system

Abstract

Provide a system. 【Solution means】 Means for managing exchange information using blockchain technology, Means for analyzing past consumption records and external environment records, Artificial intelligence agent means for setting values in real time based on the analysis results, Means for presenting and receiving confirmation of exchange conditions between users, Means for executing the exchange and recording the completion, Means for registering the supply and demand of surplus energy through a terminal device, Artificial intelligence agent means for generating and presenting appropriate conditions for supply and demand, A system including.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] With the expansion of the use of renewable energy, effective and efficient trading of surplus power is required. However, in the conventional power trading system, problems such as imbalance between demand and supply and opacity of transactions have arisen. As a result, it is difficult to optimize transactions and insufficient benefits are brought to participants. In addition, there are also risks of fraud and data tampering related to transactions.

Means for Solving the Problems

[0005] This invention provides a system for securely and transparently managing transaction information using blockchain technology. This system includes means for analyzing historical consumption data and external environmental data to forecast demand. Furthermore, an artificial intelligence agent optimizes transactions by setting prices in real time based on the analysis results. This agent also automatically presents transaction conditions between users and selects the most suitable trading partner. This promotes the effective use of surplus electricity and improves the fairness and efficiency of transactions.

[0006] Blockchain technology is a technology that encrypts data on a decentralized network and records it as a series of blocks, making it difficult to tamper with.

[0007] "Transaction information" refers to data related to the buying and selling of electricity, including details such as transaction volume, price, and participants.

[0008] "Consumption data" refers to data on the electricity consumed by a specific household or business over a certain period, including information such as the amount of electricity and the time of use.

[0009] "External environmental data" refers to data on environmental factors that affect electricity demand and supply, specifically including information such as weather, temperature, and sunshine duration.

[0010] An "artificial intelligence agent" is a program that operates autonomously based on certain rules and algorithms, performing tasks such as demand forecasting and pricing.

[0011] "Transaction terms" refer to the specific agreed-upon conditions for the buying and selling of electricity, and include elements such as price, quantity, and implementation timing.

[0012] "Demand forecasting" is the process of predicting electricity demand for a certain period in the future, and is carried out using historical consumption data and external environmental data.

[0013] "Setting prices in real time" refers to a process where prices are updated as needed, in accordance with market conditions and the balance of supply and demand.

[0014] A "trading partner" refers to a party with whom electricity is bought and sold, and this party is selected by the system. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), etc.

[0019] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] As shown in Figure 1, the 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.

[0026] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0035] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0036] This invention is a power trading platform that combines blockchain technology and artificial intelligence, aiming to efficiently utilize surplus renewable energy. The system includes a communication network between terminals, servers, and users.

[0037] Users input surplus electricity information using their devices and send it to the server. This information includes the amount of electricity generated, the expected supply time, and the desired selling price. Based on the received information, the server securely registers the tradable electricity information on the blockchain. This ensures that the information is difficult to tamper with.

[0038] The server has the capability to automatically collect and analyze historical consumption data and external environmental data. Based on this analysis data, an AI agent predicts electricity demand in real time and automatically sets the optimal transaction price that meets the requirements of both the supply and demand sides. This process adjusts the pricing to adapt to market fluctuations.

[0039] Furthermore, the AI ​​agent selects trading partners via the server, taking into account various factors such as geographical conditions, the degree of supply-demand matching, and transaction history. Users receive the transaction terms via their terminal and decide whether to agree. Once an agreement is reached, the transaction is executed by the server, and the movement of electricity and settlement information are accurately recorded.

[0040] As a concrete example, consider a case where person A, who owns a home solar power generation system, sells the surplus electricity generated during the day to person B, who has demand for it at night. Person A registers the amount of electricity they can provide and their desired price in the system via a terminal. The server uses this information to present the best transaction terms to person B, the demander. If person B agrees, the server executes the transaction and records the transaction history on the blockchain. This ensures that transactions between both parties are conducted fairly and efficiently.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The terminal receives user input and displays information about surplus power on the input screen. The user enters the amount of power available, the desired selling price, and the service period, and then sends this data to the server.

[0044] Step 2:

[0045] The server analyzes the transaction information received from the terminal, assigns an identifier, and records it on the blockchain. This guarantees the authenticity and immutability of the information.

[0046] Step 3:

[0047] The server periodically collects historical consumption data and external environmental data from a database and provides it to the AI ​​agent. This data forms the basis for demand forecasting.

[0048] Step 4:

[0049] An AI agent analyzes data collected on the server to predict future electricity demand. Based on the prediction, it calculates the optimal transaction price in real time and transmits that information to the server.

[0050] Step 5:

[0051] The server selects trading partners based on price information and transaction conditions received from the AI ​​agent. The selection process takes into account factors such as the user's location, supply, and demand to achieve the optimal pairing.

[0052] Step 6:

[0053] The terminal displays the transaction terms notified by the server to the user and requests confirmation of approval. If the user agrees to the terms, the terminal sends an approval response to the server.

[0054] Step 7:

[0055] The server executes the transaction after confirming the user's consent. The process is handled securely and transparently by initiating the power supply and payment procedures and recording the completion information of the transaction on the blockchain.

[0056] Step 8:

[0057] The terminal receives a transaction completion notification from the server and informs the user that the transaction has been successfully completed. The user can then check their transaction history on the terminal.

[0058] (Example 1)

[0059] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0060] As the use of renewable energy increases, a platform is needed for the efficient and fair trading of surplus electricity. However, current systems have problems such as concerns about the falsification of trading information and difficulties in setting fair prices in real time. Furthermore, there is a need for efficient methods for selecting trading partners.

[0061] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0062] In this invention, the server includes means for managing transaction information using blockchain technology, means for analyzing past consumption data and external environmental data, means for an artificial intelligence agent that sets prices in real time based on the analysis results, and means for selecting trading partners based on geographical conditions and matching degree. This ensures the reliability of transactions while enabling pricing that quickly adapts to market fluctuations and efficient selection of trading partners.

[0063] Blockchain technology is a distributed ledger technology that records transaction information in a chain-like structure, preventing tampering.

[0064] "Means for managing transaction information" refers to a system that records, updates, and allows reference to buying and selling data in electricity transactions as needed.

[0065] "Past consumption data and external environmental data" refers to past electricity usage history, as well as data related to the environment, such as weather and temperature.

[0066] "Methods of analysis" refer to analytical techniques that use collected data to discover patterns and trends and predict electricity demand.

[0067] An "artificial intelligence agent" is a program that uses machine learning and data analysis to make decisions and provide optimized information.

[0068] "Setting in real time" means that calculations are performed instantly every time the data is updated, and settings are automatically adjusted according to the fluctuating conditions.

[0069] "Methods for selecting trading partners based on geographical conditions and matching degree" refers to methods for finding the optimal trading partner by considering factors such as distance and the rate of supply-demand matching.

[0070] This invention aims to build a power trading platform that combines blockchain technology and artificial intelligence. It primarily functions as a server, terminal, and user system.

[0071] Server Role

[0072] The server receives surplus power information sent by users and manages it securely using blockchain technology. The server maintains a distributed ledger for data integration and analysis, preventing tampering. Furthermore, the server collects external environmental data (such as weather and temperature) and historical power consumption data via APIs. This data is used for demand forecasting by an AI agent.

[0073] Terminal role

[0074] Users input information about their surplus electricity using a terminal. The terminal transmits this information to the server, and the usability of the interface is crucial. The terminal also presents and confirms transaction terms.

[0075] User roles

[0076] Users play the role of either supplying or demanding electricity, and provide information about surplus electricity and trading requests through their terminals. It is also the user's responsibility to review the presented trading terms and decide whether to agree to them.

[0077] Hardware and software to be used

[0078] The server will utilize a high-performance computer system suitable for data processing, along with specialized software to support blockchain and AI analysis. Specifically, it will use an open-source blockchain platform for blockchain management and machine learning libraries for AI analysis. The terminals will be smartphones and tablets owned by users, running a dedicated application.

[0079] Specific example

[0080] A concrete example is a user with a solar power generation system at home who sells surplus electricity generated during the day to a specific user with high demand at night. In this case, the user selling the electricity registers the amount of electricity and their desired price in the system using a terminal, and the optimal transaction is executed through the server.

[0081] Example of a prompt:

[0082] "I want to design a platform for efficiently trading surplus renewable energy. How can we combine blockchain technology with AI?"

[0083] "How can we build an efficient system for selling surplus electricity generated by home solar power systems?"

[0084] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0085] Step 1:

[0086] Users input surplus power information using their own devices. Specifically, they open a dedicated application on their devices and input data such as power generation amount, available supply time, and desired selling price. The entered data is sent from the device to the server. This allows the server to store detailed information about the amount of electricity the user can provide.

[0087] Step 2:

[0088] The server receives surplus power information from users and registers the data on the blockchain. At this time, the server encrypts the received data and transmits it to the blockchain network using a secure communication protocol. This prevents data tampering and ensures reliability. As a result, the accuracy and security of the registered data are guaranteed by the blockchain.

[0089] Step 3:

[0090] The server collects external environmental data and historical power consumption data. This data includes temperature, weather, and regional power consumption patterns. The server retrieves this data using an API and stores it in a database for AI analysis. Based on the obtained data, AI-driven demand forecasting becomes possible in subsequent steps.

[0091] Step 4:

[0092] An AI agent performs analysis using data collected on the server. Here, primarily using machine learning algorithms, it predicts electricity demand in real time. The goal is to analyze the input data as a multidimensional vector and understand demand trends. The analysis results help optimize the transaction terms offered to users.

[0093] Step 5:

[0094] The server sets the transaction price based on the analysis results of the AI ​​agent. In this step, it calculates the optimal price that reflects the real-time supply and demand balance of the market. The AI ​​model considers past price fluctuations and uses an algorithm to determine a fair and competitive price. The set price is then reflected in transactions between users.

[0095] Step 6:

[0096] The server selects trading partners based on recommendations from the AI ​​agent. The selection process considers geographical conditions and the degree of supply-demand matching. The server scores this information and selects high-scoring trading candidates. This selection is a crucial element for achieving efficient and effective transactions.

[0097] Step 7:

[0098] The user reviews the transaction terms presented via their terminal. Information such as the trading partner, transaction price, and delivery time is displayed. The user selects whether to agree to the terms and sends their selection back to the server from their terminal. This process leads to a final transaction agreement.

[0099] Step 8:

[0100] Once the terms of the transaction are agreed upon, the server executes the transaction. Upon execution, the transfer of electricity begins, and the server generates settlement information. This information is registered on the blockchain as a transaction history, ensuring the integrity and transparency of the transaction.

[0101] (Application Example 1)

[0102] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0103] A trading platform for efficiently and fairly utilizing surplus renewable energy is underdeveloped, and the current system is prone to supply-demand imbalances. Furthermore, ensuring transparency and reliability of trading information is difficult, potentially leading to unfair transactions. In addition, there is a need for the real-time presentation of appropriate trading conditions.

[0104] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0105] In this invention, the server includes means for managing exchange information using blockchain technology, means for analyzing past consumption records and external environment records, artificial intelligence agent means for setting values ​​in real time based on the analysis results, means for presenting and receiving confirmation of exchange conditions between users, means for executing exchanges and recording their completion, means for registering the supply and demand of surplus energy through terminal devices, and artificial intelligence agent means for generating and presenting appropriate supply and demand conditions. This enables the efficient trading of surplus renewable energy and provides a fair and reliable platform.

[0106] Blockchain technology is a technology that securely records transaction information on a distributed ledger using cryptographic techniques.

[0107] "Exchange information" refers to information that includes data such as supply, demand, and price related to energy trading.

[0108] "Past consumption records" refer to historical data on energy consumption in the past.

[0109] "External environmental records" refer to data on external factors that affect energy demand and supply, such as weather conditions and market trends.

[0110] An "artificial intelligence agent" is a software agent that autonomously assesses its environment and makes decisions according to a specific purpose.

[0111] "Exchange terms between users" refer to the conditions for conducting a transaction, such as price and supply time.

[0112] A "terminal device" refers to an electronic device used by a user, such as a computer or smartphone.

[0113] "Surplus energy" refers to the portion of renewable energy generation that is not consumed and is left over.

[0114] "Appropriate supply and demand conditions" refer to the most efficient and beneficial trading conditions for both energy suppliers and consumers.

[0115] This invention is a system designed to efficiently trade surplus renewable energy. The system primarily utilizes a server, user terminal devices, and a communication network.

[0116] The server securely manages transaction information using blockchain technology. The database stores each user's past consumption records and external environment records, and an artificial intelligence agent is used to analyze this data. This analysis enables demand forecasting for power supply and generates optimal transaction conditions in real time.

[0117] The terminal device is used by users to register their surplus renewable energy and confirm transaction terms. By inputting information on the supply and demand of surplus energy through the terminal, an artificial intelligence agent presents appropriate transaction terms based on that information. If an agreement is reached, the transaction is automatically executed.

[0118] As a concrete example, consider a situation where one user generates surplus renewable energy during the day, and another user wants to use that energy at night. In this case, the server uses AI to generate and present the optimal transaction terms for both parties.

[0119] The hardware required for the system to operate includes data center facilities as servers, smartphones as user terminals, and internet connectivity. The software used includes Ethereum for blockchain, Tensorflow® for AI models, and Pandas for data analysis.

