system

Abstract

We provide the system. [Solution] A data acquisition method for obtaining power consumption information, An analytical method for analyzing and predicting consumption trends based on past electricity consumption information, A strategy generation means for generating an electricity usage plan based on analyzed consumption trends, An information exchange means that uses communication technology to ensure secure information transmission to perform secure transmission and reception of data, A means of adjusting the balance between power supply and consumption in real time, An information display device that shows the electricity consumption status of homes and businesses on the user's mobile device and suggests ways to improve energy efficiency, A system that includes this.

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] In the current power supply system, imbalance between power demand and supply easily occurs, and power shortage or over - supply during peak hours becomes a problem. Also, there are concerns about data leakage and falsification due to cyber - attacks, threatening the security of the power grid. Furthermore, with the expansion of the use of renewable energy, the adjustment of supply - demand balance has become more complicated. As a result, it is difficult to ensure the efficiency, security, and sustainability of power supply.

Means for Solving the Problems

[0005] This invention optimizes power supply planning by using information acquisition means to acquire power consumption information and analysis means to analyze and predict consumption patterns based on past power consumption information. It also includes planning generation means to generate a power usage plan based on the analyzed consumption patterns, proposing efficient power distribution. Furthermore, it achieves secure transmission and reception of data using communication means utilizing quantum communication technology, preventing leakage and tampering of power-related information. In addition, by including control means to adjust the balance between power supply and consumption in real time, it aims to stabilize supply and demand while maximizing the use of renewable energy.

[0006] "Electricity consumption information" refers to data that shows the amount of electricity used by households and businesses, as well as their usage patterns at different times of the day.

[0007] "Information acquisition means" refers to devices and processes for collecting various types of data, including power consumption information.

[0008] "Analysis methods" refer to technologies used to analyze consumption patterns based on acquired data and predict future demand.

[0009] A "consumption pattern" refers to the trends and characteristics of electricity usage over a certain period, and is extracted based on past consumption data.

[0010] A "plan generation method" is a method for constructing electricity usage plans and supply strategies based on analyzed consumption patterns.

[0011] "Quantum communication technology" is a communication method that uses the principles of quantum mechanics to transmit information safely and quickly.

[0012] "Communication methods" refer to means for sending and receiving data, and in this context, specifically those utilizing quantum communication technology.

[0013] A "control means" refers to a device or process for managing and adjusting the balance between power supply and consumption in real time.

[0014] "Renewable energy" refers to sustainable energy sources that can be repeatedly obtained from nature, such as solar and wind power. [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] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of a 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, a 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), and the like.

[0019] In the following embodiments, a 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, a 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] The system of this invention possesses advanced information processing technology to achieve efficient and safe power supply in homes and businesses. The system mainly consists of a server and terminals, and optimizes power supply according to the following procedure.

[0037] First, the device acquires consumption information in real time from electricity meters in each home and business. This data is measured, for example, every 5 minutes and includes current electricity usage and past consumption history. Weather information is also continuously acquired from external weather information services.

[0038] Next, the server receives this data and stores it in a database. There, it analyzes data from the past few weeks to months to generate consumption patterns. Machine learning algorithms are applied to this consumption pattern analysis, and by analyzing past consumption trends and seasonal fluctuations in particular, it makes highly accurate future predictions.

[0039] Furthermore, based on the generated consumption patterns, the AI ​​agent proposes an optimal power usage plan for each household or business. This plan includes specific actions to reduce peak power consumption, such as "setting the washing machine timer to increase power consumption in the morning" or "adjusting the office air conditioning temperature during specific time periods."

[0040] In terms of communication, the server uses quantum communication technology to securely transfer data to power companies and power plants. This reduces the risk of unauthorized acquisition of transmitted power consumption information and supply and demand adjustment instructions, allowing for secure data management.

[0041] Finally, the servers and terminals monitor the electricity demand of each household and business, and automatically adjust the balance of power supply whenever possible. This adjustment enables immediate feedback on power supply and demand, increasing efficiency in maximizing the use of renewable energy. This reduces wasted electricity use while ensuring a stable power supply.

[0042] Based on the above, the present invention is a system that provides efficient use and safe supply of electricity, thereby reducing the electricity burden on households and businesses.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The terminal acquires real-time electricity consumption data from home and business electricity meters. This data is measured every 5 minutes and sent to the server, along with past consumption information.

[0046] Step 2:

[0047] The device accesses external weather information services to obtain current weather and forecast data. This weather data is also updated regularly and sent to the server.

[0048] Step 3:

[0049] The server stores the received power consumption data and weather data in a database. This creates a comprehensive dataset covering the past and present.

[0050] Step 4:

[0051] The server uses machine learning algorithms to analyze consumption patterns. This analysis takes into account past consumption trends and seasonal fluctuations to build a model that predicts future consumption behavior.

[0052] Step 5:

[0053] The AI ​​agent generates an optimal power usage plan for each household or business based on consumption patterns obtained from the server. The plan includes specific actions to avoid peak consumption.

[0054] Step 6:

[0055] The server transmits the generated power usage plan to terminals in each home and business. This process utilizes quantum communication technology to ensure secure data transfer.

[0056] Step 7:

[0057] The server monitors power demand in real time and adjusts the supply balance as needed. This maximizes the use of renewable energy and reduces wasteful consumption.

[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] In modern society, efficient and stable electricity consumption is a critical issue. Excessive electricity consumption and unpredictable fluctuations in demand lead to wasteful energy resources, unstable supply, and increased environmental burden. Furthermore, the secure management and transmission of collected electricity consumption information is also a challenge, as the unauthorized acquisition of this information could lead to privacy violations and economic losses.

[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 a device for acquiring power consumption information, a device for collecting weather information from an external information source, and a computing device for analyzing and predicting consumption patterns based on past power consumption information. This enables improved efficiency and stable supply of power consumption, as well as enhanced security of data communications.

[0063] A "device for acquiring power consumption information" is a machine that continuously and accurately collects power usage data from measuring instruments installed in homes and businesses.

[0064] A "device for collecting weather information from external sources" is a device for obtaining weather condition data from external data services via the internet.

[0065] A "computational device for analyzing and predicting consumption patterns" is a computer system that calculates and predicts future power consumption based on collected power consumption data and historical data.

[0066] A "planning device for generating power usage plans" is a device that creates an optimal power consumption schedule based on analyzed consumption patterns.

