database, including the base station location, current electricity rate, and desired rate.

[0744] Step 5:

[0745] The server accesses the database of local power supply companies to obtain electricity rate history and market trend data for the specified area.

[0746] Step 6:

[0747] The server runs an algorithm based on the acquired data to calculate the appropriate electricity unit price, taking into account past price history, local market fluctuations, and future market forecasts.

[0748] Step 7:

[0749] The server stores the calculated fair unit price in a database and simultaneously notifies the terminal.

[0750] Step 8:

[0751] The terminal displays the appropriate unit price to the user, who then checks the appropriate electricity unit price of the base station.

[0752] Step 9:

[0753] The emotion engine analyzes the user's input data and past behavioral history to recognize the user's emotional state. For example, it extracts emotions such as "satisfied" or "dissatisfied" from text content and click patterns.

[0754] Step 10:

[0755] The terminal transmits the user's emotional state recognized by the emotion engine to the server.

[0756] Step 11:

[0757] The server tailors the notification message based on the emotional state received from the emotion engine, for example by including a message offering further information or support to a frustrated user.

[0758] Step 12:

[0759] The server then sends the adjusted notification message to the terminal and displays it to the user, who receives feedback according to their emotional state.

[0760] Step 13:

[0761] A user logs into the system and requests the data needed to negotiate a price increase.

[0762] Step 14:

[0763] The terminal transmits the user's request to the server.

[0764] Step 15:

[0765] The server extracts relevant information from the database (e.g., electricity rate data for nearby base stations, historical rate fluctuation data, and local market trend data).

[0766] Step 16:

[0767] The server formats the extracted data into visual reports, converting the data into graphs and tables.

[0768] Step 17:

[0769] The server sends the generated report to the terminal, where it is displayed to the user.

[0770] Step 18:

[0771] The terminal displays a visual report to the user, who can then use this report to negotiate discounts with the power company.

[0772] Step 19:

[0773] The server periodically collects and analyzes nationwide electricity price data, which it then runs an algorithm to generate standard index data.

[0774] Step 20:

[0775] The server packages the generated metrics data and prepares APIs and dashboards to provide to external clients.

[0776] Step 21:

[0777] External clients can use the provided APIs and dashboards to obtain standard metrics and use them to set their own prices and negotiate discounts.

[0778] Example 2

[0779] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0780] The current system has difficulty effectively registering and managing requests for electricity rate increases and quickly and accurately calculating appropriate electricity unit prices for each region. It also lacks the ability to recognize user emotions and appropriately adjust notification messages accordingly, making it difficult to improve the user experience. Furthermore, there are issues with the efficiency of providing data required for price negotiations and rate setting to external clients. A system that solves these problems is needed.

[0781] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0782] In this invention, the server includes means for registering requests for electricity rate increases, means for calculating appropriate electricity unit prices for each region, means for notifying the user and recognizing their emotional state, means for adjusting the notification message based on the emotional state, means for providing data for price negotiations, and means for providing standard index data to external clients. This makes it possible to effectively manage requests for electricity rate increases and adaptively calculate and notify appropriate unit prices, thereby improving the user experience and providing efficient data.

[0783] An "electricity bill" is the fee that ordinary households and businesses pay to electric power companies for energy consumption.

[0784] A "price increase request" refers to a user expressing to the system a request to increase the current electricity rate.

[0785] A "fair electricity unit price" is a unit price of electricity that is considered reasonable in a particular area, calculated based on market trends and past price history.

[0786] "User" refers to an individual or corporation that uses the system to manage electricity charges or request rate increases.

[0787] An "emotion engine" is a system component that analyzes a user's input and behavioral history and recognizes their emotional state (e.g., satisfaction, dissatisfaction, excitement, etc.).

[0788] A "notification message" is an information message sent from the system to the user, and includes information such as the appropriate unit price and system update information.

[0789] "Discount negotiation data" refers to relevant information required when a user negotiates a discount with an electric power company.

[0790] "Standard index data" is reference data that indicates pricing and market trends, generated by analyzing electricity rate data nationwide.

[0791] "External Client" means a third-party individual or entity that uses standard indicator data provided by the System.

[0792] A "database" refers to data storage that regularly stores and manages information within a system.

[0793] "Validation" is the process of checking the accuracy and validity of entered data.

[0794] An "algorithm" is a set of computational steps that a system executes to solve a particular problem.

[0795] "API" refers to an interface that allows a system to exchange data with external clients.

[0796] A "dashboard" is a user interface that visually displays system usage status and important indicators.

[0797] A "visual report" is a report that organizes data in a visually easy-to-understand manner in the form of graphs, charts, etc.

[0798] The present invention is an integrated system that registers requests for electricity rate increases, calculates appropriate unit prices for each region, and provides data that can be used in price negotiations, and is combined with an emotion engine that recognizes user emotions. Detailed embodiments of the present invention are described below.

[0799] System Configuration

[0800] The system consists of the following main components:

[0801] 1. User terminal: A device on which a user inputs information and checks related data. Examples include smartphones, tablets, and PCs.

[0802] 2. Server: A central computing device that processes, stores, and analyzes data. In this invention, a high-performance cloud server is recommended.

[0803] 3. Database: This is data storage for saving electricity rate information, request information, historical data, fair unit prices, etc. For example, a database management system such as MySQL or PostgreSQL is used.

[0804] 4. Emotion engine: A system that analyzes user input data and recognizes the user's emotions. Specifically, it uses emotion analysis software that uses natural language processing (NLP) technology.

[0805] Program Processing Overview

[0806] The system has the following main processing functions:

[0807] Registering a request for an increase in electricity rates

[0808] The user uses a terminal to input the required information (e.g., base station location, current electricity rate, desired rate) into a web form or application. This information is first validated by the terminal and then sent to the server. The server registers the received data in a database, enabling request management.

[0809] Calculation of appropriate unit prices for each region

[0810] The server accesses the database of each local power supplier to obtain electricity rate history and market trend data for the specified area. The obtained data is analyzed within the server using an algorithm to calculate the appropriate unit price, and the calculation results are saved in the database and updated as necessary.

[0811] User Notifications and Emotion Recognition

[0812] Once the calculation of the appropriate unit price is complete, the server notifies the terminal of the result, which is displayed to the user. Furthermore, at this time, the emotion engine analyzes the user's input data (e.g., text input content and past behavioral history) and recognizes the user's emotional state (e.g., satisfaction, dissatisfaction, excitement, etc.). Based on the recognized emotion, the server adjusts the wording of the notification message and provides adaptive feedback to the user.

[0813] Providing data for price negotiations

[0814] A user logs into the system and requests the data needed to negotiate a price increase. The device forwards this request to the server, which extracts relevant information from the database (e.g., electricity rates for nearby base stations, historical price fluctuations, and local market trends) and generates a visual report. This report is sent to the device and displayed to the user.

[0815] Providing standard metrics data to external clients

[0816] The server collects electricity bill data from across the country and periodically analyzes it. It then runs the applied algorithms to generate standard index data. This data is packaged and provided to external clients via APIs and dashboards. External clients can use the provided data to set their own rates and negotiate discounts.

[0817] Specific examples

[0818] For example, suppose a base station owner in one of Tokyo's 23 wards inputs a request through the system saying, "I would like to raise my current electricity rate from 3,000 yen / month to 5,000 yen / month." This information is validated on the terminal, then sent to the server and registered in the database.

[0819] Next, the server retrieves data from electricity suppliers in Tokyo's 23 wards and calculates the appropriate unit price based on past price history and market trends. In this case, the appropriate unit price of 4,500 yen / month is calculated and notified to the user.

[0820] Furthermore, the emotion engine analyzes the user's input and recognizes emotions such as "I'm dissatisfied with the results." Based on the recognized emotion, the server adjusts the notification message to "We will propose a more optimal plan to bring you closer to your needs," and displays it to the user.

[0821] Prompt Sentence Examples

[0822] An example of a prompt to input to a generative AI model is as follows:

[0823] "As a base station owner within Tokyo's 23 wards, I would like to raise my current electricity bill from 3,000 yen / month to 5,000 yen / month. Please calculate the appropriate electricity unit price and provide data for price negotiation based on the results. Also, please create a system that recognizes user emotions and provides adaptive feedback."

[0824] Using this prompt, the generative AI model can understand the specific instructions and generate an appropriate response.

[0825] The system of the present invention effectively manages requests for electricity rate increases, supports calculation of appropriate unit prices for new base stations, and provides data for price negotiations. Furthermore, it can provide a better user experience by recognizing user emotions and responding adaptively.

[0826] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0827] Step 1:

[0828] The user enters a request

[0829] The user uses the terminal to input the required information (e.g., base station location, current electricity price, desired price) into the web form or application. The input data is entered in the following format:

[0830] Input: Base station location (e.g., "Shinagawa-ku, Tokyo"), current electricity rate (e.g., "3,000 yen / month"), desired rate (e.g., "5,000 yen / month")

[0831] When the terminal receives this, it formats the data internally and proceeds to the next step.

[0832] Step 2:

[0833] The terminal validates the data

[0834] The terminal validates the input data, specifically performing the following data manipulations and calculations:

[0835] Check whether the base station location is in a real area (e.g., verify whether "Shinagawa Ward, Tokyo" is a valid area).

[0836] Check that your current electricity rate and desired rate are numerical values.

[0837] Input: Information entered by the user

[0838] Output: Valid data (e.g., "Shinagawa-ku, Tokyo", "3000 yen / month", "5000 yen / month")

[0839] If the validation is successful, the terminal transmits the data to the server.

[0840] Step 3:

[0841] The server receives the data and registers it in the database

[0842] The server receives the data sent from the device. The received data is stored in the following format:

[0843] Input: Valid data from the device (e.g., "Shinagawa-ku, Tokyo", "3000 yen / month", "5000 yen / month")

[0844] The server registers this in a database, enabling request management.

[0845] Output: Add a new record to the database (e.g., add the current electricity rate and desired rate to the "Shinagawa Ward, Tokyo" field)

[0846] Step 4:

[0847] The server obtains data to calculate the appropriate unit price for each region.

[0848] The server accesses the power supplier's database to obtain electricity rate history and market trend data for the specified area.

[0849] Input: Area information (e.g. "Shinagawa-ku, Tokyo")

[0850] Output: Electricity rate history by region, market trend data (e.g., "Price history for the past year", "Market trend data")

[0851] The acquired data is used in the next step.

[0852] Step 5:

[0853] The server calculates the appropriate unit price

[0854] The server uses the acquired data to apply an algorithm to calculate the appropriate unit price for each region. Specifically, the following data calculations are performed:

[0855] Calculate the average price from past price history

[0856] Applying predictive models based on market trend data

[0857] Input: Electricity rate history by region, market trend data

[0858] Output: Fair price (e.g. "4500 yen / month")

[0859] The calculation results are stored in a database.

[0860] Step 6:

[0861] The server notifies the device of the results, and the emotion engine recognizes the user's emotions.

[0862] The server notifies the terminal of the calculated fair price and displays it to the user. Based on the displayed result, the emotion engine analyzes the user's input data (e.g., text input content and past behavior history) and recognizes the user's emotional state.

[0863] Input: Fair unit price result (e.g. "4500 yen / month"), user input data

[0864] Output: User's emotional state (e.g. "unhappy")

[0865] The result of the fair unit price being fair will evoke feelings of satisfaction, dissatisfaction, excitement, etc. in the user.

[0866] Step 7:

[0867] The server adjusts notification messages based on emotional state.

[0868] The server adjusts the notification message based on the recognized emotion and provides adaptive feedback to the user. Specifically, it works as follows:

[0869] Select an appropriate feedback message from templates stored on the server for the recognized emotion (e.g., "unhappy").

[0870] Input: User's emotional state

[0871] Output: Optimized notification message (e.g. "We will propose a more optimal plan to meet your needs")

[0872] This provides feedback according to the user's emotions.

[0873] Step 8:

[0874] The user requests data for price negotiation, and the server generates and serves the report.

[0875] Users log into the system and request the data they need to negotiate a price increase. The device forwards this request to the server, which extracts the relevant information from the database and generates a visual report.

[0876] Input: User request (e.g. "Request for price negotiation data")

[0877] Output: Visual report (e.g. "PDF report")

[0878] The report is sent to the terminal and displayed to the user.

[0879] Step 9:

[0880] The server collects and analyzes electricity rate data nationwide to provide standard index data.

[0881] The server periodically collects electricity bill data from across the country and applies algorithms to generate standard index data, which is then provided to external clients via APIs and dashboards.

[0882] Input: Nationwide electricity rate data

[0883] Output: Standard indicator data (e.g., "national average, standard deviation")

[0884] External clients can use this information to set their own prices and negotiate discounts.

[0885] Through these steps, the system can improve the user experience while efficiently managing requests for electricity rate increases and providing data for calculating fair unit prices and negotiating discounts.

[0886] (Application example 2)

[0887] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0888] Conventional electricity rate management systems lack the ability to respond to user needs with detailed consideration, making it difficult to improve user satisfaction. Furthermore, it is difficult to provide the appropriate data required for price negotiations, resulting in a low success rate for negotiations. The present invention aims to solve these problems and support improved user satisfaction and efficient price negotiations.

[0889] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0890] In this invention, the server includes a means for registering requests for an increase in electricity rates, a means for calculating appropriate electricity unit prices for each region, a means for notifying the user of the appropriate electricity unit price, a means for recognizing the user's emotions and adjusting the notification message, and a means for generating a visual report including nearby prices and trend information during price negotiations. This enables a detailed response that takes the user's emotions into consideration, improves the success rate of negotiations, and increases user satisfaction.

[0891] The "means for registering a request for an increase in electricity rates" is a function that allows a user to input a request for an increase in electricity rates into the system and register that information in the database.

[0892] The "means for calculating appropriate electricity unit prices for each region" is a function that calculates appropriate electricity unit prices based on past price history and market trend data in a specific region.

