system

Abstract

Provide a system. A method for acquiring power usage data from a user; A means for externally obtaining real-time electricity market data; a means for generating an optimal electricity procurement plan based on the electricity usage data and the electricity market data using an AI algorithm; a means for presenting the generated optimal power procurement plan to a user; means for automatically processing an electricity supply contract based on a user selection; 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] In the past, in order for households and businesses to optimally procure electricity, they needed specialized knowledge of electricity market data analysis and contract procedures. This meant that efficiency and cost reductions in electricity procurement were not sufficiently achieved, and the use of environmentally friendly energy sources was not promoted. Another problem was that the procedures for signing electricity supply contracts were complicated, placing a heavy burden on users. [Means for solving the problem]

[0005] The present invention provides a system that acquires electricity usage data from users and electricity market data from external sources in real time. It then uses an AI algorithm to generate an optimal electricity procurement plan based on this data and presents the generated plan to the user. Furthermore, by automatically completing the electricity supply contract based on the user's selection, it becomes possible to procure electricity efficiently and environmentally without the need for specialized knowledge. Furthermore, by using a web interface or application, users can intuitively operate the system, reducing the burden of the contract procedure.

[0006] "User" refers to a household or business that intends to use the system to procure electricity.

[0007] "Power usage data" refers to information that indicates the user's past power consumption history.

[0008] "Electricity market data" refers to information showing real-time trading prices and supply status of electricity.

[0009] "AI algorithm" refers to a program that uses artificial intelligence to perform data analysis and optimization calculations.

[0010] "Power Procurement Plan" means a specific proposal for obtaining electricity in the most efficient and environmentally responsible manner.

[0011] The "presentation means" refers to an interface for notifying or displaying the generated power procurement plan to the user.

[0012] "Electricity Supply Agreement" means an agreement for the supply of electricity between a User and an Electricity Supplier.

[0013] "Automatic procedure" refers to the process by which the system automatically processes the electricity supply contract based on the user's selection.

[0014] "Web Interface" refers to the web page for operating the system over the Internet.

[0015] "Application" refers to software that runs on a smartphone or tablet and provides system functions. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] The present invention describes a system that allows users to optimally procure power without having specialized knowledge. Specific programs and processing flows for implementing this system are described below.

[0038] The system begins with the user providing their own electricity consumption data. The user registers for the first time by accessing the system's website or application and entering the required information. After completing registration, the user uploads their electricity usage data to the system. This includes past electricity consumption history data and data provided by the power company.

[0039] The server acquires the electricity consumption data provided by the user and stores it in a database. The stored data is then analyzed by an analysis module on the server. Specifically, the analysis is performed to identify the average and peak times of the user's electricity consumption, as well as seasonal variations.

[0040] The server then uses the appropriate external API to obtain real-time price information from external electricity markets. Through this external API, real-time electricity market prices and renewable energy supplier data are obtained. The obtained market data is also stored in the database.

[0041] The server then runs an AI algorithm to generate an optimal electricity procurement plan based on the electricity consumption data and market data. The algorithm aims to minimize costs and maximize the proportion of renewable energy. The generated plan is displayed to the user through an interface (web interface or application).

[0042] The user selects the most suitable electricity procurement plan from among several options presented by the server. Based on the selected plan, the server automatically executes procedures and transmits the necessary information and documents to complete the contract with the electricity supplier. This process allows the user to complete the complex contract procedure hassle-free.

[0043] As a concrete example, in a household scenario, a user who moves into a new home uploads their electricity consumption data from the past year to the system. The server then retrieves market data, and an AI algorithm generates a plan that uses more than 50% renewable energy and reduces annual costs by 5%. The user then selects this plan, and the server automatically completes the contract process with the electricity supplier.

[0044] In a business scenario, a company uploads three years of electricity usage data, and the AI ​​algorithm generates a plan to increase electricity usage at night and maximize solar power generation. Once the company selects this plan, the server automatically processes contracts with the electricity supplier and makes any necessary adjustments.

[0045] As described above, the present invention provides a specific embodiment for realizing optimal power procurement based on trends in the power market, even if the user does not have specialized knowledge. This enables efficient and environmentally friendly power procurement.

[0046] The processing flow will be explained below.

[0047] Step 1:

[0048] The user opens a website or application on the system.

[0049] Step 2:

[0050] When a user registers for the first time, they must enter basic information such as their name, address, contact details, and email address.

[0051] Step 3:

[0052] The server stores the information entered by the user in a database and sends a confirmation email containing a link to verify the account.

[0053] Step 4:

[0054] The user clicks on the authentication link to activate the account.

[0055] Step 5:

[0056] Users log in to the system and upload their own electricity usage history data, or link their account information with a specific power company.

[0057] Step 6:

[0058] The server acquires the power usage data provided by the user and stores it in a database.

[0059] Step 7:

[0060] The server runs a data analysis module to analyze the electricity usage data, and the analysis results include information such as average consumption, peak hours, and seasonal variations.

[0061] Step 8:

[0062] The server obtains real-time electricity market price data and renewable energy supplier data through external APIs.

[0063] Step 9:

[0064] The server stores the acquired electricity market data in a database.

[0065] Step 10:

[0066] The server runs an AI algorithm to generate an optimal electricity procurement plan based on the user's electricity usage data and market data.

[0067] Step 11:

[0068] The server presents the generated electricity procurement plan to the user via a web interface or application.

[0069] Step 12:

[0070] The user selects the most suitable plan from the multiple plans presented.

[0071] Step 13:

[0072] The server initiates an automated procedure for signing a contract for electricity supply based on the user's selection.

[0073] Step 14:

[0074] The server sends the necessary information and documents to the electricity supplier to complete the contract process.

[0075] Step 15:

[0076] The server notifies the user that the contract has been completed and provides monitoring information for future power usage.

[0077] Example 1

[0078] 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."

[0079] In today's electricity market, consumers need a great deal of specialized knowledge and time to choose the optimal electricity procurement method. It is also difficult to grasp fluctuations in electricity market prices and supply in real time, making it difficult to use electricity efficiently and reduce costs. For this reason, there is a need for a method that allows consumers to procure electricity efficiently, even without specialized knowledge.

[0080] 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.

[0081] In this invention, the server includes: means for acquiring electricity usage data from a user; means for externally acquiring electricity market data in real time; means for generating an optimal electricity procurement plan based on the electricity usage data and the electricity market data using an AI algorithm; means for presenting the generated optimal electricity procurement plan to the user; means for automatically processing an electricity supply contract based on the user's selection; means for storing the electricity usage data and the electricity market data in a database; means for using an analysis module to calculate average electricity consumption, peak hours, and seasonal fluctuations; and means for displaying the optimal electricity procurement plan to the user using a web interface or application, thereby enabling consumers to procure electricity efficiently and optimally without specialized knowledge.

[0082] "User" refers to an individual or company that uses this system to procure electricity.

[0083] "Electricity usage data" refers to historical information about the amount of electricity consumed by a user, including consumption by date and time, peak usage, seasonal variations, and the like.

[0084] "Electricity market data" refers to data obtained from external sources, such as real-time fluctuating electricity market prices and supply status, and renewable energy supply information.

[0085] "AI algorithm" refers to a calculation method that uses artificial intelligence technology to analyze data and generate optimal electricity procurement plans.

[0086] "Power Procurement Plan" refers to a plan that indicates the most cost-effective and environmentally friendly method of procuring electricity based on the user's electricity usage trends and market data.

[0087] "Database" refers to a storage device for organizing and centrally managing acquired and analyzed data.

[0088] "Analysis Module" means a software component used to calculate and analyze electricity usage data to identify average consumption, peak hours, and seasonal variations.

[0089] "Web Interface" refers to a screen display that utilizes web technology to allow a user to access a system via the Internet and input and retrieve information.

[0090] An "application" is software that runs on devices such as smartphones and tablets, and refers to the interface that allows users to access and operate the system.

[0091] The present invention provides a system that allows users to optimally procure power without having specialized knowledge. A specific program for implementing this system and its processing flow will be described below.

[0092] This system begins with the user providing their own electricity consumption data. The user registers for the first time by accessing the system's website or application and entering the required information. After completing registration, the user uploads their electricity usage data to the system. This includes past electricity consumption history data and data provided by the power company. The data uploaded by the user is in CSV format, for example.

[0093] The server acquires the electricity consumption data provided by the user and stores it in a database. The stored data is then analyzed by an analysis module on the server. Specifically, analysis is performed to identify the average and peak times of the user's electricity consumption, as well as seasonal fluctuations. This analysis is performed using analysis libraries such as Python's pandas and numpy.

[0094] The server then uses an appropriate external API to retrieve real-time price information from external electricity markets. Through this external API, real-time electricity market prices and renewable energy supplier data are retrieved. For example, the Open Energy API is used. The retrieved market data is also stored in a database.

[0095] The server then launches an AI algorithm to generate an optimal power procurement plan based on power consumption data and market data. The algorithm aims to minimize costs and maximize the proportion of renewable energy. Generative AI models such as TENSORFLOW (registered trademark) and PyTorch are used to build the AI ​​algorithm. The generated plan is presented to the user, who can view it on their screen via a web interface or application.

[0096] The user selects the most suitable electricity procurement plan from among several options presented by the server. Based on the selected plan, the server automatically executes procedures and transmits the necessary information and documents to complete the contract with the electricity supplier. This process allows the user to complete the complex contract procedure hassle-free.

[0097] As a concrete example, in a household scenario, a user who moves into a new home uploads their electricity consumption data from the past year to the system. The server then retrieves market data, and an AI algorithm generates a plan that uses more than 50% renewable energy and reduces annual costs by 5%. The user selects this plan, and the server automatically completes the contract process with the electricity supplier.

[0098] In a business scenario, a company uploads three years of electricity usage data, and the AI ​​algorithm generates a plan to increase electricity usage at night and maximize solar power generation. Once the company selects this plan, the server automatically processes contracts with the electricity supplier and makes any necessary adjustments.

[0099] Below is an example of a prompt sentence to input to the generative AI model.

[0100] "I have uploaded my electricity usage data for the past year. Based on this, please generate a plan that minimizes annual costs while achieving a renewable energy usage rate of 50% or more."

[0101] "Generate a plan to increase nighttime electricity use and maximize solar power generation based on the company's electricity usage data for the past three years."

[0102] The present invention enables users to realize optimal power procurement based on trends in the power market without requiring specialized knowledge, thereby enabling efficient and environmentally friendly power procurement.

[0103] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0104] Step 1:

[0105] First time registration and login

[0106] Input: The user enters their first-time registration information, such as their name, email address, and password.

[0107] Server operation: The server receives the entered information, stores the new user information in the database, and automatically sends a confirmation email to the user upon registration completion.

[0108] Output: The server displays a registration success message to the user.

[0109] Step 2:

[0110] Uploading electricity usage data

[0111] Input: User uploads electricity usage data (e.g. electricity consumption data for the past year) in CSV format.

[0112] Server operation: The server receives the uploaded CSV file, checks the format and integrity of the data, and stores the data in the database if there are no errors.

[0113] Output: The server displays the message "Power usage data successfully saved" to the user.

[0114] Step 3:

[0115] Analysis of power consumption data

[0116] Input: User electricity usage data stored in the database.

[0117] Server operation: The server uses analysis modules (Python's pandas and numpy) to calculate average electricity consumption, peak hours, and seasonal fluctuations.

[0118] Output: Analyzed power consumption data based on the analysis results.

[0119] Step 4:

[0120] Obtaining Market Data

[0121] Input: Access information to an external API (e.g., the Open Energy API endpoint).

[0122] Server operation: The server calls external APIs to obtain real-time electricity market data, including market prices, renewable energy supply information, etc.

[0123] Output: Store the obtained market data in a database.

[0124] Step 5:

[0125] Launching AI algorithms

[0126] Input: Parsed electricity consumption data and market data.

[0127] Server operation: The server runs an AI algorithm using TensorFlow and PyTorch to generate an optimal electricity procurement plan based on this data. The algorithm aims to minimize costs and maximize the use of renewable energy.

[0128] Output: Save the generated electricity procurement plan in the database.

[0129] Step 6:

[0130] Presenting the plan

[0131] Input: The generated optimal power procurement plan.

[0132] Server operation: The server presents the plan to the user's screen through a web interface or application, where the user can view the presented plan.

[0133] Output: The plan details are displayed to the user.

[0134] Step 7:

[0135] Select and confirm your plan

[0136] Input: The electricity procurement plan selected by the user.

[0137] User action: The user compares the plans presented on the screen, selects the best plan, and clicks the "Confirm" button for the selected plan.

[0138] Output: The user's selection is sent to the server.

[0139] Step 8:

[0140] Executing automated procedures

[0141] Input: Information about the plan selected by the user.

[0142] Server operation: The server automatically sends the necessary information and documents to the electricity supplier and proceeds with the contract procedure.

[0143] Output: The contract process is tracked and the user is notified upon completion, and any related documentation is provided to the user.

[0144] (Application example 1)

[0145] 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."

[0146] In conventional autonomous vehicle operation management, power procurement plans to optimize power consumption and reduce costs must be created manually, placing a heavy burden on operation managers. Additionally, a lack of specialized knowledge about fluctuations in the power market and the use of renewable energy makes it difficult to optimally procure power.

[0147] 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.

[0148] In this invention, the server includes: means for acquiring power usage data from a user; means for externally acquiring power market data in real time; means for generating an optimal power procurement plan based on the power usage data and the power market data using an AI algorithm; means for presenting the generated optimal power procurement plan to the user; means for automatically processing a power supply contract based on a user selection; means for analyzing power consumption data and market data and presenting multiple power procurement plans to an autonomous vehicle operations manager; means for automatically processing a contract with a power supplier based on a plan selected by the operations manager; and means for managing power consumption data of multiple autonomous vehicles, presenting the optimized power procurement plan to the operations manager via a head-mounted display, and automatically processing a contract based on the selected plan. This enables an operations manager to procure power efficiently and environmentally friendly, even without specialized knowledge.

[0149] A "user" is an individual or company that uses the system to procure electricity.

[0150] "Power usage data" is information about the amount of power consumed by the user in the past, such as power consumption, time periods when power was used, and seasonal variations.

[0151] "Electricity Market Data" means electricity market price information and renewable energy supplier data obtained in real time.

[0152] "AI algorithm" is an artificial intelligence technology that analyzes electricity usage data and electricity market data to generate optimal electricity procurement plans.

[0153] The "Power Procurement Plan" is a proposed power supply contract that aims to reduce costs and maximize the use of renewable energy based on power consumption and electricity market trends.

[0154] "Operator" means an individual or organization responsible for the management and operation of an automated vehicle.

[0155] A "head-mounted display" is a display device that is worn on the head and provides visual information to the user.

[0156] An "electricity supplier" is a company or organization that supplies electricity to users.

[0157] The "contract procedure" refers to a series of procedures for concluding a contract with an electricity supplier based on the electricity procurement plan selected by the user.

[0158] This invention details a system that allows a user to optimally procure power without having specialized knowledge.

[0159] System Overview

[0160] This system collects electricity usage data from users, combines it with electricity market data obtained in real time from external sources, and uses AI algorithms to generate an optimal electricity procurement plan. The generated plan is provided through an interface such as a head-mounted display (HMD), and the system automatically processes electricity supply contracts based on the plan selected by the user.

[0161] Program processing

[0162] The system server performs the following process.

[0163] First, users upload their electricity usage data to the system from their devices. The data includes historical electricity consumption data. The data is processed using the pandas library and stored in a database.

[0164] The server then uses an external API to retrieve real-time electricity market data using the requests library, which is also stored in a database.

[0165] The server analyzes the data using AI algorithms such as the RandomForestRegressor from the sklearn library based on electricity usage data and market data. This analysis identifies average, peak, and seasonal fluctuations in the user's electricity consumption. Based on this information, multiple electricity procurement plans are generated that maximize cost savings and renewable energy use.

[0166] The generated plans are presented to the dispatcher for review through the HMD. The dispatcher can then select one of the plans presented, and the contract procedure with the power supplier will be automatically carried out based on the selected plan. This procedure again uses the requests library.

[0167] Specific example explanation

[0168] For example, suppose a user uploads the past year's historical power consumption data for multiple newly introduced autonomous vehicles to the system. The system stores the data, analyzes it, and obtains the latest power market data from an external API. An AI algorithm processes the data and generates plans such as "a plan to use more than 60% renewable energy and reduce annual operating costs by 10%" or "a night plan to avoid peak power charges." The fleet manager reviews these plans through the HMD and selects the most appropriate one. Based on the selected plan, the server automatically processes the contract with the power supplier.

[0169] In this way, users can procure electricity efficiently and in an environmentally friendly manner, even if they do not have specialized knowledge.

[0170] Prompt Sentence Examples

[0171] Below is an example of a prompt sentence to input to the generative AI model.

[0172] Using the past year's worth of power consumption data from autonomous vehicles and real-time electricity market information, generate and present an optimal power procurement plan that maximizes renewable energy utilization while minimizing costs.

[0173] The above is an embodiment of the present invention.

[0174] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0175] Step 1:

[0176] Users access the system using a terminal and upload their past electricity consumption history data. The input is a CSV format electricity consumption history data file, which is sent to the system. The server receives this, reads the data using the pandas library, and saves it in a database. The output is formatted electricity consumption data.

[0177] Step 2:

[0178] The server uses an external API to obtain real-time electricity market data. The input is the endpoint URL of the external API. The server uses the requests library to send API requests and receive market data. This data is returned in JSON format, which is converted into a data frame using the pandas library and stored in a database. The output is the formatted market data.

[0179] Step 3:

[0180] The server analyzes the user's electricity consumption data and market data. The input is the electricity consumption data obtained in step 1 and the market data obtained in step 2. The server scales the data using StandardScaler from the sklearn library, and generates an optimal electricity procurement plan using an AI algorithm that uses RandomForestRegressor. Data analysis includes time series analysis of electricity consumption and analysis of market price fluctuations. The output is the multiple electricity procurement plans generated.

[0181] Step 4:

[0182] The generated power procurement plan is presented to the dispatcher. The input is the plan generated in step 3. The server processes it and presents it through a user interface such as a head-mounted display (HMD). Specifically, when the dispatcher puts on the HMD, a display is displayed that allows the dispatcher to visually check multiple plans. The output is information that the dispatcher can check and select.

[0183] Step 5:

[0184] The dispatcher selects the optimal plan through the HMD. The input is the plan presented in step 4 and the dispatcher's selection information. The dispatcher's selection is sent to the server through the HMD interface. The output is the selection information of the optimal power procurement plan.