[0067] A "communication device using quantum communication technology" is a communication device that utilizes quantum key distribution technology to ensure high security in data transmission and reception.

[0068] A "control device that adjusts the balance between power supply and consumption in real time" is a device that monitors the energy supply and demand situation and adjusts the power supply as needed, thereby enabling efficient energy management.

[0069] The system of this invention is intended to promote efficient and safe power supply in homes and businesses. This system mainly consists of a server and terminals and uses data from measuring instruments installed in each home and business, as well as from external information sources.

[0070] The terminal is a device for obtaining real-time power consumption information from power meters. For example, it uses a smart meter to measure power usage every five minutes and transmits the data to a server. The terminal also connects to external information sources and obtains weather information via APIs. This allows for real-time monitoring of weather conditions that may affect power consumption.

[0071] The server is a system that receives data provided by terminals and stores it in a database. Using a database management system (e.g., MySQL®, PostgreSQL), it integrates hourly consumption data and weather information and stores it over long periods. Based on this data, the server uses machine learning algorithms to analyze power consumption patterns and predict future consumption.

[0072] Furthermore, the server uses an AI agent to suggest an optimal power usage plan to the user based on the analyzed consumption patterns. This plan includes specific actions to reduce power consumption during peak hours. For example, it might suggest "use the washing machine in the morning and reduce power usage during the afternoon peak." Users receive these suggestions through a smartphone app or web interface.

[0073] In this system, the server uses quantum communication technology to securely transmit data to power companies and power plants. Quantum key distribution technology is used for data encryption and decryption, enhancing communication security. Therefore, it is possible to prevent the unauthorized acquisition of power consumption information and supply and demand adjustment instructions.

[0074] For example, when a user utilizes this system in a smart home environment, the AI ​​agent automatically adjusts the operating schedule of home appliances according to the proposed power usage plan, optimizing energy efficiency. This allows the user to reduce electricity costs while maintaining a comfortable living environment.

[0075] Examples of prompts to input into a generative AI model:

[0076] "Based on current electricity consumption data and weather information, please propose the optimal electricity usage plan for this week."

[0077] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0078] Step 1:

[0079] The terminal acquires electricity consumption information from electricity meters in each home and business. This acquisition is performed at 5-minute intervals, collecting the current electricity consumption measured by the smart meter as digital data. The input is numerical data from the meter, and the output is the process of preparing this data as digital data ready to be transmitted to the server in real time.

[0080] Step 2:

[0081] The device accesses an external weather service to obtain weather information. This process uses an API to retrieve data such as current temperature, humidity, and weather conditions, and then formats this data for transmission to the server. The input is raw data from the weather service, and the output is weather information data in a parseable format.

[0082] Step 3:

[0083] The server stores power consumption data and weather information data received from terminals in a database. Specifically, it organizes and records this data appropriately in the database management system. The input is power consumption and weather information transmitted from terminals, and the output is a record as a database entry suitable for long-term storage.

[0084] Step 4:

[0085] The server performs analysis using data stored in the database. In this step, machine learning algorithms are applied to generate consumption patterns. The input consists of historical power consumption data and weather data, and the output is predicted future power consumption trends and patterns.

[0086] Step 5:

[0087] The server uses an AI agent to create an optimal power usage plan based on the generated consumption patterns. The plan includes specific power usage suggestions for each household or business. The input is the consumption patterns extracted in step 4, and the output is the specific power usage schedule proposed to the user.

[0088] Step 6:

[0089] The server securely transmits power consumption information and proposed power usage plans using quantum communication technology. Here, quantum key distribution technology is used to encrypt the communication and ensure security. The input is the plan data, and the output is the securely transmitted plan information.

[0090] Step 7:

[0091] Users receive a proposed power usage plan and provide feedback. They review the information received via a smartphone app or web interface and fine-tune the plan as needed. The input is the plan information received from the server, and the output is the final plan with the user's consent or adjustments.

[0092] (Application Example 1)

[0093] 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."

[0094] In modern homes and businesses, electricity consumption continues to increase, necessitating efficient energy use. Furthermore, there is a lack of systems capable of secure and rapid data communication and providing concrete energy-saving suggestions. Therefore, a means is needed to ensure the stability of the power supply while allowing users to understand the situation in real time and improve energy efficiency.

[0095] 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.

[0096] In this invention, the server includes data acquisition means for acquiring power consumption information, analysis means for analyzing and predicting consumption trends based on past power consumption information, and strategy generation means for generating a power usage plan based on the analyzed consumption trends. This enables real-time optimization of energy consumption in homes and businesses, and allows for safe and efficient power supply.

[0097] "Data acquisition means" refers to a device or function that has the function of collecting electricity consumption information in homes and businesses in real time and transferring the data from each terminal to a server.

[0098] "Analysis means" refers to a device or function that uses collected past electricity consumption information to analyze consumption trends and perform processing to predict future electricity demand.

[0099] A "strategy generation tool" is a device or function that has the function of formulating a plan to achieve efficient power utilization based on analyzed power consumption trends.

[0100] "Information exchange means" refers to a device or function that uses communication technology to ensure secure information transmission to send and receive data, and to perform encryption and decryption.

[0101] "Adjustment means" refers to a device or function that performs the necessary controls to monitor and adjust the balance between power supply and consumption in real time.

[0102] "Information display means" refers to a device or function that has the ability to display information in real time on the screen of a mobile device or similar device, so that users can easily understand the power consumption status of their home or business.

[0103] The system constructed to implement this invention includes data acquisition means, analysis means, strategy generation means, information exchange means, coordination means, and information display means. The server uses these means to improve power consumption efficiency and secure data communication.

[0104] The server collects power consumption data in real time via IoT devices as a data acquisition method. Specifically, it collects data using the MQTT protocol, for example, and manages backend processing with an API that employs the Flask framework. The collected data is analyzed using TENSORFLOW® as an analysis tool to form a model that predicts future power demand based on past consumption trends.

[0105] The strategy generation tool presents users with efficient power usage methods based on the generated analysis results. This functionality is delivered directly to users through a mobile application built using React Native. Users can use this app to monitor their power usage in real time and obtain specific actions to take to save energy.

[0106] As a means of information exchange, the server utilizes quantum communication technology to ensure secure information transmission, encrypting data transmission and reception over the communication network. Furthermore, the adjustment mechanism monitors power supply and consumption in real time, automatically adjusting the supply-demand balance.