[0893] The "means for notifying the user of the appropriate electricity unit price" is a function for notifying the user of the calculated appropriate electricity unit price.

[0894] The "means for providing data for price negotiation" is a function for providing relevant data necessary when a user negotiates a price.

[0895] The "means for recognizing the user's emotions and adjusting the notification message" is a function that uses an emotion engine to analyze the user's emotions and adaptively adjusts the notification message in accordance with those emotions.

[0896] "Means for generating visual reports including nearby price and trend information during price negotiations" refers to a function for generating reports that visually display nearby prices and market trend information to assist in negotiations.

[0897] "Means for providing standard index data to external clients" refers to a function for collecting and analyzing nationwide electricity rate data, generating standard indexes, and providing them to external clients.

[0898] The "means for managing requests for an increase in electricity rates and storing the same in a database" is a function for efficiently managing requests for an increase in electricity rates from users and storing the data in a database.

[0899] "Means for automatically calculating appropriate unit prices based on past rate history and market fluctuation data" is a function that automatically calculates appropriate electricity unit prices based on past electricity rate history and market fluctuation data.

[0900] "Means for recognizing emotions by analyzing user input data and past behavioral history" is a function for analyzing and recognizing emotions based on user input data and past behavioral history.

[0901] "Means for extracting relevant data in response to a user request and providing it as a visual report" refers to a function that extracts necessary data in response to a user request and provides that data as a visually displayed report.

[0902] "Means for collecting and analyzing electricity rate data nationwide" is a function for analyzing electricity rate data collected from across the country.

[0903] The "means for executing an algorithm for generating a standard index" is a function for executing a specific algorithm for generating a standard index.

[0904] The "means for generating an adaptive notification message based on the user's emotion" is a function for generating an adaptive notification message based on the user's emotion analyzed by the emotion engine.

[0905] "Means for providing an API or dashboard for providing index data to external clients" refers to a function for setting up an API or dashboard for providing index data to external clients.

[0906] This is an integrated system that manages requests for electricity rate increases, calculates appropriate electricity unit prices for each region, notifies users of these prices, and provides adaptive notification messages through emotion recognition. It also generates visual reports including nearby prices and trend information during price negotiations, and provides standard index data to external clients.

[0907] System configuration

[0908] This system consists of the following components:

[0909] 1. User terminal: A device on which a user inputs their request for an increase in electricity rates and checks related data. This is often a smartphone or tablet.

[0910] 2. Server: The central computing device that processes, stores, and analyzes data, and performs fair pricing and emotion recognition.

[0911] 3. Database: Data storage for saving electricity rate information, user request information, historical data, appropriate unit prices for each region, etc.

[0912] 4. Emotion Engine: A system that analyzes user input data and recognizes user emotions. It uses the BERT model and other emotion recognition algorithms.

[0913] Program Processing Overview

[0914] 1. Request registration

[0915] A user uses a user terminal to input required information into a web form or application, including location, current electricity rate, and desired rate.

[0916] The entered information is validated in real time and then sent to the server, which registers the received data in a database and manages requests.

[0917] 2. Calculating the appropriate unit price

[0918] The server retrieves past electricity rate history and market trend data from the database and calculates the appropriate unit price. The system calculates the appropriate unit price using data analysis libraries such as Pandas and Scikit-learn.

[0919] The calculated fair unit price is stored in a database and updated as necessary.

[0920] 3. Emotion Recognition and Notification

[0921] The server notifies the user of the calculated fair price. When notifying the user, the emotion engine analyzes the user's input data and recognizes the user's emotion.

[0922] Generative AI models such as the BERT model are used for emotion recognition. An example prompt is as follows:

[0923] python

[0924] import transformers

[0925] Loading the model

[0926] model_name = "nlptown / bert-base-multilingual-uncased-sentiment"

[0927] tokenizer = transformers.AutoTokenizer.from_pretrained(model_name)

[0928] model = transformers.AutoModelForSequenceClassification.from_pretrained(model_name)

[0929] text = "I am extremely dissatisfied with this service."

[0930] inputs = tokenizer.encode_plus(

[0931] text,

[0932] add_special_tokens=True,

[0933] return_tensors="pt"

[0934] )

[0935] Model prediction

[0936] outputs = model(inputs)

[0937] prediction = torch.argmax(outputs.logits, dim=1).item()

[0938] Emotion-based response message generation

[0939] if prediction == 0:

[0940] response_message = "We apologize for the inconvenience. We will look into resolving this issue immediately."

[0941] elif prediction == 1:

[0942] response_message = "We appreciate your feedback."

[0943] else:

[0944] response_message = "Thank you for using our service. We look forward to working with you in the future."

[0945] print(response_message)

[0946] Based on the recognized emotion, the server adjusts the wording of the notification message and provides adaptive feedback to the user.

[0947] 4. Providing discount negotiation data

[0948] When a user logs into the system and requests the data needed to negotiate a price, the server extracts the relevant information from the database and uses libraries (Matplotlib and Seaborn) to generate visual reports.

[0949] The generated report is sent to the user terminal and displayed to the user.

[0950] 5. Providing standard indicator data to external clients

[0951] The server periodically collects electricity bill data from across the country and runs data analysis algorithms such as Pandas and Scikit-learn.

[0952] The generated standard metrics data is provided to external clients via APIs and dashboards.

[0953] In this way, the system efficiently manages requests for electricity rate increases, improves the user experience by providing notification messages that reflect the user's feelings, and increases the user's success rate in negotiating discounts by providing necessary data for price negotiations.

[0954] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0955] Step 1:

[0956] Register your request

[0957] The user uses a terminal to open a web form or application and input a request for an increase in electricity rates. The information entered includes location, current electricity rate, and desired rate. This input data is validated in real time and, if there are no problems, is sent to the server. The server registers the received data in a database and manages the request.

[0958] Input: User's request for rate increase (location, current electricity rate, desired rate)

[0959] Output: Request information registered in the database

[0960] Processing operation: The server validates the input data and saves it in the database.

[0961] Step 2:

[0962] Calculating the appropriate unit price

[0963] The server retrieves historical electricity rates and market trend data from the database. Based on the retrieved data, the server calculates the appropriate unit price using data analysis libraries such as Pandas and Scikit-learn. The calculated appropriate unit price is saved in the database and updated as necessary.

[0964] Input: Past electricity rate history and market trend data obtained from the database

[0965] Output: Fair unit price stored in the database

[0966] Processing operation: The server analyzes the data using the data analysis library and calculates the appropriate unit price.

[0967] Step 3:

[0968] Emotion Recognition and Notification

[0969] The server notifies the user device of the calculated fair price. When this notification is sent, the emotion engine analyzes the user's input data and recognizes the user's emotions. Emotion recognition uses a generative AI model such as the BERT model.

[0970] Example prompt sentence:

[0971] python

[0972] import transformers

[0973] Loading the model

[0974] model_name = "nlptown / bert-base-multilingual-uncased-sentiment"

[0975] tokenizer = transformers.AutoTokenizer.from_pretrained(model_name)

[0976] model = transformers.AutoModelForSequenceClassification.from_pretrained(model_name)

[0977] text = "I am extremely dissatisfied with this service."

[0978] inputs = tokenizer.encode_plus(

[0979] text,

[0980] add_special_tokens=True,

[0981] return_tensors="pt"

[0982] )

[0983] Model prediction

[0984] outputs = model(inputs)

[0985] prediction = torch.argmax(outputs.logits, dim=1).item()

[0986] Emotion-based response message generation

[0987] if prediction == 0:

[0988] response_message = "We apologize for the inconvenience. We will look into resolving this issue immediately."

[0989] elif prediction == 1:

[0990] response_message = "We appreciate your feedback."

[0991] else:

[0992] response_message = "Thank you for using our service. We look forward to working with you in the future."

[0993] print(response_message)

[0994] Input: User-entered data

[0995] Output: Adaptive notification message based on emotions

[0996] Processing operation: The server analyzes the user's emotions using the emotion engine, adjusts the text of the notification message, and notifies the user.

[0997] Step 4:

[0998] Providing discount negotiation data

[0999] When a user logs in to the system and requests data for price negotiation, the server extracts nearby prices and market trend information from the database and generates a visual report using libraries such as Matplotlib and Seaborn. The generated report is sent to the user's terminal and displayed for the user.

[1000] Input: User requests and data extracted from the database

[1001] Output: Data displayed as a visual report

[1002] Processing operations: The server extracts and analyzes the data, generates a visual report and sends it to the user.

[1003] Step 5:

[1004] Providing standard metrics data to external clients

[1005] The server periodically collects electricity rate data from across the country and runs data analysis algorithms such as Pandas and Scikit-learn to generate standard indicator data, which is then provided to external clients via APIs and dashboards.

[1006] Input: Nationwide electricity rate data

[1007] Output: Standard metrics data provided to external clients

[1008] Processing operations: The server analyzes the collected data and provides the generated standard metrics data to external clients via APIs and dashboards.

[1009] The specific processing unit 290 transmits the result of the specific processing 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[1010] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1011] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1012] [Third embodiment]

[1013] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1014] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1015] 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 a "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).

[1016] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. 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 microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1017] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1018] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1019] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1020] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1021] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1022] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1023] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1024] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1025] The present invention is an integrated system for registering requests for electricity rate increases, quickly calculating appropriate unit prices for each region, and providing data that can be used in price negotiations. A specific embodiment of the present invention will be described below.

[1026] System Configuration

[1027] This system mainly consists of the following components:

[1028] 1. User terminal: A device through which base station owners and other users enter information and view relevant data.

[1029] 2. Server: A central computing device that processes, stores, and analyzes data.

[1030] 3. Database: Data storage for saving electricity tariff information, request information, historical data, fair unit prices, etc.

[1031] Program Processing Overview

[1032] The programs in this system have the following functions:

[1033] Registering a request for an increase in electricity rates

[1034] The user uses the user terminal to input the required information (e.g., base station location, current electricity rate, desired rate) into a web form or application. This information is first validated by the terminal and then sent to the server. The server registers the received data in a database, enabling request management.

[1035] Calculation of appropriate unit prices for each region

[1036] The server accesses the database of each local power supplier to obtain past electricity rate history and market fluctuation data. The obtained data is analyzed within the server using an algorithm to calculate the appropriate unit price, and the calculation results are saved in the database and updated as needed.

[1037] User notification of fair unit price

[1038] Once the calculation of the appropriate unit price is complete, the server notifies the terminal of the result, which is displayed to the user. For example, if the appropriate unit price for base station A is calculated to be "4,500 yen / month," this information is displayed on the user's screen.

[1039] Providing data for price negotiations

[1040] A user logs into the system and requests data for negotiating price increases. The device forwards this request to the server, which extracts relevant information from the database (e.g., electricity rates for nearby base stations, historical rate fluctuations, and local market trends) and generates a visual report. This report is sent to the device and displayed to the user.

[1041] Providing standard metrics data to external clients

[1042] The server collects electricity bill data from across the country and periodically analyzes it. It then runs the applied algorithms to generate standard index data. This data is packaged and provided to external clients via APIs and dashboards. External clients can use the provided data to set their own rates and negotiate discounts.

[1043] Specific examples

[1044] For example, suppose a base station owner in one of Tokyo's 23 wards inputs a request through the system saying, "I would like to raise my current electricity rate from 3,000 yen / month to 5,000 yen / month." This information is validated on the terminal, then sent to the server and registered in the database.

[1045] Next, the server retrieves data from electricity suppliers in Tokyo's 23 wards and calculates the appropriate unit price based on past price history and market trends. In this case, the appropriate unit price of 4,500 yen / month is calculated and notified to the user.

[1046] Finally, users can log into the system and view detailed reports including nearby cell tower pricing data and market trends, and use this information to negotiate discounts with their power company.

[1047] In this way, the system efficiently manages requests for electricity rate increases and supports the calculation of appropriate unit prices and the provision of data for price negotiations when installing new stations.

[1048] The processing flow will be explained below.

[1049] Step 1:

[1050] Users input their electricity rate increase request using a dedicated web form or application, specifically by entering information such as the base station location, current electricity rate, and desired rate.

[1051] Step 2:

[1052] The terminal receives the data entered by the user and performs initial validation, which checks for required fields and the data format.

[1053] Step 3:

[1054] The terminal transmits the successfully validated data to the server.

[1055] Step 4:

[1056] The server stores the received electricity rate increase request in a database, including the base station location, current electricity rate, and desired rate.

[1057] Step 5:

[1058] The server accesses the database of local power supply companies to obtain electricity rate history and market trend data for the specified area.

[1059] Step 6:

[1060] The server runs an algorithm based on the acquired data to calculate the appropriate electricity unit price, taking into account past price history, local market fluctuations, and future market forecasts.

[1061] Step 7:

[1062] The server stores the calculated fair unit price in a database and simultaneously notifies the terminal.

[1063] Step 8:

[1064] The terminal displays the appropriate unit price to the user, who then checks the appropriate electricity unit price of the base station.

[1065] Step 9:

[1066] A user logs into the system and makes a request for the data needed to negotiate a price increase.

[1067] Step 10:

[1068] The terminal transmits the user's request to the server.

[1069] Step 11:

[1070] The server extracts relevant information from the database (e.g., electricity rate data for nearby base stations, historical rate fluctuation data, and local market trend data).

[1071] Step 12:

[1072] The server formats the extracted data into visual reports, converting the data into graphs and tables.

[1073] Step 13:

[1074] The server transmits the generated report to the terminal.

[1075] Step 14:

[1076] The terminal displays a visual report to the user, who can then use this report to negotiate discounts with the power company.

[1077] Step 15:

[1078] The server periodically collects and analyzes nationwide electricity price data, which it then runs an algorithm to generate standard index data.

[1079] Step 16:

[1080] The server packages the generated metrics data and prepares APIs and dashboards to provide to external clients.

[1081] Step 17:

[1082] External clients can use the provided APIs and dashboards to obtain standard metrics and use them to set their own prices and negotiate discounts.