[0185] Step 6:

[0186] The server automatically completes the contract procedure with the electricity supplier based on the plan selected by the dispatcher. The input is the plan information selected in step 5. The server uses the requests library to send a request to the contract procedure API and provides the necessary contract information. The output is a contract confirmation notification, which is also sent to the dispatcher.

[0187] This process allows users to procure electricity efficiently and in an environmentally friendly manner, even without specialized knowledge, and can significantly reduce the burden on operation managers.

[0188] 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.

[0189] The present invention combines a system that enables users to optimally procure electricity without specialized knowledge with an emotion engine that recognizes the user's emotions. This improves the user experience and supports the selection of the optimal electricity procurement plan. The specific programs and processing flow for implementing this system are described below.

[0190] The system begins with the user providing their own electricity consumption data. The user accesses the system's website or application and enters the required information to register for the first time. After registration, the user uploads their electricity usage history data to the system. This electricity usage data includes past electricity consumption history and data provided by the electric power company.

[0191] The server acquires the electricity consumption data provided by the user and stores it in a database. The stored data is analyzed by an analysis module on the server. The analysis results include the average electricity consumption of the user, peak hours, and seasonal fluctuations. Next, the server uses an appropriate external API to obtain real-time price information from the external electricity market. Through the external API, real-time electricity market prices and renewable energy supplier data are obtained. This market data is also stored in the database.

[0192] The server then runs an AI algorithm to generate an optimal electricity procurement plan based on electricity consumption data and market data, with the goal of minimizing costs and maximizing the share of renewable energy.

[0193] This system also incorporates an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's emotional state based on their voice, facial expressions, and text input. The server uses the emotion engine to confirm the user's emotional state and adaptively presents an electricity procurement plan based on that information.

[0194] For example, if a user is feeling stressed, the emotion engine will detect this and the server will make suggestions to reduce stress. Similarly, if the user is happy, the server will suggest plans to actively use renewable energy. The plans generated in this way are presented to the user via a web interface or application via the server.

[0195] The user selects the most suitable electricity procurement plan from the multiple plans presented. Based on the selected plan, the server automatically executes the procedure and sends the necessary information and documents to complete the contract with the electricity supplier. This process allows the user to complete the complicated contract procedure hassle-free.

[0196] As a concrete example, in a household scenario, a user uploads their electricity consumption data from the past year to the system. The server then retrieves market data and uses AI algorithms and an emotion engine to generate a plan that uses more than 50% renewable energy and reduces annual costs by 5%. Next, if the user is feeling emotionally stressed, the server uses that information to present a plan that provides a sense of security.

[0197] In a business scenario, a company uploads three years of electricity usage data, and the AI ​​algorithm generates a plan that increases nighttime electricity usage and maximizes solar power generation. When selecting this plan, the emotion engine checks whether the company representative is emotionally satisfied and makes recommendations that will result in the highest satisfaction.

[0198] As described above, the present invention provides a specific embodiment for improving the user experience and realizing efficient and environmentally friendly power procurement by combining an emotion engine.

[0199] The processing flow will be explained below.

[0200] Step 1:

[0201] The user opens a website or application on the system.

[0202] Step 2:

[0203] When a user registers for the first time, they must enter basic information such as their name, address, contact details, and email address.

[0204] Step 3:

[0205] The server stores the information entered by the user in a database and sends a confirmation email containing a link to verify the account.

[0206] Step 4:

[0207] The user clicks on the authentication link to activate the account.

[0208] Step 5:

[0209] Users log in to the system and upload their own electricity usage history data, or link their account information with a specific power company.

[0210] Step 6:

[0211] The server acquires the power usage data provided by the user and stores it in a database.

[0212] Step 7:

[0213] The server runs a data analysis module to analyze the electricity usage data, and the analysis results include information such as average consumption, peak hours, and seasonal variations.

[0214] Step 8:

[0215] The server obtains real-time electricity market price data and renewable energy supplier data through external APIs.

[0216] Step 9:

[0217] The server stores the acquired electricity market data in a database.

[0218] Step 10:

[0219] The server runs an AI algorithm to generate an optimal electricity procurement plan based on the user's electricity usage data and market data.

[0220] Step 11:

[0221] The server activates an emotion engine and analyzes the user's emotional state based on their voice, facial expressions, text input, etc.

[0222] Step 12:

[0223] The server selects an optimal power procurement plan based on the user's emotional state and presents the plan to the user.

[0224] Step 13:

[0225] The user selects the most suitable plan from the multiple plans presented.

[0226] Step 14:

[0227] The server initiates an automated procedure for signing a contract for electricity supply based on the user's selection.

[0228] Step 15:

[0229] The server sends the necessary information and documents to the electricity supplier to complete the contract process.

[0230] Step 16:

[0231] The server notifies the user that the contract has been completed and provides monitoring information for future power usage.

[0232] Example 2

[0233] 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."

[0234] Conventional power procurement systems make it difficult for users without specialized knowledge to optimally procure power. Other issues include a lack of real-time information to respond quickly to fluctuations in the power market, and a lack of proposals that take into account the user's feelings. It is particularly difficult to propose plans that provide a sense of security to users who are feeling stressed.

[0235] 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.

[0236] In this invention, the server includes means for acquiring electricity usage data from a user, means for externally acquiring electricity market data in real time, means for generating an optimal electricity procurement plan based on the electricity usage data and the electricity market data using an AI algorithm, means for presenting the generated optimal electricity procurement plan to the user, means for adaptively presenting an electricity procurement plan based on the user's emotional state using an emotion engine that recognizes the user's emotional state, and means for automatically completing an electricity supply contract based on the user's selection. This enables a user to procure electricity optimally in response to fluctuations in the electricity market without requiring specialized knowledge, and further improves the user experience by providing suggestions that take emotions into consideration.

[0237] "Power usage data" refers to information about the amount of power consumed by a user in the past, including hourly consumption and peak consumption.

[0238] "Electricity Market Data" means real-time pricing and supplier information obtained from external electricity markets.

[0239] "AI algorithm" refers to a calculation method that uses artificial intelligence technology to perform complex data analysis and predictions, and in this system it is used to generate optimal electricity procurement plans.

[0240] An "emotion engine" is a technology that analyzes a user's emotional state based on their voice, facial expression, text input, etc., and evaluates their stress level, satisfaction level, etc.

[0241] "Power procurement plan" refers to a plan that proposes contract terms and prices for power supply that are suitable for users based on power consumption data and power market data.

[0242] "User" refers to general consumers or companies that aim to optimize their electricity procurement by using this system.

[0243] "External API" refers to an application program interface used to obtain data from external electricity markets.

[0244] "Database" refers to an information management system for storing and managing acquired and analyzed electricity usage data and electricity market data.

[0245] The present invention combines a system that enables users to optimally procure electricity without requiring specialized knowledge with an emotion engine that recognizes the user's emotions. This system is configured as follows.

[0246] First, users register for the first time using the system's website or application. This requires basic information such as name, address, and electricity company. Once registration is complete, users upload their past electricity consumption data. This data can be in CSV file format or obtained via API.

[0247] The server receives the electricity consumption data provided by the user, checks the data format and consistency, and then stores it in a database (e.g., MySQL (registered trademark)). Next, it uses a Python (registered trademark)-based data analysis module (e.g., Pandas or NumPy) to analyze the electricity consumption data and calculate monthly electricity consumption, peak hours, seasonal fluctuation trends, and other data.

[0248] The server then uses external electricity market APIs (e.g., electricity market price API, renewable energy tracker API) to obtain real-time electricity market price and supplier data, which are also stored in the database.

[0249] Based on the stored electricity consumption data and market data, the server runs an AI algorithm (e.g., a TensorFlow model) to generate an optimal electricity procurement plan. The algorithm's goal is to minimize electricity costs and maximize the proportion of renewable energy used. The generated plan includes detailed recommendations based on the expected annual cost, the proportion of renewable energy used, and the user's electricity consumption pattern.

[0250] Furthermore, the system includes an emotion engine (e.g., Microsoft® Azure® Emotion API) to recognize the user's emotional state. The device collects the user's voice recordings, facial expression captures, and text input data and uploads these data to the system.

[0251] The server selects an electricity procurement plan that best suits the user's emotional state based on the emotion-analyzed data. For example, if the user is feeling stressed, the server will present a plan that includes suggestions for stress reduction. If the user is satisfied, the server will present a plan that uses more renewable energy.

[0252] After multiple electricity procurement plans are presented, the user selects the most suitable plan. Once the selection is complete, the server automatically completes the contract procedure with the electricity supplier and sends the necessary information and documents. This procedure allows the user to complete the complicated contract procedure hassle-free.

[0253] As a concrete example, in a household scenario, a user uploads their electricity usage history from the past year to the system, and the server retrieves market data and uses AI algorithms and an emotion engine to generate a plan that uses more than 50% renewable energy and reduces annual costs by 5%. Next, if the user is feeling emotionally stressed, the server uses that information to present a plan that gives them more peace of mind.

[0254] In a business scenario, a company uploads the past three years of electricity usage data, and the server uses an AI algorithm to generate a plan that increases nighttime electricity usage and maximizes solar power generation. When selecting this plan, an emotion engine checks whether the company's representative is emotionally satisfied and makes suggestions that will increase satisfaction.

[0255] Examples of prompts include specific instructions such as, "Based on the electricity consumption data from the past year, please suggest an electricity procurement plan that uses more than 50% renewable energy and reduces annual costs by 5%. Also, if the user's emotions are detected as stressed, please suggest a plan that provides a greater sense of security."

[0256] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0257] Step 1: First-time registration

[0258] Users access the system's website or application and register by entering basic information such as name, address, and electricity company. The information is sent to the server and stored in a database, which then generates a user ID and password and starts a protected session.

[0259] Input: Name, address, power company information

[0260] Output: User ID, registration completion notification

[0261] Step 2: Upload your electricity consumption data

[0262] Users upload historical electricity consumption data to the system, including data in CSV file format or obtained via API. The server checks the format and integrity of the received electricity consumption data before storing it in the database. If the format is correct, the data is saved.

[0263] Input: Power consumption history data (CSV file, etc.)

[0264] Output: Power consumption data stored in the database, consistency check message

[0265] Step 3: Analyze power consumption data

[0266] The server performs analysis using the stored power consumption data. It uses Python-based data analysis modules (e.g., Pandas and NumPy) to calculate monthly power consumption, peak hours, seasonal trends, etc. The results of this analysis are stored in a database.

[0267] Input: Power consumption data stored in the database

[0268] Output: Analysis result data (peak hours, monthly consumption, etc.)

[0269] Step 4: Obtaining external electricity market data

[0270] The server calls external electricity market APIs (e.g., electricity market price API, renewable energy tracker API) to obtain real-time electricity market price and supplier data. The obtained market data is stored in a database.

[0271] Input: A request to an external API

[0272] Output: Electricity market data (real-time prices, supplier information, etc.), stored in a database

[0273] Step 5: Generate an optimal power procurement plan

[0274] The server runs an AI algorithm (e.g., a TensorFlow model) to generate an optimal power procurement plan based on the stored power consumption analysis data and market data, aiming to minimize costs and maximize the use of renewable energy.

[0275] Input: Power consumption analysis data, power market data

[0276] Output: Optimal power procurement plan

[0277] Step 6: Collect and analyze emotion data

[0278] The device collects the user's voice recordings, facial expression captures, and text input data, and sends this data to a server, which uses an emotion engine (e.g., Microsoft Azure Emotion API) to analyze the user's emotional state.

[0279] Input: Voice data, facial expression data, text data

[0280] Output: Analyzed emotion data (stress, satisfaction, etc.)

[0281] Step 7: Adjust and present your plan based on emotions

[0282] The server then adjusts an optimal power procurement plan based on the emotion data and presents it to the user. For example, if the user is feeling stressed, the server presents a plan that includes suggestions for reducing stress. The device then displays the plan to the user through a web interface or application.

[0283] Input: Optimal power procurement plan, emotional data

[0284] Output: Present a coordinated power procurement plan

[0285] Step 8: User plan selection and final confirmation

[0286] The user selects the most suitable plan from the multiple electricity procurement plans presented. Once the selection is complete, a confirmation screen is displayed for final confirmation.

[0287] Input: Multiple power procurement plans

[0288] Output: Selected plan, final confirmation notice

[0289] Step 9: Execute automated procedures

[0290] The server automatically completes the contract with the electricity supplier based on the selected plan, sending the necessary information and documents to complete the contract. This allows users to complete the complicated contract procedures without any hassle.

[0291] Input: Selected plan

[0292] Output: Sending contract documents, contract completion notification

[0293] (Application example 2)

[0294] 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."

[0295] The present invention relates to a system that enables users to optimally procure power without specialized knowledge. In particular, the objective is to optimize power procurement plans by taking into account the user's emotional state, thereby improving user satisfaction. Conventional systems lack a function that takes into account the user's emotional state, and therefore have the problem of not fully improving the user experience. Furthermore, factory workers also require convenience from the devices they use, so a method for efficient power management is necessary.

[0296] 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.

[0297] In this invention, the server includes means for acquiring power usage data from a user, means for externally acquiring power market data in real time, means for generating an optimal power procurement plan based on the power usage data and the power market data using an AI algorithm, means for presenting the generated optimal power procurement plan to the user, means for automatically completing a power supply contract based on the user's selection, means for analyzing the user's emotional state and reflecting it in the optimal power procurement plan, and means for displaying the optimal power procurement plan on the smart glasses, thereby supporting optimal power procurement taking user emotions into consideration and enabling people, particularly factory workers, to efficiently manage power in real time.

[0298] "User" means a person or organization that uses the System.

[0299] "Power usage data" is data regarding a user's past and current power consumption.

[0300] "Acquiring in real time" means acquiring data instantly that reflects the current situation.

[0301] "Electricity market data" refers to data relating to the market price and supply status of electricity.

[0302] An "AI algorithm" is a program that uses artificial intelligence technology to analyze data and derive optimal results.

[0303] An "optimal power procurement plan" is a power procurement plan that optimizes power consumption costs and the use of renewable energy.

[0304] "Presenting to the user" means showing the generated plan to the user.

[0305] "Automatically proceeding" means automating a manual operation without requiring user intervention.

[0306] "Emotional state" refers to the user's current psychological and emotional state.

[0307] "Smart glasses" are a wearable eyeglass-type device equipped with a display function.

[0308] The present invention provides a system that enables users to optimally procure electricity without requiring specialized knowledge, and further combines it with an emotion engine that recognizes the user's emotional state. This system aims to present optimal electricity procurement plans using smart glasses, particularly for factory workers. Specific embodiments of the system are described below.

[0309] First, the user provides their own electricity consumption data. The user accesses the system's website or application and enters the required information to register for the first time. After registration, the user uploads their electricity usage history data to the system. This includes past electricity consumption history and data provided by the power company. The user is responsible for inputting this data from their terminal.

[0310] The server retrieves the electricity consumption data provided by users and stores it in a database. The main software used here is a database management system (e.g., MySQL) and a data analysis tool (e.g., Python's NumPy library). It also uses an external API to retrieve real-time electricity market data. Real-time electricity market prices and renewable energy supplier data are retrieved through the external API. This market data is also stored in the database.

[0311] The server then runs an AI algorithm to generate an optimal electricity procurement plan based on the electricity consumption data and market data. The AI ​​algorithm aims to minimize costs and maximize the proportion of renewable energy. The AI ​​technology used includes machine learning libraries (e.g., scikit-learn).

[0312] Furthermore, this system incorporates an emotion engine to recognize the user's emotional state. The emotion engine analyzes the user's emotional state based on their voice, facial expressions, text input, etc. Specifically, it uses a facial recognition library (e.g., dlib) and a pre-trained emotion classification model (e.g., emotion_classifier.pkl). The server uses the emotion engine to identify the user's emotional state and adaptively presents an electricity procurement plan based on that information.

[0313] The user's device (smart glasses) displays the generated optimal electricity procurement plan. The smart glasses are equipped with a display function and can present the optimal plan to the user in real time. The user reviews the proposed electricity procurement plans and selects the optimal one. Based on the selected plan, the server executes an automated procedure and sends the necessary information and documents to complete the contract with the electricity supplier.

[0314] As a concrete example, consider a situation where a factory worker is working using smart glasses. The worker uploads his or her electricity usage history from the past year to the system as power consumption data. The server then retrieves market data and uses an AI algorithm and emotion engine to generate a plan that uses more than 50% renewable energy and reduces annual costs by 5%. If the worker is feeling stressed, the emotion engine detects this and the server presents a plan that provides a greater sense of security.

[0315] An example of a prompt for a generative AI model could be, "Based on my current electricity usage data and market price data, please suggest the best electricity plan for me when I'm feeling stressed."

[0316] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0317] Step 1:

[0318] Users access the system's website or application and register for the first time. At this time, users enter basic information and upload their own electricity usage history data to the system. The input data includes past electricity consumption history and data provided by the power company. This data is sent from the terminal to the server.

[0319] Step 2:

[0320] The server acquires the power consumption data provided by the user and stores it in a database. This data includes past monthly consumption amounts, daily peak consumption times, etc. The server uses a database management system to effectively manage and store this data. This data will be used for later analysis.

[0321] Step 3:

[0322] The server uses an external API to retrieve real-time electricity market data. The API calls retrieve real-time electricity market prices and renewable energy supplier data. This market data is also stored in the database. The market data is retrieved periodically, and new data is constantly updated.

[0323] Step 4:

[0324] The server runs an AI algorithm and performs data analysis based on the acquired power consumption data and market data. This analysis takes into account past consumption patterns (e.g., peak times and seasonal fluctuations) and current market prices, aiming to minimize costs and maximize the proportion of renewable energy. The results of this analysis are used to generate an optimal power procurement plan.

[0325] Step 5:

[0326] The server analyzes the user's emotional state using an emotion engine. The emotion engine detects emotions based on data such as the user's voice, facial expressions, and text input. This process utilizes a facial recognition library (e.g., dlib) and pre-trained emotion classification models. The user's emotional state (e.g., satisfaction, stress) is determined.

[0327] Step 6:

[0328] The server adaptively adjusts the optimal power procurement plan based on the user's emotional state detected by the emotion engine. For example, if the user is feeling stressed, the plan is adjusted to one that brings a sense of security. The adjusted plan is then saved back in the database.

[0329] Step 7:

[0330] The server presents the generated and adjusted optimal electricity procurement plan to the user. This information is displayed in real time on the user's smart glasses. The user can then review multiple plans on the smart glasses' display and select the optimal plan. The selection result is then sent to the server.

[0331] Step 8:

[0332] The server executes the automated procedures based on the electricity procurement plan selected by the user, including generating and sending the necessary information and documents to complete the contract with the electricity supplier. After completing the procedures, the server sends a notification message to the user's device.

[0333] 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.