[0107] For example, if excessive power consumption is predicted during a specific time of day, the system will send a notification to the user such as, "Please change the washing machine usage time to reduce power consumption during this time." An example of a prompt to be input into the generating AI model might be, "Based on power consumption data from the past month and weather forecast data, predict next week's energy consumption pattern and propose an effective action plan for peak shifting."

[0108] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0109] Step 1:

[0110] The server receives power consumption data in real time from terminals via the MQTT protocol. This input data includes information from electricity meters in specific homes or businesses, and the server stores this data in a database.

[0111] Step 2:

[0112] The server uses stored power consumption data to perform data analysis based on a machine learning model utilizing TensorFlow. It takes historical power consumption data and weather information as input to model consumption trends. As a result of the analysis, a forecast of future power demand is output.

[0113] Step 3:

[0114] The server uses the analysis results to present a power usage plan to a mobile app built with React Native via an AI agent. Input information includes predicted consumption trends, and the output generates specific savings suggestions for the user.

[0115] Step 4:

[0116] Users receive power usage plans and suggestions sent from the server via a mobile app. Based on this information, users can select specific power-saving actions. The suggestions provided might include things like "avoid using electrical appliances during peak hours."

[0117] Step 5:

[0118] The terminal controls each device to adjust power consumption within homes and businesses, following instructions from the server. It receives adjustment instructions from the server as input and controls the operation of the corresponding device as output. This optimizes the balance between power supply and consumption in real time.

[0119] 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.

[0120] The system in this invention formulates an optimal power usage plan based on power consumption information and user emotion information. The system mainly consists of a server, a terminal, and an emotion engine, and is implemented in the following procedure.

[0121] First, the terminal acquires real-time power consumption data from home and business electricity meters. This data is recorded every 5 minutes and sent to the server, and weather information is also obtained from external services and sent to the server.

[0122] Next, the emotion engine analyzes emotional information from the user's voice input and camera input. This analysis determines the user's current emotional state, and the result is sent to the server.

[0123] The server stores received power consumption data, weather information, and sentiment information in a database. Based on this data, machine learning algorithms are used to analyze consumption patterns and predict future power consumption. User sentiment information, in particular, is considered important as a factor influencing consumption behavior and is reflected in the system for individual optimization.

[0124] Next, the AI ​​agent uses the analyzed data to generate an optimized power usage plan for specific emotional states. For example, when the user is relaxed, it adjusts lighting and temperature settings for greater comfort, and when stress levels are high, it suggests things like playing music to reduce stress.

[0125] To ensure privacy and data security, the server uses quantum communication technology to encrypt and decrypt communications while smoothly exchanging data. This ensures that user emotional information and power usage data are managed securely.

[0126] Finally, users can review the proposed electricity usage plan on their smartphone app or device. They can then accept the system's proposal or adjust the plan as needed to achieve energy management tailored to their individual needs.

[0127] This embodiment enables the efficient and safe supply of electricity, making the user's living environment more comfortable.

[0128] The following describes the processing flow.

[0129] Step 1:

[0130] The terminal acquires real-time power consumption data from home and business electricity meters. This data is sent to the server at 5-minute intervals. The terminal also acquires weather data from weather information services and sends it to the server in the same manner.

[0131] Step 2:

[0132] The emotion engine acquires user audio and video data from the microphone and camera connected to the device. It analyzes this data to identify the user's current emotional state. This emotional information is then sent to the server.

[0133] Step 3:

[0134] The server integrates the received power consumption data, weather data, and sentiment information and stores it in a database. This creates a foundational dataset for comprehensively understanding the situation.

[0135] Step 4:

[0136] The server uses machine learning algorithms to analyze past consumption data and sentiment information. This allows it to more accurately predict future electricity demand and user behavior.

[0137] Step 5:

[0138] The AI ​​agent generates a power usage plan tailored to the user's emotional state, based on data predicted by the server. This plan may include lighting and air conditioning settings to improve comfort.

[0139] Step 6:

[0140] The server transmits the generated power usage plan to terminals in each home and business. Quantum communication technology is used to ensure the security and privacy of the communication.

[0141] Step 7:

[0142] Users review suggestions from the AI ​​agent via their device or smartphone app. Based on these suggestions, users can adjust their actual power usage and operate according to a plan that also reflects emotional information.

[0143] (Example 2)

[0144] 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 will be referred to as the "terminal."

[0145] Managing electricity consumption efficiently in modern society and creating optimal power usage plans tailored to the emotional state of individual users presents a significant challenge. Furthermore, there is a need to balance power supply and consumption in real time while ensuring privacy and data security. Conventional systems are insufficient to address these challenges.

[0146] 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.

[0147] In this invention, the server includes data acquisition means for acquiring power consumption information and weather information, emotion analysis means for analyzing user emotion information and determining the emotional state, and consumption analysis means for analyzing and predicting consumption patterns based on past power consumption information and emotion information. This makes it possible to generate and securely manage power usage plans optimized for each individual user.

[0148] "Data acquisition means" refers to a device or method for acquiring power consumption information and weather information in real time.

[0149] "Emotion analysis means" refers to a technology or device for identifying a user's emotional state based on the user's voice input or camera footage.

[0150] A "consumption analysis tool" is a method or program for analyzing consumption patterns from past electricity consumption information and emotional information to predict future consumption.

[0151] "Plan generation means" refers to a technology or device for creating an optimal power usage plan for individual users based on predicted consumption patterns and emotional information.

[0152] "Secure communication means" refers to a method or device for encrypting and decrypting data using quantum communication technology and for securely transmitting and receiving it.

[0153] "Balance control means" refers to a technology or device that adjusts the balance between power supply and consumption in real time to maintain the efficiency and stability of the entire system.

[0154] This invention is a system that formulates an optimal power usage plan based on power consumption information and user emotion information. This system mainly consists of a server, terminals, and an emotion engine.

[0155] The terminal uses smart electricity meters to obtain real-time electricity consumption information from homes and businesses. Furthermore, weather information is obtained from external information services via an internet connection. This data is updated every five minutes and transmitted to the server.

[0156] The emotion engine analyzes emotional information using the user's voice and video input from the camera. A voice emotion analysis algorithm is used for voice analysis, and facial recognition technology is used for facial expression analysis. The analyzed emotional information is sent to the server.

[0157] The server aggregates power consumption information, weather information, and emotional information received from the terminal and the emotion engine, and stores it in a database. Based on the stored data, it uses machine learning algorithms to analyze consumption patterns and predict future power consumption. For example, the server might suggest a plan to adjust the lighting to warmer colors and maintain a comfortable room temperature during a relaxed weekend afternoon. It might also suggest playing healing music.