[1083] Example 1

[1084] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1085] In the conventional system, registering requests for electricity rate increases and calculating appropriate unit prices were often time-consuming and difficult to execute efficiently. Furthermore, there was a lack of effective means to provide the necessary information for users to negotiate discounts. Furthermore, there was a need for a comprehensive and rapid response in collecting electricity rate data nationwide and providing standard index data.

[1086] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1087] In this invention, the server includes means for registering requests for an electricity rate increase, means for calculating an appropriate electricity unit price for each region, means for notifying users of the appropriate electricity unit price, means for providing data for discount negotiations, means for providing standard index data to external clients, means for validating information on the requested electricity rate increase, means for accessing a rate database for each region, means for executing an algorithm for calculating the appropriate unit price, means for structuring the request information and registering it in the database, and means for extracting related information in response to user requests and generating visual reports. This enables efficient registration of requests for an electricity rate increase, rapid calculation of the appropriate unit price, and provision of useful data to users and external clients.

[1088] "Means for registering requests for an increase in electricity rates" refers to a function that allows a user to input a request for an increase in electricity rates and record it in the system.

[1089] "Means for calculating appropriate electricity unit prices for each region" refers to a function for calculating appropriate electricity unit prices for each region based on power supply companies and market data from different regions.

[1090] "Means for notifying the user of the appropriate electricity unit price" refers to a function for notifying the user of the calculated appropriate electricity unit price on the user's terminal so that the user can check it.

[1091] The "means for providing data for price negotiation" refers to a function for providing a user with data and information required for negotiating a price reduction for electricity charges.

[1092] "Means of providing standard index data to external clients" refers to APIs, dashboards, etc. for providing standard electricity rates and market index data to external client companies.

[1093] "Means for validating electricity rate increase request information" refers to a function for verifying and confirming the accuracy and completeness of the rate increase request information entered by the user.

[1094] "Means for accessing a regional fee database" refers to a function for accessing a database that stores fee data for a specific region and obtaining the required information.

[1095] "Means for executing an algorithm for calculating a fair unit price" refers to a function for executing an analytical algorithm for calculating a fair unit price for electricity based on a variety of data.

[1096] "Means for structuring request information and registering it in a database" refers to a function for organizing request information submitted by users and efficiently storing it in a database.

[1097] "Means for extracting relevant information in response to a user request and generating a visual report" refers to a function for extracting information requested by a user from a database and generating a report in an easy-to-read format.

[1098] The present invention is an integrated system for registering requests for electricity rate increases, quickly calculating appropriate unit prices for each region, and providing data that can be used in price negotiations. The following describes in detail an embodiment of the present invention.

[1099] System Configuration

[1100] This system mainly consists of the following components:

[1101] 1. User terminal: A device through which base station owners and other users enter information and view relevant data.

[1102] 2. Server: A central computing device that processes, stores, and analyzes data.

[1103] 3. Database: Data storage for saving electricity tariff information, request information, historical data, fair unit prices, etc.

[1104] 4. API: An interface for providing data to external clients.

[1105] Registering a request for an increase in electricity rates

[1106] The user uses a user terminal to enter the required information (e.g., base station location, current electricity rate, desired rate) into a web form or application. This information is validated in real time by the terminal. For example, if a required field is missing or an invalid value is entered, an error message is displayed to the user. Data that has been successfully validated is sent to the server using HTTPS. The server registers the received data in a database, enabling request management.

[1107] Calculation of appropriate unit prices for each region

[1108] The server accesses the API of the local power supply company to obtain the necessary data. For example, data may be obtained through the API of Tokyo Electric Power Company. In addition, past electricity rate history and market fluctuation data are retrieved from the database. This data is analyzed by the server's appropriate unit price calculation algorithm, and the appropriate electricity unit price is calculated. The calculation results are stored in the database and updated as needed.

[1109] User notification of fair unit price

[1110] Once the calculation of the appropriate unit price has been completed, the server calls an API to notify the device of the results. Some notifications may use WebSocket technology. The device receives the results and displays a specific message on the user's screen, such as "The appropriate unit price for your base station is 4,500 yen / month."

[1111] Providing data for price negotiations

[1112] A user logs into the system and requests data for price increase negotiations. The request can be made with a simple button press. The device forwards this request to the server via HTTPS. The server extracts relevant information from the database, such as "electricity rates of nearby base stations," "past price fluctuations," and "local market trends." The server generates a visual report from the extracted data using a BI tool (e.g., Tableau). The generated report is sent to the device as a PDF or Excel file, and the device displays it to the user.

[1113] Providing standard metrics data to external clients

[1114] The server periodically collects data from each regional electricity supplier in order to centralize nationwide electricity rate data. The server analyzes the collected data at regular intervals (e.g., once a month) and also analyzes long-term market trends. It generates standard indicators using specific algorithms (e.g., moving average method) and packages them in JSON format or similar. It provides the generated standard indicator data to external clients via APIs or dedicated dashboards. External clients download this data and apply it to their own business.

[1115] Examples and prompts

[1116] For example, if a base station owner in Tokyo's 23 wards submits a request through the system saying, "I want to raise my current electricity rate from 3,000 yen / month to 5,000 yen / month," the request would be:

[1117] The user enters information into a web form and submits it.

[1118] The device performs validation and sends the data to the server.

[1119] The server registers the data and accesses TEPCO's API to retrieve the necessary data.

[1120] The server uses past pricing data to calculate the appropriate unit price and comes up with the result "4,500 yen / month."

[1121] The server communicates this information to the terminal, which displays the results to the user.

[1122] Users can request detailed reports and receive reports that include neighboring cell tower data and market trends.

[1123] To operate this system, the prompts sent to the generative AI model are as follows:

[1124] "A base station owner in Tokyo's 23 wards has entered a request to raise their current electricity rate from 3,000 yen / month to 5,000 yen / month. Please explain the detailed process flow, step by step, for calculating the appropriate electricity rate based on this information and notifying the user."

[1125] This prompt sentence enables the generative AI model to generate a specific processing flow for calculating the appropriate unit price and notifying the user.

[1126] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1127] Step 1:

[1128] Input and registration of electricity rate increase requests

[1129] The user uses the user terminal to input the required information into a web form or application. The input information includes the location of the base station, the current electricity rate, and the desired electricity rate. When the user clicks the "Submit" button, the terminal validates the input data (e.g., checking for missing fields or incorrect data format). Data that passes validation is sent to the server via HTTPS. The server structures the received data and registers it in a database along with a timestamp and user ID. The input to the server is the requested information sent from the user terminal, and the output is the structured data registered in the database.

[1130] Step 2:

[1131] Obtaining data on electricity supply companies by region

[1132] The server accesses the power supply company's API to obtain past electricity rate history and market fluctuation data for the specified region. For example, the server obtains data through Tokyo Electric Power Company's API. At this time, the server temporarily stores the obtained data in memory and then also stores it in a database for further analysis. The input is the region-specified request data, and the output is the obtained power supply data.

[1133] Step 3:

[1134] Calculation of appropriate electricity unit price

[1135] The server runs an algorithm to calculate the appropriate electricity unit price based on the historical electricity rate history for each region and market fluctuation data obtained from the database. This algorithm includes, for example, the past average value and the moving average method. The server calculates the appropriate unit price based on the analysis results and saves the result in the database. The input is the obtained power supply data and past rate history, and the output is the calculated appropriate unit price.

[1136] Step 4:

[1137] Notification of fair unit price

[1138] Once the server has calculated the appropriate unit price, it calls an API to notify the user device of the result. The server composes the content of the notification and sends it to the user device in real time using WebSocket technology. Based on the notification received, the device displays details of the appropriate unit price (e.g., 4,500 yen / month) on the user's screen. The input is the calculated appropriate unit price, and the output is a notification message to the user.

[1139] Step 5:

[1140] Requesting and providing price negotiation data

[1141] A user logs into the system and requests data for price negotiation. This request is sent from the user's terminal to the server. The server extracts relevant information based on the request from the database. This information may include "electricity rates of nearby base stations," "past price fluctuations," and "market trends." The server uses a BI tool (e.g., Tableau) to generate a visual report. This report is saved in PDF or Excel format and sent from the server to the user's terminal. The user can view the report on their terminal and use it in negotiations. The input is the user's request, and the output is the generated visual report.

[1142] Step 6:

[1143] Providing standard indicator data

[1144] The server periodically collects data from each regional power supply company in order to centralize nationwide electricity rate data. The server analyzes the collected data at regular intervals and also analyzes long-term market trends. It generates standard indicators using specific algorithms and packages them in formats such as JSON or CSV. These data packages are provided to external clients via APIs or dedicated dashboards. External clients can download this data and use it to set their own rates and negotiate discounts. The input is the collected electricity rate data, and the output is standard indicator data.

[1145] (Application example 1)

[1146] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1147] Because logistics centers consume large amounts of energy, proper management of electricity rates and negotiation of price increases are extremely important. However, current systems have difficulty quickly collecting and analyzing regional electricity rate data and market fluctuation data, calculating appropriate unit prices, and notifying them in real time. Furthermore, the provision of data for price negotiation is insufficient, resulting in inefficient energy management. The purpose of this invention is to provide an integrated system that solves these problems.

[1148] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1149] In this invention, the server includes: means for registering requests for an electricity rate increase; means for calculating an appropriate electricity unit price for each region; means for notifying users of the appropriate electricity unit price; means for providing data for discount negotiations; means for providing standard index data to external clients; means for calculating an appropriate energy unit price based on energy consumption data and supporting energy management at logistics centers; means for including an algorithm for calculating an average appropriate unit price based on past rate data; and means for notifying users of the appropriate unit price in real time to their terminals. This enables prompt and appropriate management of electricity rates and makes it possible to improve the efficiency of energy management at logistics centers by providing data useful for discount negotiations.

[1150] The "means for registering a request for an increase in electricity rates" is a function that allows the user to input and save the current electricity rate and the desired rate.

[1151] The "means for calculating appropriate electricity unit prices for each region" is a function for calculating fair electricity unit prices for each region based on past rate data and market fluctuation data.

[1152] The "means for notifying the user of the appropriate electricity unit price" is a function that transmits the calculated appropriate electricity unit price to the user terminal in real time.

[1153] The "means for providing data for price negotiation" is a function that provides past price data and market information necessary to support the user in price negotiation.

[1154] "Means for providing standard index data to external clients" refers to an API or dashboard that provides unified electricity rate index data to external users.

[1155] "A means to support energy management at logistics centers by calculating appropriate energy rates based on energy consumption data" is a function that supports energy management by collecting and analyzing energy consumption data at logistics centers and calculating fair energy rates.

[1156] The "algorithm for calculating the average fair price based on past rate data" is a calculation method that uses past electricity rate data to find the average value and derive the fair price.

[1157] "Means for notifying the user of the fair unit price in real time" is a function that immediately transmits the calculated fair unit price to the user's device.

[1158] System Configuration

[1159] The present invention is realized by providing a number of components, including a user terminal, a server, a database, and the like.

[1160] 1. User Device

[1161] The user terminal is a device used by the energy manager at the logistics center to input information and check related data. Smartphones, tablets, PCs, etc. are used as user terminals.

[1162] 2. Server

[1163] The server is a central computing device that processes, stores, and analyzes data. The server receives information sent from user devices, calculates appropriate energy rates, and notifies the results to users.

[1164] 3. Database

[1165] The system includes data storage for storing electricity bill information, energy consumption data, billing history data, fair unit prices, etc.

[1166] Program Processing Overview

[1167] Registering a request for an increase in electricity rates

[1168] The user uses the user terminal to input the required information (for example, current electricity bill, desired rate) into a web form or application. This information is first validated by the terminal and then sent to the server. The server registers the received data in a database, enabling request management.

[1169] Calculation of appropriate unit prices for each region

[1170] The server accesses the database of each local power supplier to obtain past electricity rate history and market fluctuation data. The obtained data is analyzed within the server using an algorithm to calculate the appropriate unit price, and the calculation results are saved in the database and updated as needed.

[1171] User notification of fair unit price

[1172] Once the calculation of the appropriate unit price is complete, the server notifies the user of the result and displays it to the user. For example, if the appropriate unit price for logistics center A is calculated to be "4,500 yen / month," this information is displayed on the user's screen.

[1173] Providing data for price negotiations

[1174] A user logs into the system and requests data for negotiating price increases. The terminal forwards this request to the server, which extracts relevant information from the database (e.g., electricity rates for nearby logistics depots, historical rate fluctuations, and local market trends) and generates a visual report. This report is sent to the terminal and displayed to the user.

[1175] Providing standard metrics data to external clients

[1176] The server collects electricity bill data from across the country and periodically analyzes it. It then runs the applied algorithms to generate standard index data. This data is packaged and provided to external clients via APIs and dashboards. External clients can use the provided data to set their own rates and negotiate discounts.

[1177] Adding specific examples

[1178] For example, suppose a logistics center manager in one of Tokyo's 23 wards inputs a request through the system saying, "I would like to raise the current electricity rate from 3,000 yen / month to 5,000 yen / month." This information is validated on the terminal, then sent to the server and registered in the database.

[1179] Next, the server retrieves data from electricity suppliers in Tokyo's 23 wards and calculates the appropriate unit price based on past price history and market trends. In this case, the appropriate unit price of 4,500 yen / month is calculated and notified to the user.

[1180] Finally, users can log into the system and view detailed reports including pricing data from nearby logistics depots and market trends, which they can use to negotiate discounts with their energy provider.

[1181] Prompt Sentence Examples

[1182] "I have entered a request to raise the electricity bill for my logistics center in Tokyo's 23 wards from 3,500 yen / month to 5,000 yen / month. Please calculate the appropriate unit price based on past billing history and generate an analysis report."

[1183] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1184] Step 1:

[1185] The user uses a user terminal to enter desired information such as the current electricity rate, desired rate, and base station location into a web form or application. This input information is validated (format checked) by the terminal and then sent to the server. If the validation results are correct, the system proceeds to the next step.