[0334] 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.

[0335] 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.

[0336] [Second embodiment]

[0337] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0338] 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.

[0339] 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).

[0340] 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.

[0341] 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.

[0342] 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).

[0343] 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.

[0344] 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.

[0345] 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.

[0346] 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.

[0347] In the smart glasses 214, the 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.

[0348] 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."

[0349] The present invention describes a system that allows users to optimally procure power without having specialized knowledge. Specific programs and processing flows for implementing this system are described below.

[0350] The system begins with the user providing their own electricity consumption data. The user registers for the first time by accessing the system's website or application and entering the required information. After completing registration, the user uploads their electricity usage data to the system. This includes past electricity consumption history data and data provided by the power company.

[0351] The server acquires the electricity consumption data provided by the user and stores it in a database. The stored data is then analyzed by an analysis module on the server. Specifically, the analysis is performed to identify the average and peak times of the user's electricity consumption, as well as seasonal variations.

[0352] The server then uses the appropriate external API to obtain real-time price information from external electricity markets. Through this external API, real-time electricity market prices and renewable energy supplier data are obtained. The obtained market data is also stored in the database.

[0353] The server then runs an AI algorithm to generate an optimal electricity procurement plan based on the electricity consumption data and market data. The algorithm aims to minimize costs and maximize the proportion of renewable energy. The generated plan is displayed to the user through an interface (web interface or application).

[0354] The user selects the most suitable electricity procurement plan from among several options presented by the server. Based on the selected plan, the server automatically executes procedures and transmits the necessary information and documents to complete the contract with the electricity supplier. This process allows the user to complete the complex contract procedure hassle-free.

[0355] As a concrete example, in a household scenario, a user who moves into a new home uploads their electricity consumption data from the past year to the system. The server then retrieves market data, and an AI algorithm generates a plan that uses more than 50% renewable energy and reduces annual costs by 5%. The user then selects this plan, and the server automatically completes the contract process with the electricity supplier.

[0356] In a business scenario, a company uploads three years of electricity usage data, and the AI ​​algorithm generates a plan to increase electricity usage at night and maximize solar power generation. Once the company selects this plan, the server automatically processes contracts with the electricity supplier and makes any necessary adjustments.

[0357] As described above, the present invention provides a specific embodiment for realizing optimal power procurement based on trends in the power market, even if the user does not have specialized knowledge. This enables efficient and environmentally friendly power procurement.

[0358] The processing flow will be explained below.

[0359] Step 1:

[0360] The user opens a website or application on the system.

[0361] Step 2:

[0362] When a user registers for the first time, they must enter basic information such as their name, address, contact details, and email address.

[0363] Step 3:

[0364] The server stores the information entered by the user in a database and sends a confirmation email containing a link to verify the account.

[0365] Step 4:

[0366] The user clicks on the authentication link to activate the account.

[0367] Step 5:

[0368] Users log in to the system and upload their own electricity usage history data, or link their account information with a specific power company.

[0369] Step 6:

[0370] The server acquires the power usage data provided by the user and stores it in a database.

[0371] Step 7:

[0372] The server runs a data analysis module to analyze the electricity usage data, and the analysis results include information such as average consumption, peak hours, and seasonal variations.

[0373] Step 8:

[0374] The server obtains real-time electricity market price data and renewable energy supplier data through external APIs.

[0375] Step 9:

[0376] The server stores the acquired electricity market data in a database.

[0377] Step 10:

[0378] The server runs an AI algorithm to generate an optimal electricity procurement plan based on the user's electricity usage data and market data.

[0379] Step 11:

[0380] The server presents the generated electricity procurement plan to the user via a web interface or application.

[0381] Step 12:

[0382] The user selects the most suitable plan from the multiple plans presented.

[0383] Step 13:

[0384] The server initiates an automated procedure for signing a contract for electricity supply based on the user's selection.

[0385] Step 14:

[0386] The server sends the necessary information and documents to the electricity supplier to complete the contract process.

[0387] Step 15:

[0388] The server notifies the user that the contract has been completed and provides monitoring information for future power usage.

[0389] Example 1

[0390] 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."

[0391] In today's electricity market, consumers need a great deal of specialized knowledge and time to choose the optimal electricity procurement method. It is also difficult to grasp fluctuations in electricity market prices and supply in real time, making it difficult to use electricity efficiently and reduce costs. For this reason, there is a need for a method that allows consumers to procure electricity efficiently, even without specialized knowledge.

[0392] 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.

[0393] In this invention, the server includes: means for acquiring electricity usage data from a user; means for externally acquiring electricity market data in real time; means for generating an optimal electricity procurement plan based on the electricity usage data and the electricity market data using an AI algorithm; means for presenting the generated optimal electricity procurement plan to the user; means for automatically processing an electricity supply contract based on the user's selection; means for storing the electricity usage data and the electricity market data in a database; means for using an analysis module to calculate average electricity consumption, peak hours, and seasonal fluctuations; and means for displaying the optimal electricity procurement plan to the user using a web interface or application, thereby enabling consumers to procure electricity efficiently and optimally without specialized knowledge.

[0394] "User" refers to an individual or company that uses this system to procure electricity.

[0395] "Electricity usage data" refers to historical information about the amount of electricity consumed by a user, including consumption by date and time, peak usage, seasonal variations, and the like.

[0396] "Electricity market data" refers to data obtained from external sources, such as real-time fluctuating electricity market prices and supply status, and renewable energy supply information.

[0397] "AI algorithm" refers to a calculation method that uses artificial intelligence technology to analyze data and generate optimal electricity procurement plans.

[0398] "Power Procurement Plan" refers to a plan that indicates the most cost-effective and environmentally friendly method of procuring electricity based on the user's electricity usage trends and market data.

[0399] "Database" refers to a storage device for organizing and centrally managing acquired and analyzed data.

[0400] "Analysis Module" means a software component used to calculate and analyze electricity usage data to identify average consumption, peak hours, and seasonal variations.

[0401] "Web Interface" refers to a screen display that utilizes web technology to allow a user to access a system via the Internet and input and retrieve information.

[0402] An "application" is software that runs on devices such as smartphones and tablets, and refers to the interface that allows users to access and operate the system.

[0403] The present invention provides a system that allows users to optimally procure power without having specialized knowledge. A specific program for implementing this system and its processing flow will be described below.

[0404] This system begins with the user providing their own electricity consumption data. The user registers for the first time by accessing the system's website or application and entering the required information. After completing registration, the user uploads their electricity usage data to the system. This includes past electricity consumption history data and data provided by the power company. The data uploaded by the user is in CSV format, for example.

[0405] The server acquires the electricity consumption data provided by the user and stores it in a database. The stored data is then analyzed by an analysis module on the server. Specifically, analysis is performed to identify the average and peak times of the user's electricity consumption, as well as seasonal fluctuations. This analysis is performed using analysis libraries such as Python's pandas and numpy.

[0406] The server then uses an appropriate external API to retrieve real-time price information from external electricity markets. Through this external API, real-time electricity market prices and renewable energy supplier data are retrieved. For example, the Open Energy API is used. The retrieved market data is also stored in a database.

[0407] The server then launches an AI algorithm to generate an optimal electricity procurement plan based on the electricity consumption data and market data. The algorithm aims to minimize costs and maximize the proportion of renewable energy. Generative AI models such as TensorFlow and PyTorch are used to build the AI ​​algorithm. The generated plan is then presented to the user, who can view it on their screen via a web interface or application.

[0408] The user selects the most suitable electricity procurement plan from among several options presented by the server. Based on the selected plan, the server automatically executes procedures and transmits the necessary information and documents to complete the contract with the electricity supplier. This process allows the user to complete the complex contract procedure hassle-free.

[0409] As a concrete example, in a household scenario, a user who moves into a new home uploads their electricity consumption data from the past year to the system. The server then retrieves market data, and an AI algorithm generates a plan that uses more than 50% renewable energy and reduces annual costs by 5%. The user selects this plan, and the server automatically completes the contract process with the electricity supplier.

[0410] In a business scenario, a company uploads three years of electricity usage data, and the AI ​​algorithm generates a plan to increase electricity usage at night and maximize solar power generation. Once the company selects this plan, the server automatically processes contracts with the electricity supplier and makes any necessary adjustments.

[0411] Below is an example of a prompt sentence to input to the generative AI model.

[0412] "I have uploaded my electricity usage data for the past year. Based on this, please generate a plan that minimizes annual costs while achieving a renewable energy usage rate of 50% or more."

[0413] "Generate a plan to increase nighttime electricity use and maximize solar power generation based on the company's electricity usage data for the past three years."

[0414] The present invention enables users to realize optimal power procurement based on trends in the power market without requiring specialized knowledge, thereby enabling efficient and environmentally friendly power procurement.

[0415] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0416] Step 1:

[0417] First time registration and login

[0418] Input: The user enters their first-time registration information, such as their name, email address, and password.

[0419] Server operation: The server receives the entered information, stores the new user information in the database, and automatically sends a confirmation email to the user upon registration completion.

[0420] Output: The server displays a registration success message to the user.

[0421] Step 2:

[0422] Uploading electricity usage data

[0423] Input: User uploads electricity usage data (e.g. electricity consumption data for the past year) in CSV format.

[0424] Server operation: The server receives the uploaded CSV file, checks the format and integrity of the data, and stores the data in the database if there are no errors.

[0425] Output: The server displays the message "Power usage data successfully saved" to the user.

[0426] Step 3:

[0427] Analysis of power consumption data

[0428] Input: User electricity usage data stored in the database.

[0429] Server operation: The server uses analysis modules (Python's pandas and numpy) to calculate average electricity consumption, peak hours, and seasonal fluctuations.

[0430] Output: Analyzed power consumption data based on the analysis results.

[0431] Step 4:

[0432] Obtaining Market Data

[0433] Input: Access information to an external API (e.g., the Open Energy API endpoint).

[0434] Server operation: The server calls external APIs to obtain real-time electricity market data, including market prices, renewable energy supply information, etc.

[0435] Output: Store the obtained market data in a database.

[0436] Step 5:

[0437] Launching AI algorithms

[0438] Input: Parsed electricity consumption data and market data.

[0439] Server operation: The server runs an AI algorithm using TensorFlow and PyTorch to generate an optimal electricity procurement plan based on this data. The algorithm aims to minimize costs and maximize the use of renewable energy.

[0440] Output: Save the generated electricity procurement plan in the database.

[0441] Step 6:

[0442] Presenting the plan

[0443] Input: The generated optimal power procurement plan.

[0444] Server operation: The server presents the plan to the user's screen through a web interface or application, where the user can view the presented plan.

[0445] Output: The plan details are displayed to the user.

[0446] Step 7:

[0447] Select and confirm your plan

[0448] Input: The electricity procurement plan selected by the user.

[0449] User action: The user compares the plans presented on the screen, selects the best plan, and clicks the "Confirm" button for the selected plan.

[0450] Output: The user's selection is sent to the server.

[0451] Step 8:

[0452] Executing automated procedures

[0453] Input: Information about the plan selected by the user.

[0454] Server operation: The server automatically sends the necessary information and documents to the electricity supplier and proceeds with the contract procedure.

[0455] Output: The contract process is tracked and the user is notified upon completion, and any related documentation is provided to the user.

[0456] (Application example 1)

[0457] 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."

[0458] In conventional autonomous vehicle operation management, power procurement plans to optimize power consumption and reduce costs must be created manually, placing a heavy burden on operation managers. Additionally, a lack of specialized knowledge about fluctuations in the power market and the use of renewable energy makes it difficult to optimally procure power.

[0459] 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.

[0460] In this invention, the server includes: means for acquiring power usage data from a user; means for externally acquiring power market data in real time; means for generating an optimal power procurement plan based on the power usage data and the power market data using an AI algorithm; means for presenting the generated optimal power procurement plan to the user; means for automatically processing a power supply contract based on a user selection; means for analyzing power consumption data and market data and presenting multiple power procurement plans to an autonomous vehicle operations manager; means for automatically processing a contract with a power supplier based on a plan selected by the operations manager; and means for managing power consumption data of multiple autonomous vehicles, presenting the optimized power procurement plan to the operations manager via a head-mounted display, and automatically processing a contract based on the selected plan. This enables an operations manager to procure power efficiently and environmentally friendly, even without specialized knowledge.

[0461] A "user" is an individual or company that uses the system to procure electricity.

[0462] "Power usage data" is information about the amount of power consumed by the user in the past, such as power consumption, time periods when power was used, and seasonal variations.

[0463] "Electricity Market Data" means electricity market price information and renewable energy supplier data obtained in real time.

[0464] "AI algorithm" is an artificial intelligence technology that analyzes electricity usage data and electricity market data to generate optimal electricity procurement plans.

[0465] The "Power Procurement Plan" is a proposed power supply contract that aims to reduce costs and maximize the use of renewable energy based on power consumption and electricity market trends.

[0466] "Operator" means an individual or organization responsible for the management and operation of an automated vehicle.

[0467] A "head-mounted display" is a display device that is worn on the head and provides visual information to the user.

[0468] An "electricity supplier" is a company or organization that supplies electricity to users.

[0469] The "contract procedure" refers to a series of procedures for concluding a contract with an electricity supplier based on the electricity procurement plan selected by the user.

[0470] This invention details a system that allows a user to optimally procure power without having specialized knowledge.

[0471] System Overview

[0472] This system collects electricity usage data from users, combines it with electricity market data obtained in real time from external sources, and uses AI algorithms to generate an optimal electricity procurement plan. The generated plan is provided through an interface such as a head-mounted display (HMD), and the system automatically processes electricity supply contracts based on the plan selected by the user.

[0473] Program processing

[0474] The system server performs the following process.

[0475] First, users upload their electricity usage data to the system from their devices. The data includes historical electricity consumption data. The data is processed using the pandas library and stored in a database.

[0476] The server then uses an external API to retrieve real-time electricity market data using the requests library, which is also stored in a database.

[0477] The server analyzes the data using AI algorithms such as the RandomForestRegressor from the sklearn library based on electricity usage data and market data. This analysis identifies average, peak, and seasonal fluctuations in the user's electricity consumption. Based on this information, multiple electricity procurement plans are generated that maximize cost savings and renewable energy use.

[0478] The generated plans are presented to the dispatcher for review through the HMD. The dispatcher can then select one of the plans presented, and the contract procedure with the power supplier will be automatically carried out based on the selected plan. This procedure again uses the requests library.

[0479] Specific example explanation

[0480] For example, suppose a user uploads the past year's historical power consumption data for multiple newly introduced autonomous vehicles to the system. The system stores the data, analyzes it, and obtains the latest power market data from an external API. An AI algorithm processes the data and generates plans such as "a plan to use more than 60% renewable energy and reduce annual operating costs by 10%" or "a night plan to avoid peak power charges." The fleet manager reviews these plans through the HMD and selects the most appropriate one. Based on the selected plan, the server automatically processes the contract with the power supplier.

[0481] In this way, users can procure electricity efficiently and in an environmentally friendly manner, even if they do not have specialized knowledge.

[0482] Prompt Sentence Examples

[0483] Below is an example of a prompt sentence to input to the generative AI model.

[0484] Using the past year's worth of power consumption data from autonomous vehicles and real-time electricity market information, generate and present an optimal power procurement plan that maximizes renewable energy utilization while minimizing costs.

[0485] The above is an embodiment of the present invention.

[0486] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0487] Step 1:

[0488] Users access the system using a terminal and upload their past electricity consumption history data. The input is a CSV format electricity consumption history data file, which is sent to the system. The server receives this, reads the data using the pandas library, and saves it in a database. The output is formatted electricity consumption data.

[0489] Step 2:

[0490] The server uses an external API to obtain real-time electricity market data. The input is the endpoint URL of the external API. The server uses the requests library to send API requests and receive market data. This data is returned in JSON format, which is converted into a data frame using the pandas library and stored in a database. The output is the formatted market data.

[0491] Step 3:

[0492] The server analyzes the user's electricity consumption data and market data. The input is the electricity consumption data obtained in step 1 and the market data obtained in step 2. The server scales the data using StandardScaler from the sklearn library, and generates an optimal electricity procurement plan using an AI algorithm that uses RandomForestRegressor. Data analysis includes time series analysis of electricity consumption and analysis of market price fluctuations. The output is the multiple electricity procurement plans generated.

[0493] Step 4:

[0494] The generated power procurement plan is presented to the dispatcher. The input is the plan generated in step 3. The server processes it and presents it through a user interface such as a head-mounted display (HMD). Specifically, when the dispatcher puts on the HMD, a display is displayed that allows the dispatcher to visually check multiple plans. The output is information that the dispatcher can check and select.

[0495] Step 5:

[0496] The dispatcher selects the optimal plan through the HMD. The input is the plan presented in step 4 and the dispatcher's selection information. The dispatcher's selection is sent to the server through the HMD interface. The output is the selection information of the optimal power procurement plan.

[0497] Step 6:

[0498] The server automatically completes the contract procedure with the electricity supplier based on the plan selected by the dispatcher. The input is the plan information selected in step 5. The server uses the requests library to send a request to the contract procedure API and provides the necessary contract information. The output is a contract confirmation notification, which is also sent to the dispatcher.

[0499] This process allows users to procure electricity efficiently and in an environmentally friendly manner, even without specialized knowledge, and can significantly reduce the burden on operation managers.

[0500] 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.

[0501] The present invention combines a system that enables users to optimally procure electricity without specialized knowledge with an emotion engine that recognizes the user's emotions. This improves the user experience and supports the selection of the optimal electricity procurement plan. The specific programs and processing flow for implementing this system are described below.

[0502] The system begins with the user providing their own electricity consumption data. The user accesses the system's website or application and enters the required information to register for the first time. After registration, the user uploads their electricity usage history data to the system. This electricity usage data includes past electricity consumption history and data provided by the electric power company.

[0503] The server acquires the electricity consumption data provided by the user and stores it in a database. The stored data is analyzed by an analysis module on the server. The analysis results include the average electricity consumption of the user, peak hours, and seasonal fluctuations. Next, the server uses an appropriate external API to obtain real-time price information from the external electricity market. Through the external API, real-time electricity market prices and renewable energy supplier data are obtained. This market data is also stored in the database.

[0504] The server then runs an AI algorithm to generate an optimal electricity procurement plan based on electricity consumption data and market data, with the goal of minimizing costs and maximizing the share of renewable energy.

[0505] This system also incorporates an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's emotional state based on their voice, facial expressions, and text input. The server uses the emotion engine to confirm the user's emotional state and adaptively presents an electricity procurement plan based on that information.

[0506] For example, if a user is feeling stressed, the emotion engine will detect this and the server will make suggestions to reduce stress. Similarly, if the user is happy, the server will suggest plans to actively use renewable energy. The plans generated in this way are presented to the user via a web interface or application via the server.