[0158] The AI ​​agent generates an optimal power usage plan based on data analyzed by the server, tailored to the user's emotional state. This plan is particularly effective when the user is relaxed and includes settings for comfortable lighting and temperature.

[0159] To ensure privacy, the server uses quantum communication technology to encrypt and decrypt data, ensuring secure data transmission. Furthermore, user emotional information and power consumption data are highly protected.

[0160] Ultimately, users can review, accept, or adjust the power usage plan generated by the AI ​​agent through a smartphone app or dedicated device. In this way, users can achieve comfortable and efficient energy management tailored to their individual needs.

[0161] An example of a prompt for a generative AI model is: "Please suggest an optimal power usage plan for when the user is relaxing. Include specific suggestions regarding lighting, temperature settings, and music playback."

[0162] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0163] Step 1:

[0164] The terminal acquires electricity consumption information from smart electricity meters for homes and businesses. Input data includes information on power consumption and time of day. This data is updated every 5 minutes and transmitted to a server via the internet. The output, electricity consumption information, is then transferred to the server for management.

[0165] Step 2:

[0166] The terminal obtains weather information from external information services. Input data includes current temperature, humidity, and probability of precipitation. This information is obtained via the internet and transmitted to the server. The latest weather information data is stored on the server as output.

[0167] Step 3:

[0168] The emotion engine performs emotion analysis using voice input and camera footage from the user. Input data includes voice tone and facial expressions. Using voice emotion analysis algorithms and facial recognition technology, it identifies the user's emotional state. The analyzed emotional state is then sent to the server as output.

[0169] Step 4:

[0170] The server centrally manages power consumption information, weather information, and emotion information received from terminals and the emotion engine, storing them in a database. Various types of information are included in the input and stored in the database. No output is generated at this stage, but data is accumulated in preparation for subsequent analysis.

[0171] Step 5:

[0172] The server uses machine learning algorithms to analyze stored data. Input data includes previously stored power consumption information, weather information, and sentiment information. Based on this data, it analyzes consumption patterns and predicts future power consumption. The output is the predicted consumption pattern.

[0173] Step 6:

[0174] The AI ​​agent generates an optimal power usage plan based on consumption patterns and current emotional state. Input data includes analyzed consumption patterns and emotional information. The AI ​​uses a generative AI model to create a specific usage plan. The output is a customized power usage plan tailored to the user.

[0175] Step 7:

[0176] The server uses quantum communication technology to encrypt and decrypt data, securely transmitting the plan to the terminal. The input data includes the generated power usage plan. The output is encrypted data delivered to the terminal, allowing the user to receive the information securely.

[0177] Step 8:

[0178] Users can view the provided electricity usage plan through a smartphone app or dedicated terminal. The input includes decrypted plan information. Users can view the plan, adjust it as needed, and apply it. The output is the electricity usage schedule customized by the user, which is then put into action.

[0179] (Application Example 2)

[0180] 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".

[0181] In modern society, efficient energy management is essential, but conventional electricity usage plans are based solely on consumption patterns and do not take into account the emotional state of users or the optimization of electricity distribution across the entire city. This can lead to problems such as oversupply and decreased resident satisfaction. As a result, efficiency improvements in electricity supply and improvements in quality of life are hindered.

[0182] 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.

[0183] In this invention, the server includes information acquisition means for acquiring power consumption information, analysis means for analyzing and predicting consumption patterns based on past power consumption information, plan generation means for generating a power usage plan based on the analyzed consumption patterns, communication means for securely transmitting and receiving data using quantum communication technology, control means for adjusting the balance between power supply and consumption in real time, emotion analysis means for optimizing the power usage plan by considering factors based on the emotional state of the user, and urban optimization means for optimizing the power distribution of the entire city. This makes it possible to generate and implement a more accurate power usage plan that takes into account the emotional state of the user and the power distribution of the entire city.

[0184] "Electricity consumption information" refers to data on the amount of electricity used by households and businesses.

[0185] "Information acquisition means" refers to a device or procedure for collecting electricity consumption information.

[0186] "Analysis means" refers to the process of analyzing past power consumption information, extracting patterns, and predicting future consumption.

[0187] "Plan generation means" refers to a method or function for creating an efficient power usage plan based on analyzed data.

[0188] "Quantum communication technology" is a communication technology that uses the properties of quantum mechanics to ensure the security of data.

[0189] "Communication means" refers to a method, device, or technology for sending and receiving data.

[0190] A "control system" is a system or process that makes adjustments in real time to balance the supply and consumption of power.

[0191] "Emotional analysis means" refers to a function that evaluates the emotional state of users and reflects it in the power usage plan.

[0192] "Urban optimization methods" are methods and technologies designed to optimize the distribution of electricity throughout a city.

[0193] The system for implementing this invention mainly consists of a server, a terminal, and an emotion analysis engine. The terminal is responsible for acquiring power consumption information from electricity meters in each home and business and transmitting it to the server. Furthermore, the terminal accesses external weather information services and transmits that data to the server as well. The server stores the received power consumption information and weather information in a database and applies machine learning algorithms to analyze past data and identify consumption patterns.

[0194] The emotion analysis engine uses data input from the user's voice and camera to analyze the user's emotional state. This result is sent to a server and used to optimize the power usage plan. Based on the analyzed consumption data, weather information, and emotion information, the server uses an AI agent to generate a individually optimized power usage plan. The server uses quantum communication technology to securely transmit the generated plan to the user's terminal.

[0195] This process includes suggestions for adjusting lighting and music, and changing air conditioning settings, based on the user's emotional state. Simultaneously, city-level power distribution plans are considered to optimize overall city power consumption. Users can review the suggestions provided by this system via a smartphone app and accept or adjust the plans.

[0196] As a concrete example, the system might suggest softening the lighting in the living space when the user is relaxed, or streaming calming music when the user is stressed. Furthermore, prompts such as, "How are you feeling today? Shall we play some music you like to help you relax and enjoy yourself?" are input into the AI ​​model to enable appropriate responses to the user. Using these prompts allows the system to provide more personalized and accurate suggestions.

[0197] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0198] Step 1:

[0199] The terminal acquires power consumption data from the power meter. This data is sampled every 5 minutes and sent to the server in real time. The input is raw data from the power meter, and the output is power consumption information every 5 minutes.