[0120] An example of a prompt statement a user could ask the generated AI model: "How can we optimize the overall power efficiency of a city by sharing renewable energy through a smart energy sharing app?"

[0121] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0122] Step 1:

[0123] Users input information about their surplus energy supply using their own devices. This input includes the amount of energy available, the estimated supply time, and the desired price. This information is transmitted from the device to the server. The input data is processed as basic numerical data.

[0124] Step 2:

[0125] The server registers transaction information on the blockchain based on the received data. The use of blockchain prevents data tampering and maintains security. The input is transaction information from the user, and the output is a transaction history securely recorded on the blockchain.

[0126] Step 3:

[0127] The server collects historical consumption records and external environmental records from a database and performs data analysis based on these. An AI model (using TensorFlow) is used to predict the optimal conditions for both supply and demand. The input is historical consumption and environmental data, and the output is the predicted optimal transaction conditions.

[0128] Step 4:

[0129] The AI ​​agent automatically sets transaction conditions between users based on the optimal conditions obtained through analysis and presents them to the user via the terminal. In this process, user input information and the results of the AI ​​analysis are combined to generate prompt sentences for presenting the conditions. The input is the analysis results, and the output is the presented transaction conditions.

[0130] Step 5:

[0131] The user reviews the transaction terms on their device and chooses to agree or reject them. The input here is the user's response to the presented terms, and the output is the result of the user's selection. If the user agrees, the process proceeds to the next step.

[0132] Step 6:

[0133] The server executes the transaction with the user's consent. After the transaction is completed, it adds this transaction record to the blockchain to maintain data reliability. The input is the user's consent and approval, and the output is the newly recorded transaction history.

[0134] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0135] This invention is a power trading platform that combines blockchain technology, artificial intelligence, and an emotion engine. It not only efficiently utilizes surplus renewable energy but also provides flexible trading that takes into account the user's emotional state. The system consists of a user terminal, a server, and an emotion engine.

[0136] The user inputs information about surplus power through their device and sends it to the server. The device is equipped with input devices such as a camera and microphone, and an emotion engine analyzes the user's facial expressions and voice to determine their emotional state. The analysis results can generate data representing the user's current emotional state (e.g., reassurance, tension, anxiety).

[0137] The server processes electricity consumption and sentiment data received from users and records transaction information on the blockchain. This enables management in a way that makes it difficult to tamper with the information. Furthermore, the server collects historical consumption data and external environmental data in real time and analyzes it through an AI agent. This analysis enables future electricity demand forecasting and the setting of optimal prices.

[0138] The AI ​​agent adjusts trading conditions based on the user's emotional data, proposing trades in a way that does not stress the user. If the user is relaxed, it will present the information in a normal interface; if the user is stressed, it will reduce the amount of information and present a simpler interface.

[0139] For example, when user A offers surplus solar power, if the emotion engine detects that A is slightly stressed, the server will concisely summarize and display the transaction terms. Furthermore, the proposed transaction terms can be slightly conservative, as suggested by the AI ​​agent to alleviate A's stress. This allows A to confidently agree to the terms. Once the transaction is agreed upon, the server records the transaction on the blockchain and sends a notification to the terminal. In this way, fair and efficient transactions can be achieved while taking the user's emotional state into consideration.

[0140] The following describes the processing flow.

[0141] Step 1:

[0142] The terminal receives user input and displays information about surplus electricity (generation amount, availability time, desired price) on the input screen. The user enters this information and sends it to the system.

[0143] Step 2:

[0144] The device's camera and microphone capture the user's facial expressions and voice, and the emotion engine analyzes this data. The analysis generates data on the user's emotional state (e.g., feeling safe, tense, anxious).

[0145] Step 3:

[0146] The server analyzes surplus power information and sentiment data received from the terminals and generates transaction information for use in power trading. This information is recorded on the blockchain to ensure security and transparency.

[0147] Step 4:

[0148] The server collects historical consumption data and external environmental data and provides it to the AI ​​agent. Based on this data, the AI ​​agent predicts electricity demand and calculates the optimal transaction price in real time.

[0149] Step 5:

[0150] The AI ​​agent considers the user's emotional state and adjusts the trading conditions accordingly. If it determines that the user is stressed, the AI ​​agent presents the trading conditions using a simple and easy-to-understand interface.

[0151] Step 6:

[0152] The terminal displays the transaction terms obtained from the server to the user and requests the user's approval. If the user agrees to the proposed terms, the terminal sends the approval to the server.

[0153] Step 7:

[0154] Once the server confirms the user's consent, the transaction is formally executed. Information regarding the supply of electricity and the settlement of its payment is recorded on the blockchain to maintain transaction transparency.

[0155] Step 8:

[0156] The terminal receives a transaction completion notification from the server and informs the user that the transaction has been successfully completed. The user can then check the transaction history on the terminal and confidently exit the system.

[0157] (Example 2)

[0158] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0159] Traditional electricity trading systems offered fixed interfaces and trading conditions without considering the emotional aspects of users, potentially leading to user stress and dissatisfaction. Furthermore, they carried the risk of tampering and fraudulent activity regarding trading information.

[0160] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0161] In this invention, the server includes means for managing transaction information using blockchain technology, means for analyzing past consumption data and external environment data, and emotion engine means for analyzing the user's emotional state. This enables fair and user-friendly transactions by managing tamper-proof transaction information while taking the user's emotional state into consideration.

[0162] Blockchain is a database technology that records multiple transaction details in a chain of blocks, making it extremely difficult to tamper with on a decentralized network.

[0163] An "artificial intelligence agent" is a software system that autonomously determines and adjusts trading conditions based on data analysis and provides optimized information.

[0164] An "emotion engine" is an algorithm and system that analyzes a user's facial expressions and voice data to identify their emotional state.

[0165] A "user" is an individual or entity that inputs information about the supply or demand of electricity into the system and participates in the trading process.

[0166] "Transaction information" refers to a series of data related to the buying and selling of electricity, including details about the amount of electricity, price, time, and the parties involved in the transaction.

[0167] This invention relates to a power trading platform that combines blockchain technology, artificial intelligence, and an emotion engine, which not only efficiently trades surplus renewable energy but also provides flexible trading that takes into account the emotional state of the user.

[0168] The user transmits information about surplus electricity obtained from renewable energy sources to a server via a device. This device has built-in input devices such as a camera and microphone, which collect the user's facial expressions and voice. The emotion engine analyzes this data to identify the user's emotional state, such as feeling relaxed or anxious.

[0169] The server processes data based on electricity information received from users and analyzed sentiment data, and records the results on the blockchain. This makes it difficult to tamper with transaction information. The server also collects historical electricity consumption data and external environmental data such as weather in real time, and an AI agent performs demand forecasting and pricing. This AI agent adjusts transaction conditions based on the user's sentiment state, providing an interface that allows for stress-free transactions.

[0170] For example, if a user attempts to supply surplus electricity generated by solar power, and the emotion engine detects a state of tension, the server will simplify the transaction conditions and the AI ​​agent will propose more conservative conditions to ensure the user can agree to the transaction with confidence. As a result of this process, once the transaction is completed, the server records the completion on the blockchain and notifies the user.

[0171] Examples of prompt statements to input into a generative AI model are as follows:

[0172] "Use user sentiment data and power trading information to generate optimal trading conditions for the user. For example, suggest conservative conditions if the user is stressed, and provide normal conditions if the user is relaxed."

[0173] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0174] Step 1:

[0175] Users input information about surplus electricity obtained from renewable energy sources using a terminal. Specifically, they input data such as the amount of electricity that can be supplied, the desired price, and the time period during which transactions are possible. This information becomes input data and is sent to the server.

[0176] Step 2:

[0177] The system uses the camera and microphone on the user's device to collect the user's facial expressions and voice. This data is then used as input by an emotion engine to analyze the user's emotional state. The output from this analysis is quantified as data representing the user's emotional state, such as feeling safe, tense, or anxious.

[0178] Step 3:

[0179] The terminal combines power information entered by the user with emotional data analyzed by the emotion engine and sends this to the server. The resulting dataset is then passed to the server.

[0180] Step 4:

[0181] The server processes the received power and sentiment data, and first records the transaction information on the blockchain. This ensures that the information is managed in a way that makes tampering difficult. By using blockchain technology for the input dataset, highly reliable output data is accumulated.

[0182] Step 5:

[0183] The server collects historical consumption data and external environmental data in real time. This collected data is analyzed by an AI agent. The analyzed output is used to forecast future electricity demand and set optimal prices.

[0184] Step 6:

[0185] The AI ​​agent adjusts and proposes trading conditions tailored to the user based on the analysis results and the user's emotional data. If the user is stressed, the proposed output conditions will be more conservative and concise than usual. Conversely, if the user is relaxed, detailed trading conditions will be presented.

[0186] Step 7:

[0187] Once the user agrees to the presented transaction terms, the server executes the transaction based on those terms. The resulting transaction completion data is output and recorded on the blockchain. Finally, a transaction completion notification is sent to the terminal.

[0188] (Application Example 2)

[0189] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0190] As the use of renewable energy increases, there is a need for efficient trading of surplus electricity. However, conventional trading systems often cause stress to users because they present conditions without considering their psychological state. Furthermore, systems with insufficient transparency and security can undermine the reliability of transactions. There is a need to solve these problems and provide a more user-friendly and reliable electricity trading platform.

[0191] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0192] In this invention, the server includes means for managing transaction information using blockchain technology, means for analyzing past consumption data and external environment data, artificial intelligence agent means for setting prices in real time based on the analysis results, emotion engine means for analyzing the user's emotional state, and means for dynamically adjusting transaction conditions based on the user's emotional state. This makes it possible to realize flexible and transparent transactions that respond to the user's emotions and ensure reliability.

[0193] Blockchain technology is a method that records data on a distributed ledger and uses cryptographic techniques to prevent unauthorized tampering.

[0194] "Transaction information" refers to various data related to electricity buying and selling transactions, including transaction terms and agreements.

[0195] "Consumption data" refers to records of past electricity usage.

[0196] "External environmental data" refers to information about external factors that affect transactions, such as weather and market trends.

[0197] An "artificial intelligence agent" is a program that analyzes data to make optimal decisions.

[0198] An "emotion engine" is a system that analyzes a user's emotional state and generates data based on the results.

[0199] An "interface" refers to the screens and input methods that a user uses to interact with a system.

[0200] "User emotional state" refers to the user's mental state, such as feeling safe, tense, or anxious.

[0201] "Terms of trade" refer to the price and other conditions agreed upon between the parties in the buying and selling of electricity.

[0202] To implement this invention, it is necessary to build a system that integrates a server, a user terminal, and an emotion engine. This system efficiently and securely conducts electricity trading while taking into account the user's emotional state. The user terminal includes input devices such as a camera and a microphone, which the emotion engine uses to analyze the user's facial expressions and voice. The server manages transaction information using blockchain technology and uses an artificial intelligence agent to analyze consumption data and external environmental data.

[0203] When a user participates in selling surplus electricity via their smartphone, the device acquires emotional data from its camera and microphone and sends the analysis results to a server. Based on this information, the server uses an AI agent to dynamically set transaction conditions that are tailored to the user's emotional state. If the user agrees to the transaction conditions, the server records this information on the blockchain in a way that makes it difficult to tamper with. As a result, users can trade with peace of mind under conditions optimized for their own emotional state.

[0204] As a concrete example, consider a scenario where a user, while spending a holiday at home, provides surplus electricity generated from their rooftop solar power system to the surrounding community. In this case, the transaction terms are displayed on the screen in a format that is easiest for the user to understand. This allows the user to participate in the transaction without feeling any anxiety.

[0205] An example of a prompt from a generated AI model might be: "Please describe in detail the requirements necessary to build a superior energy trading platform, including flexible trading conditions based on the user's emotional state and secure trading using blockchain."

[0206] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0207] Step 1:

[0208] The device uses its camera and microphone to capture the user's facial expressions and voice as input data. This input information is sent to an emotion engine, which analyzes the user's emotional state. The emotion engine analyzes the input data and outputs emotion data representing emotional states such as reassurance, tension, and anxiety.

[0209] Step 2:

[0210] The terminal sends emotional data obtained from the emotion engine to the server. The server then receives the user's current emotional state and stores it for use in the next step. Based on the emotional data, the server weights it within the system and prepares to present transaction terms that are less burdensome for the user.

[0211] Step 3:

[0212] The server collects historical consumption data and external environmental data, and analyzes it through an artificial intelligence agent. Based on the input consumption data and external environmental data, it performs demand forecasting and pricing, and generates the results as output. This prepares the server for use in generating transaction conditions in the next step.

[0213] Step 4:

[0214] The server integrates analysis results and sentiment data, and uses an AI agent to generate trading conditions that are appropriate for the user's emotions. The trading conditions are dynamically adjusted based on the sentiment data; for example, simpler conditions are output to a user who is stressed. The generated trading conditions are designed to allow the user to trade without stress.

[0215] Step 5:

[0216] The server sends the generated transaction terms to the user's terminal and displays the proposed terms on the interface. The user reviews these terms and chooses whether to agree or not. This choice is input from the terminal to the server and prepared as output for determining the success or failure of the transaction in the next step.