[0507] The user selects the most suitable electricity procurement plan from the multiple plans presented. Based on the selected plan, the server automatically executes the procedure and sends the necessary information and documents to complete the contract with the electricity supplier. This process allows the user to complete the complicated contract procedure hassle-free.

[0508] As a concrete example, in a household scenario, a user uploads their electricity consumption data from the past year to the system. The server then retrieves market data and uses AI algorithms and an emotion engine to generate a plan that uses more than 50% renewable energy and reduces annual costs by 5%. Next, if the user is feeling emotionally stressed, the server uses that information to present a plan that provides a sense of security.

[0509] In a business scenario, a company uploads three years of electricity usage data, and the AI ​​algorithm generates a plan that increases nighttime electricity usage and maximizes solar power generation. When selecting this plan, the emotion engine checks whether the company representative is emotionally satisfied and makes recommendations that will result in the highest satisfaction.

[0510] As described above, the present invention provides a specific embodiment for improving the user experience and realizing efficient and environmentally friendly power procurement by combining an emotion engine.

[0511] The processing flow will be explained below.

[0512] Step 1:

[0513] The user opens a website or application on the system.

[0514] Step 2:

[0515] When a user registers for the first time, they must enter basic information such as their name, address, contact details, and email address.

[0516] Step 3:

[0517] The server stores the information entered by the user in a database and sends a confirmation email containing a link to verify the account.

[0518] Step 4:

[0519] The user clicks on the authentication link to activate the account.

[0520] Step 5:

[0521] Users log in to the system and upload their own electricity usage history data, or link their account information with a specific power company.

[0522] Step 6:

[0523] The server acquires the power usage data provided by the user and stores it in a database.

[0524] Step 7:

[0525] The server runs a data analysis module to analyze the electricity usage data, and the analysis results include information such as average consumption, peak hours, and seasonal variations.

[0526] Step 8:

[0527] The server obtains real-time electricity market price data and renewable energy supplier data through external APIs.

[0528] Step 9:

[0529] The server stores the acquired electricity market data in a database.

[0530] Step 10:

[0531] The server runs an AI algorithm to generate an optimal electricity procurement plan based on the user's electricity usage data and market data.

[0532] Step 11:

[0533] The server activates an emotion engine and analyzes the user's emotional state based on their voice, facial expressions, text input, etc.

[0534] Step 12:

[0535] The server selects an optimal power procurement plan based on the user's emotional state and presents the plan to the user.

[0536] Step 13:

[0537] The user selects the most suitable plan from the multiple plans presented.

[0538] Step 14:

[0539] The server initiates an automated procedure for signing a contract for electricity supply based on the user's selection.

[0540] Step 15:

[0541] The server sends the necessary information and documents to the electricity supplier to complete the contract process.

[0542] Step 16:

[0543] The server notifies the user that the contract has been completed and provides monitoring information for future power usage.

[0544] Example 2

[0545] 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."

[0546] Conventional power procurement systems make it difficult for users without specialized knowledge to optimally procure power. Other issues include a lack of real-time information to respond quickly to fluctuations in the power market, and a lack of proposals that take into account the user's feelings. It is particularly difficult to propose plans that provide a sense of security to users who are feeling stressed.

[0547] 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.

[0548] In this invention, the server includes means for acquiring electricity usage data from a user, means for externally acquiring electricity market data in real time, means for generating an optimal electricity procurement plan based on the electricity usage data and the electricity market data using an AI algorithm, means for presenting the generated optimal electricity procurement plan to the user, means for adaptively presenting an electricity procurement plan based on the user's emotional state using an emotion engine that recognizes the user's emotional state, and means for automatically completing an electricity supply contract based on the user's selection. This enables a user to procure electricity optimally in response to fluctuations in the electricity market without requiring specialized knowledge, and further improves the user experience by providing suggestions that take emotions into consideration.

[0549] "Power usage data" refers to information about the amount of power consumed by a user in the past, including hourly consumption and peak consumption.

[0550] "Electricity Market Data" means real-time pricing and supplier information obtained from external electricity markets.

[0551] "AI algorithm" refers to a calculation method that uses artificial intelligence technology to perform complex data analysis and predictions, and in this system it is used to generate optimal electricity procurement plans.

[0552] An "emotion engine" is a technology that analyzes a user's emotional state based on their voice, facial expression, text input, etc., and evaluates their stress level, satisfaction level, etc.

[0553] "Power procurement plan" refers to a plan that proposes contract terms and prices for power supply that are suitable for users based on power consumption data and power market data.

[0554] "User" refers to general consumers or companies that aim to optimize their electricity procurement by using this system.

[0555] "External API" refers to an application program interface used to obtain data from external electricity markets.

[0556] "Database" refers to an information management system for storing and managing acquired and analyzed electricity usage data and electricity market data.

[0557] The present invention combines a system that enables users to optimally procure electricity without requiring specialized knowledge with an emotion engine that recognizes the user's emotions. This system is configured as follows.

[0558] First, users register for the first time using the system's website or application. This requires basic information such as name, address, and electricity company. Once registration is complete, users upload their past electricity consumption data. This data can be in CSV file format or obtained via API.

[0559] The server receives the electricity consumption data provided by the user, checks the data format and integrity, and then stores it in a database (e.g., MySQL). Next, it uses a Python-based data analysis module (e.g., Pandas or NumPy) to analyze the electricity consumption data and calculate monthly electricity consumption, peak hours, seasonal trends, and so on.

[0560] The server then uses external electricity market APIs (e.g., electricity market price API, renewable energy tracker API) to obtain real-time electricity market price and supplier data, which are also stored in the database.

[0561] Based on the stored electricity consumption data and market data, the server runs an AI algorithm (e.g., a TensorFlow model) to generate an optimal electricity procurement plan. The algorithm's goal is to minimize electricity costs and maximize the proportion of renewable energy used. The generated plan includes detailed recommendations based on the expected annual cost, the proportion of renewable energy used, and the user's electricity consumption pattern.

[0562] Furthermore, the system includes an emotion engine (e.g., Microsoft Azure Emotion API) to recognize the user's emotional state. The device collects the user's voice recordings, facial expression captures, and text input data and uploads these data to the system.

[0563] The server selects an electricity procurement plan that best suits the user's emotional state based on the emotion-analyzed data. For example, if the user is feeling stressed, the server will present a plan that includes suggestions for stress reduction. If the user is satisfied, the server will present a plan that uses more renewable energy.

[0564] After multiple electricity procurement plans are presented, the user selects the most suitable plan. Once the selection is complete, the server automatically completes the contract procedure with the electricity supplier and sends the necessary information and documents. This procedure allows the user to complete the complicated contract procedure hassle-free.

[0565] As a concrete example, in a household scenario, a user uploads their electricity usage history from the past year to the system, and the server retrieves market data and uses AI algorithms and an emotion engine to generate a plan that uses more than 50% renewable energy and reduces annual costs by 5%. Next, if the user is feeling emotionally stressed, the server uses that information to present a plan that gives them more peace of mind.

[0566] In a business scenario, a company uploads the past three years of electricity usage data, and the server uses an AI algorithm to generate a plan that increases nighttime electricity usage and maximizes solar power generation. When selecting this plan, an emotion engine checks whether the company's representative is emotionally satisfied and makes suggestions that will increase satisfaction.

[0567] Examples of prompts include specific instructions such as, "Based on the electricity consumption data from the past year, please suggest an electricity procurement plan that uses more than 50% renewable energy and reduces annual costs by 5%. Also, if the user's emotions are detected as stressed, please suggest a plan that provides a greater sense of security."

[0568] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0569] Step 1: First-time registration

[0570] Users access the system's website or application and register by entering basic information such as name, address, and electricity company. The information is sent to the server and stored in a database, which then generates a user ID and password and starts a protected session.

[0571] Input: Name, address, power company information

[0572] Output: User ID, registration completion notification

[0573] Step 2: Upload your electricity consumption data

[0574] Users upload historical electricity consumption data to the system, including data in CSV file format or obtained via API. The server checks the format and integrity of the received electricity consumption data before storing it in the database. If the format is correct, the data is saved.

[0575] Input: Power consumption history data (CSV file, etc.)

[0576] Output: Power consumption data stored in the database, consistency check message

[0577] Step 3: Analyze power consumption data

[0578] The server performs analysis using the stored power consumption data. It uses Python-based data analysis modules (e.g., Pandas and NumPy) to calculate monthly power consumption, peak hours, seasonal trends, etc. The results of this analysis are stored in a database.

[0579] Input: Power consumption data stored in the database

[0580] Output: Analysis result data (peak hours, monthly consumption, etc.)

[0581] Step 4: Obtaining external electricity market data

[0582] The server calls external electricity market APIs (e.g., electricity market price API, renewable energy tracker API) to obtain real-time electricity market price and supplier data. The obtained market data is stored in a database.

[0583] Input: A request to an external API

[0584] Output: Electricity market data (real-time prices, supplier information, etc.), stored in a database

[0585] Step 5: Generate an optimal power procurement plan

[0586] The server runs an AI algorithm (e.g., a TensorFlow model) to generate an optimal power procurement plan based on the stored power consumption analysis data and market data, aiming to minimize costs and maximize the use of renewable energy.

[0587] Input: Power consumption analysis data, power market data

[0588] Output: Optimal power procurement plan

[0589] Step 6: Collect and analyze emotion data

[0590] The device collects the user's voice recordings, facial expression captures, and text input data, and sends this data to a server, which uses an emotion engine (e.g., Microsoft Azure Emotion API) to analyze the user's emotional state.

[0591] Input: Voice data, facial expression data, text data

[0592] Output: Analyzed emotion data (stress, satisfaction, etc.)

[0593] Step 7: Adjust and present your plan based on emotions

[0594] The server then adjusts an optimal power procurement plan based on the emotion data and presents it to the user. For example, if the user is feeling stressed, the server presents a plan that includes suggestions for reducing stress. The device then displays the plan to the user through a web interface or application.

[0595] Input: Optimal power procurement plan, emotional data

[0596] Output: Present a coordinated power procurement plan

[0597] Step 8: User plan selection and final confirmation

[0598] The user selects the most suitable plan from the multiple electricity procurement plans presented. Once the selection is complete, a confirmation screen is displayed for final confirmation.

[0599] Input: Multiple power procurement plans

[0600] Output: Selected plan, final confirmation notice

[0601] Step 9: Execute automated procedures

[0602] The server automatically completes the contract with the electricity supplier based on the selected plan, sending the necessary information and documents to complete the contract. This allows users to complete the complicated contract procedures without any hassle.

[0603] Input: Selected plan

[0604] Output: Sending contract documents, contract completion notification

[0605] (Application example 2)

[0606] 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."

[0607] The present invention relates to a system that enables users to optimally procure power without specialized knowledge. In particular, the objective is to optimize power procurement plans by taking into account the user's emotional state, thereby improving user satisfaction. Conventional systems lack a function that takes into account the user's emotional state, and therefore have the problem of not fully improving the user experience. Furthermore, factory workers also require convenience from the devices they use, so a method for efficient power management is necessary.

[0608] 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.

[0609] In this invention, the server includes means for acquiring power usage data from a user, means for externally acquiring power market data in real time, means for generating an optimal power procurement plan based on the power usage data and the power market data using an AI algorithm, means for presenting the generated optimal power procurement plan to the user, means for automatically completing a power supply contract based on the user's selection, means for analyzing the user's emotional state and reflecting it in the optimal power procurement plan, and means for displaying the optimal power procurement plan on the smart glasses, thereby supporting optimal power procurement taking user emotions into consideration and enabling people, particularly factory workers, to efficiently manage power in real time.

[0610] "User" means a person or organization that uses the System.

[0611] "Power usage data" is data regarding a user's past and current power consumption.

[0612] "Acquiring in real time" means acquiring data instantly that reflects the current situation.

[0613] "Electricity market data" refers to data relating to the market price and supply status of electricity.

[0614] An "AI algorithm" is a program that uses artificial intelligence technology to analyze data and derive optimal results.

[0615] An "optimal power procurement plan" is a power procurement plan that optimizes power consumption costs and the use of renewable energy.

[0616] "Presenting to the user" means showing the generated plan to the user.

[0617] "Automatically proceeding" means automating a manual operation without requiring user intervention.

[0618] "Emotional state" refers to the user's current psychological and emotional state.

[0619] "Smart glasses" are a wearable eyeglass-type device equipped with a display function.

[0620] The present invention provides a system that enables users to optimally procure electricity without requiring specialized knowledge, and further combines it with an emotion engine that recognizes the user's emotional state. This system aims to present optimal electricity procurement plans using smart glasses, particularly for factory workers. Specific embodiments of the system are described below.

[0621] First, the user provides their own electricity consumption data. The user accesses the system's website or application and enters the required information to register for the first time. After registration, the user uploads their electricity usage history data to the system. This includes past electricity consumption history and data provided by the power company. The user is responsible for inputting this data from their terminal.

[0622] The server retrieves the electricity consumption data provided by users and stores it in a database. The main software used here is a database management system (e.g., MySQL) and a data analysis tool (e.g., Python's NumPy library). It also uses an external API to retrieve real-time electricity market data. Real-time electricity market prices and renewable energy supplier data are retrieved through the external API. This market data is also stored in the database.

[0623] The server then runs an AI algorithm to generate an optimal electricity procurement plan based on the electricity consumption data and market data. The AI ​​algorithm aims to minimize costs and maximize the proportion of renewable energy. The AI ​​technology used includes machine learning libraries (e.g., scikit-learn).

[0624] Furthermore, this system incorporates an emotion engine to recognize the user's emotional state. The emotion engine analyzes the user's emotional state based on their voice, facial expressions, text input, etc. Specifically, it uses a facial recognition library (e.g., dlib) and a pre-trained emotion classification model (e.g., emotion_classifier.pkl). The server uses the emotion engine to identify the user's emotional state and adaptively presents an electricity procurement plan based on that information.

[0625] The user's device (smart glasses) displays the generated optimal electricity procurement plan. The smart glasses are equipped with a display function and can present the optimal plan to the user in real time. The user reviews the proposed electricity procurement plans and selects the optimal one. Based on the selected plan, the server executes an automated procedure and sends the necessary information and documents to complete the contract with the electricity supplier.

[0626] As a concrete example, consider a situation where a factory worker is working using smart glasses. The worker uploads his or her electricity usage history from the past year to the system as power consumption data. The server then retrieves market data and uses an AI algorithm and emotion engine to generate a plan that uses more than 50% renewable energy and reduces annual costs by 5%. If the worker is feeling stressed, the emotion engine detects this and the server presents a plan that provides a greater sense of security.

[0627] An example of a prompt for a generative AI model could be, "Based on my current electricity usage data and market price data, please suggest the best electricity plan for me when I'm feeling stressed."

[0628] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0629] Step 1:

[0630] Users access the system's website or application and register for the first time. At this time, users enter basic information and upload their own electricity usage history data to the system. The input data includes past electricity consumption history and data provided by the power company. This data is sent from the terminal to the server.

[0631] Step 2:

[0632] The server acquires the power consumption data provided by the user and stores it in a database. This data includes past monthly consumption amounts, daily peak consumption times, etc. The server uses a database management system to effectively manage and store this data. This data will be used for later analysis.

[0633] Step 3:

[0634] The server uses an external API to retrieve real-time electricity market data. The API calls retrieve real-time electricity market prices and renewable energy supplier data. This market data is also stored in the database. The market data is retrieved periodically, and new data is constantly updated.

[0635] Step 4:

[0636] The server runs an AI algorithm and performs data analysis based on the acquired power consumption data and market data. This analysis takes into account past consumption patterns (e.g., peak times and seasonal fluctuations) and current market prices, aiming to minimize costs and maximize the proportion of renewable energy. The results of this analysis are used to generate an optimal power procurement plan.

[0637] Step 5:

[0638] The server analyzes the user's emotional state using an emotion engine. The emotion engine detects emotions based on data such as the user's voice, facial expressions, and text input. This process utilizes a facial recognition library (e.g., dlib) and pre-trained emotion classification models. The user's emotional state (e.g., satisfaction, stress) is determined.

[0639] Step 6:

[0640] The server adaptively adjusts the optimal power procurement plan based on the user's emotional state detected by the emotion engine. For example, if the user is feeling stressed, the plan is adjusted to one that brings a sense of security. The adjusted plan is then saved back in the database.

[0641] Step 7:

[0642] The server presents the generated and adjusted optimal electricity procurement plan to the user. This information is displayed in real time on the user's smart glasses. The user can then review multiple plans on the smart glasses' display and select the optimal plan. The selection result is then sent to the server.

[0643] Step 8:

[0644] The server executes the automated procedures based on the electricity procurement plan selected by the user, including generating and sending the necessary information and documents to complete the contract with the electricity supplier. After completing the procedures, the server sends a notification message to the user's device.

[0645] 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.

[0646] 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.

[0647] 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.

[0648] [Third embodiment]

[0649] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0650] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0651] 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).

[0652] 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.

[0653] 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.

[0654] 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).

[0655] 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.

[0656] 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.

[0657] 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.

[0658] 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.

[0659] 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.

[0660] 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."

[0661] The present invention describes a system that allows users to optimally procure power without having specialized knowledge. Specific programs and processing flows for implementing this system are described below.

[0662] The system begins with the user providing their own electricity consumption data. The user registers for the first time by accessing the system's website or application and entering the required information. After completing registration, the user uploads their electricity usage data to the system. This includes past electricity consumption history data and data provided by the power company.

[0663] The server acquires the electricity consumption data provided by the user and stores it in a database. The stored data is then analyzed by an analysis module on the server. Specifically, the analysis is performed to identify the average and peak times of the user's electricity consumption, as well as seasonal variations.

[0664] The server then uses the appropriate external API to obtain real-time price information from external electricity markets. Through this external API, real-time electricity market prices and renewable energy supplier data are obtained. The obtained market data is also stored in the database.

[0665] The server then runs an AI algorithm to generate an optimal electricity procurement plan based on the electricity consumption data and market data. The algorithm aims to minimize costs and maximize the proportion of renewable energy. The generated plan is displayed to the user through an interface (web interface or application).

[0666] The user selects the most suitable electricity procurement plan from among several options presented by the server. Based on the selected plan, the server automatically executes procedures and transmits the necessary information and documents to complete the contract with the electricity supplier. This process allows the user to complete the complex contract procedure hassle-free.

[0667] As a concrete example, in a household scenario, a user who moves into a new home uploads their electricity consumption data from the past year to the system. The server then retrieves market data, and an AI algorithm generates a plan that uses more than 50% renewable energy and reduces annual costs by 5%. The user then selects this plan, and the server automatically completes the contract process with the electricity supplier.