[0200] Step 2:

[0201] The terminal retrieves weather information from an external service and sends it to the server. The input is real-time data from the weather information service, and the output is information about current weather conditions.

[0202] Step 3:

[0203] The emotion analysis engine collects emotion data from the user's voice and camera and analyzes the user's emotional state. The input is the user's voice and image data, and the output is evaluation data representing the user's emotional state.

[0204] Step 4:

[0205] The server integrates received power consumption information, weather information, and sentiment rating data and stores it in a database. The input is the integrated data from the previous step, and the output is the stored data.

[0206] Step 5:

[0207] The server uses machine learning algorithms to analyze consumption patterns based on historical data and predict future power consumption. The inputs are historical power consumption information and weather information, and the output is a forecast of future power consumption.

[0208] Step 6:

[0209] The server uses sentiment analysis data to generate individually optimized power usage plans, with particular consideration given to the user's emotional state. Inputs are consumption forecast data and sentiment evaluation data, while output is the optimized power usage plan.

[0210] Step 7:

[0211] The server generates prompt messages using a generative AI model and sends them to the user. These prompt messages include suggestions tailored to the user's current situation. The input is the user's emotional state and optimization plan, and the output is a customized prompt message.

[0212] Step 8:

[0213] Users review the power usage plan and suggestions presented in the smartphone app and adjust the plan as needed. The input is the plan and suggestions sent from the server, and the output is the final adjusted power usage plan.

[0214] 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.

[0215] 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.

[0216] 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.

[0217] [Second Embodiment]

[0218] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0219] 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.

[0220] 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).

[0221] 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.

[0222] 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.

[0223] 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).

[0224] 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.

[0225] 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.

[0226] 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.

[0227] 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.

[0228] 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.

[0229] 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".

[0230] The system of this invention possesses advanced information processing technology to achieve efficient and safe power supply in homes and businesses. The system mainly consists of a server and terminals, and optimizes power supply according to the following procedure.

[0231] First, the device acquires consumption information in real time from electricity meters in each home and business. This data is measured, for example, every 5 minutes and includes current electricity usage and past consumption history. Weather information is also continuously acquired from external weather information services.

[0232] Next, the server receives this data and stores it in a database. There, it analyzes data from the past few weeks to months to generate consumption patterns. Machine learning algorithms are applied to this consumption pattern analysis, and by analyzing past consumption trends and seasonal fluctuations in particular, it makes highly accurate future predictions.

[0233] Furthermore, based on the generated consumption patterns, the AI ​​agent proposes an optimal power usage plan for each household or business. This plan includes specific actions to reduce peak power consumption, such as "setting the washing machine timer to increase power consumption in the morning" or "adjusting the office air conditioning temperature during specific time periods."

[0234] In terms of communication, the server uses quantum communication technology to securely transfer data to power companies and power plants. This reduces the risk of unauthorized acquisition of transmitted power consumption information and supply and demand adjustment instructions, allowing for secure data management.

[0235] Finally, the servers and terminals monitor the electricity demand of each household and business, and automatically adjust the balance of power supply whenever possible. This adjustment enables immediate feedback on power supply and demand, increasing efficiency in maximizing the use of renewable energy. This reduces wasted electricity use while ensuring a stable power supply.

[0236] Based on the above, the present invention is a system that provides efficient use and safe supply of electricity, thereby reducing the electricity burden on households and businesses.

[0237] The following describes the processing flow.

[0238] Step 1:

[0239] The terminal acquires real-time electricity consumption data from home and business electricity meters. This data is measured every 5 minutes and sent to the server, along with past consumption information.

[0240] Step 2:

[0241] The device accesses external weather information services to obtain current weather and forecast data. This weather data is also updated regularly and sent to the server.

[0242] Step 3:

[0243] The server stores the received power consumption data and weather data in a database. This creates a comprehensive dataset covering the past and present.

[0244] Step 4:

[0245] The server uses machine learning algorithms to analyze consumption patterns. This analysis takes into account past consumption trends and seasonal fluctuations to build a model that predicts future consumption behavior.

[0246] Step 5:

[0247] The AI ​​agent generates an optimal power usage plan for each household or business based on consumption patterns obtained from the server. The plan includes specific actions to avoid peak consumption.

[0248] Step 6:

[0249] The server transmits the generated power usage plan to terminals in each home and business. This process utilizes quantum communication technology to ensure secure data transfer.

[0250] Step 7:

[0251] The server monitors power demand in real time and adjusts the supply balance as needed. This maximizes the use of renewable energy and reduces wasteful consumption.

[0252] (Example 1)

[0253] 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."

[0254] In modern society, efficient and stable electricity consumption is a critical issue. Excessive electricity consumption and unpredictable fluctuations in demand lead to wasteful energy resources, unstable supply, and increased environmental burden. Furthermore, the secure management and transmission of collected electricity consumption information is also a challenge, as the unauthorized acquisition of this information could lead to privacy violations and economic losses.

[0255] 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.

[0256] In this invention, the server includes a device for acquiring power consumption information, a device for collecting weather information from an external information source, and a computing device for analyzing and predicting consumption patterns based on past power consumption information. This enables improved efficiency and stable supply of power consumption, as well as enhanced security of data communications.

[0257] A "device for acquiring power consumption information" is a machine that continuously and accurately collects power usage data from measuring instruments installed in homes and businesses.

[0258] A "device for collecting weather information from external sources" is a device for obtaining weather condition data from external data services via the internet.

[0259] A "computational device for analyzing and predicting consumption patterns" is a computer system that calculates and predicts future power consumption based on collected power consumption data and historical data.

[0260] A "planning device for generating power usage plans" is a device that creates an optimal power consumption schedule based on analyzed consumption patterns.

[0261] A "communication device using quantum communication technology" is a communication device that utilizes quantum key distribution technology to ensure high security in data transmission and reception.

[0262] A "control device that adjusts the balance between power supply and consumption in real time" is a device that monitors the energy supply and demand situation and adjusts the power supply as needed, thereby enabling efficient energy management.

[0263] The system of this invention is intended to promote efficient and safe power supply in homes and businesses. This system mainly consists of a server and terminals and uses data from measuring instruments installed in each home and business, as well as from external information sources.

[0264] The terminal is a device for obtaining real-time power consumption information from power meters. For example, it uses a smart meter to measure power usage every five minutes and transmits the data to a server. The terminal also connects to external information sources and obtains weather information via APIs. This allows for real-time monitoring of weather conditions that may affect power consumption.