[1186] Step 2:

[1187] The server receives the electricity rate request data sent from the terminal and registers the data in the database. Specific input data includes user identification information, base station location, current electricity rate, desired rate, etc. This allows for request management.

[1188] Step 3:

[1189] The server accesses the databases of local power suppliers to retrieve historical electricity rates and market trend data. The server then executes appropriate database queries based on the local information. The retrieved data is then used as input data for calculating the appropriate unit price within the server.

[1190] Step 4:

[1191] The server uses the acquired historical electricity rate data and market fluctuation data to execute an algorithm to calculate the appropriate unit price. For example, it calculates the average electricity rate for each region over the past five years to calculate the appropriate unit price. The calculation results are stored in a database and are notified to the user in the next step.

[1192] Step 5:

[1193] After the calculated fair unit price is saved in the database, the server sends the fair unit price information via the communication dispatch system to notify the result to the user terminal. The user terminal receives this and displays it on the screen. For example, if the fair unit price for base station A is calculated to be "4,500 yen / month," this information will be displayed on the user's screen.

[1194] Step 6:

[1195] A user logs into the system and requests data for negotiating price increases. The request includes relevant data (electricity rates from nearby base stations, historical price fluctuations, local market trends, etc.). The device then sends this request to the server.

[1196] Step 7:

[1197] The server extracts the requested relevant data from the database and generates a visual report, specifically, visualizing the relevant data as graphs and charts, and then generates a report summarizing the data. The generated report is then transmitted to the user's device.

[1198] Step 8:

[1199] Users can view the report on their device and use it to negotiate discounts with their power company. The report displays nearby base station fee data and market trends, and users can use this information as a basis for negotiations.

[1200] Step 9:

[1201] The server periodically collects nationwide electricity price data and uses algorithms to generate standard index data, including data processing to analyze average prices by region and historical price trends. The generated index data is then made available to external clients via APIs and dashboards.

[1202] Step 10:

[1203] External clients can use the standard metrics provided to them to set their own prices and negotiate discounts, while data obtained via APIs can be integrated into their own systems to help inform strategic decision-making.

[1204] In this way, the system of the present invention efficiently carries out a series of processes related to energy management, and realizes appropriate calculation of electricity charges and user support.

[1205] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1206] The present invention combines an emotion engine that recognizes the emotions of users with an integrated system that registers requests for electricity rate increases, calculates appropriate unit prices for each region, and provides data that can be used in price negotiations. A specific embodiment of the present invention will be described below.

[1207] System Configuration

[1208] This system mainly consists of the following components:

[1209] 1. User terminal: A device through which base station owners and other users enter information and view relevant data.

[1210] 2. Server: A central computing device that processes, stores, and analyzes data.

[1211] 3. Database: Data storage for saving electricity tariff information, request information, historical data, fair unit prices, etc.

[1212] 4. Emotion engine: A system that analyzes user input data and recognizes the user's emotions.

[1213] Program Processing Overview

[1214] The programs in this system have the following functions:

[1215] Registering a request for an increase in electricity rates

[1216] The user uses a terminal to input the required information (e.g., base station location, current electricity rate, desired rate) into a web form or application. This information is first validated by the terminal and then sent to the server. The server registers the received data in a database, enabling request management.

[1217] Calculation of appropriate unit prices for each region

[1218] The server accesses the database of each local power supplier to obtain electricity rate history and market trend data for the specified area. The obtained data is analyzed within the server using an algorithm to calculate the appropriate unit price, and the calculation results are saved in the database and updated as necessary.

[1219] User Notifications and Emotion Recognition

[1220] Once the calculation of the appropriate unit price is complete, the server notifies the terminal of the result, which is displayed to the user. Furthermore, at this time, the emotion engine analyzes the user's input data (e.g., text input content and past behavioral history) and recognizes the user's emotional state (e.g., satisfaction, dissatisfaction, excitement, etc.). Based on the recognized emotion, the server adjusts the wording of the notification message and provides adaptive feedback to the user.

[1221] Providing data for price negotiations

[1222] A user logs into the system and requests the data needed to negotiate a price increase. The device forwards this request to the server, which extracts relevant information from the database (e.g., electricity rates for nearby base stations, historical price fluctuations, and local market trends) and generates a visual report. This report is sent to the device and displayed to the user.

[1223] Providing standard metrics data to external clients

[1224] The server collects electricity bill data from across the country and periodically analyzes it. It then runs the applied algorithms to generate standard index data. This data is packaged and provided to external clients via APIs and dashboards. External clients can use the provided data to set their own rates and negotiate discounts.

[1225] Specific examples

[1226] For example, suppose a base station owner in one of Tokyo's 23 wards inputs a request through the system saying, "I would like to raise my current electricity rate from 3,000 yen / month to 5,000 yen / month." This information is validated on the terminal, then sent to the server and registered in the database.

[1227] Next, the server retrieves data from electricity suppliers in Tokyo's 23 wards and calculates the appropriate unit price based on past price history and market trends. In this case, the appropriate unit price of 4,500 yen / month is calculated and notified to the user.

[1228] Furthermore, the emotion engine analyzes the user's input and recognizes emotions such as "I'm dissatisfied with the results." Based on the recognized emotion, the server adjusts the notification message to "We will propose a more optimal plan to bring you closer to your needs," and displays it to the user.

[1229] In this way, this system efficiently manages requests for electricity rate increases, supports the calculation of appropriate unit prices when installing new stations, and provides data for price negotiations. It also recognizes user emotions and responds adaptively to provide a better user experience.

[1230] The processing flow will be explained below.

[1231] Step 1:

[1232] Users input their electricity rate increase request using a dedicated web form or application, specifically by entering information such as the base station location, current electricity rate, and desired rate.

[1233] Step 2:

[1234] The terminal receives the data entered by the user and performs initial validation, which checks for required fields and the data format.

[1235] Step 3:

[1236] The terminal transmits the successfully validated data to the server.

[1237] Step 4:

[1238] The server stores the received electricity rate increase request in a database, including the base station location, current electricity rate, and desired rate.

[1239] Step 5:

[1240] The server accesses the database of local power supply companies to obtain electricity rate history and market trend data for the specified area.

[1241] Step 6:

[1242] The server runs an algorithm based on the acquired data to calculate the appropriate electricity unit price, taking into account past price history, local market fluctuations, and future market forecasts.

[1243] Step 7:

[1244] The server stores the calculated fair unit price in a database and simultaneously notifies the terminal.

[1245] Step 8:

[1246] The terminal displays the appropriate unit price to the user, who then checks the appropriate electricity unit price of the base station.

[1247] Step 9:

[1248] The emotion engine analyzes the user's input data and past behavioral history to recognize the user's emotional state. For example, it extracts emotions such as "satisfied" or "dissatisfied" from text content and click patterns.

[1249] Step 10:

[1250] The terminal transmits the user's emotional state recognized by the emotion engine to the server.

[1251] Step 11:

[1252] The server tailors the notification message based on the emotional state received from the emotion engine, for example by including a message offering further information or support to a frustrated user.

[1253] Step 12:

[1254] The server then sends the adjusted notification message to the terminal and displays it to the user, who receives feedback according to their emotional state.

[1255] Step 13:

[1256] A user logs into the system and requests the data needed to negotiate a price increase.

[1257] Step 14:

[1258] The terminal transmits the user's request to the server.

[1259] Step 15:

[1260] The server extracts relevant information from the database (e.g., electricity rate data for nearby base stations, historical rate fluctuation data, and local market trend data).

[1261] Step 16:

[1262] The server formats the extracted data into visual reports, converting the data into graphs and tables.

[1263] Step 17:

[1264] The server sends the generated report to the terminal, where it is displayed to the user.

[1265] Step 18:

[1266] The terminal displays a visual report to the user, who can then use this report to negotiate discounts with the power company.

[1267] Step 19:

[1268] The server periodically collects and analyzes nationwide electricity price data, which it then runs an algorithm to generate standard index data.

[1269] Step 20:

[1270] The server packages the generated metrics data and prepares APIs and dashboards to provide to external clients.

[1271] Step 21:

[1272] External clients can use the provided APIs and dashboards to obtain standard metrics and use them to set their own prices and negotiate discounts.

[1273] Example 2

[1274] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1275] The current system has difficulty effectively registering and managing requests for electricity rate increases and quickly and accurately calculating appropriate electricity unit prices for each region. It also lacks the ability to recognize user emotions and appropriately adjust notification messages accordingly, making it difficult to improve the user experience. Furthermore, there are issues with the efficiency of providing data required for price negotiations and rate setting to external clients. A system that solves these problems is needed.

[1276] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1277] In this invention, the server includes means for registering requests for electricity rate increases, means for calculating appropriate electricity unit prices for each region, means for notifying the user and recognizing their emotional state, means for adjusting the notification message based on the emotional state, means for providing data for price negotiations, and means for providing standard index data to external clients. This makes it possible to effectively manage requests for electricity rate increases and adaptively calculate and notify appropriate unit prices, thereby improving the user experience and providing efficient data.

[1278] An "electricity bill" is the fee that ordinary households and businesses pay to electric power companies for energy consumption.

[1279] A "price increase request" refers to a user expressing to the system a request to increase the current electricity rate.

[1280] A "fair electricity unit price" is a unit price of electricity that is considered reasonable in a particular area, calculated based on market trends and past price history.

[1281] "User" refers to an individual or corporation that uses the system to manage electricity charges or request rate increases.

[1282] An "emotion engine" is a system component that analyzes a user's input and behavioral history and recognizes their emotional state (e.g., satisfaction, dissatisfaction, excitement, etc.).

[1283] A "notification message" is an information message sent from the system to the user, and includes information such as the appropriate unit price and system update information.

[1284] "Discount negotiation data" refers to relevant information required when a user negotiates a discount with an electric power company.

[1285] "Standard index data" is reference data that indicates pricing and market trends, generated by analyzing electricity rate data nationwide.

[1286] "External Client" means a third-party individual or entity that uses standard indicator data provided by the System.

[1287] A "database" refers to data storage that regularly stores and manages information within a system.

[1288] "Validation" is the process of checking the accuracy and validity of entered data.

[1289] An "algorithm" is a set of computational steps that a system executes to solve a particular problem.

[1290] "API" refers to an interface that allows a system to exchange data with external clients.

[1291] A "dashboard" is a user interface that visually displays system usage status and important indicators.

[1292] A "visual report" is a report that organizes data in a visually easy-to-understand manner in the form of graphs, charts, etc.

[1293] The present invention is an integrated system that registers requests for electricity rate increases, calculates appropriate unit prices for each region, and provides data that can be used in price negotiations, and is combined with an emotion engine that recognizes user emotions. Detailed embodiments of the present invention are described below.

[1294] System Configuration

[1295] The system consists of the following main components:

[1296] 1. User terminal: A device on which a user inputs information and checks related data. Examples include smartphones, tablets, and PCs.

[1297] 2. Server: A central computing device that processes, stores, and analyzes data. In this invention, a high-performance cloud server is recommended.

[1298] 3. Database: This is data storage for saving electricity rate information, request information, historical data, fair unit prices, etc. For example, a database management system such as MySQL or PostgreSQL is used.

[1299] 4. Emotion engine: A system that analyzes user input data and recognizes the user's emotions. Specifically, it uses emotion analysis software that uses natural language processing (NLP) technology.

[1300] Program Processing Overview

[1301] The system has the following main processing functions:

[1302] Registering a request for an increase in electricity rates

[1303] The user uses a terminal to input the required information (e.g., base station location, current electricity rate, desired rate) into a web form or application. This information is first validated by the terminal and then sent to the server. The server registers the received data in a database, enabling request management.

[1304] Calculation of appropriate unit prices for each region

[1305] The server accesses the database of each local power supplier to obtain electricity rate history and market trend data for the specified area. The obtained data is analyzed within the server using an algorithm to calculate the appropriate unit price, and the calculation results are saved in the database and updated as necessary.

[1306] User Notifications and Emotion Recognition

[1307] Once the calculation of the appropriate unit price is complete, the server notifies the terminal of the result, which is displayed to the user. Furthermore, at this time, the emotion engine analyzes the user's input data (e.g., text input content and past behavioral history) and recognizes the user's emotional state (e.g., satisfaction, dissatisfaction, excitement, etc.). Based on the recognized emotion, the server adjusts the wording of the notification message and provides adaptive feedback to the user.

[1308] Providing data for price negotiations

[1309] A user logs into the system and requests the data needed to negotiate a price increase. The device forwards this request to the server, which extracts relevant information from the database (e.g., electricity rates for nearby base stations, historical price fluctuations, and local market trends) and generates a visual report. This report is sent to the device and displayed to the user.

[1310] Providing standard metrics data to external clients

[1311] The server collects electricity bill data from across the country and periodically analyzes it. It then runs the applied algorithms to generate standard index data. This data is packaged and provided to external clients via APIs and dashboards. External clients can use the provided data to set their own rates and negotiate discounts.

[1312] Specific examples

[1313] For example, suppose a base station owner in one of Tokyo's 23 wards inputs a request through the system saying, "I would like to raise my current electricity rate from 3,000 yen / month to 5,000 yen / month." This information is validated on the terminal, then sent to the server and registered in the database.

[1314] Next, the server retrieves data from electricity suppliers in Tokyo's 23 wards and calculates the appropriate unit price based on past price history and market trends. In this case, the appropriate unit price of 4,500 yen / month is calculated and notified to the user.

[1315] Furthermore, the emotion engine analyzes the user's input and recognizes emotions such as "I'm dissatisfied with the results." Based on the recognized emotion, the server adjusts the notification message to "We will propose a more optimal plan to bring you closer to your needs," and displays it to the user.

[1316] Prompt Sentence Examples

[1317] An example of a prompt to input to a generative AI model is as follows:

[1318] "As a base station owner within Tokyo's 23 wards, I would like to raise my current electricity bill from 3,000 yen / month to 5,000 yen / month. Please calculate the appropriate electricity unit price and provide data for price negotiation based on the results. Also, please create a system that recognizes user emotions and provides adaptive feedback."