[0668] In a business scenario, a company uploads three years of electricity usage data, and the AI ​​algorithm generates a plan to increase electricity usage at night and maximize solar power generation. Once the company selects this plan, the server automatically processes contracts with the electricity supplier and makes any necessary adjustments.

[0669] As described above, the present invention provides a specific embodiment for realizing optimal power procurement based on trends in the power market, even if the user does not have specialized knowledge. This enables efficient and environmentally friendly power procurement.

[0670] The processing flow will be explained below.

[0671] Step 1:

[0672] The user opens a website or application on the system.

[0673] Step 2:

[0674] When a user registers for the first time, they must enter basic information such as their name, address, contact details, and email address.

[0675] Step 3:

[0676] The server stores the information entered by the user in a database and sends a confirmation email containing a link to verify the account.

[0677] Step 4:

[0678] The user clicks on the authentication link to activate the account.

[0679] Step 5:

[0680] Users log in to the system and upload their own electricity usage history data, or link their account information with a specific power company.

[0681] Step 6:

[0682] The server acquires the power usage data provided by the user and stores it in a database.

[0683] Step 7:

[0684] The server runs a data analysis module to analyze the electricity usage data, and the analysis results include information such as average consumption, peak hours, and seasonal variations.

[0685] Step 8:

[0686] The server obtains real-time electricity market price data and renewable energy supplier data through external APIs.

[0687] Step 9:

[0688] The server stores the acquired electricity market data in a database.

[0689] Step 10:

[0690] The server runs an AI algorithm to generate an optimal electricity procurement plan based on the user's electricity usage data and market data.

[0691] Step 11:

[0692] The server presents the generated electricity procurement plan to the user via a web interface or application.

[0693] Step 12:

[0694] The user selects the most suitable plan from the multiple plans presented.

[0695] Step 13:

[0696] The server initiates an automated procedure for signing a contract for electricity supply based on the user's selection.

[0697] Step 14:

[0698] The server sends the necessary information and documents to the electricity supplier to complete the contract process.

[0699] Step 15:

[0700] The server notifies the user that the contract has been completed and provides monitoring information for future power usage.

[0701] Example 1

[0702] 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."

[0703] In today's electricity market, consumers need a great deal of specialized knowledge and time to choose the optimal electricity procurement method. It is also difficult to grasp fluctuations in electricity market prices and supply in real time, making it difficult to use electricity efficiently and reduce costs. For this reason, there is a need for a method that allows consumers to procure electricity efficiently, even without specialized knowledge.

[0704] 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.

[0705] In this invention, the server includes: means for acquiring electricity usage data from a user; means for externally acquiring electricity market data in real time; means for generating an optimal electricity procurement plan based on the electricity usage data and the electricity market data using an AI algorithm; means for presenting the generated optimal electricity procurement plan to the user; means for automatically processing an electricity supply contract based on the user's selection; means for storing the electricity usage data and the electricity market data in a database; means for using an analysis module to calculate average electricity consumption, peak hours, and seasonal fluctuations; and means for displaying the optimal electricity procurement plan to the user using a web interface or application, thereby enabling consumers to procure electricity efficiently and optimally without specialized knowledge.

[0706] "User" refers to an individual or company that uses this system to procure electricity.

[0707] "Electricity usage data" refers to historical information about the amount of electricity consumed by a user, including consumption by date and time, peak usage, seasonal variations, and the like.

[0708] "Electricity market data" refers to data obtained from external sources, such as real-time fluctuating electricity market prices and supply status, and renewable energy supply information.

[0709] "AI algorithm" refers to a calculation method that uses artificial intelligence technology to analyze data and generate optimal electricity procurement plans.

[0710] "Power Procurement Plan" refers to a plan that indicates the most cost-effective and environmentally friendly method of procuring electricity based on the user's electricity usage trends and market data.

[0711] "Database" refers to a storage device for organizing and centrally managing acquired and analyzed data.

[0712] "Analysis Module" means a software component used to calculate and analyze electricity usage data to identify average consumption, peak hours, and seasonal variations.

[0713] "Web Interface" refers to a screen display that utilizes web technology to allow a user to access a system via the Internet and input and retrieve information.

[0714] An "application" is software that runs on devices such as smartphones and tablets, and refers to the interface that allows users to access and operate the system.

[0715] The present invention provides a system that allows users to optimally procure power without having specialized knowledge. A specific program for implementing this system and its processing flow will be described below.

[0716] This system begins with the user providing their own electricity consumption data. The user registers for the first time by accessing the system's website or application and entering the required information. After completing registration, the user uploads their electricity usage data to the system. This includes past electricity consumption history data and data provided by the power company. The data uploaded by the user is in CSV format, for example.

[0717] The server acquires the electricity consumption data provided by the user and stores it in a database. The stored data is then analyzed by an analysis module on the server. Specifically, analysis is performed to identify the average and peak times of the user's electricity consumption, as well as seasonal fluctuations. This analysis is performed using analysis libraries such as Python's pandas and numpy.

[0718] The server then uses an appropriate external API to retrieve real-time price information from external electricity markets. Through this external API, real-time electricity market prices and renewable energy supplier data are retrieved. For example, the Open Energy API is used. The retrieved market data is also stored in a database.

[0719] The server then launches an AI algorithm to generate an optimal electricity procurement plan based on the electricity consumption data and market data. The algorithm aims to minimize costs and maximize the proportion of renewable energy. Generative AI models such as TensorFlow and PyTorch are used to build the AI ​​algorithm. The generated plan is then presented to the user, who can view it on their screen via a web interface or application.

[0720] The user selects the most suitable electricity procurement plan from among several options presented by the server. Based on the selected plan, the server automatically executes procedures and transmits the necessary information and documents to complete the contract with the electricity supplier. This process allows the user to complete the complex contract procedure hassle-free.

[0721] As a concrete example, in a household scenario, a user who moves into a new home uploads their electricity consumption data from the past year to the system. The server then retrieves market data, and an AI algorithm generates a plan that uses more than 50% renewable energy and reduces annual costs by 5%. The user selects this plan, and the server automatically completes the contract process with the electricity supplier.

[0722] In a business scenario, a company uploads three years of electricity usage data, and the AI ​​algorithm generates a plan to increase electricity usage at night and maximize solar power generation. Once the company selects this plan, the server automatically processes contracts with the electricity supplier and makes any necessary adjustments.

[0723] Below is an example of a prompt sentence to input to the generative AI model.

[0724] "I have uploaded my electricity usage data for the past year. Based on this, please generate a plan that minimizes annual costs while achieving a renewable energy usage rate of 50% or more."

[0725] "Generate a plan to increase nighttime electricity use and maximize solar power generation based on the company's electricity usage data for the past three years."

[0726] The present invention enables users to realize optimal power procurement based on trends in the power market without requiring specialized knowledge, thereby enabling efficient and environmentally friendly power procurement.

[0727] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0728] Step 1:

[0729] First time registration and login

[0730] Input: The user enters their first-time registration information, such as their name, email address, and password.

[0731] Server operation: The server receives the entered information, stores the new user information in the database, and automatically sends a confirmation email to the user upon registration completion.

[0732] Output: The server displays a registration success message to the user.

[0733] Step 2:

[0734] Uploading electricity usage data

[0735] Input: User uploads electricity usage data (e.g. electricity consumption data for the past year) in CSV format.

[0736] Server operation: The server receives the uploaded CSV file, checks the format and integrity of the data, and stores the data in the database if there are no errors.

[0737] Output: The server displays the message "Power usage data successfully saved" to the user.

[0738] Step 3:

[0739] Analysis of power consumption data

[0740] Input: User electricity usage data stored in the database.

[0741] Server operation: The server uses analysis modules (Python's pandas and numpy) to calculate average electricity consumption, peak hours, and seasonal fluctuations.

[0742] Output: Analyzed power consumption data based on the analysis results.

[0743] Step 4:

[0744] Obtaining Market Data

[0745] Input: Access information to an external API (e.g., the Open Energy API endpoint).

[0746] Server operation: The server calls external APIs to obtain real-time electricity market data, including market prices, renewable energy supply information, etc.

[0747] Output: Store the obtained market data in a database.

[0748] Step 5:

[0749] Launching AI algorithms

[0750] Input: Parsed electricity consumption data and market data.

[0751] Server operation: The server runs an AI algorithm using TensorFlow and PyTorch to generate an optimal electricity procurement plan based on this data. The algorithm aims to minimize costs and maximize the use of renewable energy.

[0752] Output: Save the generated electricity procurement plan in the database.

[0753] Step 6:

[0754] Presenting the plan

[0755] Input: The generated optimal power procurement plan.

[0756] Server operation: The server presents the plan to the user's screen through a web interface or application, where the user can view the presented plan.

[0757] Output: The plan details are displayed to the user.

[0758] Step 7:

[0759] Select and confirm your plan

[0760] Input: The electricity procurement plan selected by the user.

[0761] User action: The user compares the plans presented on the screen, selects the best plan, and clicks the "Confirm" button for the selected plan.

[0762] Output: The user's selection is sent to the server.

[0763] Step 8:

[0764] Executing automated procedures

[0765] Input: Information about the plan selected by the user.

[0766] Server operation: The server automatically sends the necessary information and documents to the electricity supplier and proceeds with the contract procedure.

[0767] Output: The contract process is tracked and the user is notified upon completion, and any related documentation is provided to the user.

[0768] (Application example 1)

[0769] 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."

[0770] In conventional autonomous vehicle operation management, power procurement plans to optimize power consumption and reduce costs must be created manually, placing a heavy burden on operation managers. Additionally, a lack of specialized knowledge about fluctuations in the power market and the use of renewable energy makes it difficult to optimally procure power.

[0771] 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.

[0772] In this invention, the server includes: means for acquiring power usage data from a user; means for externally acquiring power market data in real time; means for generating an optimal power procurement plan based on the power usage data and the power market data using an AI algorithm; means for presenting the generated optimal power procurement plan to the user; means for automatically processing a power supply contract based on a user selection; means for analyzing power consumption data and market data and presenting multiple power procurement plans to an autonomous vehicle operations manager; means for automatically processing a contract with a power supplier based on a plan selected by the operations manager; and means for managing power consumption data of multiple autonomous vehicles, presenting the optimized power procurement plan to the operations manager via a head-mounted display, and automatically processing a contract based on the selected plan. This enables an operations manager to procure power efficiently and environmentally friendly, even without specialized knowledge.

[0773] A "user" is an individual or company that uses the system to procure electricity.

[0774] "Power usage data" is information about the amount of power consumed by the user in the past, such as power consumption, time periods when power was used, and seasonal variations.

[0775] "Electricity Market Data" means electricity market price information and renewable energy supplier data obtained in real time.

[0776] "AI algorithm" is an artificial intelligence technology that analyzes electricity usage data and electricity market data to generate optimal electricity procurement plans.

[0777] The "Power Procurement Plan" is a proposed power supply contract that aims to reduce costs and maximize the use of renewable energy based on power consumption and electricity market trends.

[0778] "Operator" means an individual or organization responsible for the management and operation of an automated vehicle.

[0779] A "head-mounted display" is a display device that is worn on the head and provides visual information to the user.

[0780] An "electricity supplier" is a company or organization that supplies electricity to users.

[0781] The "contract procedure" refers to a series of procedures for concluding a contract with an electricity supplier based on the electricity procurement plan selected by the user.

[0782] This invention details a system that allows a user to optimally procure power without having specialized knowledge.

[0783] System Overview

[0784] This system collects electricity usage data from users, combines it with electricity market data obtained in real time from external sources, and uses AI algorithms to generate an optimal electricity procurement plan. The generated plan is provided through an interface such as a head-mounted display (HMD), and the system automatically processes electricity supply contracts based on the plan selected by the user.

[0785] Program processing

[0786] The system server performs the following process.

[0787] First, users upload their electricity usage data to the system from their devices. The data includes historical electricity consumption data. The data is processed using the pandas library and stored in a database.

[0788] The server then uses an external API to retrieve real-time electricity market data using the requests library, which is also stored in a database.

[0789] The server analyzes the data using AI algorithms such as the RandomForestRegressor from the sklearn library based on electricity usage data and market data. This analysis identifies average, peak, and seasonal fluctuations in the user's electricity consumption. Based on this information, multiple electricity procurement plans are generated that maximize cost savings and renewable energy use.

[0790] The generated plans are presented to the dispatcher for review through the HMD. The dispatcher can then select one of the plans presented, and the contract procedure with the power supplier will be automatically carried out based on the selected plan. This procedure again uses the requests library.

[0791] Specific example explanation

[0792] For example, suppose a user uploads the past year's historical power consumption data for multiple newly introduced autonomous vehicles to the system. The system stores the data, analyzes it, and obtains the latest power market data from an external API. An AI algorithm processes the data and generates plans such as "a plan to use more than 60% renewable energy and reduce annual operating costs by 10%" or "a night plan to avoid peak power charges." The fleet manager reviews these plans through the HMD and selects the most appropriate one. Based on the selected plan, the server automatically processes the contract with the power supplier.

[0793] In this way, users can procure electricity efficiently and in an environmentally friendly manner, even if they do not have specialized knowledge.

[0794] Prompt Sentence Examples

[0795] Below is an example of a prompt sentence to input to the generative AI model.

[0796] Using the past year's worth of power consumption data from autonomous vehicles and real-time electricity market information, generate and present an optimal power procurement plan that maximizes renewable energy utilization while minimizing costs.

[0797] The above is an embodiment of the present invention.

[0798] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0799] Step 1:

[0800] Users access the system using a terminal and upload their past electricity consumption history data. The input is a CSV format electricity consumption history data file, which is sent to the system. The server receives this, reads the data using the pandas library, and saves it in a database. The output is formatted electricity consumption data.

[0801] Step 2:

[0802] The server uses an external API to obtain real-time electricity market data. The input is the endpoint URL of the external API. The server uses the requests library to send API requests and receive market data. This data is returned in JSON format, which is converted into a data frame using the pandas library and stored in a database. The output is the formatted market data.

[0803] Step 3:

[0804] The server analyzes the user's electricity consumption data and market data. The input is the electricity consumption data obtained in step 1 and the market data obtained in step 2. The server scales the data using StandardScaler from the sklearn library, and generates an optimal electricity procurement plan using an AI algorithm that uses RandomForestRegressor. Data analysis includes time series analysis of electricity consumption and analysis of market price fluctuations. The output is the multiple electricity procurement plans generated.

[0805] Step 4:

[0806] The generated power procurement plan is presented to the dispatcher. The input is the plan generated in step 3. The server processes it and presents it through a user interface such as a head-mounted display (HMD). Specifically, when the dispatcher puts on the HMD, a display is displayed that allows the dispatcher to visually check multiple plans. The output is information that the dispatcher can check and select.

[0807] Step 5:

[0808] The dispatcher selects the optimal plan through the HMD. The input is the plan presented in step 4 and the dispatcher's selection information. The dispatcher's selection is sent to the server through the HMD interface. The output is the selection information of the optimal power procurement plan.

[0809] Step 6:

[0810] The server automatically completes the contract procedure with the electricity supplier based on the plan selected by the dispatcher. The input is the plan information selected in step 5. The server uses the requests library to send a request to the contract procedure API and provides the necessary contract information. The output is a contract confirmation notification, which is also sent to the dispatcher.

[0811] This process allows users to procure electricity efficiently and in an environmentally friendly manner, even without specialized knowledge, and can significantly reduce the burden on operation managers.

[0812] 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.

[0813] The present invention combines a system that enables users to optimally procure electricity without specialized knowledge with an emotion engine that recognizes the user's emotions. This improves the user experience and supports the selection of the optimal electricity procurement plan. The specific programs and processing flow for implementing this system are described below.

[0814] The system begins with the user providing their own electricity consumption data. The user accesses the system's website or application and enters the required information to register for the first time. After registration, the user uploads their electricity usage history data to the system. This electricity usage data includes past electricity consumption history and data provided by the electric power company.

[0815] The server acquires the electricity consumption data provided by the user and stores it in a database. The stored data is analyzed by an analysis module on the server. The analysis results include the average electricity consumption of the user, peak hours, and seasonal fluctuations. Next, the server uses an appropriate external API to obtain real-time price information from the external electricity market. Through the external API, real-time electricity market prices and renewable energy supplier data are obtained. This market data is also stored in the database.

[0816] The server then runs an AI algorithm to generate an optimal electricity procurement plan based on electricity consumption data and market data, with the goal of minimizing costs and maximizing the share of renewable energy.

[0817] This system also incorporates an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's emotional state based on their voice, facial expressions, and text input. The server uses the emotion engine to confirm the user's emotional state and adaptively presents an electricity procurement plan based on that information.

[0818] For example, if a user is feeling stressed, the emotion engine will detect this and the server will make suggestions to reduce stress. Similarly, if the user is happy, the server will suggest plans to actively use renewable energy. The plans generated in this way are presented to the user via a web interface or application via the server.

[0819] The user selects the most suitable electricity procurement plan from the multiple plans presented. Based on the selected plan, the server automatically executes the procedure and sends the necessary information and documents to complete the contract with the electricity supplier. This process allows the user to complete the complicated contract procedure hassle-free.

[0820] As a concrete example, in a household scenario, a user uploads their electricity consumption data from the past year to the system. The server then retrieves market data and uses AI algorithms and an emotion engine to generate a plan that uses more than 50% renewable energy and reduces annual costs by 5%. Next, if the user is feeling emotionally stressed, the server uses that information to present a plan that provides a sense of security.

[0821] In a business scenario, a company uploads three years of electricity usage data, and the AI ​​algorithm generates a plan that increases nighttime electricity usage and maximizes solar power generation. When selecting this plan, the emotion engine checks whether the company representative is emotionally satisfied and makes recommendations that will result in the highest satisfaction.

[0822] As described above, the present invention provides a specific embodiment for improving the user experience and realizing efficient and environmentally friendly power procurement by combining an emotion engine.

[0823] The processing flow will be explained below.

[0824] Step 1:

[0825] The user opens a website or application on the system.

[0826] Step 2:

[0827] When a user registers for the first time, they must enter basic information such as their name, address, contact details, and email address.

[0828] Step 3:

[0829] The server stores the information entered by the user in a database and sends a confirmation email containing a link to verify the account.

[0830] Step 4:

[0831] The user clicks on the authentication link to activate the account.

[0832] Step 5:

[0833] Users log in to the system and upload their own electricity usage history data, or link their account information with a specific power company.

[0834] Step 6:

[0835] The server acquires the power usage data provided by the user and stores it in a database.

[0836] Step 7:

[0837] The server runs a data analysis module to analyze the electricity usage data, and the analysis results include information such as average consumption, peak hours, and seasonal variations.