[0217] Step 6:

[0218] If the user agrees to the transaction terms, the server records the transaction information on the blockchain. Based on the entered consent information, the transaction is completed in a way that is difficult to tamper with using blockchain technology, and the completion information is sent as output to the user's terminal. This ensures that transactions are conducted fairly and transparently.

[0219] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0220] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0221] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0222] [Second Embodiment]

[0223] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0224] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0225] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0226] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0227] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0228] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0229] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0230] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0231] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0232] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0233] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0234] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0235] This invention is a power trading platform that combines blockchain technology and artificial intelligence, aiming to efficiently utilize surplus renewable energy. The system includes a communication network between terminals, servers, and users.

[0236] Users input surplus electricity information using their devices and send it to the server. This information includes the amount of electricity generated, the expected supply time, and the desired selling price. Based on the received information, the server securely registers the tradable electricity information on the blockchain. This ensures that the information is difficult to tamper with.

[0237] The server has the capability to automatically collect and analyze historical consumption data and external environmental data. Based on this analysis data, an AI agent predicts electricity demand in real time and automatically sets the optimal transaction price that meets the requirements of both the supply and demand sides. This process adjusts the pricing to adapt to market fluctuations.

[0238] Furthermore, the AI ​​agent selects trading partners via the server, taking into account various factors such as geographical conditions, the degree of supply-demand matching, and transaction history. Users receive the transaction terms via their terminal and decide whether to agree. Once an agreement is reached, the transaction is executed by the server, and the movement of electricity and settlement information are accurately recorded.

[0239] As a concrete example, consider a case where person A, who owns a home solar power generation system, sells the surplus electricity generated during the day to person B, who has demand for it at night. Person A registers the amount of electricity they can provide and their desired price in the system via a terminal. The server uses this information to present the best transaction terms to person B, the demander. If person B agrees, the server executes the transaction and records the transaction history on the blockchain. This ensures that transactions between both parties are conducted fairly and efficiently.

[0240] The following describes the processing flow.

[0241] Step 1:

[0242] The terminal receives user input and displays information about surplus power on the input screen. The user enters the amount of power available, the desired selling price, and the service period, and then sends this data to the server.

[0243] Step 2:

[0244] The server analyzes the transaction information received from the terminal, assigns an identifier, and records it on the blockchain. This guarantees the authenticity and immutability of the information.

[0245] Step 3:

[0246] The server periodically collects historical consumption data and external environmental data from a database and provides it to the AI ​​agent. This data forms the basis for demand forecasting.

[0247] Step 4:

[0248] An AI agent analyzes data collected on the server to predict future electricity demand. Based on the prediction, it calculates the optimal transaction price in real time and transmits that information to the server.

[0249] Step 5:

[0250] The server selects trading partners based on price information and transaction conditions received from the AI ​​agent. The selection process takes into account factors such as the user's location, supply, and demand to achieve the optimal pairing.

[0251] Step 6:

[0252] The terminal displays the transaction terms notified by the server to the user and requests confirmation of approval. If the user agrees to the terms, the terminal sends an approval response to the server.

[0253] Step 7:

[0254] The server executes the transaction after confirming the user's consent. The process is handled securely and transparently by initiating the power supply and payment procedures and recording the completion information of the transaction on the blockchain.

[0255] Step 8:

[0256] The terminal receives a transaction completion notification from the server and informs the user that the transaction has been successfully completed. The user can then check their transaction history on the terminal.

[0257] (Example 1)

[0258] Next, we will describe Example 1. 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."

[0259] As the use of renewable energy increases, a platform is needed for the efficient and fair trading of surplus electricity. However, current systems have problems such as concerns about the falsification of trading information and difficulties in setting fair prices in real time. Furthermore, there is a need for efficient methods for selecting trading partners.

[0260] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0261] In this invention, the server includes means for managing transaction information using blockchain technology, means for analyzing past consumption data and external environmental data, means for an artificial intelligence agent that sets prices in real time based on the analysis results, and means for selecting trading partners based on geographical conditions and matching degree. This ensures the reliability of transactions while enabling pricing that quickly adapts to market fluctuations and efficient selection of trading partners.

[0262] Blockchain technology is a distributed ledger technology that records transaction information in a chain-like structure, preventing tampering.

[0263] "Means for managing transaction information" refers to a system that records, updates, and allows reference to buying and selling data in electricity transactions as needed.

[0264] "Past consumption data and external environmental data" refers to past electricity usage history, as well as data related to the environment, such as weather and temperature.

[0265] "Methods of analysis" refer to analytical techniques that use collected data to discover patterns and trends and predict electricity demand.

[0266] An "artificial intelligence agent" is a program that uses machine learning and data analysis to make decisions and provide optimized information.

[0267] "Setting in real time" means that calculations are performed instantly every time the data is updated, and settings are automatically adjusted according to the fluctuating conditions.

[0268] "Methods for selecting trading partners based on geographical conditions and matching degree" refers to methods for finding the optimal trading partner by considering factors such as distance and the rate of supply-demand matching.

[0269] This invention aims to build a power trading platform that combines blockchain technology and artificial intelligence. It primarily functions as a server, terminal, and user system.

[0270] Server Role

[0271] The server receives surplus power information sent by users and manages it securely using blockchain technology. The server maintains a distributed ledger for data integration and analysis, preventing tampering. Furthermore, the server collects external environmental data (such as weather and temperature) and historical power consumption data via APIs. This data is used for demand forecasting by an AI agent.

[0272] Terminal role

[0273] Users input information about their surplus electricity using a terminal. The terminal transmits this information to the server, and the usability of the interface is crucial. The terminal also presents and confirms transaction terms.

[0274] User roles

[0275] Users play the role of either supplying or demanding electricity, and provide information about surplus electricity and trading requests through their terminals. It is also the user's responsibility to review the presented trading terms and decide whether to agree to them.

[0276] Hardware and software to be used

[0277] The server uses a computer system suitable for high-performance data processing and dedicated software for supporting blockchain and AI analysis. Specifically, an open-source blockchain platform is used for blockchain management, and a machine learning library is used for AI analysis. As for the terminal, smartphones and tablets owned by users are assumed, and a dedicated application operates.

[0278] Specific example

[0279] As a specific example, there is a case where a user having a solar power generation system at home sells the surplus power generated during the day to a specific user with high demand at night. In this case, the selling user uses a terminal to register the amount of power and the desired price with the system and executes an optimal transaction through the server.

[0280] Examples of prompt sentences:

[0281] "I want to consider the platform design for how to efficiently trade surplus power of renewable energy. What is the method of combining blockchain technology and AI?"

[0282] "How can an efficient system for selling surplus power of household solar power generation be constructed?"

[0283] The flow of the specific process in Example 1 will be described using FIG. 11.

[0284] Step 1:

[0285] The user inputs surplus power information using their own terminal. Specifically, the user opens a dedicated application on the terminal and inputs data such as power generation amount, available supply time, and desired selling price. The input data is transmitted from the terminal to the server. As a result, the details of the power amount that the user can provide are stored on the server.

[0286] Step 2:

[0287] The server receives the surplus power information received from the user and registers the data on the blockchain. At this time, the server encrypts the received data and transmits it to the blockchain network using a secure communication protocol. This prevents data tampering and ensures reliability. As a result, the accuracy and security of the registered data are guaranteed by the blockchain.

[0288] Step 3:

[0289] The server collects external environment data and past power consumption data. This data includes temperature, weather, and the power consumption patterns of the region. The server uses APIs to obtain this data and accumulates it in a database for AI analysis. Based on the obtained data, AI-based demand prediction becomes possible in subsequent steps.

[0290] Step 4:

[0291] The AI agent analyzes the data collected by the server. Here, mainly machine learning algorithms are used to predict power demand in real time. The purpose is to analyze the input data as a multi-dimensional vector and grasp the demand trend. The analysis results are useful for optimizing the transaction conditions provided to the user.

[0292] Step 5:

[0293] The server sets the transaction price based on the analysis results of the AI ​​agent. In this step, it calculates the optimal price that reflects the real-time supply and demand balance of the market. The AI ​​model considers past price fluctuations and uses an algorithm to determine a fair and competitive price. The set price is then reflected in transactions between users.

[0294] Step 6:

[0295] The server selects trading partners based on recommendations from the AI ​​agent. The selection process considers geographical conditions and the degree of supply-demand matching. The server scores this information and selects high-scoring trading candidates. This selection is a crucial element for achieving efficient and effective transactions.

[0296] Step 7:

[0297] The user reviews the transaction terms presented via their terminal. Information such as the trading partner, transaction price, and delivery time is displayed. The user selects whether to agree to the terms and sends their selection back to the server from their terminal. This process leads to a final transaction agreement.

[0298] Step 8:

[0299] Once the terms of the transaction are agreed upon, the server executes the transaction. Upon execution, the transfer of electricity begins, and the server generates settlement information. This information is registered on the blockchain as a transaction history, ensuring the integrity and transparency of the transaction.

[0300] (Application Example 1)

[0301] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0302] The trading platform for efficiently and fairly utilising the surplus of renewable energy is not well-developed, and in the current system, imbalances between demand and supply are likely to occur. Also, since it is difficult to ensure the transparency and reliability of trading information, there is a possibility that trading will become unfair. Furthermore, the presentation of appropriate trading conditions in real time is required.

[0303] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Application Example 1 is realised by the following respective means.

[0304] In this invention, the server includes means for managing exchange information using blockchain technology, means for analysing past consumption records and external environment records, artificial intelligence agent means for setting values in real time based on the analysis results, means for presenting and receiving confirmation of exchange conditions between users, means for executing exchanges and recording completion, means for registering the supply and demand of surplus energy through terminal devices, and artificial intelligence agent means for generating and presenting appropriate conditions for supply and demand. Thereby, it becomes possible to efficiently trade the surplus of renewable energy and provide a fair and reliable platform.

[0305] "Blockchain technology" is a technology for securely recording transaction information in a distributed ledger using cryptographic techniques.

[0306] "Exchange information" is information including data such as supply volume, demand volume, and price related to energy trading.

[0307] "Past consumption records" refer to historical data of energy consumption in the past.

[0308] "External environment records" are data related to external factors that affect energy demand and supply, such as weather conditions and market trends.

[0309] "Artificial intelligence agent" is a software agent that autonomously judges the environment and makes decisions according to a specific purpose.

[0310] "Exchange terms between users" refer to the conditions for conducting a transaction, such as price and supply time.

[0311] A "terminal device" refers to an electronic device used by a user, such as a computer or smartphone.

[0312] "Surplus energy" refers to the portion of renewable energy generation that is not consumed and is left over.

[0313] "Appropriate supply and demand conditions" refer to the most efficient and beneficial trading conditions for both energy suppliers and consumers.

[0314] This invention is a system designed to efficiently trade surplus renewable energy. The system primarily utilizes a server, user terminal devices, and a communication network.

[0315] The server securely manages transaction information using blockchain technology. The database stores each user's past consumption records and external environment records, and an artificial intelligence agent is used to analyze this data. This analysis enables demand forecasting for power supply and generates optimal transaction conditions in real time.

[0316] The terminal device is used by users to register their surplus renewable energy and confirm transaction terms. By inputting information on the supply and demand of surplus energy through the terminal, an artificial intelligence agent presents appropriate transaction terms based on that information. If an agreement is reached, the transaction is automatically executed.

[0317] As a concrete example, consider a situation where one user generates surplus renewable energy during the day, and another user wants to use that energy at night. In this case, the server uses AI to generate and present the optimal transaction terms for both parties.

[0318] The hardware required for the system to operate includes data center facilities as servers, smartphones as user terminals, and internet connectivity. The software used includes Ethereum for blockchain, TensorFlow for AI models, and Pandas for data analysis.

[0319] An example of a prompt statement a user could ask the generated AI model: "How can we optimize the overall power efficiency of a city by sharing renewable energy through a smart energy sharing app?"

[0320] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0321] Step 1:

[0322] Users input information about their surplus energy supply using their own devices. This input includes the amount of energy available, the estimated supply time, and the desired price. This information is transmitted from the device to the server. The input data is processed as basic numerical data.

[0323] Step 2:

[0324] The server registers transaction information on the blockchain based on the received data. The use of blockchain prevents data tampering and maintains security. The input is transaction information from the user, and the output is a transaction history securely recorded on the blockchain.

[0325] Step 3:

[0326] The server collects historical consumption records and external environmental records from a database and performs data analysis based on these. An AI model (using TensorFlow) is used to predict the optimal conditions for both supply and demand. The input is historical consumption and environmental data, and the output is the predicted optimal transaction conditions.

[0327] Step 4:

[0328] The AI ​​agent automatically sets transaction conditions between users based on the optimal conditions obtained through analysis and presents them to the user via the terminal. In this process, user input information and the results of the AI ​​analysis are combined to generate prompt sentences for presenting the conditions. The input is the analysis results, and the output is the presented transaction conditions.

[0329] Step 5:

[0330] The user reviews the transaction terms on their device and chooses to agree or reject them. The input here is the user's response to the presented terms, and the output is the result of the user's selection. If the user agrees, the process proceeds to the next step.