[1319] Using this prompt, the generative AI model can understand the specific instructions and generate an appropriate response.

[1320] The system of the present invention effectively manages requests for electricity rate increases, supports calculation of appropriate unit prices for new base stations, and provides data for price negotiations. Furthermore, it can provide a better user experience by recognizing user emotions and responding adaptively.

[1321] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1322] Step 1:

[1323] The user enters a request

[1324] The user uses the terminal to input the required information (e.g., base station location, current electricity price, desired price) into the web form or application. The input data is entered in the following format:

[1325] Input: Base station location (e.g., "Shinagawa-ku, Tokyo"), current electricity rate (e.g., "3,000 yen / month"), desired rate (e.g., "5,000 yen / month")

[1326] When the terminal receives this, it formats the data internally and proceeds to the next step.

[1327] Step 2:

[1328] The terminal validates the data

[1329] The terminal validates the input data, specifically performing the following data manipulations and calculations:

[1330] Check whether the base station location is in a real area (e.g., verify whether "Shinagawa Ward, Tokyo" is a valid area).

[1331] Check that your current electricity rate and desired rate are numerical values.

[1332] Input: Information entered by the user

[1333] Output: Valid data (e.g., "Shinagawa-ku, Tokyo", "3000 yen / month", "5000 yen / month")

[1334] If the validation is successful, the terminal transmits the data to the server.

[1335] Step 3:

[1336] The server receives the data and registers it in the database

[1337] The server receives the data sent from the device. The received data is stored in the following format:

[1338] Input: Valid data from the device (e.g., "Shinagawa-ku, Tokyo", "3000 yen / month", "5000 yen / month")

[1339] The server registers this in a database, enabling request management.

[1340] Output: Add a new record to the database (e.g., add the current electricity rate and desired rate to the "Shinagawa Ward, Tokyo" field)

[1341] Step 4:

[1342] The server obtains data to calculate the appropriate unit price for each region.

[1343] The server accesses the power supplier's database to obtain electricity rate history and market trend data for the specified area.

[1344] Input: Area information (e.g. "Shinagawa-ku, Tokyo")

[1345] Output: Electricity rate history by region, market trend data (e.g., "Price history for the past year", "Market trend data")

[1346] The acquired data is used in the next step.

[1347] Step 5:

[1348] The server calculates the appropriate unit price

[1349] The server uses the acquired data to apply an algorithm to calculate the appropriate unit price for each region. Specifically, the following data calculations are performed:

[1350] Calculate the average price from past price history

[1351] Applying predictive models based on market trend data

[1352] Input: Electricity rate history by region, market trend data

[1353] Output: Fair price (e.g. "4500 yen / month")

[1354] The calculation results are stored in a database.

[1355] Step 6:

[1356] The server notifies the device of the results, and the emotion engine recognizes the user's emotions.

[1357] The server notifies the terminal of the calculated fair price and displays it to the user. Based on the displayed result, the emotion engine analyzes the user's input data (e.g., text input content and past behavior history) and recognizes the user's emotional state.

[1358] Input: Fair unit price result (e.g. "4500 yen / month"), user input data

[1359] Output: User's emotional state (e.g. "unhappy")

[1360] The result of the fair unit price being fair will evoke feelings of satisfaction, dissatisfaction, excitement, etc. in the user.

[1361] Step 7:

[1362] The server adjusts notification messages based on emotional state.

[1363] The server adjusts the notification message based on the recognized emotion and provides adaptive feedback to the user. Specifically, it works as follows:

[1364] Select an appropriate feedback message from templates stored on the server for the recognized emotion (e.g., "unhappy").

[1365] Input: User's emotional state

[1366] Output: Optimized notification message (e.g. "We will propose a more optimal plan to meet your needs")

[1367] This provides feedback according to the user's emotions.

[1368] Step 8:

[1369] The user requests data for price negotiation, and the server generates and serves the report.

[1370] Users log into the system and request the data they need to negotiate a price increase. The device forwards this request to the server, which extracts the relevant information from the database and generates a visual report.

[1371] Input: User request (e.g. "Request for price negotiation data")

[1372] Output: Visual report (e.g. "PDF report")

[1373] The report is sent to the terminal and displayed to the user.

[1374] Step 9:

[1375] The server collects and analyzes electricity rate data nationwide to provide standard index data.

[1376] The server periodically collects electricity bill data from across the country and applies algorithms to generate standard index data, which is then provided to external clients via APIs and dashboards.

[1377] Input: Nationwide electricity rate data

[1378] Output: Standard indicator data (e.g., "national average, standard deviation")

[1379] External clients can use this information to set their own prices and negotiate discounts.

[1380] Through these steps, the system can improve the user experience while efficiently managing requests for electricity rate increases and providing data for calculating fair unit prices and negotiating discounts.

[1381] (Application example 2)

[1382] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1383] Conventional electricity rate management systems lack the ability to respond to user needs with detailed consideration, making it difficult to improve user satisfaction. Furthermore, it is difficult to provide the appropriate data required for price negotiations, resulting in a low success rate for negotiations. The present invention aims to solve these problems and support improved user satisfaction and efficient price negotiations.

[1384] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1385] In this invention, the server includes a means for registering requests for an increase in electricity rates, a means for calculating appropriate electricity unit prices for each region, a means for notifying the user of the appropriate electricity unit price, a means for recognizing the user's emotions and adjusting the notification message, and a means for generating a visual report including nearby prices and trend information during price negotiations. This enables a detailed response that takes the user's emotions into consideration, improves the success rate of negotiations, and increases user satisfaction.

[1386] The "means for registering a request for an increase in electricity rates" is a function that allows a user to input a request for an increase in electricity rates into the system and register that information in the database.

[1387] The "means for calculating appropriate electricity unit prices for each region" is a function that calculates appropriate electricity unit prices based on past price history and market trend data in a specific region.

[1388] The "means for notifying the user of the appropriate electricity unit price" is a function for notifying the user of the calculated appropriate electricity unit price.

[1389] The "means for providing data for price negotiation" is a function for providing relevant data necessary when a user negotiates a price.

[1390] The "means for recognizing the user's emotions and adjusting the notification message" is a function that uses an emotion engine to analyze the user's emotions and adaptively adjusts the notification message in accordance with those emotions.

[1391] "Means for generating visual reports including nearby price and trend information during price negotiations" refers to a function for generating reports that visually display nearby prices and market trend information to assist in negotiations.

[1392] "Means for providing standard index data to external clients" refers to a function for collecting and analyzing nationwide electricity rate data, generating standard indexes, and providing them to external clients.

[1393] The "means for managing requests for an increase in electricity rates and storing the same in a database" is a function for efficiently managing requests for an increase in electricity rates from users and storing the data in a database.

[1394] "Means for automatically calculating appropriate unit prices based on past rate history and market fluctuation data" is a function that automatically calculates appropriate electricity unit prices based on past electricity rate history and market fluctuation data.

[1395] "Means for recognizing emotions by analyzing user input data and past behavioral history" is a function for analyzing and recognizing emotions based on user input data and past behavioral history.

[1396] "Means for extracting relevant data in response to a user request and providing it as a visual report" refers to a function that extracts necessary data in response to a user request and provides that data as a visually displayed report.

[1397] "Means for collecting and analyzing electricity rate data nationwide" is a function for analyzing electricity rate data collected from across the country.

[1398] The "means for executing an algorithm for generating a standard index" is a function for executing a specific algorithm for generating a standard index.

[1399] The "means for generating an adaptive notification message based on the user's emotion" is a function for generating an adaptive notification message based on the user's emotion analyzed by the emotion engine.

[1400] "Means for providing an API or dashboard for providing index data to external clients" refers to a function for setting up an API or dashboard for providing index data to external clients.

[1401] This is an integrated system that manages requests for electricity rate increases, calculates appropriate electricity unit prices for each region, notifies users of these prices, and provides adaptive notification messages through emotion recognition. It also generates visual reports including nearby prices and trend information during price negotiations, and provides standard index data to external clients.

[1402] System configuration

[1403] This system consists of the following components:

[1404] 1. User terminal: A device on which a user inputs their request for an increase in electricity rates and checks related data. This is often a smartphone or tablet.

[1405] 2. Server: The central computing device that processes, stores, and analyzes data, and performs fair pricing and emotion recognition.

[1406] 3. Database: Data storage for saving electricity rate information, user request information, historical data, appropriate unit prices for each region, etc.

[1407] 4. Emotion Engine: A system that analyzes user input data and recognizes user emotions. It uses the BERT model and other emotion recognition algorithms.

[1408] Program Processing Overview

[1409] 1. Request registration

[1410] A user uses a user terminal to input required information into a web form or application, including location, current electricity rate, and desired rate.

[1411] The entered information is validated in real time and then sent to the server, which registers the received data in a database and manages requests.

[1412] 2. Calculating the appropriate unit price

[1413] The server retrieves past electricity rate history and market trend data from the database and calculates the appropriate unit price. The system calculates the appropriate unit price using data analysis libraries such as Pandas and Scikit-learn.

[1414] The calculated fair unit price is stored in a database and updated as necessary.

[1415] 3. Emotion Recognition and Notification

[1416] The server notifies the user of the calculated fair price. When notifying the user, the emotion engine analyzes the user's input data and recognizes the user's emotion.

[1417] Generative AI models such as the BERT model are used for emotion recognition. An example prompt is as follows:

[1418] python

[1419] import transformers

[1420] Loading the model

[1421] model_name = "nlptown / bert-base-multilingual-uncased-sentiment"

[1422] tokenizer = transformers.AutoTokenizer.from_pretrained(model_name)

[1423] model = transformers.AutoModelForSequenceClassification.from_pretrained(model_name)

[1424] text = "I am extremely dissatisfied with this service."

[1425] inputs = tokenizer.encode_plus(

[1426] text,

[1427] add_special_tokens=True,

[1428] return_tensors="pt"

[1429] )

[1430] Model prediction

[1431] outputs = model(inputs)

[1432] prediction = torch.argmax(outputs.logits, dim=1).item()

[1433] Emotion-based response message generation

[1434] if prediction == 0:

[1435] response_message = "We apologize for the inconvenience. We will look into resolving this issue immediately."

[1436] elif prediction == 1:

[1437] response_message = "We appreciate your feedback."

[1438] else:

[1439] response_message = "Thank you for using our service. We look forward to working with you in the future."

[1440] print(response_message)

[1441] Based on the recognized emotion, the server adjusts the wording of the notification message and provides adaptive feedback to the user.

[1442] 4. Providing discount negotiation data

[1443] When a user logs into the system and requests the data needed to negotiate a price, the server extracts the relevant information from the database and uses libraries (Matplotlib and Seaborn) to generate visual reports.

[1444] The generated report is sent to the user terminal and displayed to the user.

[1445] 5. Providing standard indicator data to external clients

[1446] The server periodically collects electricity bill data from across the country and runs data analysis algorithms such as Pandas and Scikit-learn.

[1447] The generated standard metrics data is provided to external clients via APIs and dashboards.

[1448] In this way, the system efficiently manages requests for electricity rate increases, improves the user experience by providing notification messages that reflect the user's feelings, and increases the user's success rate in negotiating discounts by providing necessary data for price negotiations.

[1449] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1450] Step 1:

[1451] Register your request

[1452] The user uses a terminal to open a web form or application and input a request for an increase in electricity rates. The information entered includes location, current electricity rate, and desired rate. This input data is validated in real time and, if there are no problems, is sent to the server. The server registers the received data in a database and manages the request.

[1453] Input: User's request for rate increase (location, current electricity rate, desired rate)

[1454] Output: Request information registered in the database

[1455] Processing operation: The server validates the input data and saves it in the database.

[1456] Step 2:

[1457] Calculating the appropriate unit price

[1458] The server retrieves historical electricity rates and market trend data from the database. Based on the retrieved data, the server calculates the appropriate unit price using data analysis libraries such as Pandas and Scikit-learn. The calculated appropriate unit price is saved in the database and updated as necessary.

[1459] Input: Past electricity rate history and market trend data obtained from the database

[1460] Output: Fair unit price stored in the database

[1461] Processing operation: The server analyzes the data using the data analysis library and calculates the appropriate unit price.

[1462] Step 3:

[1463] Emotion Recognition and Notification

[1464] The server notifies the user device of the calculated fair price. When this notification is sent, the emotion engine analyzes the user's input data and recognizes the user's emotions. Emotion recognition uses a generative AI model such as the BERT model.

[1465] Example prompt sentence:

[1466] python

[1467] import transformers

[1468] Loading the model

[1469] model_name = "nlptown / bert-base-multilingual-uncased-sentiment"

[1470] tokenizer = transformers.AutoTokenizer.from_pretrained(model_name)

[1471] model = transformers.AutoModelForSequenceClassification.from_pretrained(model_name)

[1472] text = "I am extremely dissatisfied with this service."

[1473] inputs = tokenizer.encode_plus(

[1474] text,

[1475] add_special_tokens=True,

[1476] return_tensors="pt"

[1477] )

[1478] Model prediction

[1479] outputs = model(inputs)

[1480] prediction = torch.argmax(outputs.logits, dim=1).item()

[1481] Emotion-based response message generation

[1482] if prediction == 0:

[1483] response_message = "We apologize for the inconvenience. We will look into resolving this issue immediately."

[1484] elif prediction == 1:

[1485] response_message = "We appreciate your feedback."

[1486] else:

[1487] response_message = "Thank you for using our service. We look forward to working with you in the future."

[1488] print(response_message)

[1489] Input: User-entered data

[1490] Output: Adaptive notification message based on emotions

[1491] Processing operation: The server analyzes the user's emotions using the emotion engine, adjusts the text of the notification message, and notifies the user.

[1492] Step 4:

[1493] Providing discount negotiation data

[1494] When a user logs in to the system and requests data for price negotiation, the server extracts nearby prices and market trend information from the database and generates a visual report using libraries such as Matplotlib and Seaborn. The generated report is sent to the user's terminal and displayed for the user.