[0838] Step 8:

[0839] The server obtains real-time electricity market price data and renewable energy supplier data through external APIs.

[0840] Step 9:

[0841] The server stores the acquired electricity market data in a database.

[0842] Step 10:

[0843] The server runs an AI algorithm to generate an optimal electricity procurement plan based on the user's electricity usage data and market data.

[0844] Step 11:

[0845] The server activates an emotion engine and analyzes the user's emotional state based on their voice, facial expressions, text input, etc.

[0846] Step 12:

[0847] The server selects an optimal power procurement plan based on the user's emotional state and presents the plan to the user.

[0848] Step 13:

[0849] The user selects the most suitable plan from the multiple plans presented.

[0850] Step 14:

[0851] The server initiates an automated procedure for signing a contract for electricity supply based on the user's selection.

[0852] Step 15:

[0853] The server sends the necessary information and documents to the electricity supplier to complete the contract process.

[0854] Step 16:

[0855] The server notifies the user that the contract has been completed and provides monitoring information for future power usage.

[0856] Example 2

[0857] 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."

[0858] Conventional power procurement systems make it difficult for users without specialized knowledge to optimally procure power. Other issues include a lack of real-time information to respond quickly to fluctuations in the power market, and a lack of proposals that take into account the user's feelings. It is particularly difficult to propose plans that provide a sense of security to users who are feeling stressed.

[0859] 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.

[0860] In this invention, the server includes means for acquiring electricity usage data from a user, means for externally acquiring electricity market data in real time, means for generating an optimal electricity procurement plan based on the electricity usage data and the electricity market data using an AI algorithm, means for presenting the generated optimal electricity procurement plan to the user, means for adaptively presenting an electricity procurement plan based on the user's emotional state using an emotion engine that recognizes the user's emotional state, and means for automatically completing an electricity supply contract based on the user's selection. This enables a user to procure electricity optimally in response to fluctuations in the electricity market without requiring specialized knowledge, and further improves the user experience by providing suggestions that take emotions into consideration.

[0861] "Power usage data" refers to information about the amount of power consumed by a user in the past, including hourly consumption and peak consumption.

[0862] "Electricity Market Data" means real-time pricing and supplier information obtained from external electricity markets.

[0863] "AI algorithm" refers to a calculation method that uses artificial intelligence technology to perform complex data analysis and predictions, and in this system it is used to generate optimal electricity procurement plans.

[0864] An "emotion engine" is a technology that analyzes a user's emotional state based on their voice, facial expression, text input, etc., and evaluates their stress level, satisfaction level, etc.

[0865] "Power procurement plan" refers to a plan that proposes contract terms and prices for power supply that are suitable for users based on power consumption data and power market data.

[0866] "User" refers to general consumers or companies that aim to optimize their electricity procurement by using this system.

[0867] "External API" refers to an application program interface used to obtain data from external electricity markets.

[0868] "Database" refers to an information management system for storing and managing acquired and analyzed electricity usage data and electricity market data.

[0869] The present invention combines a system that enables users to optimally procure electricity without requiring specialized knowledge with an emotion engine that recognizes the user's emotions. This system is configured as follows.

[0870] First, users register for the first time using the system's website or application. This requires basic information such as name, address, and electricity company. Once registration is complete, users upload their past electricity consumption data. This data can be in CSV file format or obtained via API.

[0871] The server receives the electricity consumption data provided by the user, checks the data format and integrity, and then stores it in a database (e.g., MySQL). Next, it uses a Python-based data analysis module (e.g., Pandas or NumPy) to analyze the electricity consumption data and calculate monthly electricity consumption, peak hours, seasonal trends, and so on.

[0872] The server then uses external electricity market APIs (e.g., electricity market price API, renewable energy tracker API) to obtain real-time electricity market price and supplier data, which are also stored in the database.

[0873] Based on the stored electricity consumption data and market data, the server runs an AI algorithm (e.g., a TensorFlow model) to generate an optimal electricity procurement plan. The algorithm's goal is to minimize electricity costs and maximize the proportion of renewable energy used. The generated plan includes detailed recommendations based on the expected annual cost, the proportion of renewable energy used, and the user's electricity consumption pattern.

[0874] Furthermore, the system includes an emotion engine (e.g., Microsoft Azure Emotion API) to recognize the user's emotional state. The device collects the user's voice recordings, facial expression captures, and text input data and uploads these data to the system.

[0875] The server selects an electricity procurement plan that best suits the user's emotional state based on the emotion-analyzed data. For example, if the user is feeling stressed, the server will present a plan that includes suggestions for stress reduction. If the user is satisfied, the server will present a plan that uses more renewable energy.

[0876] After multiple electricity procurement plans are presented, the user selects the most suitable plan. Once the selection is complete, the server automatically completes the contract procedure with the electricity supplier and sends the necessary information and documents. This procedure allows the user to complete the complicated contract procedure hassle-free.

[0877] As a concrete example, in a household scenario, a user uploads their electricity usage history from the past year to the system, and the server retrieves market data and uses AI algorithms and an emotion engine to generate a plan that uses more than 50% renewable energy and reduces annual costs by 5%. Next, if the user is feeling emotionally stressed, the server uses that information to present a plan that gives them more peace of mind.

[0878] In a business scenario, a company uploads the past three years of electricity usage data, and the server uses an AI algorithm to generate a plan that increases nighttime electricity usage and maximizes solar power generation. When selecting this plan, an emotion engine checks whether the company's representative is emotionally satisfied and makes suggestions that will increase satisfaction.

[0879] Examples of prompts include specific instructions such as, "Based on the electricity consumption data from the past year, please suggest an electricity procurement plan that uses more than 50% renewable energy and reduces annual costs by 5%. Also, if the user's emotions are detected as stressed, please suggest a plan that provides a greater sense of security."

[0880] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0881] Step 1: First-time registration

[0882] Users access the system's website or application and register by entering basic information such as name, address, and electricity company. The information is sent to the server and stored in a database, which then generates a user ID and password and starts a protected session.

[0883] Input: Name, address, power company information

[0884] Output: User ID, registration completion notification

[0885] Step 2: Upload your electricity consumption data

[0886] Users upload historical electricity consumption data to the system, including data in CSV file format or obtained via API. The server checks the format and integrity of the received electricity consumption data before storing it in the database. If the format is correct, the data is saved.

[0887] Input: Power consumption history data (CSV file, etc.)

[0888] Output: Power consumption data stored in the database, consistency check message

[0889] Step 3: Analyze power consumption data

[0890] The server performs analysis using the stored power consumption data. It uses Python-based data analysis modules (e.g., Pandas and NumPy) to calculate monthly power consumption, peak hours, seasonal trends, etc. The results of this analysis are stored in a database.

[0891] Input: Power consumption data stored in the database

[0892] Output: Analysis result data (peak hours, monthly consumption, etc.)

[0893] Step 4: Obtaining external electricity market data

[0894] The server calls external electricity market APIs (e.g., electricity market price API, renewable energy tracker API) to obtain real-time electricity market price and supplier data. The obtained market data is stored in a database.

[0895] Input: A request to an external API

[0896] Output: Electricity market data (real-time prices, supplier information, etc.), stored in a database

[0897] Step 5: Generate an optimal power procurement plan

[0898] The server runs an AI algorithm (e.g., a TensorFlow model) to generate an optimal power procurement plan based on the stored power consumption analysis data and market data, aiming to minimize costs and maximize the use of renewable energy.

[0899] Input: Power consumption analysis data, power market data

[0900] Output: Optimal power procurement plan

[0901] Step 6: Collect and analyze emotion data

[0902] The device collects the user's voice recordings, facial expression captures, and text input data, and sends this data to a server, which uses an emotion engine (e.g., Microsoft Azure Emotion API) to analyze the user's emotional state.

[0903] Input: Voice data, facial expression data, text data

[0904] Output: Analyzed emotion data (stress, satisfaction, etc.)

[0905] Step 7: Adjust and present your plan based on emotions

[0906] The server then adjusts an optimal power procurement plan based on the emotion data and presents it to the user. For example, if the user is feeling stressed, the server presents a plan that includes suggestions for reducing stress. The device then displays the plan to the user through a web interface or application.

[0907] Input: Optimal power procurement plan, emotional data

[0908] Output: Present a coordinated power procurement plan

[0909] Step 8: User plan selection and final confirmation

[0910] The user selects the most suitable plan from the multiple electricity procurement plans presented. Once the selection is complete, a confirmation screen is displayed for final confirmation.

[0911] Input: Multiple power procurement plans

[0912] Output: Selected plan, final confirmation notice

[0913] Step 9: Execute automated procedures

[0914] The server automatically completes the contract with the electricity supplier based on the selected plan, sending the necessary information and documents to complete the contract. This allows users to complete the complicated contract procedures without any hassle.

[0915] Input: Selected plan

[0916] Output: Sending contract documents, contract completion notification

[0917] (Application example 2)

[0918] 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."

[0919] The present invention relates to a system that enables users to optimally procure power without specialized knowledge. In particular, the objective is to optimize power procurement plans by taking into account the user's emotional state, thereby improving user satisfaction. Conventional systems lack a function that takes into account the user's emotional state, and therefore have the problem of not fully improving the user experience. Furthermore, factory workers also require convenience from the devices they use, so a method for efficient power management is necessary.

[0920] 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.

[0921] In this invention, the server includes means for acquiring power usage data from a user, means for externally acquiring power market data in real time, means for generating an optimal power procurement plan based on the power usage data and the power market data using an AI algorithm, means for presenting the generated optimal power procurement plan to the user, means for automatically completing a power supply contract based on the user's selection, means for analyzing the user's emotional state and reflecting it in the optimal power procurement plan, and means for displaying the optimal power procurement plan on the smart glasses, thereby supporting optimal power procurement taking user emotions into consideration and enabling people, particularly factory workers, to efficiently manage power in real time.

[0922] "User" means a person or organization that uses the System.

[0923] "Power usage data" is data regarding a user's past and current power consumption.

[0924] "Acquiring in real time" means acquiring data instantly that reflects the current situation.

[0925] "Electricity market data" refers to data relating to the market price and supply status of electricity.

[0926] An "AI algorithm" is a program that uses artificial intelligence technology to analyze data and derive optimal results.

[0927] An "optimal power procurement plan" is a power procurement plan that optimizes power consumption costs and the use of renewable energy.

[0928] "Presenting to the user" means showing the generated plan to the user.

[0929] "Automatically proceeding" means automating a manual operation without requiring user intervention.

[0930] "Emotional state" refers to the user's current psychological and emotional state.

[0931] "Smart glasses" are a wearable eyeglass-type device equipped with a display function.

[0932] The present invention provides a system that enables users to optimally procure electricity without requiring specialized knowledge, and further combines it with an emotion engine that recognizes the user's emotional state. This system aims to present optimal electricity procurement plans using smart glasses, particularly for factory workers. Specific embodiments of the system are described below.

[0933] First, the user provides their own electricity consumption data. The user accesses the system's website or application and enters the required information to register for the first time. After registration, the user uploads their electricity usage history data to the system. This includes past electricity consumption history and data provided by the power company. The user is responsible for inputting this data from their terminal.

[0934] The server retrieves the electricity consumption data provided by users and stores it in a database. The main software used here is a database management system (e.g., MySQL) and a data analysis tool (e.g., Python's NumPy library). It also uses an external API to retrieve real-time electricity market data. Real-time electricity market prices and renewable energy supplier data are retrieved through the external API. This market data is also stored in the database.

[0935] The server then runs an AI algorithm to generate an optimal electricity procurement plan based on the electricity consumption data and market data. The AI ​​algorithm aims to minimize costs and maximize the proportion of renewable energy. The AI ​​technology used includes machine learning libraries (e.g., scikit-learn).

[0936] Furthermore, this system incorporates an emotion engine to recognize the user's emotional state. The emotion engine analyzes the user's emotional state based on their voice, facial expressions, text input, etc. Specifically, it uses a facial recognition library (e.g., dlib) and a pre-trained emotion classification model (e.g., emotion_classifier.pkl). The server uses the emotion engine to identify the user's emotional state and adaptively presents an electricity procurement plan based on that information.

[0937] The user's device (smart glasses) displays the generated optimal electricity procurement plan. The smart glasses are equipped with a display function and can present the optimal plan to the user in real time. The user reviews the proposed electricity procurement plans and selects the optimal one. Based on the selected plan, the server executes an automated procedure and sends the necessary information and documents to complete the contract with the electricity supplier.

[0938] As a concrete example, consider a situation where a factory worker is working using smart glasses. The worker uploads his or her electricity usage history from the past year to the system as power consumption data. The server then retrieves market data and uses an AI algorithm and emotion engine to generate a plan that uses more than 50% renewable energy and reduces annual costs by 5%. If the worker is feeling stressed, the emotion engine detects this and the server presents a plan that provides a greater sense of security.

[0939] An example of a prompt for a generative AI model could be, "Based on my current electricity usage data and market price data, please suggest the best electricity plan for me when I'm feeling stressed."

[0940] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0941] Step 1:

[0942] Users access the system's website or application and register for the first time. At this time, users enter basic information and upload their own electricity usage history data to the system. The input data includes past electricity consumption history and data provided by the power company. This data is sent from the terminal to the server.

[0943] Step 2:

[0944] The server acquires the power consumption data provided by the user and stores it in a database. This data includes past monthly consumption amounts, daily peak consumption times, etc. The server uses a database management system to effectively manage and store this data. This data will be used for later analysis.

[0945] Step 3:

[0946] The server uses an external API to retrieve real-time electricity market data. The API calls retrieve real-time electricity market prices and renewable energy supplier data. This market data is also stored in the database. The market data is retrieved periodically, and new data is constantly updated.

[0947] Step 4:

[0948] The server runs an AI algorithm and performs data analysis based on the acquired power consumption data and market data. This analysis takes into account past consumption patterns (e.g., peak times and seasonal fluctuations) and current market prices, aiming to minimize costs and maximize the proportion of renewable energy. The results of this analysis are used to generate an optimal power procurement plan.

[0949] Step 5:

[0950] The server analyzes the user's emotional state using an emotion engine. The emotion engine detects emotions based on data such as the user's voice, facial expressions, and text input. This process utilizes a facial recognition library (e.g., dlib) and pre-trained emotion classification models. The user's emotional state (e.g., satisfaction, stress) is determined.

[0951] Step 6:

[0952] The server adaptively adjusts the optimal power procurement plan based on the user's emotional state detected by the emotion engine. For example, if the user is feeling stressed, the plan is adjusted to one that brings a sense of security. The adjusted plan is then saved back in the database.

[0953] Step 7:

[0954] The server presents the generated and adjusted optimal electricity procurement plan to the user. This information is displayed in real time on the user's smart glasses. The user can then review multiple plans on the smart glasses' display and select the optimal plan. The selection result is then sent to the server.

[0955] Step 8:

[0956] The server executes the automated procedures based on the electricity procurement plan selected by the user, including generating and sending the necessary information and documents to complete the contract with the electricity supplier. After completing the procedures, the server sends a notification message to the user's device.

[0957] 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.

[0958] 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.

[0959] 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.

[0960] [Fourth embodiment]

[0961] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0962] 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.

[0963] 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).

[0964] 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.

[0965] 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.

[0966] 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).

[0967] 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.

[0968] 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.

[0969] 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.

[0970] 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.

[0971] 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.

[0972] 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.

[0973] 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."

[0974] The present invention describes a system that allows users to optimally procure power without having specialized knowledge. Specific programs and processing flows for implementing this system are described below.

[0975] The system begins with the user providing their own electricity consumption data. The user registers for the first time by accessing the system's website or application and entering the required information. After completing registration, the user uploads their electricity usage data to the system. This includes past electricity consumption history data and data provided by the power company.

[0976] The server acquires the electricity consumption data provided by the user and stores it in a database. The stored data is then analyzed by an analysis module on the server. Specifically, the analysis is performed to identify the average and peak times of the user's electricity consumption, as well as seasonal variations.

[0977] The server then uses the appropriate external API to obtain real-time price information from external electricity markets. Through this external API, real-time electricity market prices and renewable energy supplier data are obtained. The obtained market data is also stored in the database.

[0978] The server then runs an AI algorithm to generate an optimal electricity procurement plan based on the electricity consumption data and market data. The algorithm aims to minimize costs and maximize the proportion of renewable energy. The generated plan is displayed to the user through an interface (web interface or application).

[0979] The user selects the most suitable electricity procurement plan from among several options presented by the server. Based on the selected plan, the server automatically executes procedures and transmits the necessary information and documents to complete the contract with the electricity supplier. This process allows the user to complete the complex contract procedure hassle-free.

[0980] As a concrete example, in a household scenario, a user who moves into a new home uploads their electricity consumption data from the past year to the system. The server then retrieves market data, and an AI algorithm generates a plan that uses more than 50% renewable energy and reduces annual costs by 5%. The user then selects this plan, and the server automatically completes the contract process with the electricity supplier.

[0981] In a business scenario, a company uploads three years of electricity usage data, and the AI ​​algorithm generates a plan to increase electricity usage at night and maximize solar power generation. Once the company selects this plan, the server automatically processes contracts with the electricity supplier and makes any necessary adjustments.

[0982] As described above, the present invention provides a specific embodiment for realizing optimal power procurement based on trends in the power market, even if the user does not have specialized knowledge. This enables efficient and environmentally friendly power procurement.

[0983] The processing flow will be explained below.

[0984] Step 1:

[0985] The user opens a website or application on the system.

[0986] Step 2:

[0987] When a user registers for the first time, they must enter basic information such as their name, address, contact details, and email address.

[0988] Step 3:

[0989] The server stores the information entered by the user in a database and sends a confirmation email containing a link to verify the account.

[0990] Step 4:

[0991] The user clicks on the authentication link to activate the account.

[0992] Step 5:

[0993] Users log in to the system and upload their own electricity usage history data, or link their account information with a specific power company.

[0994] Step 6:

[0995] The server acquires the power usage data provided by the user and stores it in a database.

[0996] Step 7:

[0997] The server runs a data analysis module to analyze the electricity usage data, and the analysis results include information such as average consumption, peak hours, and seasonal variations.

[0998] Step 8:

[0999] The server obtains real-time electricity market price data and renewable energy supplier data through external APIs.

[1000] Step 9:

[1001] The server stores the acquired electricity market data in a database.

[1002] Step 10:

[1003] The server runs an AI algorithm to generate an optimal electricity procurement plan based on the user's electricity usage data and market data.

[1004] Step 11:

[1005] The server presents the generated electricity procurement plan to the user via a web interface or application.

[1006] Step 12:

[1007] The user selects the most suitable plan from the multiple plans presented.