[0265] The server is a system that receives data provided by terminals and stores it in a database. Using a database management system (e.g., MySQL, PostgreSQL), it integrates hourly consumption data and weather information, and stores it over long periods. Based on this data, the server uses machine learning algorithms to analyze power consumption patterns and predict future consumption.

[0266] Furthermore, the server uses an AI agent to suggest an optimal power usage plan to the user based on the analyzed consumption patterns. This plan includes specific actions to reduce power consumption during peak hours. For example, it might suggest "use the washing machine in the morning and reduce power usage during the afternoon peak." Users receive these suggestions through a smartphone app or web interface.

[0267] In this system, the server uses quantum communication technology to securely transmit data to power companies and power plants. Quantum key distribution technology is used for data encryption and decryption, enhancing communication security. Therefore, it is possible to prevent the unauthorized acquisition of power consumption information and supply and demand adjustment instructions.

[0268] For example, when a user utilizes this system in a smart home environment, the AI ​​agent automatically adjusts the operating schedule of home appliances according to the proposed power usage plan, optimizing energy efficiency. This allows the user to reduce electricity costs while maintaining a comfortable living environment.

[0269] Examples of prompts to input into a generative AI model:

[0270] "Based on current electricity consumption data and weather information, please propose the optimal electricity usage plan for this week."

[0271] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0272] Step 1:

[0273] The terminal acquires electricity consumption information from electricity meters in each home and business. This acquisition is performed at 5-minute intervals, collecting the current electricity consumption measured by the smart meter as digital data. The input is numerical data from the meter, and the output is the process of preparing this data as digital data ready to be transmitted to the server in real time.

[0274] Step 2:

[0275] The device accesses an external weather service to obtain weather information. This process uses an API to retrieve data such as current temperature, humidity, and weather conditions, and then formats this data for transmission to the server. The input is raw data from the weather service, and the output is weather information data in a parseable format.

[0276] Step 3:

[0277] The server stores the power consumption data and weather information data received from the terminal in the database. Specifically, the database management system appropriately organizes and records these data. The input is the power consumption and weather information transmitted from the terminal, and the output is the record as an entry in the database suitable for long-term storage.

[0278] Step 4:

[0279] The server performs analysis using the data accumulated in the database. In this step, a machine learning algorithm is applied to generate a consumption pattern. The input consists of past power consumption data and weather data, and the output is the predicted future power consumption trend and pattern.

[0280] Step 5:

[0281] The server creates an optimal power usage plan by the AI agent based on the generated consumption pattern. The plan includes specific power usage proposals for each household and enterprise. The input is the consumption pattern extracted in Step 4, and the output is the specific power usage schedule proposed to the user.

[0282] Step 6:

[0283] The server securely transmits the power consumption information and the proposed power usage plan using quantum communication technology. Here, quantum key distribution technology is utilized to encrypt the communication and ensure security. The input is the plan data, and the output is the securely transmitted plan information.

[0284] Step 7:

[0285] The user receives the proposed power usage plan and provides feedback. The user checks the information received through the smartphone app or web interface and fine-tunes the plan as needed. The input is the plan information received from the server, and the output is the final plan with the user's consent or adjustments.

[0286] (Application Example 1)

[0287] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0288] In modern homes and businesses, power consumption continues to increase, and efficient energy utilization is required. Also, there is a lack of systems that can provide safe and rapid data communication and propose specific energy-saving measures. Therefore, there is a need for means to ensure the stability of power supply while allowing users to grasp the situation in real time and improve energy efficiency.

[0289] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0290] In this invention, the server includes data acquisition means for acquiring power consumption information, analysis means for analyzing and predicting consumption trends based on past power consumption information, and strategy generation means for generating a power usage plan based on the analyzed consumption trends. This enables the real-time optimization of energy consumption in homes and businesses and enables safe and efficient power supply.

[0291] The "data acquisition means" is a device or function that has the function of collecting power consumption information in homes and businesses in real time and transferring data from each terminal to the server.

[0292] The "analysis means" is a device or function that performs processing for analyzing consumption trends using the collected past power consumption information and predicting future power demand.

[0293] A "strategy generation tool" is a device or function that has the function of formulating a plan to achieve efficient power utilization based on analyzed power consumption trends.

[0294] "Information exchange means" refers to a device or function that uses communication technology to ensure secure information transmission to send and receive data, and to perform encryption and decryption.

[0295] "Adjustment means" refers to a device or function that performs the necessary controls to monitor and adjust the balance between power supply and consumption in real time.

[0296] "Information display means" refers to a device or function that has the ability to display information in real time on the screen of a mobile device or similar device, so that users can easily understand the power consumption status of their home or business.

[0297] The system constructed to implement this invention includes data acquisition means, analysis means, strategy generation means, information exchange means, coordination means, and information display means. The server uses these means to improve power consumption efficiency and secure data communication.

[0298] The server collects power consumption data in real time via IoT devices as a data acquisition method. Specifically, it collects data using the MQTT protocol, for example, and manages backend processing with an API that employs the Flask framework. The collected data is analyzed using TensorFlow as an analysis tool to form a model that predicts future power demand based on past consumption trends.

[0299] The strategy generation tool presents users with efficient power usage methods based on the generated analysis results. This functionality is delivered directly to users through a mobile application built using React Native. Users can use this app to monitor their power usage in real time and obtain specific actions to take to save energy.

[0300] As an information exchange means, the server uses quantum communication technology to achieve secure information transmission and encrypts data transmission and reception on the communication network. Also, the adjustment means monitors the power supply and consumption status in real time and automatically adjusts the supply-demand balance.

[0301] As a specific example, when excessive power consumption is predicted during a specific time period of a day, the system sends a notification to the user such as "Please change the usage time of the washing machine to suppress power usage during this time period." As an example of the prompt text input to the generative AI model, content such as "Based on the power consumption data and weather prediction data for the past month, predict the energy consumption pattern for next week and propose an action plan effective for peak shifting." can be considered.

[0302] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0303] Step 1:

[0304] The server receives power consumption data in real time from the terminal through the MQTT protocol. This input data includes information from power meters in specific households or enterprises, and the server stores this in the database.

[0305] Step 2:

[0306] The server uses the stored power consumption data to perform data analysis based on a machine learning model utilizing TensorFlow. It takes in past power consumption data and weather information as inputs and models the consumption trends. As a result of the analysis, a future power demand prediction is output.