[1495] Input: User requests and data extracted from the database

[1496] Output: Data displayed as a visual report

[1497] Processing operations: The server extracts and analyzes the data, generates a visual report and sends it to the user.

[1498] Step 5:

[1499] Providing standard metrics data to external clients

[1500] The server periodically collects electricity rate data from across the country and runs data analysis algorithms such as Pandas and Scikit-learn to generate standard indicator data, which is then provided to external clients via APIs and dashboards.

[1501] Input: Nationwide electricity rate data

[1502] Output: Standard metrics data provided to external clients

[1503] Processing operations: The server analyzes the collected data and provides the generated standard metrics data to external clients via APIs and dashboards.

[1504] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[1505] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1506] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1507] [Fourth embodiment]

[1508] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1509] 7, a 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.

[1510] 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 a "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).

[1511] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. 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 microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1512] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1513] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1514] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1515] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1516] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1517] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1518] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1519] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1520] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1521] The present invention is an integrated system for registering requests for electricity rate increases, quickly calculating appropriate unit prices for each region, and providing data that can be used in price negotiations. A specific embodiment of the present invention will be described below.

[1522] System Configuration

[1523] This system mainly consists of the following components:

[1524] 1. User terminal: A device through which base station owners and other users enter information and view relevant data.

[1525] 2. Server: A central computing device that processes, stores, and analyzes data.

[1526] 3. Database: Data storage for saving electricity tariff information, request information, historical data, fair unit prices, etc.

[1527] Program Processing Overview

[1528] The programs in this system have the following functions:

[1529] Registering a request for an increase in electricity rates

[1530] The user uses the user terminal to input the required information (e.g., base station location, current electricity rate, desired rate) into a web form or application. This information is first validated by the terminal and then sent to the server. The server registers the received data in a database, enabling request management.

[1531] Calculation of appropriate unit prices for each region

[1532] The server accesses the database of each local power supplier to obtain past electricity rate history and market fluctuation data. The obtained data is analyzed within the server using an algorithm to calculate the appropriate unit price, and the calculation results are saved in the database and updated as needed.

[1533] User notification of fair unit price

[1534] Once the calculation of the appropriate unit price is complete, the server notifies the terminal of the result, which is displayed to the user. For example, if the appropriate unit price for base station A is calculated to be "4,500 yen / month," this information is displayed on the user's screen.

[1535] Providing data for price negotiations

[1536] A user logs into the system and requests data for negotiating price increases. The device forwards this request to the server, which extracts relevant information from the database (e.g., electricity rates for nearby base stations, historical rate fluctuations, and local market trends) and generates a visual report. This report is sent to the device and displayed to the user.

[1537] Providing standard metrics data to external clients

[1538] The server collects electricity bill data from across the country and periodically analyzes it. It then runs the applied algorithms to generate standard index data. This data is packaged and provided to external clients via APIs and dashboards. External clients can use the provided data to set their own rates and negotiate discounts.

[1539] Specific examples

[1540] For example, suppose a base station owner in one of Tokyo's 23 wards inputs a request through the system saying, "I would like to raise my current electricity rate from 3,000 yen / month to 5,000 yen / month." This information is validated on the terminal, then sent to the server and registered in the database.

[1541] Next, the server retrieves data from electricity suppliers in Tokyo's 23 wards and calculates the appropriate unit price based on past price history and market trends. In this case, the appropriate unit price of 4,500 yen / month is calculated and notified to the user.

[1542] Finally, users can log into the system and view detailed reports including nearby cell tower pricing data and market trends, and use this information to negotiate discounts with their power company.

[1543] In this way, the system efficiently manages requests for electricity rate increases and supports the calculation of appropriate unit prices and the provision of data for price negotiations when installing new stations.

[1544] The processing flow will be explained below.

[1545] Step 1:

[1546] Users input their electricity rate increase request using a dedicated web form or application, specifically by entering information such as the base station location, current electricity rate, and desired rate.

[1547] Step 2:

[1548] The terminal receives the data entered by the user and performs initial validation, which checks for required fields and the data format.

[1549] Step 3:

[1550] The terminal transmits the successfully validated data to the server.

[1551] Step 4:

[1552] The server stores the received electricity rate increase request in a database, including the base station location, current electricity rate, and desired rate.

[1553] Step 5:

[1554] The server accesses the database of local power supply companies to obtain electricity rate history and market trend data for the specified area.

[1555] Step 6:

[1556] The server runs an algorithm based on the acquired data to calculate the appropriate electricity unit price, taking into account past price history, local market fluctuations, and future market forecasts.

[1557] Step 7:

[1558] The server stores the calculated fair unit price in a database and simultaneously notifies the terminal.

[1559] Step 8:

[1560] The terminal displays the appropriate unit price to the user, who then checks the appropriate electricity unit price of the base station.

[1561] Step 9:

[1562] A user logs into the system and makes a request for the data needed to negotiate a price increase.

[1563] Step 10:

[1564] The terminal transmits the user's request to the server.

[1565] Step 11:

[1566] The server extracts relevant information from the database (e.g., electricity rate data for nearby base stations, historical rate fluctuation data, and local market trend data).

[1567] Step 12:

[1568] The server formats the extracted data into visual reports, converting the data into graphs and tables.

[1569] Step 13:

[1570] The server transmits the generated report to the terminal.

[1571] Step 14:

[1572] The terminal displays a visual report to the user, who can then use this report to negotiate discounts with the power company.

[1573] Step 15:

[1574] The server periodically collects and analyzes nationwide electricity price data, which it then runs an algorithm to generate standard index data.

[1575] Step 16:

[1576] The server packages the generated metrics data and prepares APIs and dashboards to provide to external clients.

[1577] Step 17:

[1578] External clients can use the provided APIs and dashboards to obtain standard metrics and use them to set their own prices and negotiate discounts.

[1579] Example 1

[1580] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1581] In the conventional system, registering requests for electricity rate increases and calculating appropriate unit prices were often time-consuming and difficult to execute efficiently. Furthermore, there was a lack of effective means to provide the necessary information for users to negotiate discounts. Furthermore, there was a need for a comprehensive and rapid response in collecting electricity rate data nationwide and providing standard index data.

[1582] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1583] In this invention, the server includes means for registering requests for an electricity rate increase, means for calculating an appropriate electricity unit price for each region, means for notifying users of the appropriate electricity unit price, means for providing data for discount negotiations, means for providing standard index data to external clients, means for validating information on the requested electricity rate increase, means for accessing a rate database for each region, means for executing an algorithm for calculating the appropriate unit price, means for structuring the request information and registering it in the database, and means for extracting related information in response to user requests and generating visual reports. This enables efficient registration of requests for an electricity rate increase, rapid calculation of the appropriate unit price, and provision of useful data to users and external clients.

[1584] "Means for registering requests for an increase in electricity rates" refers to a function that allows a user to input a request for an increase in electricity rates and record it in the system.

[1585] "Means for calculating appropriate electricity unit prices for each region" refers to a function for calculating appropriate electricity unit prices for each region based on power supply companies and market data from different regions.

[1586] "Means for notifying the user of the appropriate electricity unit price" refers to a function for notifying the user of the calculated appropriate electricity unit price on the user's terminal so that the user can check it.

[1587] The "means for providing data for price negotiation" refers to a function for providing a user with data and information required for negotiating a price reduction for electricity charges.

[1588] "Means of providing standard index data to external clients" refers to APIs, dashboards, etc. for providing standard electricity rates and market index data to external client companies.

[1589] "Means for validating electricity rate increase request information" refers to a function for verifying and confirming the accuracy and completeness of the rate increase request information entered by the user.

[1590] "Means for accessing a regional fee database" refers to a function for accessing a database that stores fee data for a specific region and obtaining the required information.

[1591] "Means for executing an algorithm for calculating a fair unit price" refers to a function for executing an analytical algorithm for calculating a fair unit price for electricity based on a variety of data.

[1592] "Means for structuring request information and registering it in a database" refers to a function for organizing request information submitted by users and efficiently storing it in a database.

[1593] "Means for extracting relevant information in response to a user request and generating a visual report" refers to a function for extracting information requested by a user from a database and generating a report in an easy-to-read format.

[1594] The present invention is an integrated system for registering requests for electricity rate increases, quickly calculating appropriate unit prices for each region, and providing data that can be used in price negotiations. The following describes in detail an embodiment of the present invention.

[1595] System Configuration

[1596] This system mainly consists of the following components:

[1597] 1. User terminal: A device through which base station owners and other users enter information and view relevant data.

[1598] 2. Server: A central computing device that processes, stores, and analyzes data.

[1599] 3. Database: Data storage for saving electricity tariff information, request information, historical data, fair unit prices, etc.

[1600] 4. API: An interface for providing data to external clients.

[1601] Registering a request for an increase in electricity rates

[1602] The user uses a user terminal to enter the required information (e.g., base station location, current electricity rate, desired rate) into a web form or application. This information is validated in real time by the terminal. For example, if a required field is missing or an invalid value is entered, an error message is displayed to the user. Data that has been successfully validated is sent to the server using HTTPS. The server registers the received data in a database, enabling request management.

[1603] Calculation of appropriate unit prices for each region

[1604] The server accesses the API of the local power supply company to obtain the necessary data. For example, data may be obtained through the API of Tokyo Electric Power Company. In addition, past electricity rate history and market fluctuation data are retrieved from the database. This data is analyzed by the server's appropriate unit price calculation algorithm, and the appropriate electricity unit price is calculated. The calculation results are stored in the database and updated as needed.

[1605] User notification of fair unit price

[1606] Once the calculation of the appropriate unit price has been completed, the server calls an API to notify the device of the results. Some notifications may use WebSocket technology. The device receives the results and displays a specific message on the user's screen, such as "The appropriate unit price for your base station is 4,500 yen / month."

[1607] Providing data for price negotiations

[1608] A user logs into the system and requests data for price increase negotiations. The request can be made with a simple button press. The device forwards this request to the server via HTTPS. The server extracts relevant information from the database, such as "electricity rates of nearby base stations," "past price fluctuations," and "local market trends." The server generates a visual report from the extracted data using a BI tool (e.g., Tableau). The generated report is sent to the device as a PDF or Excel file, and the device displays it to the user.

[1609] Providing standard metrics data to external clients

[1610] The server periodically collects data from each regional electricity supplier in order to centralize nationwide electricity rate data. The server analyzes the collected data at regular intervals (e.g., once a month) and also analyzes long-term market trends. It generates standard indicators using specific algorithms (e.g., moving average method) and packages them in JSON format or similar. It provides the generated standard indicator data to external clients via APIs or dedicated dashboards. External clients download this data and apply it to their own business.

[1611] Examples and prompts

[1612] For example, if a base station owner in Tokyo's 23 wards submits a request through the system saying, "I want to raise my current electricity rate from 3,000 yen / month to 5,000 yen / month," the request would be:

[1613] The user enters information into a web form and submits it.

[1614] The device performs validation and sends the data to the server.

[1615] The server registers the data and accesses TEPCO's API to retrieve the necessary data.

[1616] The server uses past pricing data to calculate the appropriate unit price and comes up with the result "4,500 yen / month."

[1617] The server communicates this information to the terminal, which displays the results to the user.

[1618] Users can request detailed reports and receive reports that include neighboring cell tower data and market trends.

[1619] To operate this system, the prompts sent to the generative AI model are as follows:

[1620] "A base station owner in Tokyo's 23 wards has entered a request to raise their current electricity rate from 3,000 yen / month to 5,000 yen / month. Please explain the detailed process flow, step by step, for calculating the appropriate electricity rate based on this information and notifying the user."

[1621] This prompt sentence enables the generative AI model to generate a specific processing flow for calculating the appropriate unit price and notifying the user.

[1622] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1623] Step 1:

[1624] Input and registration of electricity rate increase requests

[1625] The user uses the user terminal to input the required information into a web form or application. The input information includes the location of the base station, the current electricity rate, and the desired electricity rate. When the user clicks the "Submit" button, the terminal validates the input data (e.g., checking for missing fields or incorrect data format). Data that passes validation is sent to the server via HTTPS. The server structures the received data and registers it in a database along with a timestamp and user ID. The input to the server is the requested information sent from the user terminal, and the output is the structured data registered in the database.

[1626] Step 2:

[1627] Obtaining data on electricity supply companies by region

[1628] The server accesses the power supply company's API to obtain past electricity rate history and market fluctuation data for the specified region. For example, the server obtains data through Tokyo Electric Power Company's API. At this time, the server temporarily stores the obtained data in memory and then also stores it in a database for further analysis. The input is the region-specified request data, and the output is the obtained power supply data.

[1629] Step 3:

[1630] Calculation of appropriate electricity unit price

[1631] The server runs an algorithm to calculate the appropriate electricity unit price based on the historical electricity rate history for each region and market fluctuation data obtained from the database. This algorithm includes, for example, the past average value and the moving average method. The server calculates the appropriate unit price based on the analysis results and saves the result in the database. The input is the obtained power supply data and past rate history, and the output is the calculated appropriate unit price.

[1632] Step 4:

[1633] Notification of fair unit price

[1634] Once the server has calculated the appropriate unit price, it calls an API to notify the user device of the result. The server composes the content of the notification and sends it to the user device in real time using WebSocket technology. Based on the notification received, the device displays details of the appropriate unit price (e.g., 4,500 yen / month) on the user's screen. The input is the calculated appropriate unit price, and the output is a notification message to the user.

[1635] Step 5:

[1636] Requesting and providing price negotiation data

[1637] A user logs into the system and requests data for price negotiation. This request is sent from the user's terminal to the server. The server extracts relevant information based on the request from the database. This information may include "electricity rates of nearby base stations," "past price fluctuations," and "market trends." The server uses a BI tool (e.g., Tableau) to generate a visual report. This report is saved in PDF or Excel format and sent from the server to the user's terminal. The user can view the report on their terminal and use it in negotiations. The input is the user's request, and the output is the generated visual report.