[0331] Step 6:

[0332] The server executes the transaction with the user's consent. After the transaction is completed, it adds this transaction record to the blockchain to maintain data reliability. The input is the user's consent and approval, and the output is the newly recorded transaction history.

[0333] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0334] This invention is a power trading platform that combines blockchain technology, artificial intelligence, and an emotion engine. It not only efficiently utilizes surplus renewable energy but also provides flexible trading that takes into account the user's emotional state. The system consists of a user terminal, a server, and an emotion engine.

[0335] The user inputs information about surplus power through their device and sends it to the server. The device is equipped with input devices such as a camera and microphone, and an emotion engine analyzes the user's facial expressions and voice to determine their emotional state. The analysis results can generate data representing the user's current emotional state (e.g., reassurance, tension, anxiety).

[0336] The server processes electricity consumption and sentiment data received from users and records transaction information on the blockchain. This enables management in a way that makes it difficult to tamper with the information. Furthermore, the server collects historical consumption data and external environmental data in real time and analyzes it through an AI agent. This analysis enables future electricity demand forecasting and the setting of optimal prices.

[0337] The AI ​​agent adjusts trading conditions based on the user's emotional data, proposing trades in a way that does not stress the user. If the user is relaxed, it will present the information in a normal interface; if the user is stressed, it will reduce the amount of information and present a simpler interface.

[0338] For example, when user A offers surplus solar power, if the emotion engine detects that A is slightly stressed, the server will concisely summarize and display the transaction terms. Furthermore, the proposed transaction terms can be slightly conservative, as suggested by the AI ​​agent to alleviate A's stress. This allows A to confidently agree to the terms. Once the transaction is agreed upon, the server records the transaction on the blockchain and sends a notification to the terminal. In this way, fair and efficient transactions can be achieved while taking the user's emotional state into consideration.

[0339] The following describes the processing flow.

[0340] Step 1:

[0341] The terminal receives user input and displays information about surplus electricity (generation amount, availability time, desired price) on the input screen. The user enters this information and sends it to the system.

[0342] Step 2:

[0343] The device's camera and microphone capture the user's facial expressions and voice, and the emotion engine analyzes this data. The analysis generates data on the user's emotional state (e.g., feeling safe, tense, anxious).

[0344] Step 3:

[0345] The server analyzes surplus power information and sentiment data received from the terminals and generates transaction information for use in power trading. This information is recorded on the blockchain to ensure security and transparency.

[0346] Step 4:

[0347] The server collects historical consumption data and external environmental data and provides it to the AI ​​agent. Based on this data, the AI ​​agent predicts electricity demand and calculates the optimal transaction price in real time.

[0348] Step 5:

[0349] The AI ​​agent considers the user's emotional state and adjusts the trading conditions accordingly. If it determines that the user is stressed, the AI ​​agent presents the trading conditions using a simple and easy-to-understand interface.

[0350] Step 6:

[0351] The terminal displays the transaction terms obtained from the server to the user and requests the user's approval. If the user agrees to the proposed terms, the terminal sends the approval to the server.

[0352] Step 7:

[0353] Once the server confirms the user's consent, the transaction is formally executed. Information regarding the supply of electricity and the settlement of its payment is recorded on the blockchain to maintain transaction transparency.

[0354] Step 8:

[0355] The terminal receives a transaction completion notification from the server and informs the user that the transaction has been successfully completed. The user can then check the transaction history on the terminal and confidently exit the system.

[0356] (Example 2)

[0357] Next, we will describe Example 2. 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".

[0358] Traditional electricity trading systems offered fixed interfaces and trading conditions without considering the emotional aspects of users, potentially leading to user stress and dissatisfaction. Furthermore, they carried the risk of tampering and fraudulent activity regarding trading information.

[0359] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0360] In this invention, the server includes means for managing transaction information using blockchain technology, means for analyzing past consumption data and external environment data, and emotion engine means for analyzing the user's emotional state. This enables fair and user-friendly transactions by managing tamper-proof transaction information while taking the user's emotional state into consideration.

[0361] Blockchain is a database technology that records multiple transaction details in a chain of blocks, making it extremely difficult to tamper with on a decentralized network.

[0362] An "artificial intelligence agent" is a software system that autonomously determines and adjusts trading conditions based on data analysis and provides optimized information.

[0363] An "emotion engine" is an algorithm and system that analyzes a user's facial expressions and voice data to identify their emotional state.

[0364] A "user" is an individual or entity that inputs information about the supply or demand of electricity into the system and participates in the trading process.

[0365] "Transaction information" refers to a series of data related to the buying and selling of electricity, including details about the amount of electricity, price, time, and the parties involved in the transaction.

[0366] This invention relates to a power trading platform that combines blockchain technology, artificial intelligence, and an emotion engine, which not only efficiently trades surplus renewable energy but also provides flexible trading that takes into account the emotional state of the user.

[0367] The user transmits information about surplus electricity obtained from renewable energy sources to a server via a device. This device has built-in input devices such as a camera and microphone, which collect the user's facial expressions and voice. The emotion engine analyzes this data to identify the user's emotional state, such as feeling relaxed or anxious.

[0368] The server processes data based on electricity information received from users and analyzed sentiment data, and records the results on the blockchain. This makes it difficult to tamper with transaction information. The server also collects historical electricity consumption data and external environmental data such as weather in real time, and an AI agent performs demand forecasting and pricing. This AI agent adjusts transaction conditions based on the user's sentiment state, providing an interface that allows for stress-free transactions.

[0369] For example, if a user attempts to supply surplus electricity generated by solar power, and the emotion engine detects a state of tension, the server will simplify the transaction conditions and the AI ​​agent will propose more conservative conditions to ensure the user can agree to the transaction with confidence. As a result of this process, once the transaction is completed, the server records the completion on the blockchain and notifies the user.

[0370] Examples of prompt statements to input into a generative AI model are as follows:

[0371] "Use user sentiment data and power trading information to generate optimal trading conditions for the user. For example, suggest conservative conditions if the user is stressed, and provide normal conditions if the user is relaxed."

[0372] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0373] Step 1:

[0374] Users input information about surplus electricity obtained from renewable energy sources using a terminal. Specifically, they input data such as the amount of electricity that can be supplied, the desired price, and the time period during which transactions are possible. This information becomes input data and is sent to the server.

[0375] Step 2:

[0376] The system uses the camera and microphone on the user's device to collect the user's facial expressions and voice. This data is then used as input by an emotion engine to analyze the user's emotional state. The output from this analysis is quantified as data representing the user's emotional state, such as feeling safe, tense, or anxious.

[0377] Step 3:

[0378] The terminal combines power information entered by the user with emotional data analyzed by the emotion engine and sends this to the server. The resulting dataset is then passed to the server.

[0379] Step 4:

[0380] The server processes the received power and sentiment data, and first records the transaction information on the blockchain. This ensures that the information is managed in a way that makes tampering difficult. By using blockchain technology for the input dataset, highly reliable output data is accumulated.

[0381] Step 5:

[0382] The server collects historical consumption data and external environmental data in real time. This collected data is analyzed by an AI agent. The analyzed output is used to forecast future electricity demand and set optimal prices.

[0383] Step 6:

[0384] The AI ​​agent adjusts and proposes trading conditions tailored to the user based on the analysis results and the user's emotional data. If the user is stressed, the proposed output conditions will be more conservative and concise than usual. Conversely, if the user is relaxed, detailed trading conditions will be presented.

[0385] Step 7:

[0386] Once the user agrees to the presented transaction terms, the server executes the transaction based on those terms. The resulting transaction completion data is output and recorded on the blockchain. Finally, a transaction completion notification is sent to the terminal.

[0387] (Application Example 2)

[0388] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0389] As the use of renewable energy increases, there is a need for efficient trading of surplus electricity. However, conventional trading systems often cause stress to users because they present conditions without considering their psychological state. Furthermore, systems with insufficient transparency and security can undermine the reliability of transactions. There is a need to solve these problems and provide a more user-friendly and reliable electricity trading platform.

[0390] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0391] In this invention, the server includes means for managing transaction information using blockchain technology, means for analyzing past consumption data and external environment data, artificial intelligence agent means for setting prices in real time based on the analysis results, emotion engine means for analyzing the user's emotional state, and means for dynamically adjusting transaction conditions based on the user's emotional state. This makes it possible to realize flexible and transparent transactions that respond to the user's emotions and ensure reliability.

[0392] Blockchain technology is a method that records data on a distributed ledger and uses cryptographic techniques to prevent unauthorized tampering.

[0393] "Transaction information" refers to various data related to electricity buying and selling transactions, including transaction terms and agreements.

[0394] "Consumption data" refers to records of past electricity usage.

[0395] "External environmental data" refers to information about external factors that affect transactions, such as weather and market trends.

[0396] An "artificial intelligence agent" is a program that analyzes data to make optimal decisions.

[0397] An "emotion engine" is a system that analyzes a user's emotional state and generates data based on the results.

[0398] An "interface" refers to the screens and input methods that a user uses to interact with a system.

[0399] "User emotional state" refers to the user's mental state, such as feeling safe, tense, or anxious.

[0400] "Terms of trade" refer to the price and other conditions agreed upon between the parties in the buying and selling of electricity.

[0401] To implement this invention, it is necessary to build a system that integrates a server, a user terminal, and an emotion engine. This system efficiently and securely conducts electricity trading while taking into account the user's emotional state. The user terminal includes input devices such as a camera and a microphone, which the emotion engine uses to analyze the user's facial expressions and voice. The server manages transaction information using blockchain technology and uses an artificial intelligence agent to analyze consumption data and external environmental data.

[0402] When a user participates in selling surplus electricity via their smartphone, the device acquires emotional data from its camera and microphone and sends the analysis results to a server. Based on this information, the server uses an AI agent to dynamically set transaction conditions that are tailored to the user's emotional state. If the user agrees to the transaction conditions, the server records this information on the blockchain in a way that makes it difficult to tamper with. As a result, users can trade with peace of mind under conditions optimized for their own emotional state.

[0403] As a concrete example, consider a scenario where a user, while spending a holiday at home, provides surplus electricity generated from their rooftop solar power system to the surrounding community. In this case, the transaction terms are displayed on the screen in a format that is easiest for the user to understand. This allows the user to participate in the transaction without feeling any anxiety.

[0404] An example of a prompt from a generated AI model might be: "Please describe in detail the requirements necessary to build a superior energy trading platform, including flexible trading conditions based on the user's emotional state and secure trading using blockchain."

[0405] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0406] Step 1:

[0407] The device uses its camera and microphone to capture the user's facial expressions and voice as input data. This input information is sent to an emotion engine, which analyzes the user's emotional state. The emotion engine analyzes the input data and outputs emotion data representing emotional states such as reassurance, tension, and anxiety.

[0408] Step 2:

[0409] The terminal sends emotional data obtained from the emotion engine to the server. The server then receives the user's current emotional state and stores it for use in the next step. Based on the emotional data, the server weights it within the system and prepares to present transaction terms that are less burdensome for the user.

[0410] Step 3:

[0411] The server collects historical consumption data and external environmental data, and analyzes it through an artificial intelligence agent. Based on the input consumption data and external environmental data, it performs demand forecasting and pricing, and generates the results as output. This prepares the server for use in generating transaction conditions in the next step.

[0412] Step 4:

[0413] The server integrates analysis results and sentiment data, and uses an AI agent to generate trading conditions that are appropriate for the user's emotions. The trading conditions are dynamically adjusted based on the sentiment data; for example, simpler conditions are output to a user who is stressed. The generated trading conditions are designed to allow the user to trade without stress.

[0414] Step 5:

[0415] The server sends the generated transaction terms to the user's terminal and displays the proposed terms on the interface. The user reviews these terms and chooses whether to agree or not. This choice is input from the terminal to the server and prepared as output for determining the success or failure of the transaction in the next step.

[0416] Step 6:

[0417] If the user agrees to the transaction terms, the server records the transaction information on the blockchain. Based on the entered consent information, the transaction is completed in a way that is difficult to tamper with using blockchain technology, and the completion information is sent as output to the user's terminal. This ensures that transactions are conducted fairly and transparently.

[0418] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0419] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0420] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0421] [Third Embodiment]

[0422] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0423] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0424] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0425] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0426] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0427] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0428] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0429] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0430] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0431] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0432] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0433] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0434] This invention is a power trading platform that combines blockchain technology and artificial intelligence, aiming to efficiently utilize surplus renewable energy. The system includes a communication network between terminals, servers, and users.

[0435] Users input surplus electricity information using their devices and send it to the server. This information includes the amount of electricity generated, the expected supply time, and the desired selling price. Based on the received information, the server securely registers the tradable electricity information on the blockchain. This ensures that the information is difficult to tamper with.

[0436] The server has the capability to automatically collect and analyze historical consumption data and external environmental data. Based on this analysis data, an AI agent predicts electricity demand in real time and automatically sets the optimal transaction price that meets the requirements of both the supply and demand sides. This process adjusts the pricing to adapt to market fluctuations.

[0437] Furthermore, the AI ​​agent selects trading partners via the server, taking into account various factors such as geographical conditions, the degree of supply-demand matching, and transaction history. Users receive the transaction terms via their terminal and decide whether to agree. Once an agreement is reached, the transaction is executed by the server, and the movement of electricity and settlement information are accurately recorded.