[1008] Step 13:

[1009] The server initiates an automated procedure for signing a contract for electricity supply based on the user's selection.

[1010] Step 14:

[1011] The server sends the necessary information and documents to the electricity supplier to complete the contract process.

[1012] Step 15:

[1013] The server notifies the user that the contract has been completed and provides monitoring information for future power usage.

[1014] Example 1

[1015] 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."

[1016] In today's electricity market, consumers need a great deal of specialized knowledge and time to choose the optimal electricity procurement method. It is also difficult to grasp fluctuations in electricity market prices and supply in real time, making it difficult to use electricity efficiently and reduce costs. For this reason, there is a need for a method that allows consumers to procure electricity efficiently, even without specialized knowledge.

[1017] 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.

[1018] In this invention, the server includes: means for acquiring electricity usage data from a user; means for externally acquiring electricity market data in real time; means for generating an optimal electricity procurement plan based on the electricity usage data and the electricity market data using an AI algorithm; means for presenting the generated optimal electricity procurement plan to the user; means for automatically processing an electricity supply contract based on the user's selection; means for storing the electricity usage data and the electricity market data in a database; means for using an analysis module to calculate average electricity consumption, peak hours, and seasonal fluctuations; and means for displaying the optimal electricity procurement plan to the user using a web interface or application, thereby enabling consumers to procure electricity efficiently and optimally without specialized knowledge.

[1019] "User" refers to an individual or company that uses this system to procure electricity.

[1020] "Electricity usage data" refers to historical information about the amount of electricity consumed by a user, including consumption by date and time, peak usage, seasonal variations, and the like.

[1021] "Electricity market data" refers to data obtained from external sources, such as real-time fluctuating electricity market prices and supply status, and renewable energy supply information.

[1022] "AI algorithm" refers to a calculation method that uses artificial intelligence technology to analyze data and generate optimal electricity procurement plans.

[1023] "Power Procurement Plan" refers to a plan that indicates the most cost-effective and environmentally friendly method of procuring electricity based on the user's electricity usage trends and market data.

[1024] "Database" refers to a storage device for organizing and centrally managing acquired and analyzed data.

[1025] "Analysis Module" means a software component used to calculate and analyze electricity usage data to identify average consumption, peak hours, and seasonal variations.

[1026] "Web Interface" refers to a screen display that utilizes web technology to allow a user to access a system via the Internet and input and retrieve information.

[1027] An "application" is software that runs on devices such as smartphones and tablets, and refers to the interface that allows users to access and operate the system.

[1028] The present invention provides a system that allows users to optimally procure power without having specialized knowledge. A specific program for implementing this system and its processing flow will be described below.

[1029] This system begins with the user providing their own electricity consumption data. The user registers for the first time by accessing the system's website or application and entering the required information. After completing registration, the user uploads their electricity usage data to the system. This includes past electricity consumption history data and data provided by the power company. The data uploaded by the user is in CSV format, for example.

[1030] The server acquires the electricity consumption data provided by the user and stores it in a database. The stored data is then analyzed by an analysis module on the server. Specifically, analysis is performed to identify the average and peak times of the user's electricity consumption, as well as seasonal fluctuations. This analysis is performed using analysis libraries such as Python's pandas and numpy.

[1031] The server then uses an appropriate external API to retrieve real-time price information from external electricity markets. Through this external API, real-time electricity market prices and renewable energy supplier data are retrieved. For example, the Open Energy API is used. The retrieved market data is also stored in a database.

[1032] The server then launches an AI algorithm to generate an optimal electricity procurement plan based on the electricity consumption data and market data. The algorithm aims to minimize costs and maximize the proportion of renewable energy. Generative AI models such as TensorFlow and PyTorch are used to build the AI ​​algorithm. The generated plan is then presented to the user, who can view it on their screen via a web interface or application.

[1033] The user selects the most suitable electricity procurement plan from among several options presented by the server. Based on the selected plan, the server automatically executes procedures and transmits the necessary information and documents to complete the contract with the electricity supplier. This process allows the user to complete the complex contract procedure hassle-free.

[1034] As a concrete example, in a household scenario, a user who moves into a new home uploads their electricity consumption data from the past year to the system. The server then retrieves market data, and an AI algorithm generates a plan that uses more than 50% renewable energy and reduces annual costs by 5%. The user selects this plan, and the server automatically completes the contract process with the electricity supplier.

[1035] In a business scenario, a company uploads three years of electricity usage data, and the AI ​​algorithm generates a plan to increase electricity usage at night and maximize solar power generation. Once the company selects this plan, the server automatically processes contracts with the electricity supplier and makes any necessary adjustments.

[1036] Below is an example of a prompt sentence to input to the generative AI model.

[1037] "I have uploaded my electricity usage data for the past year. Based on this, please generate a plan that minimizes annual costs while achieving a renewable energy usage rate of 50% or more."

[1038] "Generate a plan to increase nighttime electricity use and maximize solar power generation based on the company's electricity usage data for the past three years."

[1039] The present invention enables users to realize optimal power procurement based on trends in the power market without requiring specialized knowledge, thereby enabling efficient and environmentally friendly power procurement.

[1040] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1041] Step 1:

[1042] First time registration and login

[1043] Input: The user enters their first-time registration information, such as their name, email address, and password.

[1044] Server operation: The server receives the entered information, stores the new user information in the database, and automatically sends a confirmation email to the user upon registration completion.

[1045] Output: The server displays a registration success message to the user.

[1046] Step 2:

[1047] Uploading electricity usage data

[1048] Input: User uploads electricity usage data (e.g. electricity consumption data for the past year) in CSV format.

[1049] Server operation: The server receives the uploaded CSV file, checks the format and integrity of the data, and stores the data in the database if there are no errors.

[1050] Output: The server displays the message "Power usage data successfully saved" to the user.

[1051] Step 3:

[1052] Analysis of power consumption data

[1053] Input: User electricity usage data stored in the database.

[1054] Server operation: The server uses analysis modules (Python's pandas and numpy) to calculate average electricity consumption, peak hours, and seasonal fluctuations.

[1055] Output: Analyzed power consumption data based on the analysis results.

[1056] Step 4:

[1057] Obtaining Market Data

[1058] Input: Access information to an external API (e.g., the Open Energy API endpoint).

[1059] Server operation: The server calls external APIs to obtain real-time electricity market data, including market prices, renewable energy supply information, etc.

[1060] Output: Store the obtained market data in a database.

[1061] Step 5:

[1062] Launching AI algorithms

[1063] Input: Parsed electricity consumption data and market data.

[1064] Server operation: The server runs an AI algorithm using TensorFlow and PyTorch to generate an optimal electricity procurement plan based on this data. The algorithm aims to minimize costs and maximize the use of renewable energy.

[1065] Output: Save the generated electricity procurement plan in the database.

[1066] Step 6:

[1067] Presenting the plan

[1068] Input: The generated optimal power procurement plan.

[1069] Server operation: The server presents the plan to the user's screen through a web interface or application, where the user can view the presented plan.

[1070] Output: The plan details are displayed to the user.

[1071] Step 7:

[1072] Select and confirm your plan

[1073] Input: The electricity procurement plan selected by the user.

[1074] User action: The user compares the plans presented on the screen, selects the best plan, and clicks the "Confirm" button for the selected plan.

[1075] Output: The user's selection is sent to the server.

[1076] Step 8:

[1077] Executing automated procedures

[1078] Input: Information about the plan selected by the user.

[1079] Server operation: The server automatically sends the necessary information and documents to the electricity supplier and proceeds with the contract procedure.

[1080] Output: The contract process is tracked and the user is notified upon completion, and any related documentation is provided to the user.

[1081] (Application example 1)

[1082] 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."

[1083] In conventional autonomous vehicle operation management, power procurement plans to optimize power consumption and reduce costs must be created manually, placing a heavy burden on operation managers. Additionally, a lack of specialized knowledge about fluctuations in the power market and the use of renewable energy makes it difficult to optimally procure power.

[1084] 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.

[1085] In this invention, the server includes: means for acquiring power usage data from a user; means for externally acquiring power market data in real time; means for generating an optimal power procurement plan based on the power usage data and the power market data using an AI algorithm; means for presenting the generated optimal power procurement plan to the user; means for automatically processing a power supply contract based on a user selection; means for analyzing power consumption data and market data and presenting multiple power procurement plans to an autonomous vehicle operations manager; means for automatically processing a contract with a power supplier based on a plan selected by the operations manager; and means for managing power consumption data of multiple autonomous vehicles, presenting the optimized power procurement plan to the operations manager via a head-mounted display, and automatically processing a contract based on the selected plan. This enables an operations manager to procure power efficiently and environmentally friendly, even without specialized knowledge.

[1086] A "user" is an individual or company that uses the system to procure electricity.

[1087] "Power usage data" is information about the amount of power consumed by the user in the past, such as power consumption, time periods when power was used, and seasonal variations.

[1088] "Electricity Market Data" means electricity market price information and renewable energy supplier data obtained in real time.

[1089] "AI algorithm" is an artificial intelligence technology that analyzes electricity usage data and electricity market data to generate optimal electricity procurement plans.

[1090] The "Power Procurement Plan" is a proposed power supply contract that aims to reduce costs and maximize the use of renewable energy based on power consumption and electricity market trends.

[1091] "Operator" means an individual or organization responsible for the management and operation of an automated vehicle.

[1092] A "head-mounted display" is a display device that is worn on the head and provides visual information to the user.

[1093] An "electricity supplier" is a company or organization that supplies electricity to users.

[1094] The "contract procedure" refers to a series of procedures for concluding a contract with an electricity supplier based on the electricity procurement plan selected by the user.

[1095] This invention details a system that allows a user to optimally procure power without having specialized knowledge.

[1096] System Overview

[1097] This system collects electricity usage data from users, combines it with electricity market data obtained in real time from external sources, and uses AI algorithms to generate an optimal electricity procurement plan. The generated plan is provided through an interface such as a head-mounted display (HMD), and the system automatically processes electricity supply contracts based on the plan selected by the user.

[1098] Program processing

[1099] The system server performs the following process.

[1100] First, users upload their electricity usage data to the system from their devices. The data includes historical electricity consumption data. The data is processed using the pandas library and stored in a database.

[1101] The server then uses an external API to retrieve real-time electricity market data using the requests library, which is also stored in a database.

[1102] The server analyzes the data using AI algorithms such as the RandomForestRegressor from the sklearn library based on electricity usage data and market data. This analysis identifies average, peak, and seasonal fluctuations in the user's electricity consumption. Based on this information, multiple electricity procurement plans are generated that maximize cost savings and renewable energy use.

[1103] The generated plans are presented to the dispatcher for review through the HMD. The dispatcher can then select one of the plans presented, and the contract procedure with the power supplier will be automatically carried out based on the selected plan. This procedure again uses the requests library.

[1104] Specific example explanation

[1105] For example, suppose a user uploads the past year's historical power consumption data for multiple newly introduced autonomous vehicles to the system. The system stores the data, analyzes it, and obtains the latest power market data from an external API. An AI algorithm processes the data and generates plans such as "a plan to use more than 60% renewable energy and reduce annual operating costs by 10%" or "a night plan to avoid peak power charges." The fleet manager reviews these plans through the HMD and selects the most appropriate one. Based on the selected plan, the server automatically processes the contract with the power supplier.

[1106] In this way, users can procure electricity efficiently and in an environmentally friendly manner, even if they do not have specialized knowledge.

[1107] Prompt Sentence Examples

[1108] Below is an example of a prompt sentence to input to the generative AI model.

[1109] Using the past year's worth of power consumption data from autonomous vehicles and real-time electricity market information, generate and present an optimal power procurement plan that maximizes renewable energy utilization while minimizing costs.

[1110] The above is an embodiment of the present invention.

[1111] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1112] Step 1:

[1113] Users access the system using a terminal and upload their past electricity consumption history data. The input is a CSV format electricity consumption history data file, which is sent to the system. The server receives this, reads the data using the pandas library, and saves it in a database. The output is formatted electricity consumption data.

[1114] Step 2:

[1115] The server uses an external API to obtain real-time electricity market data. The input is the endpoint URL of the external API. The server uses the requests library to send API requests and receive market data. This data is returned in JSON format, which is converted into a data frame using the pandas library and stored in a database. The output is the formatted market data.

[1116] Step 3:

[1117] The server analyzes the user's electricity consumption data and market data. The input is the electricity consumption data obtained in step 1 and the market data obtained in step 2. The server scales the data using StandardScaler from the sklearn library, and generates an optimal electricity procurement plan using an AI algorithm that uses RandomForestRegressor. Data analysis includes time series analysis of electricity consumption and analysis of market price fluctuations. The output is the multiple electricity procurement plans generated.

[1118] Step 4:

[1119] The generated power procurement plan is presented to the dispatcher. The input is the plan generated in step 3. The server processes it and presents it through a user interface such as a head-mounted display (HMD). Specifically, when the dispatcher puts on the HMD, a display is displayed that allows the dispatcher to visually check multiple plans. The output is information that the dispatcher can check and select.

[1120] Step 5:

[1121] The dispatcher selects the optimal plan through the HMD. The input is the plan presented in step 4 and the dispatcher's selection information. The dispatcher's selection is sent to the server through the HMD interface. The output is the selection information of the optimal power procurement plan.

[1122] Step 6:

[1123] The server automatically completes the contract procedure with the electricity supplier based on the plan selected by the dispatcher. The input is the plan information selected in step 5. The server uses the requests library to send a request to the contract procedure API and provides the necessary contract information. The output is a contract confirmation notification, which is also sent to the dispatcher.

[1124] This process allows users to procure electricity efficiently and in an environmentally friendly manner, even without specialized knowledge, and can significantly reduce the burden on operation managers.

[1125] 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.

[1126] The present invention combines a system that enables users to optimally procure electricity without specialized knowledge with an emotion engine that recognizes the user's emotions. This improves the user experience and supports the selection of the optimal electricity procurement plan. The specific programs and processing flow for implementing this system are described below.

[1127] The system begins with the user providing their own electricity consumption data. The user accesses the system's website or application and enters the required information to register for the first time. After registration, the user uploads their electricity usage history data to the system. This electricity usage data includes past electricity consumption history and data provided by the electric power company.

[1128] The server acquires the electricity consumption data provided by the user and stores it in a database. The stored data is analyzed by an analysis module on the server. The analysis results include the average electricity consumption of the user, peak hours, and seasonal fluctuations. Next, the server uses an appropriate external API to obtain real-time price information from the external electricity market. Through the external API, real-time electricity market prices and renewable energy supplier data are obtained. This market data is also stored in the database.

[1129] The server then runs an AI algorithm to generate an optimal electricity procurement plan based on electricity consumption data and market data, with the goal of minimizing costs and maximizing the share of renewable energy.

[1130] This system also incorporates an emotion engine to recognize the user's emotions. The emotion engine analyzes the user's emotional state based on their voice, facial expressions, and text input. The server uses the emotion engine to confirm the user's emotional state and adaptively presents an electricity procurement plan based on that information.

[1131] For example, if a user is feeling stressed, the emotion engine will detect this and the server will make suggestions to reduce stress. Similarly, if the user is happy, the server will suggest plans to actively use renewable energy. The plans generated in this way are presented to the user via a web interface or application via the server.

[1132] The user selects the most suitable electricity procurement plan from the multiple plans presented. Based on the selected plan, the server automatically executes the procedure and sends the necessary information and documents to complete the contract with the electricity supplier. This process allows the user to complete the complicated contract procedure hassle-free.

[1133] As a concrete example, in a household scenario, a user uploads their electricity consumption data from the past year to the system. The server then retrieves market data and uses AI algorithms and an emotion engine to generate a plan that uses more than 50% renewable energy and reduces annual costs by 5%. Next, if the user is feeling emotionally stressed, the server uses that information to present a plan that provides a sense of security.

[1134] In a business scenario, a company uploads three years of electricity usage data, and the AI ​​algorithm generates a plan that increases nighttime electricity usage and maximizes solar power generation. When selecting this plan, the emotion engine checks whether the company representative is emotionally satisfied and makes recommendations that will result in the highest satisfaction.

[1135] As described above, the present invention provides a specific embodiment for improving the user experience and realizing efficient and environmentally friendly power procurement by combining an emotion engine.

[1136] The processing flow will be explained below.

[1137] Step 1:

[1138] The user opens a website or application on the system.

[1139] Step 2:

[1140] When a user registers for the first time, they must enter basic information such as their name, address, contact details, and email address.

[1141] Step 3:

[1142] The server stores the information entered by the user in a database and sends a confirmation email containing a link to verify the account.

[1143] Step 4:

[1144] The user clicks on the authentication link to activate the account.

[1145] Step 5:

[1146] Users log in to the system and upload their own electricity usage history data, or link their account information with a specific power company.

[1147] Step 6:

[1148] The server acquires the power usage data provided by the user and stores it in a database.

[1149] Step 7:

[1150] The server runs a data analysis module to analyze the electricity usage data, and the analysis results include information such as average consumption, peak hours, and seasonal variations.

[1151] Step 8:

[1152] The server obtains real-time electricity market price data and renewable energy supplier data through external APIs.

[1153] Step 9:

[1154] The server stores the acquired electricity market data in a database.

[1155] Step 10:

[1156] The server runs an AI algorithm to generate an optimal electricity procurement plan based on the user's electricity usage data and market data.

[1157] Step 11:

[1158] The server activates an emotion engine and analyzes the user's emotional state based on their voice, facial expressions, text input, etc.

[1159] Step 12:

[1160] The server selects an optimal power procurement plan based on the user's emotional state and presents the plan to the user.

[1161] Step 13:

[1162] The user selects the most suitable plan from the multiple plans presented.

[1163] Step 14:

[1164] The server initiates an automated procedure for signing a contract for electricity supply based on the user's selection.

[1165] Step 15:

[1166] The server sends the necessary information and documents to the electricity supplier to complete the contract process.

[1167] Step 16:

[1168] The server notifies the user that the contract has been completed and provides monitoring information for future power usage.

[1169] Example 2

[1170] 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."

[1171] Conventional power procurement systems make it difficult for users without specialized knowledge to optimally procure power. Other issues include a lack of real-time information to respond quickly to fluctuations in the power market, and a lack of proposals that take into account the user's feelings. It is particularly difficult to propose plans that provide a sense of security to users who are feeling stressed.

[1172] 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.

[1173] In this invention, the server includes means for acquiring electricity usage data from a user, means for externally acquiring electricity market data in real time, means for generating an optimal electricity procurement plan based on the electricity usage data and the electricity market data using an AI algorithm, means for presenting the generated optimal electricity procurement plan to the user, means for adaptively presenting an electricity procurement plan based on the user's emotional state using an emotion engine that recognizes the user's emotional state, and means for automatically completing an electricity supply contract based on the user's selection. This enables a user to procure electricity optimally in response to fluctuations in the electricity market without requiring specialized knowledge, and further improves the user experience by providing suggestions that take emotions into consideration.