[0307] Step 3:

[0308] The server uses the analysis results to present a power usage plan to a mobile app built with React Native via an AI agent. Input information includes predicted consumption trends, and the output generates specific savings suggestions for the user.

[0309] Step 4:

[0310] Users receive power usage plans and suggestions sent from the server via a mobile app. Based on this information, users can select specific power-saving actions. The suggestions provided might include things like "avoid using electrical appliances during peak hours."

[0311] Step 5:

[0312] The terminal controls each device to adjust power consumption within homes and businesses, following instructions from the server. It receives adjustment instructions from the server as input and controls the operation of the corresponding device as output. This optimizes the balance between power supply and consumption in real time.

[0313] 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.

[0314] The system in this invention formulates an optimal power usage plan based on power consumption information and user emotion information. The system mainly consists of a server, a terminal, and an emotion engine, and is implemented in the following procedure.

[0315] First, the terminal acquires real-time power consumption data from home and business electricity meters. This data is recorded every 5 minutes and sent to the server, and weather information is also obtained from external services and sent to the server.

[0316] Next, the emotion engine analyzes emotional information from the user's voice input and camera input. This analysis determines the user's current emotional state, and the result is sent to the server.

[0317] The server stores received power consumption data, weather information, and sentiment information in a database. Based on this data, machine learning algorithms are used to analyze consumption patterns and predict future power consumption. User sentiment information, in particular, is considered important as a factor influencing consumption behavior and is reflected in the system for individual optimization.

[0318] Next, the AI ​​agent uses the analyzed data to generate an optimized power usage plan for specific emotional states. For example, when the user is relaxed, it adjusts lighting and temperature settings for greater comfort, and when stress levels are high, it suggests things like playing music to reduce stress.

[0319] To ensure privacy and data security, the server uses quantum communication technology to encrypt and decrypt communications while smoothly exchanging data. This ensures that user emotional information and power usage data are managed securely.

[0320] Finally, users can review the proposed electricity usage plan on their smartphone app or device. They can then accept the system's proposal or adjust the plan as needed to achieve energy management tailored to their individual needs.

[0321] This embodiment enables the efficient and safe supply of electricity, making the user's living environment more comfortable.

[0322] The following describes the processing flow.

[0323] Step 1:

[0324] The terminal acquires real-time power consumption data from home and business electricity meters. This data is sent to the server at 5-minute intervals. The terminal also acquires weather data from weather information services and sends it to the server in the same manner.

[0325] Step 2:

[0326] The emotion engine acquires user audio and video data from the microphone and camera connected to the device. It analyzes this data to identify the user's current emotional state. This emotional information is then sent to the server.

[0327] Step 3:

[0328] The server integrates the received power consumption data, weather data, and sentiment information and stores it in a database. This creates a foundational dataset for comprehensively understanding the situation.

[0329] Step 4:

[0330] The server uses machine learning algorithms to analyze past consumption data and sentiment information. This allows it to more accurately predict future electricity demand and user behavior.

[0331] Step 5:

[0332] The AI ​​agent generates a power usage plan tailored to the user's emotional state, based on data predicted by the server. This plan may include lighting and air conditioning settings to improve comfort.

[0333] Step 6:

[0334] The server transmits the generated power usage plan to terminals in each home and business. Quantum communication technology is used to ensure the security and privacy of the communication.

[0335] Step 7:

[0336] Users review suggestions from the AI ​​agent via their device or smartphone app. Based on these suggestions, users can adjust their actual power usage and operate according to a plan that also reflects emotional information.

[0337] (Example 2)

[0338] 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".

[0339] Managing electricity consumption efficiently in modern society and creating optimal power usage plans tailored to the emotional state of individual users presents a significant challenge. Furthermore, there is a need to balance power supply and consumption in real time while ensuring privacy and data security. Conventional systems are insufficient to address these challenges.

[0340] 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.

[0341] In this invention, the server includes data acquisition means for acquiring power consumption information and weather information, emotion analysis means for analyzing user emotion information and determining the emotional state, and consumption analysis means for analyzing and predicting consumption patterns based on past power consumption information and emotion information. This makes it possible to generate and securely manage power usage plans optimized for each individual user.

[0342] "Data acquisition means" refers to a device or method for acquiring power consumption information and weather information in real time.

[0343] "Emotion analysis means" refers to a technology or device for identifying a user's emotional state based on the user's voice input or camera footage.

[0344] A "consumption analysis tool" is a method or program for analyzing consumption patterns from past electricity consumption information and emotional information to predict future consumption.

[0345] "Plan generation means" refers to a technology or device for creating an optimal power usage plan for individual users based on predicted consumption patterns and emotional information.

[0346] "Secure communication means" refers to a method or device for encrypting and decrypting data using quantum communication technology and for securely transmitting and receiving it.

[0347] "Balance control means" refers to a technology or device that adjusts the balance between power supply and consumption in real time to maintain the efficiency and stability of the entire system.

[0348] This invention is a system that formulates an optimal power usage plan based on power consumption information and user emotion information. This system mainly consists of a server, terminals, and an emotion engine.

[0349] The terminal uses smart electricity meters to obtain real-time electricity consumption information from homes and businesses. Furthermore, weather information is obtained from external information services via an internet connection. This data is updated every five minutes and transmitted to the server.

[0350] The emotion engine analyzes emotional information using the user's voice and video input from the camera. A voice emotion analysis algorithm is used for voice analysis, and facial recognition technology is used for facial expression analysis. The analyzed emotional information is sent to the server.

[0351] The server aggregates power consumption information, weather information, and emotional information received from the terminal and the emotion engine, and stores it in a database. Based on the stored data, it uses machine learning algorithms to analyze consumption patterns and predict future power consumption. For example, the server might suggest a plan to adjust the lighting to warmer colors and maintain a comfortable room temperature during a relaxed weekend afternoon. It might also suggest playing healing music.

[0352] The AI ​​agent generates an optimal power usage plan based on data analyzed by the server, tailored to the user's emotional state. This plan is particularly effective when the user is relaxed and includes settings for comfortable lighting and temperature.

[0353] To ensure privacy, the server uses quantum communication technology to encrypt and decrypt data, ensuring secure data transmission. Furthermore, user emotional information and power consumption data are highly protected.

[0354] Ultimately, users can review, accept, or adjust the power usage plan generated by the AI ​​agent through a smartphone app or dedicated device. In this way, users can achieve comfortable and efficient energy management tailored to their individual needs.