[1638] Step 6:

[1639] Providing standard indicator data

[1640] The server periodically collects data from each regional power supply company in order to centralize nationwide electricity rate data. The server analyzes the collected data at regular intervals and also analyzes long-term market trends. It generates standard indicators using specific algorithms and packages them in formats such as JSON or CSV. These data packages are provided to external clients via APIs or dedicated dashboards. External clients can download this data and use it to set their own rates and negotiate discounts. The input is the collected electricity rate data, and the output is standard indicator data.

[1641] (Application example 1)

[1642] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1643] Because logistics centers consume large amounts of energy, proper management of electricity rates and negotiation of price increases are extremely important. However, current systems have difficulty quickly collecting and analyzing regional electricity rate data and market fluctuation data, calculating appropriate unit prices, and notifying them in real time. Furthermore, the provision of data for price negotiation is insufficient, resulting in inefficient energy management. The purpose of this invention is to provide an integrated system that solves these problems.

[1644] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1645] In this invention, the server includes: means for registering requests for an electricity rate increase; means for calculating an appropriate electricity unit price for each region; means for notifying users of the appropriate electricity unit price; means for providing data for discount negotiations; means for providing standard index data to external clients; means for calculating an appropriate energy unit price based on energy consumption data and supporting energy management at logistics centers; means for including an algorithm for calculating an average appropriate unit price based on past rate data; and means for notifying users of the appropriate unit price in real time to their terminals. This enables prompt and appropriate management of electricity rates and makes it possible to improve the efficiency of energy management at logistics centers by providing data useful for discount negotiations.

[1646] The "means for registering a request for an increase in electricity rates" is a function that allows the user to input and save the current electricity rate and the desired rate.

[1647] The "means for calculating appropriate electricity unit prices for each region" is a function for calculating fair electricity unit prices for each region based on past rate data and market fluctuation data.

[1648] The "means for notifying the user of the appropriate electricity unit price" is a function that transmits the calculated appropriate electricity unit price to the user terminal in real time.

[1649] The "means for providing data for price negotiation" is a function that provides past price data and market information necessary to support the user in price negotiation.

[1650] "Means for providing standard index data to external clients" refers to an API or dashboard that provides unified electricity rate index data to external users.

[1651] "A means to support energy management at logistics centers by calculating appropriate energy rates based on energy consumption data" is a function that supports energy management by collecting and analyzing energy consumption data at logistics centers and calculating fair energy rates.

[1652] The "algorithm for calculating the average fair price based on past rate data" is a calculation method that uses past electricity rate data to find the average value and derive the fair price.

[1653] "Means for notifying the user of the fair unit price in real time" is a function that immediately transmits the calculated fair unit price to the user's device.

[1654] System Configuration

[1655] The present invention is realized by providing a number of components, including a user terminal, a server, a database, and the like.

[1656] 1. User Device

[1657] The user terminal is a device used by the energy manager at the logistics center to input information and check related data. Smartphones, tablets, PCs, etc. are used as user terminals.

[1658] 2. Server

[1659] The server is a central computing device that processes, stores, and analyzes data. The server receives information sent from user devices, calculates appropriate energy rates, and notifies the results to users.

[1660] 3. Database

[1661] The system includes data storage for storing electricity bill information, energy consumption data, billing history data, fair unit prices, etc.

[1662] Program Processing Overview

[1663] Registering a request for an increase in electricity rates

[1664] The user uses the user terminal to input the required information (for example, current electricity bill, desired rate) into a web form or application. This information is first validated by the terminal and then sent to the server. The server registers the received data in a database, enabling request management.

[1665] Calculation of appropriate unit prices for each region

[1666] The server accesses the database of each local power supplier to obtain past electricity rate history and market fluctuation data. The obtained data is analyzed within the server using an algorithm to calculate the appropriate unit price, and the calculation results are saved in the database and updated as needed.

[1667] User notification of fair unit price

[1668] Once the calculation of the appropriate unit price is complete, the server notifies the user of the result and displays it to the user. For example, if the appropriate unit price for logistics center A is calculated to be "4,500 yen / month," this information is displayed on the user's screen.

[1669] Providing data for price negotiations

[1670] A user logs into the system and requests data for negotiating price increases. The terminal forwards this request to the server, which extracts relevant information from the database (e.g., electricity rates for nearby logistics depots, historical rate fluctuations, and local market trends) and generates a visual report. This report is sent to the terminal and displayed to the user.

[1671] Providing standard metrics data to external clients

[1672] The server collects electricity bill data from across the country and periodically analyzes it. It then runs the applied algorithms to generate standard index data. This data is packaged and provided to external clients via APIs and dashboards. External clients can use the provided data to set their own rates and negotiate discounts.

[1673] Adding specific examples

[1674] For example, suppose a logistics center manager in one of Tokyo's 23 wards inputs a request through the system saying, "I would like to raise the current electricity rate from 3,000 yen / month to 5,000 yen / month." This information is validated on the terminal, then sent to the server and registered in the database.

[1675] Next, the server retrieves data from electricity suppliers in Tokyo's 23 wards and calculates the appropriate unit price based on past price history and market trends. In this case, the appropriate unit price of 4,500 yen / month is calculated and notified to the user.

[1676] Finally, users can log into the system and view detailed reports including pricing data from nearby logistics depots and market trends, which they can use to negotiate discounts with their energy provider.

[1677] Prompt Sentence Examples

[1678] "I have entered a request to raise the electricity bill for my logistics center in Tokyo's 23 wards from 3,500 yen / month to 5,000 yen / month. Please calculate the appropriate unit price based on past billing history and generate an analysis report."

[1679] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1680] Step 1:

[1681] The user uses a user terminal to enter desired information such as the current electricity rate, desired rate, and base station location into a web form or application. This input information is validated (format checked) by the terminal and then sent to the server. If the validation results are correct, the system proceeds to the next step.

[1682] Step 2:

[1683] The server receives the electricity rate request data sent from the terminal and registers the data in the database. Specific input data includes user identification information, base station location, current electricity rate, desired rate, etc. This allows for request management.

[1684] Step 3:

[1685] The server accesses the databases of local power suppliers to retrieve historical electricity rates and market trend data. The server then executes appropriate database queries based on the local information. The retrieved data is then used as input data for calculating the appropriate unit price within the server.

[1686] Step 4:

[1687] The server uses the acquired historical electricity rate data and market fluctuation data to execute an algorithm to calculate the appropriate unit price. For example, it calculates the average electricity rate for each region over the past five years to calculate the appropriate unit price. The calculation results are stored in a database and are notified to the user in the next step.

[1688] Step 5:

[1689] After the calculated fair unit price is saved in the database, the server sends the fair unit price information via the communication dispatch system to notify the result to the user terminal. The user terminal receives this and displays it on the screen. For example, if the fair unit price for base station A is calculated to be "4,500 yen / month," this information will be displayed on the user's screen.

[1690] Step 6:

[1691] A user logs into the system and requests data for negotiating price increases. The request includes relevant data (electricity rates from nearby base stations, historical price fluctuations, local market trends, etc.). The device then sends this request to the server.

[1692] Step 7:

[1693] The server extracts the requested relevant data from the database and generates a visual report, specifically, visualizing the relevant data as graphs and charts, and then generates a report summarizing the data. The generated report is then transmitted to the user's device.

[1694] Step 8:

[1695] Users can view the report on their device and use it to negotiate discounts with their power company. The report displays nearby base station fee data and market trends, and users can use this information as a basis for negotiations.

[1696] Step 9:

[1697] The server periodically collects nationwide electricity price data and uses algorithms to generate standard index data, including data processing to analyze average prices by region and historical price trends. The generated index data is then made available to external clients via APIs and dashboards.

[1698] Step 10:

[1699] External clients can use the standard metrics provided to them to set their own prices and negotiate discounts, while data obtained via APIs can be integrated into their own systems to help inform strategic decision-making.

[1700] In this way, the system of the present invention efficiently carries out a series of processes related to energy management, and realizes appropriate calculation of electricity charges and user support.

[1701] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1702] The present invention combines an emotion engine that recognizes the emotions of users with an integrated system that registers requests for electricity rate increases, calculates appropriate unit prices for each region, and provides data that can be used in price negotiations. A specific embodiment of the present invention will be described below.

[1703] System Configuration

[1704] This system mainly consists of the following components:

[1705] 1. User terminal: A device through which base station owners and other users enter information and view relevant data.

[1706] 2. Server: A central computing device that processes, stores, and analyzes data.

[1707] 3. Database: Data storage for saving electricity tariff information, request information, historical data, fair unit prices, etc.

[1708] 4. Emotion engine: A system that analyzes user input data and recognizes the user's emotions.

[1709] Program Processing Overview

[1710] The programs in this system have the following functions:

[1711] Registering a request for an increase in electricity rates

[1712] The user uses a terminal to input the required information (e.g., base station location, current electricity rate, desired rate) into a web form or application. This information is first validated by the terminal and then sent to the server. The server registers the received data in a database, enabling request management.

[1713] Calculation of appropriate unit prices for each region

[1714] The server accesses the database of each local power supplier to obtain electricity rate history and market trend data for the specified area. The obtained data is analyzed within the server using an algorithm to calculate the appropriate unit price, and the calculation results are saved in the database and updated as necessary.

[1715] User Notifications and Emotion Recognition

[1716] Once the calculation of the appropriate unit price is complete, the server notifies the terminal of the result, which is displayed to the user. Furthermore, at this time, the emotion engine analyzes the user's input data (e.g., text input content and past behavioral history) and recognizes the user's emotional state (e.g., satisfaction, dissatisfaction, excitement, etc.). Based on the recognized emotion, the server adjusts the wording of the notification message and provides adaptive feedback to the user.

[1717] Providing data for price negotiations

[1718] A user logs into the system and requests the data needed to negotiate a price increase. The device forwards this request to the server, which extracts relevant information from the database (e.g., electricity rates for nearby base stations, historical price fluctuations, and local market trends) and generates a visual report. This report is sent to the device and displayed to the user.

[1719] Providing standard metrics data to external clients

[1720] The server collects electricity bill data from across the country and periodically analyzes it. It then runs the applied algorithms to generate standard index data. This data is packaged and provided to external clients via APIs and dashboards. External clients can use the provided data to set their own rates and negotiate discounts.

[1721] Specific examples

[1722] For example, suppose a base station owner in one of Tokyo's 23 wards inputs a request through the system saying, "I would like to raise my current electricity rate from 3,000 yen / month to 5,000 yen / month." This information is validated on the terminal, then sent to the server and registered in the database.

[1723] Next, the server retrieves data from electricity suppliers in Tokyo's 23 wards and calculates the appropriate unit price based on past price history and market trends. In this case, the appropriate unit price of 4,500 yen / month is calculated and notified to the user.

[1724] Furthermore, the emotion engine analyzes the user's input and recognizes emotions such as "I'm dissatisfied with the results." Based on the recognized emotion, the server adjusts the notification message to "We will propose a more optimal plan to bring you closer to your needs," and displays it to the user.

[1725] In this way, this system efficiently manages requests for electricity rate increases, supports the calculation of appropriate unit prices when installing new stations, and provides data for price negotiations. It also recognizes user emotions and responds adaptively to provide a better user experience.

[1726] The processing flow will be explained below.

[1727] Step 1:

[1728] Users input their electricity rate increase request using a dedicated web form or application, specifically by entering information such as the base station location, current electricity rate, and desired rate.

[1729] Step 2:

[1730] The terminal receives the data entered by the user and performs initial validation, which checks for required fields and the data format.

[1731] Step 3:

[1732] The terminal transmits the successfully validated data to the server.

[1733] Step 4:

[1734] The server stores the received electricity rate increase request in a database, including the base station location, current electricity rate, and desired rate.

[1735] Step 5:

[1736] The server accesses the database of local power supply companies to obtain electricity rate history and market trend data for the specified area.

[1737] Step 6:

[1738] The server runs an algorithm based on the acquired data to calculate the appropriate electricity unit price, taking into account past price history, local market fluctuations, and future market forecasts.

[1739] Step 7:

[1740] The server stores the calculated fair unit price in a database and simultaneously notifies the terminal.

[1741] Step 8:

[1742] The terminal displays the appropriate unit price to the user, who then checks the appropriate electricity unit price of the base station.

[1743] Step 9:

[1744] The emotion engine analyzes the user's input data and past behavioral history to recognize the user's emotional state. For example, it extracts emotions such as "satisfied" or "dissatisfied" from text content and click patterns.

[1745] Step 10:

[1746] The terminal transmits the user's emotional state recognized by the emotion engine to the server.

[1747] Step 11:

[1748] The server tailors the notification message based on the emotional state received from the emotion engine, for example by including a message offering further information or support to a frustrated user.

[1749] Step 12:

[1750] The server then sends the adjusted notification message to the terminal and displays it to the user, who receives feedback according to their emotional state.

[1751] Step 13:

[1752] A user logs into the system and requests the data needed to negotiate a price increase.

[1753] Step 14:

[1754] The terminal transmits the user's request to the server.

[1755] Step 15:

[1756] The server extracts relevant information from the database (e.g., electricity rate data for nearby base stations, historical rate fluctuation data, and local market trend data).

[1757] Step 16:

[1758] The server formats the extracted data into visual reports, converting the data into graphs and tables.

[1759] Step 17:

[1760] The server sends the generated report to the terminal, where it is displayed to the user.

[1761] Step 18:

[1762] The terminal displays a visual report to the user, who can then use this report to negotiate discounts with the power company.

[1763] Step 19:

[1764] The server periodically collects and analyzes nationwide electricity price data, which it then runs an algorithm to generate standard index data.

[1765] Step 20:

[1766] The server packages the generated metrics data and prepares APIs and dashboards to provide to external clients.

[1767] Step 21:

[1768] External clients can use the provided APIs and dashboards to obtain standard metrics and use them to set their own prices and negotiate discounts.