[1174] "Power usage data" refers to information about the amount of power consumed by a user in the past, including hourly consumption and peak consumption.

[1175] "Electricity Market Data" means real-time pricing and supplier information obtained from external electricity markets.

[1176] "AI algorithm" refers to a calculation method that uses artificial intelligence technology to perform complex data analysis and predictions, and in this system it is used to generate optimal electricity procurement plans.

[1177] An "emotion engine" is a technology that analyzes a user's emotional state based on their voice, facial expression, text input, etc., and evaluates their stress level, satisfaction level, etc.

[1178] "Power procurement plan" refers to a plan that proposes contract terms and prices for power supply that are suitable for users based on power consumption data and power market data.

[1179] "User" refers to general consumers or companies that aim to optimize their electricity procurement by using this system.

[1180] "External API" refers to an application program interface used to obtain data from external electricity markets.

[1181] "Database" refers to an information management system for storing and managing acquired and analyzed electricity usage data and electricity market data.

[1182] The present invention combines a system that enables users to optimally procure electricity without requiring specialized knowledge with an emotion engine that recognizes the user's emotions. This system is configured as follows.

[1183] First, users register for the first time using the system's website or application. This requires basic information such as name, address, and electricity company. Once registration is complete, users upload their past electricity consumption data. This data can be in CSV file format or obtained via API.

[1184] The server receives the electricity consumption data provided by the user, checks the data format and integrity, and then stores it in a database (e.g., MySQL). Next, it uses a Python-based data analysis module (e.g., Pandas or NumPy) to analyze the electricity consumption data and calculate monthly electricity consumption, peak hours, seasonal trends, and so on.

[1185] The server then uses external electricity market APIs (e.g., electricity market price API, renewable energy tracker API) to obtain real-time electricity market price and supplier data, which are also stored in the database.

[1186] Based on the stored electricity consumption data and market data, the server runs an AI algorithm (e.g., a TensorFlow model) to generate an optimal electricity procurement plan. The algorithm's goal is to minimize electricity costs and maximize the proportion of renewable energy used. The generated plan includes detailed recommendations based on the expected annual cost, the proportion of renewable energy used, and the user's electricity consumption pattern.

[1187] Furthermore, the system includes an emotion engine (e.g., Microsoft Azure Emotion API) to recognize the user's emotional state. The device collects the user's voice recordings, facial expression captures, and text input data and uploads these data to the system.

[1188] The server selects an electricity procurement plan that best suits the user's emotional state based on the emotion-analyzed data. For example, if the user is feeling stressed, the server will present a plan that includes suggestions for stress reduction. If the user is satisfied, the server will present a plan that uses more renewable energy.

[1189] After multiple electricity procurement plans are presented, the user selects the most suitable plan. Once the selection is complete, the server automatically completes the contract procedure with the electricity supplier and sends the necessary information and documents. This procedure allows the user to complete the complicated contract procedure hassle-free.

[1190] As a concrete example, in a household scenario, a user uploads their electricity usage history from the past year to the system, and the server retrieves market data and uses AI algorithms and an emotion engine to generate a plan that uses more than 50% renewable energy and reduces annual costs by 5%. Next, if the user is feeling emotionally stressed, the server uses that information to present a plan that gives them more peace of mind.

[1191] In a business scenario, a company uploads the past three years of electricity usage data, and the server uses an AI algorithm to generate a plan that increases nighttime electricity usage and maximizes solar power generation. When selecting this plan, an emotion engine checks whether the company's representative is emotionally satisfied and makes suggestions that will increase satisfaction.

[1192] Examples of prompts include specific instructions such as, "Based on the electricity consumption data from the past year, please suggest an electricity procurement plan that uses more than 50% renewable energy and reduces annual costs by 5%. Also, if the user's emotions are detected as stressed, please suggest a plan that provides a greater sense of security."

[1193] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1194] Step 1: First-time registration

[1195] Users access the system's website or application and register by entering basic information such as name, address, and electricity company. The information is sent to the server and stored in a database, which then generates a user ID and password and starts a protected session.

[1196] Input: Name, address, power company information

[1197] Output: User ID, registration completion notification

[1198] Step 2: Upload your electricity consumption data

[1199] Users upload historical electricity consumption data to the system, including data in CSV file format or obtained via API. The server checks the format and integrity of the received electricity consumption data before storing it in the database. If the format is correct, the data is saved.

[1200] Input: Power consumption history data (CSV file, etc.)

[1201] Output: Power consumption data stored in the database, consistency check message

[1202] Step 3: Analyze power consumption data

[1203] The server performs analysis using the stored power consumption data. It uses Python-based data analysis modules (e.g., Pandas and NumPy) to calculate monthly power consumption, peak hours, seasonal trends, etc. The results of this analysis are stored in a database.

[1204] Input: Power consumption data stored in the database

[1205] Output: Analysis result data (peak hours, monthly consumption, etc.)

[1206] Step 4: Obtaining external electricity market data

[1207] The server calls external electricity market APIs (e.g., electricity market price API, renewable energy tracker API) to obtain real-time electricity market price and supplier data. The obtained market data is stored in a database.

[1208] Input: A request to an external API

[1209] Output: Electricity market data (real-time prices, supplier information, etc.), stored in a database

[1210] Step 5: Generate an optimal power procurement plan

[1211] The server runs an AI algorithm (e.g., a TensorFlow model) to generate an optimal power procurement plan based on the stored power consumption analysis data and market data, aiming to minimize costs and maximize the use of renewable energy.

[1212] Input: Power consumption analysis data, power market data

[1213] Output: Optimal power procurement plan

[1214] Step 6: Collect and analyze emotion data

[1215] The device collects the user's voice recordings, facial expression captures, and text input data, and sends this data to a server, which uses an emotion engine (e.g., Microsoft Azure Emotion API) to analyze the user's emotional state.

[1216] Input: Voice data, facial expression data, text data

[1217] Output: Analyzed emotion data (stress, satisfaction, etc.)

[1218] Step 7: Adjust and present your plan based on emotions

[1219] The server then adjusts an optimal power procurement plan based on the emotion data and presents it to the user. For example, if the user is feeling stressed, the server presents a plan that includes suggestions for reducing stress. The device then displays the plan to the user through a web interface or application.

[1220] Input: Optimal power procurement plan, emotional data

[1221] Output: Present a coordinated power procurement plan

[1222] Step 8: User plan selection and final confirmation

[1223] The user selects the most suitable plan from the multiple electricity procurement plans presented. Once the selection is complete, a confirmation screen is displayed for final confirmation.

[1224] Input: Multiple power procurement plans

[1225] Output: Selected plan, final confirmation notice

[1226] Step 9: Execute automated procedures

[1227] The server automatically completes the contract with the electricity supplier based on the selected plan, sending the necessary information and documents to complete the contract. This allows users to complete the complicated contract procedures without any hassle.

[1228] Input: Selected plan

[1229] Output: Sending contract documents, contract completion notification

[1230] (Application example 2)

[1231] 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."

[1232] The present invention relates to a system that enables users to optimally procure power without specialized knowledge. In particular, the objective is to optimize power procurement plans by taking into account the user's emotional state, thereby improving user satisfaction. Conventional systems lack a function that takes into account the user's emotional state, and therefore have the problem of not fully improving the user experience. Furthermore, factory workers also require convenience from the devices they use, so a method for efficient power management is necessary.

[1233] 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.

[1234] In this invention, the server includes means for acquiring power usage data from a user, means for externally acquiring power market data in real time, means for generating an optimal power procurement plan based on the power usage data and the power market data using an AI algorithm, means for presenting the generated optimal power procurement plan to the user, means for automatically completing a power supply contract based on the user's selection, means for analyzing the user's emotional state and reflecting it in the optimal power procurement plan, and means for displaying the optimal power procurement plan on the smart glasses, thereby supporting optimal power procurement taking user emotions into consideration and enabling people, particularly factory workers, to efficiently manage power in real time.

[1235] "User" means a person or organization that uses the System.

[1236] "Power usage data" is data regarding a user's past and current power consumption.

[1237] "Acquiring in real time" means acquiring data instantly that reflects the current situation.

[1238] "Electricity market data" refers to data relating to the market price and supply status of electricity.

[1239] An "AI algorithm" is a program that uses artificial intelligence technology to analyze data and derive optimal results.

[1240] An "optimal power procurement plan" is a power procurement plan that optimizes power consumption costs and the use of renewable energy.

[1241] "Presenting to the user" means showing the generated plan to the user.

[1242] "Automatically proceeding" means automating a manual operation without requiring user intervention.

[1243] "Emotional state" refers to the user's current psychological and emotional state.

[1244] "Smart glasses" are a wearable eyeglass-type device equipped with a display function.

[1245] The present invention provides a system that enables users to optimally procure electricity without requiring specialized knowledge, and further combines it with an emotion engine that recognizes the user's emotional state. This system aims to present optimal electricity procurement plans using smart glasses, particularly for factory workers. Specific embodiments of the system are described below.

[1246] First, the user provides their own electricity consumption data. The user accesses the system's website or application and enters the required information to register for the first time. After registration, the user uploads their electricity usage history data to the system. This includes past electricity consumption history and data provided by the power company. The user is responsible for inputting this data from their terminal.

[1247] The server retrieves the electricity consumption data provided by users and stores it in a database. The main software used here is a database management system (e.g., MySQL) and a data analysis tool (e.g., Python's NumPy library). It also uses an external API to retrieve real-time electricity market data. Real-time electricity market prices and renewable energy supplier data are retrieved through the external API. This market data is also stored in the database.

[1248] The server then runs an AI algorithm to generate an optimal electricity procurement plan based on the electricity consumption data and market data. The AI ​​algorithm aims to minimize costs and maximize the proportion of renewable energy. The AI ​​technology used includes machine learning libraries (e.g., scikit-learn).

[1249] Furthermore, this system incorporates an emotion engine to recognize the user's emotional state. The emotion engine analyzes the user's emotional state based on their voice, facial expressions, text input, etc. Specifically, it uses a facial recognition library (e.g., dlib) and a pre-trained emotion classification model (e.g., emotion_classifier.pkl). The server uses the emotion engine to identify the user's emotional state and adaptively presents an electricity procurement plan based on that information.

[1250] The user's device (smart glasses) displays the generated optimal electricity procurement plan. The smart glasses are equipped with a display function and can present the optimal plan to the user in real time. The user reviews the proposed electricity procurement plans and selects the optimal one. Based on the selected plan, the server executes an automated procedure and sends the necessary information and documents to complete the contract with the electricity supplier.

[1251] As a concrete example, consider a situation where a factory worker is working using smart glasses. The worker uploads his or her electricity usage history from the past year to the system as power consumption data. The server then retrieves market data and uses an AI algorithm and emotion engine to generate a plan that uses more than 50% renewable energy and reduces annual costs by 5%. If the worker is feeling stressed, the emotion engine detects this and the server presents a plan that provides a greater sense of security.

[1252] An example of a prompt for a generative AI model could be, "Based on my current electricity usage data and market price data, please suggest the best electricity plan for me when I'm feeling stressed."

[1253] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1254] Step 1:

[1255] Users access the system's website or application and register for the first time. At this time, users enter basic information and upload their own electricity usage history data to the system. The input data includes past electricity consumption history and data provided by the power company. This data is sent from the terminal to the server.

[1256] Step 2:

[1257] The server acquires the power consumption data provided by the user and stores it in a database. This data includes past monthly consumption amounts, daily peak consumption times, etc. The server uses a database management system to effectively manage and store this data. This data will be used for later analysis.

[1258] Step 3:

[1259] The server uses an external API to retrieve real-time electricity market data. The API calls retrieve real-time electricity market prices and renewable energy supplier data. This market data is also stored in the database. The market data is retrieved periodically, and new data is constantly updated.

[1260] Step 4:

[1261] The server runs an AI algorithm and performs data analysis based on the acquired power consumption data and market data. This analysis takes into account past consumption patterns (e.g., peak times and seasonal fluctuations) and current market prices, aiming to minimize costs and maximize the proportion of renewable energy. The results of this analysis are used to generate an optimal power procurement plan.

[1262] Step 5:

[1263] The server analyzes the user's emotional state using an emotion engine. The emotion engine detects emotions based on data such as the user's voice, facial expressions, and text input. This process utilizes a facial recognition library (e.g., dlib) and pre-trained emotion classification models. The user's emotional state (e.g., satisfaction, stress) is determined.

[1264] Step 6:

[1265] The server adaptively adjusts the optimal power procurement plan based on the user's emotional state detected by the emotion engine. For example, if the user is feeling stressed, the plan is adjusted to one that brings a sense of security. The adjusted plan is then saved back in the database.

[1266] Step 7:

[1267] The server presents the generated and adjusted optimal electricity procurement plan to the user. This information is displayed in real time on the user's smart glasses. The user can then review multiple plans on the smart glasses' display and select the optimal plan. The selection result is then sent to the server.

[1268] Step 8:

[1269] The server executes the automated procedures based on the electricity procurement plan selected by the user, including generating and sending the necessary information and documents to complete the contract with the electricity supplier. After completing the procedures, the server sends a notification message to the user's device.

[1270] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice 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 voice data.

[1271] 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.

[1272] 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 robot 414.

[1273] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1274] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1275] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1276] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1277] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1278] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1279] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1280] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1281] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1282] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1283] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1284] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1285] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1286] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1287] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1288] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1289] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1290] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1291] The following is further disclosed regarding the above embodiment.

[1292] (Claim 1)

[1293] means for acquiring power usage data from a user;

[1294] A means for externally obtaining real-time electricity market data;

[1295] a means for generating an optimal electricity procurement plan based on the electricity usage data and the electricity market data using an AI algorithm;

[1296] a means for presenting the generated optimal power procurement plan to a user;

[1297] means for automatically processing an electricity supply contract based on a user selection;

[1298] A system including:

[1299] (Claim 2)

[1300] 10. The system according to claim 1, further comprising means for obtaining historical power consumption data from the user as the power usage data.

[1301] (Claim 3)

[1302] 10. The system of claim 1, further comprising means for using a web interface or application to present an optimal power procurement plan to a user.

[1303] "Example 1"

[1304] (Claim 1)

[1305] means for acquiring power usage data from a user;

[1306] A means for externally obtaining real-time electricity market data;

[1307] a means for generating an optimal electricity procurement plan based on the electricity usage data and the electricity market data using an AI algorithm;

[1308] a means for presenting the generated optimal power procurement plan to a user;

[1309] means for automatically processing an electricity supply contract based on a user selection;

[1310] means for storing electricity usage data and electricity market data in a database;

[1311] using an analysis module to calculate average, peak and seasonal variations in electricity consumption;

[1312] means for displaying an optimal electricity procurement plan to a user using a web interface or application;

[1313] A system including:

[1314] (Claim 2)

[1315] 10. The system according to claim 1, further comprising means for obtaining historical power consumption data from the user as the power usage data.

[1316] (Claim 3)

[1317] 10. The system of claim 1, further comprising a database that securely stores user information based on user input.

[1318] "Application Example 1"

[1319] (Claim 1)

[1320] means for acquiring power usage data from a user;

[1321] A means for externally obtaining real-time electricity market data;

[1322] a means for generating an optimal electricity procurement plan based on the electricity usage data and the electricity market data using an AI algorithm;

[1323] a means for presenting the generated optimal power procurement plan to a user;

[1324] means for automatically processing an electricity supply contract based on a user selection;

[1325] A means for analyzing the electricity consumption data and market data and presenting multiple electricity procurement plans to an operation manager of the autonomous vehicle;

[1326] A means for automatically entering into a contract with an electricity supplier based on the plan selected by the operator;

[1327] A system including:

[1328] (Claim 2)

[1329] 10. The system according to claim 1, further comprising means for obtaining historical power consumption data from the user as the power usage data.

[1330] (Claim 3)

[1331] 10. The system of claim 1, further comprising means for using a web interface or application to present an optimal power procurement plan to a user.

[1332] (Claim 4)

[1333] The system of claim 1 further includes means for managing power consumption data of a plurality of autonomous vehicles, presenting an optimized power procurement plan to an operation manager via a head-mounted display, and automatically carrying out contract procedures based on the selected plan.

[1334] "Example 2: Combining Emotion Engines"

[1335] (Claim 1)

[1336] means for acquiring power usage data from a user;

[1337] A means for externally obtaining real-time electricity market data;

[1338] a means for generating an optimal electricity procurement plan based on the electricity usage data and the electricity market data using an AI algorithm;

[1339] a means for presenting the generated optimal power procurement plan to a user;

[1340] a means for adaptively presenting an electricity procurement plan based on the user's emotional state using an emotion engine that recognizes the user's emotional state;

[1341] means for automatically processing an electricity supply contract based on a user selection;

[1342] A system including:

[1343] (Claim 2)

[1344] 10. The system according to claim 1, further comprising means for obtaining historical power consumption data from the user as the power usage data.

[1345] (Claim 3)

[1346] 10. The system of claim 1, further comprising means for using a web interface or application to present an optimal power procurement plan to a user.

[1347] "Application example 2 when combining emotion engines"

[1348] (Claim 1)

[1349] means for acquiring power usage data from a user;

[1350] A means for externally obtaining real-time electricity market data;

[1351] a means for generating an optimal electricity procurement plan based on the electricity usage data and the electricity market data using an AI algorithm;

[1352] a means for presenting the generated optimal power procurement plan to a user;

[1353] means for automatically processing an electricity supply contract based on a user selection;

[1354] A means for analyzing the user's emotional state and reflecting it in the optimal power procurement plan;

[1355] A means for displaying the optimal power procurement plan for smart glasses;

[1356] A system including:

[1357] (Claim 2)

[1358] 10. The system according to claim 1, further comprising means for obtaining historical power consumption data from the user as the power usage data.

[1359] (Claim 3)

[1360] 10. The system of claim 1, further comprising means for using a web interface or application to present an optimal power procurement plan to a user. [Explanation of symbols]

[1361] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for acquiring power usage data from a user; A means for externally obtaining real-time electricity market data; a means for generating an optimal electricity procurement plan based on the electricity usage data and the electricity market data using an AI algorithm; a means for presenting the generated optimal power procurement plan to a user; means for automatically processing an electricity supply contract based on a user selection; A system including:

2. The system according to claim 1 , further comprising means for acquiring historical power consumption data from the user as the power usage data.

3. The system of claim 1 further comprising means for using a web interface or application to present an optimal power procurement plan to a user.

Images