[0438] As a concrete example, consider a case where person A, who owns a home solar power generation system, sells the surplus electricity generated during the day to person B, who has demand for it at night. Person A registers the amount of electricity they can provide and their desired price in the system via a terminal. The server uses this information to present the best transaction terms to person B, the demander. If person B agrees, the server executes the transaction and records the transaction history on the blockchain. This ensures that transactions between both parties are conducted fairly and efficiently.

[0439] The following describes the processing flow.

[0440] Step 1:

[0441] The terminal receives user input and displays information about surplus power on the input screen. The user enters the amount of power available, the desired selling price, and the service period, and then sends this data to the server.

[0442] Step 2:

[0443] The server analyzes the transaction information received from the terminal, assigns an identifier, and records it on the blockchain. This guarantees the authenticity and immutability of the information.

[0444] Step 3:

[0445] The server periodically collects historical consumption data and external environmental data from a database and provides it to the AI ​​agent. This data forms the basis for demand forecasting.

[0446] Step 4:

[0447] An AI agent analyzes data collected on the server to predict future electricity demand. Based on the prediction, it calculates the optimal transaction price in real time and transmits that information to the server.

[0448] Step 5:

[0449] The server selects trading partners based on price information and transaction conditions received from the AI ​​agent. The selection process takes into account factors such as the user's location, supply, and demand to achieve the optimal pairing.

[0450] Step 6:

[0451] The terminal displays the transaction terms notified by the server to the user and requests confirmation of approval. If the user agrees to the terms, the terminal sends an approval response to the server.

[0452] Step 7:

[0453] The server executes the transaction after confirming the user's consent. The process is handled securely and transparently by initiating the power supply and payment procedures and recording the completion information of the transaction on the blockchain.

[0454] Step 8:

[0455] The terminal receives a transaction completion notification from the server and informs the user that the transaction has been successfully completed. The user can then check their transaction history on the terminal.

[0456] (Example 1)

[0457] Next, we will describe Example 1. 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."

[0458] As the use of renewable energy increases, a platform is needed for the efficient and fair trading of surplus electricity. However, current systems have problems such as concerns about the falsification of trading information and difficulties in setting fair prices in real time. Furthermore, there is a need for efficient methods for selecting trading partners.

[0459] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0460] In this invention, the server includes means for managing transaction information using blockchain technology, means for analyzing past consumption data and external environmental data, means for an artificial intelligence agent that sets prices in real time based on the analysis results, and means for selecting trading partners based on geographical conditions and matching degree. This ensures the reliability of transactions while enabling pricing that quickly adapts to market fluctuations and efficient selection of trading partners.

[0461] Blockchain technology is a distributed ledger technology that records transaction information in a chain-like structure, preventing tampering.

[0462] "Means for managing transaction information" refers to a system that records, updates, and allows reference to buying and selling data in electricity transactions as needed.

[0463] "Past consumption data and external environmental data" refers to past electricity usage history, as well as data related to the environment, such as weather and temperature.

[0464] "Methods of analysis" refer to analytical techniques that use collected data to discover patterns and trends and predict electricity demand.

[0465] An "artificial intelligence agent" is a program that uses machine learning and data analysis to make decisions and provide optimized information.

[0466] "Setting in real time" means that calculations are performed instantly every time the data is updated, and settings are automatically adjusted according to the fluctuating conditions.

[0467] "Methods for selecting trading partners based on geographical conditions and matching degree" refers to methods for finding the optimal trading partner by considering factors such as distance and the rate of supply-demand matching.

[0468] This invention aims to build a power trading platform that combines blockchain technology and artificial intelligence. It primarily functions as a server, terminal, and user system.

[0469] Server Role

[0470] The server receives surplus power information sent by users and manages it securely using blockchain technology. The server maintains a distributed ledger for data integration and analysis, preventing tampering. Furthermore, the server collects external environmental data (such as weather and temperature) and historical power consumption data via APIs. This data is used for demand forecasting by an AI agent.

[0471] Terminal role

[0472] Users input information about their surplus electricity using a terminal. The terminal transmits this information to the server, and the usability of the interface is crucial. The terminal also presents and confirms transaction terms.

[0473] User roles

[0474] Users play the role of either supplying or demanding electricity, and provide information about surplus electricity and trading requests through their terminals. It is also the user's responsibility to review the presented trading terms and decide whether to agree to them.

[0475] Hardware and software to be used

[0476] The server will utilize a high-performance computer system suitable for data processing, along with specialized software to support blockchain and AI analysis. Specifically, it will use an open-source blockchain platform for blockchain management and machine learning libraries for AI analysis. The terminals will be smartphones and tablets owned by users, running a dedicated application.

[0477] Specific example

[0478] A concrete example is a user with a solar power generation system at home who sells surplus electricity generated during the day to a specific user with high demand at night. In this case, the user selling the electricity registers the amount of electricity and their desired price in the system using a terminal, and the optimal transaction is executed through the server.

[0479] Example of a prompt:

[0480] "I want to design a platform for efficiently trading surplus renewable energy. How can we combine blockchain technology with AI?"

[0481] "How can we build an efficient system for selling surplus electricity generated by home solar power systems?"

[0482] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0483] Step 1:

[0484] Users input surplus power information using their own devices. Specifically, they open a dedicated application on their devices and input data such as power generation amount, available supply time, and desired selling price. The entered data is sent from the device to the server. This allows the server to store detailed information about the amount of electricity the user can provide.

[0485] Step 2:

[0486] The server receives surplus power information from users and registers the data on the blockchain. At this time, the server encrypts the received data and transmits it to the blockchain network using a secure communication protocol. This prevents data tampering and ensures reliability. As a result, the accuracy and security of the registered data are guaranteed by the blockchain.

[0487] Step 3:

[0488] The server collects external environmental data and historical power consumption data. This data includes temperature, weather, and regional power consumption patterns. The server retrieves this data using an API and stores it in a database for AI analysis. Based on the obtained data, AI-driven demand forecasting becomes possible in subsequent steps.

[0489] Step 4:

[0490] An AI agent performs analysis using data collected on the server. Here, primarily using machine learning algorithms, it predicts electricity demand in real time. The goal is to analyze the input data as a multidimensional vector and understand demand trends. The analysis results help optimize the transaction terms offered to users.

[0491] Step 5:

[0492] The server sets the transaction price based on the analysis results of the AI ​​agent. In this step, it calculates the optimal price that reflects the real-time supply and demand balance of the market. The AI ​​model considers past price fluctuations and uses an algorithm to determine a fair and competitive price. The set price is then reflected in transactions between users.

[0493] Step 6:

[0494] The server selects trading partners based on recommendations from the AI ​​agent. The selection process considers geographical conditions and the degree of supply-demand matching. The server scores this information and selects high-scoring trading candidates. This selection is a crucial element for achieving efficient and effective transactions.

[0495] Step 7:

[0496] The user reviews the transaction terms presented via their terminal. Information such as the trading partner, transaction price, and delivery time is displayed. The user selects whether to agree to the terms and sends their selection back to the server from their terminal. This process leads to a final transaction agreement.

[0497] Step 8:

[0498] Once the terms of the transaction are agreed upon, the server executes the transaction. Upon execution, the transfer of electricity begins, and the server generates settlement information. This information is registered on the blockchain as a transaction history, ensuring the integrity and transparency of the transaction.

[0499] (Application Example 1)

[0500] Next, we will explain Application Example 1. In the following explanation, 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."

[0501] A trading platform for efficiently and fairly utilizing surplus renewable energy is underdeveloped, and the current system is prone to supply-demand imbalances. Furthermore, ensuring transparency and reliability of trading information is difficult, potentially leading to unfair transactions. In addition, there is a need for the real-time presentation of appropriate trading conditions.

[0502] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0503] In this invention, the server includes means for managing exchange information using blockchain technology, means for analyzing past consumption records and external environment records, artificial intelligence agent means for setting values ​​in real time based on the analysis results, means for presenting and receiving confirmation of exchange conditions between users, means for executing exchanges and recording their completion, means for registering the supply and demand of surplus energy through terminal devices, and artificial intelligence agent means for generating and presenting appropriate supply and demand conditions. This enables the efficient trading of surplus renewable energy and provides a fair and reliable platform.

[0504] Blockchain technology is a technology that securely records transaction information on a distributed ledger using cryptographic techniques.

[0505] "Exchange information" refers to information that includes data such as supply, demand, and price related to energy trading.

[0506] "Past consumption records" refer to historical data on energy consumption in the past.

[0507] "External environmental records" refer to data on external factors that affect energy demand and supply, such as weather conditions and market trends.

[0508] An "artificial intelligence agent" is a software agent that autonomously assesses its environment and makes decisions according to a specific purpose.

[0509] "Exchange terms between users" refer to the conditions for conducting a transaction, such as price and supply time.

[0510] A "terminal device" refers to an electronic device used by a user, such as a computer or smartphone.

[0511] "Surplus energy" refers to the portion of renewable energy generation that is not consumed and is left over.

[0512] "Appropriate supply and demand conditions" refer to the most efficient and beneficial trading conditions for both energy suppliers and consumers.

[0513] This invention is a system designed to efficiently trade surplus renewable energy. The system primarily utilizes a server, user terminal devices, and a communication network.

[0514] The server securely manages transaction information using blockchain technology. The database stores each user's past consumption records and external environment records, and an artificial intelligence agent is used to analyze this data. This analysis enables demand forecasting for power supply and generates optimal transaction conditions in real time.

[0515] The terminal device is used by users to register their surplus renewable energy and confirm transaction terms. By inputting information on the supply and demand of surplus energy through the terminal, an artificial intelligence agent presents appropriate transaction terms based on that information. If an agreement is reached, the transaction is automatically executed.

[0516] As a concrete example, consider a situation where one user generates surplus renewable energy during the day, and another user wants to use that energy at night. In this case, the server uses AI to generate and present the optimal transaction terms for both parties.

[0517] The hardware required for the system to operate includes data center facilities as servers, smartphones as user terminals, and internet connectivity. The software used includes Ethereum for blockchain, TensorFlow for AI models, and Pandas for data analysis.

[0518] An example of a prompt statement a user could ask the generated AI model: "How can we optimize the overall power efficiency of a city by sharing renewable energy through a smart energy sharing app?"

[0519] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0520] Step 1:

[0521] Users input information about their surplus energy supply using their own devices. This input includes the amount of energy available, the estimated supply time, and the desired price. This information is transmitted from the device to the server. The input data is processed as basic numerical data.

[0522] Step 2:

[0523] The server registers transaction information on the blockchain based on the received data. The use of blockchain prevents data tampering and maintains security. The input is transaction information from the user, and the output is a transaction history securely recorded on the blockchain.

[0524] Step 3:

[0525] The server collects historical consumption records and external environmental records from a database and performs data analysis based on these. An AI model (using TensorFlow) is used to predict the optimal conditions for both supply and demand. The input is historical consumption and environmental data, and the output is the predicted optimal transaction conditions.

[0526] Step 4:

[0527] The AI ​​agent automatically sets transaction conditions between users based on the optimal conditions obtained through analysis and presents them to the user via the terminal. In this process, user input information and the results of the AI ​​analysis are combined to generate prompt sentences for presenting the conditions. The input is the analysis results, and the output is the presented transaction conditions.

[0528] Step 5:

[0529] The user reviews the transaction terms on their device and chooses to agree or reject them. The input here is the user's response to the presented terms, and the output is the result of the user's selection. If the user agrees, the process proceeds to the next step.

[0530] Step 6:

[0531] The server executes the transaction with the user's consent. After the transaction is completed, it adds this transaction record to the blockchain to maintain data reliability. The input is the user's consent and approval, and the output is the newly recorded transaction history.

[0532] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0533] This invention is a power trading platform that combines blockchain technology, artificial intelligence, and an emotion engine. It not only efficiently utilizes surplus renewable energy but also provides flexible trading that takes into account the user's emotional state. The system consists of a user terminal, a server, and an emotion engine.

[0534] The user inputs information about surplus power through their device and sends it to the server. The device is equipped with input devices such as a camera and microphone, and an emotion engine analyzes the user's facial expressions and voice to determine their emotional state. The analysis results can generate data representing the user's current emotional state (e.g., reassurance, tension, anxiety).

[0535] The server processes electricity consumption and sentiment data received from users and records transaction information on the blockchain. This enables management in a way that makes it difficult to tamper with the information. Furthermore, the server collects historical consumption data and external environmental data in real time and analyzes it through an AI agent. This analysis enables future electricity demand forecasting and the setting of optimal prices.

[0536] The AI ​​agent adjusts trading conditions based on the user's emotional data, proposing trades in a way that does not stress the user. If the user is relaxed, it will present the information in a normal interface; if the user is stressed, it will reduce the amount of information and present a simpler interface.

[0537] For example, when user A offers surplus solar power, if the emotion engine detects that A is slightly stressed, the server will concisely summarize and display the transaction terms. Furthermore, the proposed transaction terms can be slightly conservative, as suggested by the AI ​​agent to alleviate A's stress. This allows A to confidently agree to the terms. Once the transaction is agreed upon, the server records the transaction on the blockchain and sends a notification to the terminal. In this way, fair and efficient transactions can be achieved while taking the user's emotional state into consideration.