[1769] Example 2

[1770] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1771] The current system has difficulty effectively registering and managing requests for electricity rate increases and quickly and accurately calculating appropriate electricity unit prices for each region. It also lacks the ability to recognize user emotions and appropriately adjust notification messages accordingly, making it difficult to improve the user experience. Furthermore, there are issues with the efficiency of providing data required for price negotiations and rate setting to external clients. A system that solves these problems is needed.

[1772] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1773] In this invention, the server includes means for registering requests for electricity rate increases, means for calculating appropriate electricity unit prices for each region, means for notifying the user and recognizing their emotional state, means for adjusting the notification message based on the emotional state, means for providing data for price negotiations, and means for providing standard index data to external clients. This makes it possible to effectively manage requests for electricity rate increases and adaptively calculate and notify appropriate unit prices, thereby improving the user experience and providing efficient data.

[1774] An "electricity bill" is the fee that ordinary households and businesses pay to electric power companies for energy consumption.

[1775] A "price increase request" refers to a user expressing to the system a request to increase the current electricity rate.

[1776] A "fair electricity unit price" is a unit price of electricity that is considered reasonable in a particular area, calculated based on market trends and past price history.

[1777] "User" refers to an individual or corporation that uses the system to manage electricity charges or request rate increases.

[1778] An "emotion engine" is a system component that analyzes a user's input and behavioral history and recognizes their emotional state (e.g., satisfaction, dissatisfaction, excitement, etc.).

[1779] A "notification message" is an information message sent from the system to the user, and includes information such as the appropriate unit price and system update information.

[1780] "Discount negotiation data" refers to relevant information required when a user negotiates a discount with an electric power company.

[1781] "Standard index data" is reference data that indicates pricing and market trends, generated by analyzing electricity rate data nationwide.

[1782] "External Client" means a third-party individual or entity that uses standard indicator data provided by the System.

[1783] A "database" refers to data storage that regularly stores and manages information within a system.

[1784] "Validation" is the process of checking the accuracy and validity of entered data.

[1785] An "algorithm" is a set of computational steps that a system executes to solve a particular problem.

[1786] "API" refers to an interface that allows a system to exchange data with external clients.

[1787] A "dashboard" is a user interface that visually displays system usage status and important indicators.

[1788] A "visual report" is a report that organizes data in a visually easy-to-understand manner in the form of graphs, charts, etc.

[1789] The present invention is an integrated system that registers requests for electricity rate increases, calculates appropriate unit prices for each region, and provides data that can be used in price negotiations, and is combined with an emotion engine that recognizes user emotions. Detailed embodiments of the present invention are described below.

[1790] System Configuration

[1791] The system consists of the following main components:

[1792] 1. User terminal: A device on which a user inputs information and checks related data. Examples include smartphones, tablets, and PCs.

[1793] 2. Server: A central computing device that processes, stores, and analyzes data. In this invention, a high-performance cloud server is recommended.

[1794] 3. Database: This is data storage for saving electricity rate information, request information, historical data, fair unit prices, etc. For example, a database management system such as MySQL or PostgreSQL is used.

[1795] 4. Emotion engine: A system that analyzes user input data and recognizes the user's emotions. Specifically, it uses emotion analysis software that uses natural language processing (NLP) technology.

[1796] Program Processing Overview

[1797] The system has the following main processing functions:

[1798] Registering a request for an increase in electricity rates

[1799] The user uses a terminal to input the required information (e.g., base station location, current electricity rate, desired rate) into a web form or application. This information is first validated by the terminal and then sent to the server. The server registers the received data in a database, enabling request management.

[1800] Calculation of appropriate unit prices for each region

[1801] The server accesses the database of each local power supplier to obtain electricity rate history and market trend data for the specified area. The obtained data is analyzed within the server using an algorithm to calculate the appropriate unit price, and the calculation results are saved in the database and updated as necessary.

[1802] User Notifications and Emotion Recognition

[1803] Once the calculation of the appropriate unit price is complete, the server notifies the terminal of the result, which is displayed to the user. Furthermore, at this time, the emotion engine analyzes the user's input data (e.g., text input content and past behavioral history) and recognizes the user's emotional state (e.g., satisfaction, dissatisfaction, excitement, etc.). Based on the recognized emotion, the server adjusts the wording of the notification message and provides adaptive feedback to the user.

[1804] Providing data for price negotiations

[1805] A user logs into the system and requests the data needed to negotiate a price increase. The device forwards this request to the server, which extracts relevant information from the database (e.g., electricity rates for nearby base stations, historical price fluctuations, and local market trends) and generates a visual report. This report is sent to the device and displayed to the user.

[1806] Providing standard metrics data to external clients

[1807] The server collects electricity bill data from across the country and periodically analyzes it. It then runs the applied algorithms to generate standard index data. This data is packaged and provided to external clients via APIs and dashboards. External clients can use the provided data to set their own rates and negotiate discounts.

[1808] Specific examples

[1809] For example, suppose a base station owner in one of Tokyo's 23 wards inputs a request through the system saying, "I would like to raise my current electricity rate from 3,000 yen / month to 5,000 yen / month." This information is validated on the terminal, then sent to the server and registered in the database.

[1810] Next, the server retrieves data from electricity suppliers in Tokyo's 23 wards and calculates the appropriate unit price based on past price history and market trends. In this case, the appropriate unit price of 4,500 yen / month is calculated and notified to the user.

[1811] Furthermore, the emotion engine analyzes the user's input and recognizes emotions such as "I'm dissatisfied with the results." Based on the recognized emotion, the server adjusts the notification message to "We will propose a more optimal plan to bring you closer to your needs," and displays it to the user.

[1812] Prompt Sentence Examples

[1813] An example of a prompt to input to a generative AI model is as follows:

[1814] "As a base station owner within Tokyo's 23 wards, I would like to raise my current electricity bill from 3,000 yen / month to 5,000 yen / month. Please calculate the appropriate electricity unit price and provide data for price negotiation based on the results. Also, please create a system that recognizes user emotions and provides adaptive feedback."

[1815] Using this prompt, the generative AI model can understand the specific instructions and generate an appropriate response.

[1816] The system of the present invention effectively manages requests for electricity rate increases, supports calculation of appropriate unit prices for new base stations, and provides data for price negotiations. Furthermore, it can provide a better user experience by recognizing user emotions and responding adaptively.

[1817] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1818] Step 1:

[1819] The user enters a request

[1820] The user uses the terminal to input the required information (e.g., base station location, current electricity price, desired price) into the web form or application. The input data is entered in the following format:

[1821] Input: Base station location (e.g., "Shinagawa-ku, Tokyo"), current electricity rate (e.g., "3,000 yen / month"), desired rate (e.g., "5,000 yen / month")

[1822] When the terminal receives this, it formats the data internally and proceeds to the next step.

[1823] Step 2:

[1824] The terminal validates the data

[1825] The terminal validates the input data, specifically performing the following data manipulations and calculations:

[1826] Check whether the base station location is in a real area (e.g., verify whether "Shinagawa Ward, Tokyo" is a valid area).

[1827] Check that your current electricity rate and desired rate are numerical values.

[1828] Input: Information entered by the user

[1829] Output: Valid data (e.g., "Shinagawa-ku, Tokyo", "3000 yen / month", "5000 yen / month")

[1830] If the validation is successful, the terminal transmits the data to the server.

[1831] Step 3:

[1832] The server receives the data and registers it in the database

[1833] The server receives the data sent from the device. The received data is stored in the following format:

[1834] Input: Valid data from the device (e.g., "Shinagawa-ku, Tokyo", "3000 yen / month", "5000 yen / month")

[1835] The server registers this in a database, enabling request management.

[1836] Output: Add a new record to the database (e.g., add the current electricity rate and desired rate to the "Shinagawa Ward, Tokyo" field)

[1837] Step 4:

[1838] The server obtains data to calculate the appropriate unit price for each region.

[1839] The server accesses the power supplier's database to obtain electricity rate history and market trend data for the specified area.

[1840] Input: Area information (e.g. "Shinagawa-ku, Tokyo")

[1841] Output: Electricity rate history by region, market trend data (e.g., "Price history for the past year", "Market trend data")

[1842] The acquired data is used in the next step.

[1843] Step 5:

[1844] The server calculates the appropriate unit price

[1845] The server uses the acquired data to apply an algorithm to calculate the appropriate unit price for each region. Specifically, the following data calculations are performed:

[1846] Calculate the average price from past price history

[1847] Applying predictive models based on market trend data

[1848] Input: Electricity rate history by region, market trend data

[1849] Output: Fair price (e.g. "4500 yen / month")

[1850] The calculation results are stored in a database.

[1851] Step 6:

[1852] The server notifies the device of the results, and the emotion engine recognizes the user's emotions.

[1853] The server notifies the terminal of the calculated fair price and displays it to the user. Based on the displayed result, the emotion engine analyzes the user's input data (e.g., text input content and past behavior history) and recognizes the user's emotional state.

[1854] Input: Fair unit price result (e.g. "4500 yen / month"), user input data

[1855] Output: User's emotional state (e.g. "unhappy")

[1856] The result of the fair unit price being fair will evoke feelings of satisfaction, dissatisfaction, excitement, etc. in the user.

[1857] Step 7:

[1858] The server adjusts notification messages based on emotional state.

[1859] The server adjusts the notification message based on the recognized emotion and provides adaptive feedback to the user. Specifically, it works as follows:

[1860] Select an appropriate feedback message from templates stored on the server for the recognized emotion (e.g., "unhappy").

[1861] Input: User's emotional state

[1862] Output: Optimized notification message (e.g. "We will propose a more optimal plan to meet your needs")

[1863] This provides feedback according to the user's emotions.

[1864] Step 8:

[1865] The user requests data for price negotiation, and the server generates and serves the report.

[1866] Users log into the system and request the data they need to negotiate a price increase. The device forwards this request to the server, which extracts the relevant information from the database and generates a visual report.

[1867] Input: User request (e.g. "Request for price negotiation data")

[1868] Output: Visual report (e.g. "PDF report")

[1869] The report is sent to the terminal and displayed to the user.

[1870] Step 9:

[1871] The server collects and analyzes electricity rate data nationwide to provide standard index data.

[1872] The server periodically collects electricity bill data from across the country and applies algorithms to generate standard index data, which is then provided to external clients via APIs and dashboards.

[1873] Input: Nationwide electricity rate data

[1874] Output: Standard indicator data (e.g., "national average, standard deviation")

[1875] External clients can use this information to set their own prices and negotiate discounts.

[1876] Through these steps, the system can improve the user experience while efficiently managing requests for electricity rate increases and providing data for calculating fair unit prices and negotiating discounts.

[1877] (Application example 2)

[1878] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1879] Conventional electricity rate management systems lack the ability to respond to user needs with detailed consideration, making it difficult to improve user satisfaction. Furthermore, it is difficult to provide the appropriate data required for price negotiations, resulting in a low success rate for negotiations. The present invention aims to solve these problems and support improved user satisfaction and efficient price negotiations.

[1880] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1881] In this invention, the server includes a means for registering requests for an increase in electricity rates, a means for calculating appropriate electricity unit prices for each region, a means for notifying the user of the appropriate electricity unit price, a means for recognizing the user's emotions and adjusting the notification message, and a means for generating a visual report including nearby prices and trend information during price negotiations. This enables a detailed response that takes the user's emotions into consideration, improves the success rate of negotiations, and increases user satisfaction.

[1882] The "means for registering a request for an increase in electricity rates" is a function that allows a user to input a request for an increase in electricity rates into the system and register that information in the database.

[1883] The "means for calculating appropriate electricity unit prices for each region" is a function that calculates appropriate electricity unit prices based on past price history and market trend data in a specific region.

[1884] The "means for notifying the user of the appropriate electricity unit price" is a function for notifying the user of the calculated appropriate electricity unit price.

[1885] The "means for providing data for price negotiation" is a function for providing relevant data necessary when a user negotiates a price.

[1886] The "means for recognizing the user's emotions and adjusting the notification message" is a function that uses an emotion engine to analyze the user's emotions and adaptively adjusts the notification message in accordance with those emotions.

[1887] "Means for generating visual reports including nearby price and trend information during price negotiations" refers to a function for generating reports that visually display nearby prices and market trend information to assist in negotiations.

[1888] "Means for providing standard index data to external clients" refers to a function for collecting and analyzing nationwide electricity rate data, generating standard indexes, and providing them to external clients.

[1889] The "means for managing requests for an increase in electricity rates and storing the same in a database" is a function for efficiently managing requests for an increase in electricity rates from users and storing the data in a database.

[1890] "Means for automatically calculating appropriate unit prices based on past rate history and market fluctuation data" is a function that automatically calculates appropriate electricity unit prices based on past electricity rate history and market fluctuation data.

[1891] "Means for recognizing emotions by analyzing user input data and past behavioral history" is a function for analyzing and recognizing emotions based on user input data and past behavioral history.

[1892] "Means for extracting relevant data in response to a user request and providing it as a visual report" refers to a function that extracts necessary data in response to a user request and provides that data as a visually displayed report.

[1893] "Means for collecting and analyzing electricity rate data nationwide" is a function for analyzing electricity rate data collected from across the country.

[1894] The "means for executing an algorithm for generating a standard index" is a function ...

Claims

1. A means for registering requests for an increase in electricity rates; A means for calculating appropriate electricity unit prices for each region; a means for notifying a user of a fair electricity rate; a means for providing data for price negotiation; a means of providing standard metrics data to external clients; A system including:

2. a means for managing requests for electricity rate increases and storing them in a database; A method to automatically calculate the appropriate unit price based on past fee history and market fluctuation data, A means for extracting relevant data and providing it as a visual report upon user request; The system of claim 1 , comprising:

3. A means of collecting and analyzing nationwide electricity price data; means for executing an algorithm for generating standard indicators; A means to provide APIs and dashboards to provide metrics data to external clients, The system of claim 1 , comprising:

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