[0538] The following describes the processing flow.

[0539] Step 1:

[0540] The terminal receives user input and displays information about surplus electricity (generation amount, availability time, desired price) on the input screen. The user enters this information and sends it to the system.

[0541] Step 2:

[0542] The device's camera and microphone capture the user's facial expressions and voice, and the emotion engine analyzes this data. The analysis generates data on the user's emotional state (e.g., feeling safe, tense, anxious).

[0543] Step 3:

[0544] The server analyzes surplus power information and sentiment data received from the terminals and generates transaction information for use in power trading. This information is recorded on the blockchain to ensure security and transparency.

[0545] Step 4:

[0546] The server collects historical consumption data and external environmental data and provides it to the AI ​​agent. Based on this data, the AI ​​agent predicts electricity demand and calculates the optimal transaction price in real time.

[0547] Step 5:

[0548] The AI ​​agent considers the user's emotional state and adjusts the trading conditions accordingly. If it determines that the user is stressed, the AI ​​agent presents the trading conditions using a simple and easy-to-understand interface.

[0549] Step 6:

[0550] The terminal displays the transaction terms obtained from the server to the user and requests the user's approval. If the user agrees to the proposed terms, the terminal sends the approval to the server.

[0551] Step 7:

[0552] Once the server confirms the user's consent, the transaction is formally executed. Information regarding the supply of electricity and the settlement of its payment is recorded on the blockchain to maintain transaction transparency.

[0553] Step 8:

[0554] The terminal receives a transaction completion notification from the server and informs the user that the transaction has been successfully completed. The user can then check the transaction history on the terminal and confidently exit the system.

[0555] (Example 2)

[0556] Next, we will describe Example 2. 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."

[0557] Traditional electricity trading systems offered fixed interfaces and trading conditions without considering the emotional aspects of users, potentially leading to user stress and dissatisfaction. Furthermore, they carried the risk of tampering and fraudulent activity regarding trading information.

[0558] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0559] In this invention, the server includes means for managing transaction information using blockchain technology, means for analyzing past consumption data and external environment data, and emotion engine means for analyzing the user's emotional state. This enables fair and user-friendly transactions by managing tamper-proof transaction information while taking the user's emotional state into consideration.

[0560] Blockchain is a database technology that records multiple transaction details in a chain of blocks, making it extremely difficult to tamper with on a decentralized network.

[0561] An "artificial intelligence agent" is a software system that autonomously determines and adjusts trading conditions based on data analysis and provides optimized information.

[0562] An "emotion engine" is an algorithm and system that analyzes a user's facial expressions and voice data to identify their emotional state.

[0563] A "user" is an individual or entity that inputs information about the supply or demand of electricity into the system and participates in the trading process.

[0564] "Transaction information" refers to a series of data related to the buying and selling of electricity, including details about the amount of electricity, price, time, and the parties involved in the transaction.

[0565] This invention relates to a power trading platform that combines blockchain technology, artificial intelligence, and an emotion engine, which not only efficiently trades surplus renewable energy but also provides flexible trading that takes into account the emotional state of the user.

[0566] The user transmits information about surplus electricity obtained from renewable energy sources to a server via a device. This device has built-in input devices such as a camera and microphone, which collect the user's facial expressions and voice. The emotion engine analyzes this data to identify the user's emotional state, such as feeling relaxed or anxious.

[0567] The server processes data based on electricity information received from users and analyzed sentiment data, and records the results on the blockchain. This makes it difficult to tamper with transaction information. The server also collects historical electricity consumption data and external environmental data such as weather in real time, and an AI agent performs demand forecasting and pricing. This AI agent adjusts transaction conditions based on the user's sentiment state, providing an interface that allows for stress-free transactions.

[0568] For example, if a user attempts to supply surplus electricity generated by solar power, and the emotion engine detects a state of tension, the server will simplify the transaction conditions and the AI ​​agent will propose more conservative conditions to ensure the user can agree to the transaction with confidence. As a result of this process, once the transaction is completed, the server records the completion on the blockchain and notifies the user.

[0569] Examples of prompt statements to input into a generative AI model are as follows:

[0570] "Use user sentiment data and power trading information to generate optimal trading conditions for the user. For example, suggest conservative conditions if the user is stressed, and provide normal conditions if the user is relaxed."

[0571] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0572] Step 1:

[0573] Users input information about surplus electricity obtained from renewable energy sources using a terminal. Specifically, they input data such as the amount of electricity that can be supplied, the desired price, and the time period during which transactions are possible. This information becomes input data and is sent to the server.

[0574] Step 2:

[0575] The system uses the camera and microphone on the user's device to collect the user's facial expressions and voice. This data is then used as input by an emotion engine to analyze the user's emotional state. The output from this analysis is quantified as data representing the user's emotional state, such as feeling safe, tense, or anxious.

[0576] Step 3:

[0577] The terminal combines power information entered by the user with emotional data analyzed by the emotion engine and sends this to the server. The resulting dataset is then passed to the server.

[0578] Step 4:

[0579] The server processes the received power and sentiment data, and first records the transaction information on the blockchain. This ensures that the information is managed in a way that makes tampering difficult. By using blockchain technology for the input dataset, highly reliable output data is accumulated.

[0580] Step 5:

[0581] The server collects historical consumption data and external environmental data in real time. This collected data is analyzed by an AI agent. The analyzed output is used to forecast future electricity demand and set optimal prices.

[0582] Step 6:

[0583] The AI ​​agent adjusts and proposes trading conditions tailored to the user based on the analysis results and the user's emotional data. If the user is stressed, the proposed output conditions will be more conservative and concise than usual. Conversely, if the user is relaxed, detailed trading conditions will be presented.

[0584] Step 7:

[0585] Once the user agrees to the presented transaction terms, the server executes the transaction based on those terms. The resulting transaction completion data is output and recorded on the blockchain. Finally, a transaction completion notification is sent to the terminal.

[0586] (Application Example 2)

[0587] Next, we will explain application example 2. In the following explanation, 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."

[0588] As the use of renewable energy increases, there is a need for efficient trading of surplus electricity. However, conventional trading systems often cause stress to users because they present conditions without considering their psychological state. Furthermore, systems with insufficient transparency and security can undermine the reliability of transactions. There is a need to solve these problems and provide a more user-friendly and reliable electricity trading platform.

[0589] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0590] In this invention, the server includes means for managing transaction information using blockchain technology, means for analyzing past consumption data and external environment data, artificial intelligence agent means for setting prices in real time based on the analysis results, emotion engine means for analyzing the user's emotional state, and means for dynamically adjusting transaction conditions based on the user's emotional state. This makes it possible to realize flexible and transparent transactions that respond to the user's emotions and ensure reliability.

[0591] Blockchain technology is a method that records data on a distributed ledger and uses cryptographic techniques to prevent unauthorized tampering.

[0592] "Transaction information" refers to various data related to electricity buying and selling transactions, including transaction terms and agreements.

[0593] "Consumption data" refers to records of past electricity usage.

[0594] "External environmental data" refers to information about external factors that affect transactions, such as weather and market trends.

[0595] An "artificial intelligence agent" is a program that analyzes data to make optimal decisions.

[0596] An "emotion engine" is a system that analyzes a user's emotional state and generates data based on the results.

[0597] An "interface" refers to the screens and input methods that a user uses to interact with a system.

[0598] "User emotional state" refers to the user's mental state, such as feeling safe, tense, or anxious.

[0599] "Terms of trade" refer to the price and other conditions agreed upon between the parties in the buying and selling of electricity.

[0600] To implement this invention, it is necessary to build a system that integrates a server, a user terminal, and an emotion engine. This system efficiently and securely conducts electricity trading while taking into account the user's emotional state. The user terminal includes input devices such as a camera and a microphone, which the emotion engine uses to analyze the user's facial expressions and voice. The server manages transaction information using blockchain technology and uses an artificial intelligence agent to analyze consumption data and external environmental data.

[0601] When a user participates in selling surplus electricity via their smartphone, the device acquires emotional data from its camera and microphone and sends the analysis results to a server. Based on this information, the server uses an AI agent to dynamically set transaction conditions that are tailored to the user's emotional state. If the user agrees to the transaction conditions, the server records this information on the blockchain in a way that makes it difficult to tamper with. As a result, users can trade with peace of mind under conditions optimized for their own emotional state.

[0602] As a concrete example, consider a scenario where a user, while spending a holiday at home, provides surplus electricity generated from their rooftop solar power system to the surrounding community. In this case, the transaction terms are displayed on the screen in a format that is easiest for the user to understand. This allows the user to participate in the transaction without feeling any anxiety.

[0603] An example of a prompt from a generated AI model might be: "Please describe in detail the requirements necessary to build a superior energy trading platform, including flexible trading conditions based on the user's emotional state and secure trading using blockchain."

[0604] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0605] Step 1:

[0606] The device uses its camera and microphone to capture the user's facial expressions and voice as input data. This input information is sent to an emotion engine, which analyzes the user's emotional state. The emotion engine analyzes the input data and outputs emotion data representing emotional states such as reassurance, tension, and anxiety.

[0607] Step 2:

[0608] The terminal sends emotional data obtained from the emotion engine to the server. The server then receives the user's current emotional state and stores it for use in the next step. Based on the emotional data, the server weights it within the system and prepares to present transaction terms that are less burdensome for the user.

[0609] Step 3:

[0610] The server collects historical consumption data and external environmental data, and analyzes it through an artificial intelligence agent. Based on the input consumption data and external environmental data, it performs demand forecasting and pricing, and generates the results as output. This prepares the server for use in generating transaction conditions in the next step.

[0611] Step 4:

[0612] The server integrates analysis results and sentiment data, and uses an AI agent to generate trading conditions that are appropriate for the user's emotions. The trading conditions are dynamically adjusted based on the sentiment data; for example, simpler conditions are output to a user who is stressed. The generated trading conditions are designed to allow the user to trade without stress.

[0613] Step 5:

[0614] The server sends the generated transaction terms to the user's terminal and displays the proposed terms on the interface. The user reviews these terms and chooses whether to agree or not. This choice is input from the terminal to the server and prepared as output for determining the success or failure of the transaction in the next step.

[0615] Step 6:

[0616] If the user agrees to the transaction terms, the server records the transaction information on the blockchain. Based on the entered consent information, the transaction is completed in a way that is difficult to tamper with using blockchain technology, and the completion information is sent as output to the user's terminal. This ensures that transactions are conducted fairly and transparently.

[0617] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0618] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0619] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0620] [Fourth Embodiment]

[0621] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0622] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0623] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0624] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0625] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0626] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0627] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0628] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0629] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0630] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0631] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0632] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0633] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0634] This invention is a power trading platform that combines blockchain technology and artificial intelligence, aiming to efficiently utilize surplus renewable energy. The system includes a communication network between terminals, servers, and users.

[0635] Users input surplus electricity information using their devices and send it to the server. This information includes the amount of electricity generated, the expected supply time, and the desired selling price. Based on the received information, the server securely registers the tradable electricity information on the blockchain. This ensures that the information is difficult to tamper with.

[0636] The server has the capability to automatically collect and analyze historical consumption data and external environmental data. Based on this analysis data, an AI agent predicts electricity demand in real time and automatically sets the optimal transaction price that meets the requirements of both the supply and demand sides. This process adjusts the pricing to adapt to market fluctuations.

[0637] Furthermore, the AI ​​agent selects trading partners via the server, taking into account various factors such as geographical conditions, the degree of supply-demand matching, and transaction history. Users receive the transaction terms via their terminal and decide whether to agree. Once an agreement is reached, the transaction is executed by the server, and the movement of electricity and settlement information are accurately recorded.

[0638] As a concrete example, consider a case where person A, who owns a home solar power generation system, sells the surplus electricity generated during the day to person B, who has demand for it at night. Person A registers the amount of electricity they can provide and their desired price in the system via a terminal. The server uses this information to present the best transaction terms to person B, the demander. If person B agrees, the server executes the transaction and records the transaction history on the blockchain. This ensures that transactions between both parties are conducted fairly and efficiently.

[0639] The following describes the processing flow.

[0640] Step 1:

[0641] The terminal receives user input and displays information about surplus power on the input screen. The user enters the amount of power available, the desired selling price, and the service period, and then sends this data to the server.

[0642] Step 2:

[0643] The server analyzes the transaction information received from the terminal, assigns an identifier, and records it on the blockchain. This guarantees the authenticity and immutability of the information.

[0644] Step 3:

[0645] The server periodically collects historical consumption data and external environmental data from a database and provides it to the AI ​​agent. This data forms the basis for demand forecasting.

[0646] Step 4:

[0647] An AI agent analyzes data collected on the server to predict future electricity demand. Based on the prediction, it calculates the optimal transaction price in real time and transmits that information to the server.

[0648] Step 5:

[0649] The server selects trading partners based on price information and transaction conditions received from the AI ​​agent. The selection process takes into account factors such as the user's location, supply, and demand to achieve the optimal pairing.

[0650] Step 6:

[0651] The terminal displays the transaction terms notified by the server to the user and requests confirmation of approval. If the user agrees to the terms, the terminal sends an approval response to the server.

[0652] Step 7:

[0653] The server executes the transaction after confirming the user's consent. The process is handled securely and transparently by initiating the power supply and payment procedures and recording the completion information of the transaction on the blockchain.

[0654] Step 8:

[0655] The terminal receives a transaction completion notification from the server and informs the user that the transaction has been successfully completed. The user can then check their transaction history on the terminal.

[0656] (Example 1)

[0657] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0658] As the use of renewable energy increases, a platform is needed for the efficient and fair trading of surplus electricity. However, current systems have problems such as concerns about the falsification of trading information and difficulties in setting fair prices in real time. Furthermore, there is a need for efficient methods for selecting trading partners.

[0659] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0660] In this invention, the server includes means for managing transaction information using blockchain technology, means for analyzing past consumption data and external environmental data, means for an artificial intelligence agent that sets prices in real time based on the analysis results, and means for selecting trading partners based on geographical conditions and matching degree. This ensures the reliability of transactions while enabling pricing that quickly adapts to market fluctuations and efficient selection of trading partners.

[0661] Blockchain technology is a distributed ledger technology that records transaction information in a chain-like structure, preventing tampering.

[0662] "Means for managing transaction information" refers to a system that records, updates, and allows reference to buying and selling data in electricity transactions as needed.

[0663] "Past consumption data and external environmental data" refers to past electricity usage history, as well as data related to the environment, such as weather and temperature.

[0664] "Methods of analysis" refer to analytical techniques that use collected data to discover patterns and trends and predict electricity demand.

[0665] An "artificial intelligence agent" is a program that uses machine learning and data analysis to make decisions and provide optimized information.

[0666] "Setting in real time" means that calculations are performed instantly every time the data is updated, and settings are automatically adjusted according to the fluctuating conditions.

[0667] "Methods for selecting trading partners based on geographical conditions and matching degree" refers to methods for finding the optimal trading partner by considering factors such as distance and the rate of supply-demand matching.

[0668] This invention aims to build a power trading platform that combines blockchain technology and artificial intelligence. It primarily functions as a server, terminal, and user system.

[0669] Server Role

[0670] The server receives surplus power information sent by users and manages it securely using blockchain technology. The server maintains a distributed ledger for data integration and analysis, preventing tampering. Furthermore, the server collects external environmental data (such as weather and temperature) and historical power consumption data via APIs. This data is used for demand forecasting by an AI agent.

[0671] Terminal role

[0672] Users input information about their surplus electricity using a terminal. The terminal transmits this information to the server, and the usability of the interface is crucial. The terminal also presents and confirms transaction terms.

[0673] User roles

[0674] Users play the role of either supplying or demanding electricity, and provide information about surplus electricity and trading requests through their terminals. It is also the user's responsibility to review the presented trading terms and decide whether to agree to them.

[0675] Hardware and software to be used

[0676] The server will utilize a high-performance computer system suitable for data processing, along with specialized software to support blockchain and AI analysis. Specifically, it will use an open-source blockchain platform for blockchain management and machine learning libraries for AI analysis. The terminals will be smartphones and tablets owned by users, running a dedicated application.

[0677] Specific example

[0678] A concrete example is a user with a solar power generation system at home who sells surplus electricity generated during the day to a specific user with high demand at night. In this case, the user selling the electricity registers the amount of electricity and their desired price in the system using a terminal, and the optimal transaction is executed through the server.

[0679] Example of a prompt:

[0680] "I want to design a platform for efficiently trading surplus renewable energy. How can we combine blockchain technology with AI?"

[0681] "How can we build an efficient system for selling surplus electricity generated by home solar power systems?"

[0682] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0683] Step 1:

[0684] Users input surplus power information using their own devices. Specifically, they open a dedicated application on their devices and input data such as power generation amount, available supply time, and desired selling price. The entered data is sent from the device to the server. This allows the server to store detailed information about the amount of electricity the user can provide.

[0685] Step 2:

[0686] The server receives surplus power information from users and registers the data on the blockchain. At this time, the server encrypts the received data and transmits it to the blockchain network using a secure communication protocol. This prevents data tampering and ensures reliability. As a result, the accuracy and security of the registered data are guaranteed by the blockchain.

[0687] Step 3:

[0688] The server collects external environmental data and historical power consumption data. This data includes temperature, weather, and regional power consumption patterns. The server retrieves this data using an API and stores it in a database for AI analysis. Based on the obtained data, AI-driven demand forecasting becomes possible in subsequent steps.

[0689] Step 4:

[0690] An AI agent performs analysis using data collected on the server. Here, primarily using machine learning algorithms, it predicts electricity demand in real time. The goal is to analyze the input data as a multidimensional vector and understand demand trends. The analysis results help optimize the transaction terms offered to users.

[0691] Step 5:

[0692] The server sets the transaction price based on the analysis results of the AI ​​agent. In this step, it calculates the optimal price that reflects the real-time supply and demand balance of the market. The AI ​​model considers past price fluctuations and uses an algorithm to determine a fair and competitive price. The set price is then reflected in transactions between users.

[0693] Step 6:

[0694] The server selects trading partners based on recommendations from the AI ​​agent. The selection process considers geographical conditions and the degree of supply-demand matching. The server scores this information and selects high-scoring trading candidates. This selection is a crucial element for achieving efficient and effective transactions.

[0695] Step 7:

[0696] The user reviews the transaction terms presented via their terminal. Information such as the trading partner, transaction price, and delivery time is displayed. The user selects whether to agree to the terms and sends their selection back to the server from their terminal. This process leads to a final transaction agreement.

[0697] Step 8:

[0698] Once the terms of the transaction are agreed upon, the server executes the transaction. Upon execution, the transfer of electricity begins, and the server generates settlement information. This information is registered on the blockchain as a transaction history, ensuring the integrity and transparency of the transaction.

[0699] (Application Example 1)

[0700] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0701] A trading platform for efficiently and fairly utilizing surplus renewable energy is underdeveloped, and the current system is prone to supply-demand imbalances. Furthermore, ensuring transparency and reliability of trading information is difficult, potentially leading to unfair transactions. In addition, there is a need for the real-time presentation of appropriate trading conditions.

[0702] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0703] In this invention, the server includes means for managing exchange information using blockchain technology, means for analyzing past consumption records and external environment records, artificial intelligence agent means for setting values ​​in real time based on the analysis results, means for presenting and receiving confirmation of exchange conditions between users, means for executing exchanges and recording their completion, means for registering the supply and demand of surplus energy through terminal devices, and artificial intelligence agent means for generating and presenting appropriate supply and demand conditions. This enables the efficient trading of surplus renewable energy and provides a fair and reliable platform.

[0704] Blockchain technology is a technology that securely records transaction information on a distributed ledger using cryptographic techniques.

[0705] "Exchange information" refers to information that includes data such as supply, demand, and price related to energy trading.

[0706] "Past consumption records" refer to historical data on energy consumption in the past.

[0707] "External environmental records" refer to data on external factors that affect energy demand and supply, such as weather conditions and market trends.

[0708] An "artificial intelligence agent" is a software agent that autonomously assesses its environment and makes decisions according to a specific purpose.

[0709] "Exchange terms between users" refer to the conditions for conducting a transaction, such as price and supply time.

[0710] A "terminal device" refers to an electronic device used by a user, such as a computer or smartphone.

[0711] "Surplus energy" refers to the portion of renewable energy generation that is not consumed and is left over.

[0712] "Appropriate supply and demand conditions" refer to the most efficient and beneficial trading conditions for both energy suppliers and consumers.

[0713] This invention is a system designed to efficiently trade surplus renewable energy. The system primarily utilizes a server, user terminal devices, and a communication network.

[0714] The server securely manages transaction information using blockchain technology. The database stores each user's past consumption records and external environment records, and an artificial intelligence agent is used to analyze this data. This analysis enables demand forecasting for power supply and generates optimal transaction conditions in real time.

[0715] The terminal device is used by users to register their surplus renewable energy and confirm transaction terms. By inputting information on the supply and demand of surplus energy through the terminal, an artificial intelligence agent presents appropriate transaction terms based on that information. If an agreement is reached, the transaction is automatically executed.

[0716] As a concrete example, consider a situation where one user generates surplus renewable energy during the day, and another user wants to use that energy at night. In this case, the server uses AI to generate and present the optimal transaction terms for both parties.

[0717] The hardware required for the system to operate includes data center facilities as servers, smartphones as user terminals, and internet connectivity. The software used includes Ethereum for blockchain, TensorFlow for AI models, and Pandas for data analysis.

[0718] An example of a prompt statement a user could ask the generated AI model: "How can we optimize the overall power efficiency of a city by sharing renewable energy through a smart energy sharing app?"

[0719] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0720] Step 1:

[0721] Users input information about their surplus energy supply using their own devices. This input includes the amount of energy available, the estimated supply time, and the desired price. This information is transmitted from the device to the server. The input data is processed as basic numerical data.

[0722] Step 2:

[0723] The server registers transaction information on the blockchain based on the received data. The use of blockchain prevents data tampering and maintains security. The input is transaction information from the user, and the output is a transaction history securely recorded on the blockchain.

[0724] Step 3:

[0725] The server collects historical consumption records and external environmental records from a database and performs data analysis based on these. An AI model (using TensorFlow) is used to predict the optimal conditions for both supply and demand. The input is historical consumption and environmental data, and the output is the predicted optimal transaction conditions.

[0726] Step 4:

[0727] The AI ​​agent automatically sets transaction conditions between users based on the optimal conditions obtained through analysis and presents them to the user via the terminal. In this process, user input information and the results of the AI ​​analysis are combined to generate prompt sentences for presenting the conditions. The input is the analysis results, and the output is the presented transaction conditions.

[0728] Step 5:

[0729] The user reviews the transaction terms on their device and chooses to agree or reject them. The input here is the user's response to the presented terms, and the output is the result of the user's selection. If the user agrees, the process proceeds to the next step.

[0730] Step 6:

[0731] The server executes the transaction with the user's consent. After the transaction is completed, it adds this transaction record to the blockchain to maintain data reliability. The input is the user's consent and approval, and the output is the newly recorded transaction history.

[0732] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0733] This invention is a power trading platform that combines blockchain technology, artificial intelligence, and an emotion engine. It not only efficiently utilizes surplus renewable energy but also provides flexible trading that takes into account the user's emotional state. The system consists of a user terminal, a server, and an emotion engine.

[0734] The user inputs information about surplus power through their device and sends it to the server. The device is equipped with input devices such as a camera and microphone, and an emotion engine analyzes the user's facial expressions and voice to determine their emotional state. The analysis results can generate data representing the user's current emotional state (e.g., reassurance, tension, anxiety).

[0735] The server processes electricity consumption and sentiment data received from users and records transaction information on the blockchain. This enables management in a way that makes it difficult to tamper with the information. Furthermore, the server collects historical consumption data and external environmental data in real time and analyzes it through an AI agent. This analysis enables future electricity demand forecasting and the setting of optimal prices.

[0736] The AI ​​agent adjusts trading conditions based on the user's emotional data, proposing trades in a way that does not stress the user. If the user is relaxed, it will present the information in a normal interface; if the user is stressed, it will reduce the amount of information and present a simpler interface.

[0737] For example, when user A offers surplus solar power, if the emotion engine detects that A is slightly stressed, the server will concisely summarize and display the transaction terms. Furthermore, the proposed transaction terms can be slightly conservative, as suggested by the AI ​​agent to alleviate A's stress. This allows A to confidently agree to the terms. Once the transaction is agreed upon, the server records the transaction on the blockchain and sends a notification to the terminal. In this way, fair and efficient transactions can be achieved while taking the user's emotional state into consideration.

[0738] The following describes the processing flow.

[0739] Step 1:

[0740] The terminal receives user input and displays information about surplus electricity (generation amount, availability time, desired price) on the input screen. The user enters this information and sends it to the system.

[0741] Step 2:

[0742] The device's camera and microphone capture the user's facial expressions and voice, and the emotion engine analyzes this data. The analysis generates data on the user's emotional state (e.g., feeling safe, tense, anxious).

[0743] Step 3:

[0744] The server analyzes surplus power information and sentiment data received from the terminals and generates transaction information for use in power trading. This information is recorded on the blockchain to ensure security and transparency.

[0745] Step 4:

[0746] The server collects historical consumption data and external environmental data and provides it to the AI ​​agent. Based on this data, the AI ​​agent predicts electricity demand and calculates the optimal transaction price in real time.

[0747] Step 5:

[0748] The AI ​​agent considers the user's emotional state and adjusts the trading conditions accordingly. If it determines that the user is stressed, the AI ​​agent presents the trading conditions using a simple and easy-to-understand interface.

[0749] Step 6:

[0750] The terminal displays the transaction terms obtained from the server to the user and requests the user's approval. If the user agrees to the proposed terms, the terminal sends the approval to the server.

[0751] Step 7:

[0752] Once the server confirms the user's consent, the transaction is formally executed. Information regarding the supply of electricity and the settlement of its payment is recorded on the blockchain to maintain transaction transparency.

[0753] Step 8:

[0754] The terminal receives a transaction completion notification from the server and informs the user that the transaction has been successfully completed. The user can then check the transaction history on the terminal and confidently exit the system.

[0755] (Example 2)

[0756] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0757] Traditional electricity trading systems offered fixed interfaces and trading conditions without considering the emotional aspects of users, potentially leading to user stress and dissatisfaction. Furthermore, they carried the risk of tampering and fraudulent activity regarding trading information.

[0758] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0759] In this invention, the server includes means for managing transaction information using blockchain technology, means for analyzing past consumption data and external environment data, and emotion engine means for analyzing the user's emotional state. This enables fair and user-friendly transactions by managing tamper-proof transaction information while taking the user's emotional state into consideration.

[0760] Blockchain is a database technology that records multiple transaction details in a chain of blocks, making it extremely difficult to tamper with on a decentralized network.

[0761] An "artificial intelligence agent" is a software system that autonomously determines and adjusts trading conditions based on data analysis and provides optimized information.

[0762] An "emotion engine" is an algorithm and system that analyzes a user's facial expressions and voice data to identify their emotional state.

[0763] A "user" is an individual or entity that inputs information about the supply or demand of electricity into the system and participates in the trading process.

[0764] "Transaction information" refers to a series of data related to the buying and selling of electricity, including details about the amount of electricity, price, time, and the parties involved in the transaction.

[0765] This invention relates to a power trading platform that combines blockchain technology, artificial intelligence, and an emotion engine, which not only efficiently trades surplus renewable energy but also provides flexible trading that takes into account the emotional state of the user.

[0766] The user transmits information about surplus electricity obtained from renewable energy sources to a server via a device. This device has built-in input devices such as a camera and microphone, which collect the user's facial expressions and voice. The emotion engine analyzes this data to identify the user's emotional state, such as feeling relaxed or anxious.

[0767] The server processes data based on electricity information received from users and analyzed sentiment data, and records the results on the blockchain. This makes it difficult to tamper with transaction information. The server also collects historical electricity consumption data and external environmental data such as weather in real time, and an AI agent performs demand forecasting and pricing. This AI agent adjusts transaction conditions based on the user's sentiment state, providing an interface that allows for stress-free transactions.

[0768] For example, if a user attempts to supply surplus electricity generated by solar power, and the emotion engine detects a state of tension, the server will simplify the transaction conditions and the AI ​​agent will propose more conservative conditions to ensure the user can agree to the transaction with confidence. As a result of this process, once the transaction is completed, the server records the completion on the blockchain and notifies the user.

[0769] Examples of prompt statements to input into a generative AI model are as follows:

[0770] "Use user sentiment data and power trading information to generate optimal trading conditions for the user. For example, suggest conservative conditions if the user is stressed, and provide normal conditions if the user is relaxed."

[0771] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0772] Step 1:

[0773] Users input information about surplus electricity obtained from renewable energy sources using a terminal. Specifically, they input data such as the amount of electricity that can be supplied, the desired price, and the time period during which transactions are possible. This information becomes input data and is sent to the server.

[0774] Step 2:

[0775] The system uses the camera and microphone on the user's device to collect the user's facial expressions and voice. This data is then used as input by an emotion engine to analyze the user's emotional state. The output from this analysis is quantified as data representing the user's emotional state, such as feeling safe, tense, or anxious.

[0776] Step 3:

[0777] The terminal combines power information entered by the user with emotional data analyzed by the emotion engine and sends this to the server. The resulting dataset is then passed to the server.

[0778] Step 4:

[0779] The server processes the received power and sentiment data, and first records the transaction information on the blockchain. This ensures that the information is managed in a way that makes tampering difficult. By using blockchain technology for the input dataset, highly reliable output data is accumulated.

[0780] Step 5:

[0781] The server collects historical consumption data and external environmental data in real time. This collected data is analyzed by an AI agent. The analyzed output is used to forecast future electricity demand and set optimal prices.

[0782] Step 6:

[0783] The AI ​​agent adjusts and proposes trading conditions tailored to the user based on the analysis results and the user's emotional data. If the user is stressed, the proposed output conditions will be more conservative and concise than usual. Conversely, if the user is relaxed, detailed trading conditions will be presented.

[0784] Step 7:

[0785] Once the user agrees to the presented transaction terms, the server executes the transaction based on those terms. The resulting transaction completion data is output and recorded on the blockchain. Finally, a transaction completion notification is sent to the terminal.

[0786] (Application Example 2)

[0787] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0788] As the use of renewable energy increases, there is a need for efficient trading of surplus electricity. However, conventional trading systems often cause stress to users because they present conditions without considering their psychological state. Furthermore, systems with insufficient transparency and security can undermine the reliability of transactions. There is a need to solve these problems and provide a more user-friendly and reliable electricity trading platform.

[0789] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0790] In this invention, the server includes means for managing transaction information using blockchain technology, means for analyzing past consumption data and external environment data, artificial intelligence agent means for setting prices in real time based on the analysis results, emotion engine means for analyzing the user's emotional state, and means for dynamically adjusting transaction conditions based on the user's emotional state. This makes it possible to realize flexible and transparent transactions that respond to the user's emotions and ensure reliability.

[0791] Blockchain technology is a method that records data on a distributed ledger and uses cryptographic techniques to prevent unauthorized tampering.

[0792] "Transaction information" refers to various data related to electricity buying and selling transactions, including transaction terms and agreements.

[0793] "Consumption data" refers to records of past electricity usage.

[0794] "External environmental data" refers to information about external factors that affect transactions, such as weather and market trends.

[0795] An "artificial intelligence agent" is a program that analyzes data to make optimal decisions.

[0796] An "emotion engine" is a system that analyzes a user's emotional state and generates data based on the results.

[0797] An "interface" refers to the screens and input methods that a user uses to interact with a system.

[0798] "User emotional state" refers to the user's mental state, such as feeling safe, tense, or anxious.

[0799] "Terms of trade" refer to the price and other conditions agreed upon between the parties in the buying and selling of electricity.

[0800] To implement this invention, it is necessary to build a system that integrates a server, a user terminal, and an emotion engine. This system efficiently and securely conducts electricity trading while taking into account the user's emotional state. The user terminal includes input devices such as a camera and a microphone, which the emotion engine uses to analyze the user's facial expressions and voice. The server manages transaction information using blockchain technology and uses an artificial intelligence agent to analyze consumption data and external environmental data.

[0801] When a user participates in selling surplus electricity via their smartphone, the device acquires emotional data from its camera and microphone and sends the analysis results to a server. Based on this information, the server uses an AI agent to dynamically set transaction conditions that are tailored to the user's emotional state. If the user agrees to the transaction conditions, the server records this information on the blockchain in a way that makes it difficult to tamper with. As a result, users can trade with peace of mind under conditions optimized for their own emotional state.

[0802] As a concrete example, consider a scenario where a user, while spending a holiday at home, provides surplus electricity generated from their rooftop solar power system to the surrounding community. In this case, the transaction terms are displayed on the screen in a format that is easiest for the user to understand. This allows the user to participate in the transaction without feeling any anxiety.

[0803] An example of a prompt from a generated AI model might be: "Please describe in detail the requirements necessary to build a superior energy trading platform, including flexible trading conditions based on the user's emotional state and secure trading using blockchain."

[0804] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0805] Step 1:

[0806] The device uses its camera and microphone to capture the user's facial expressions and voice as input data. This input information is sent to an emotion engine, which analyzes the user's emotional state. The emotion engine analyzes the input data and outputs emotion data representing emotional states such as reassurance, tension, and anxiety.

[0807] Step 2:

[0808] The terminal sends emotional data obtained from the emotion engine to the server. The server then receives the user's current emotional state and stores it for use in the next step. Based on the emotional data, the server weights it within the system and prepares to present transaction terms that are less burdensome for the user.

[0809] Step 3:

[0810] The server collects historical consumption data and external environmental data, and analyzes it through an artificial intelligence agent. Based on the input consumption data and external environmental data, it performs demand forecasting and pricing, and generates the results as output. This prepares the server for use in generating transaction conditions in the next step.

[0811] Step 4:

[0812] The server integrates analysis results and sentiment data, and uses an AI agent to generate trading conditions that are appropriate for the user's emotions. The trading conditions are dynamically adjusted based on the sentiment data; for example, simpler conditions are output to a user who is stressed. The generated trading conditions are designed to allow the user to trade without stress.

[0813] Step 5:

[0814] The server sends the generated transaction terms to the user's terminal and displays the proposed terms on the interface. The user reviews these terms and chooses whether to agree or not. This choice is input from the terminal to the server and prepared as output for determining the success or failure of the transaction in the next step.

[0815] Step 6:

[0816] If the user agrees to the transaction terms, the server records the transaction information on the blockchain. Based on the entered consent information, the transaction is completed in a way that is difficult to tamper with using blockchain technology, and the completion information is sent as output to the user's terminal. This ensures that transactions are conducted fairly and transparently.

[0817] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0818] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0819] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0820] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0821] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0822] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0823] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0824] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0825] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0826] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0827] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0828] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0829] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0830] 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.

[0831] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0832] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0833] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0834] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0835] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0836] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0837] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0838] The following is further disclosed regarding the embodiments described above.

[0839] (Claim 1)

[0840] A means of managing transaction information using blockchain technology,

[0841] A means of analyzing past consumption data and external environmental data,

[0842] An artificial intelligence agent that sets prices in real time based on analysis results,

[0843] A means of presenting and confirming transaction terms between users,

[0844] A means of executing and recording the completion of a transaction,

[0845] A system that includes this.

[0846] (Claim 2)

[0847] The system according to claim 1, comprising means for forecasting demand based on past consumption data and external environmental data.

[0848] (Claim 3)

[0849] The system according to claim 1, comprising a means for selecting trading partners selected by an artificial intelligence agent.

[0850] "Example 1"

[0851] (Claim 1)

[0852] A means of managing transaction information using blockchain technology,

[0853] A means of analyzing past consumption data and external environmental data,

[0854] An artificial intelligence agent that sets prices in real time based on analysis results,

[0855] A means of presenting and confirming transaction terms between users,

[0856] A means of executing and recording the completion of a transaction,

[0857] Methods for selecting trading partners based on geographical conditions and degree of compatibility,

[0858] A system that includes this.

[0859] (Claim 2)

[0860] The system according to claim 1, comprising means for forecasting demand based on past consumption data and external environmental data.

[0861] (Claim 3)

[0862] The system according to claim 1, comprising a means for selecting trading partners selected by an artificial intelligence agent.

[0863] "Application Example 1"

[0864] (Claim 1)

[0865] A means of managing exchanged information using blockchain technology,

[0866] A means for analyzing past consumption records and external environmental records,

[0867] An artificial intelligence agent means that sets value in real time based on analysis results,

[0868] A means of presenting and confirming the terms of exchange between users,

[0869] A means of performing an exchange and recording its completion,

[0870] A means for registering the supply and demand of surplus energy through a terminal device,

[0871] An artificial intelligence agent means that generates and presents appropriate conditions for supply and demand,

[0872] A system that includes this.

[0873] (Claim 2)

[0874] The system according to claim 1, comprising means for performing supply forecasts based on past consumption records and external environmental records.

[0875] (Claim 3)

[0876] The system according to claim 1, comprising a selection means for an exchange target selected by an artificial intelligence agent.

[0877] "Example 2 of combining an emotion engine"

[0878] (Claim 1)

[0879] A means of managing transaction information using blockchain technology,

[0880] A means of analyzing past consumption data and external environmental data,

[0881] An artificial intelligence agent that sets prices in real time based on analysis results,

[0882] An emotion engine means for analyzing the user's emotional state,

[0883] A means of adjusting and presenting transaction conditions to the user based on their emotional state,

[0884] A means of executing and recording the completion of a transaction,

[0885] A system that includes this.

[0886] (Claim 2)

[0887] The system according to claim 1, comprising means for forecasting demand based on past consumption data and external environmental data.

[0888] (Claim 3)

[0889] The system according to claim 1, comprising a means for selecting trading partners selected by an artificial intelligence agent.

[0890] "Application example 2 when combining with an emotional engine"

[0891] (Claim 1)

[0892] A means of managing transaction information using blockchain technology,

[0893] A means of analyzing past consumption data and external environmental data,

[0894] An artificial intelligence agent that sets prices in real time based on analysis results,

[0895] A means of presenting and confirming transaction terms between users,

[0896] A means of executing and recording the completion of a transaction,

[0897] An emotion engine for analyzing the user's emotional state,

[0898] A means of dynamically adjusting trading conditions based on the user's emotional state,

[0899] A means of presenting an emotion-based trading interface,

[0900] A system that includes this.

[0901] (Claim 2)

[0902] The system according to claim 1, comprising means for forecasting demand based on past consumption data and external environmental data.

[0903] (Claim 3)

[0904] The system according to claim 1, comprising a means for selecting trading partners selected by an artificial intelligence agent. [Explanation of Symbols]

[0905] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of managing exchanged information using blockchain technology, A means for analyzing past consumption records and external environmental records, An artificial intelligence agent means that sets value in real time based on analysis results, A means of presenting and confirming the terms of exchange between users, A means of performing an exchange and recording its completion, A means for registering the supply and demand of surplus energy through a terminal device, An artificial intelligence agent means that generates and presents appropriate conditions for supply and demand, A system that includes this.

2. The system according to claim 1, comprising means for performing supply forecasts based on past consumption records and external environmental records.

3. The system according to claim 1, comprising a selection means for an exchange target selected by an artificial intelligence agent.

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