[0355] An example of a prompt for a generative AI model is: "Please suggest an optimal power usage plan for when the user is relaxing. Include specific suggestions regarding lighting, temperature settings, and music playback."

[0356] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0357] Step 1:

[0358] The terminal acquires electricity consumption information from smart electricity meters for homes and businesses. Input data includes information on power consumption and time of day. This data is updated every 5 minutes and transmitted to a server via the internet. The output, electricity consumption information, is then transferred to the server for management.

[0359] Step 2:

[0360] The terminal obtains weather information from external information services. Input data includes current temperature, humidity, and probability of precipitation. This information is obtained via the internet and transmitted to the server. The latest weather information data is stored on the server as output.

[0361] Step 3:

[0362] The emotion engine performs emotion analysis using voice input and camera footage from the user. Input data includes voice tone and facial expressions. Using voice emotion analysis algorithms and facial recognition technology, it identifies the user's emotional state. The analyzed emotional state is then sent to the server as output.

[0363] Step 4:

[0364] The server centrally manages power consumption information, weather information, and emotion information received from terminals and the emotion engine, storing them in a database. Various types of information are included in the input and stored in the database. No output is generated at this stage, but data is accumulated in preparation for subsequent analysis.

[0365] Step 5:

[0366] The server uses machine learning algorithms to analyze stored data. Input data includes previously stored power consumption information, weather information, and sentiment information. Based on this data, it analyzes consumption patterns and predicts future power consumption. The output is the predicted consumption pattern.

[0367] Step 6:

[0368] The AI ​​agent generates an optimal power usage plan based on consumption patterns and current emotional state. Input data includes analyzed consumption patterns and emotional information. The AI ​​uses a generative AI model to create a specific usage plan. The output is a customized power usage plan tailored to the user.

[0369] Step 7:

[0370] The server uses quantum communication technology to encrypt and decrypt data, securely transmitting the plan to the terminal. The input data includes the generated power usage plan. The output is encrypted data delivered to the terminal, allowing the user to receive the information securely.

[0371] Step 8:

[0372] Users can view the provided electricity usage plan through a smartphone app or dedicated terminal. The input includes decrypted plan information. Users can view the plan, adjust it as needed, and apply it. The output is the electricity usage schedule customized by the user, which is then put into action.

[0373] (Application Example 2)

[0374] 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".

[0375] In modern society, efficient energy management is essential, but conventional electricity usage plans are based solely on consumption patterns and do not take into account the emotional state of users or the optimization of electricity distribution across the entire city. This can lead to problems such as oversupply and decreased resident satisfaction. As a result, efficiency improvements in electricity supply and improvements in quality of life are hindered.

[0376] 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.

[0377] In this invention, the server includes information acquisition means for acquiring power consumption information, analysis means for analyzing and predicting consumption patterns based on past power consumption information, plan generation means for generating a power usage plan based on the analyzed consumption patterns, communication means for securely transmitting and receiving data using quantum communication technology, control means for adjusting the balance between power supply and consumption in real time, emotion analysis means for optimizing the power usage plan by considering factors based on the emotional state of the user, and urban optimization means for optimizing the power distribution of the entire city. This makes it possible to generate and implement a more accurate power usage plan that takes into account the emotional state of the user and the power distribution of the entire city.

[0378] "Electricity consumption information" refers to data on the amount of electricity used by households and businesses.

[0379] "Information acquisition means" refers to a device or procedure for collecting electricity consumption information.

[0380] "Analysis means" refers to the process of analyzing past power consumption information, extracting patterns, and predicting future consumption.

[0381] "Plan generation means" refers to a method or function for creating an efficient power usage plan based on analyzed data.

[0382] "Quantum communication technology" is a communication technology that uses the properties of quantum mechanics to ensure the security of data.

[0383] "Communication means" refers to a method, device, or technology for sending and receiving data.

[0384] A "control system" is a system or process that makes adjustments in real time to balance the supply and consumption of power.

[0385] "Emotional analysis means" refers to a function that evaluates the emotional state of users and reflects it in the power usage plan.

[0386] "Urban optimization methods" are methods and technologies designed to optimize the distribution of electricity throughout a city.

[0387] The system for implementing this invention mainly consists of a server, a terminal, and an emotion analysis engine. The terminal is responsible for acquiring power consumption information from electricity meters in each home and business and transmitting it to the server. Furthermore, the terminal accesses external weather information services and transmits that data to the server as well. The server stores the received power consumption information and weather information in a database and applies machine learning algorithms to analyze past data and identify consumption patterns.

[0388] The emotion analysis engine uses data input from the user's voice and camera to analyze the user's emotional state. This result is sent to a server and used to optimize the power usage plan. Based on the analyzed consumption data, weather information, and emotion information, the server uses an AI agent to generate a individually optimized power usage plan. The server uses quantum communication technology to securely transmit the generated plan to the user's terminal.

[0389] This process includes suggestions for adjusting lighting and music, and changing air conditioning settings, based on the user's emotional state. Simultaneously, city-level power distribution plans are considered to optimize overall city power consumption. Users can review the suggestions provided by this system via a smartphone app and accept or adjust the plans.

[0390] As a concrete example, the system might suggest softening the lighting in the living space when the user is relaxed, or streaming calming music when the user is stressed. Furthermore, prompts such as, "How are you feeling today? Shall we play some music you like to help you relax and enjoy yourself?" are input into the AI ​​model to enable appropriate responses to the user. Using these prompts allows the system to provide more personalized and accurate suggestions.

[0391] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0392] Step 1:

[0393] The terminal acquires power consumption data from the power meter. This data is sampled every 5 minutes and sent to the server in real time. The input is raw data from the power meter, and the output is power consumption information every 5 minutes.

[0394] Step 2:

[0395] The terminal retrieves weather information from an external service and sends it to the server. The input is real-time data from the weather information service, and the output is information about current weather conditions.

[0396] Step 3:

[0397] The emotion analysis engine collects emotion data from the user's voice and camera and analyzes the user's emotional state. The input is the user's voice and image data, and the output is evaluation data representing the user's emotional state.

[0398] Step 4:

[0399] The server integrates received power consumption information, weather information, and sentiment rating data and stores it in a database. The input is the integrated data from the previous step, and the output is the stored data.

[0400] Step 5:

[0401] The server uses machine learning algorithms to analyze consumption patterns based on historical data and predict future power consumption. The inputs are historical power consumption information and weather information, and the output is a forecast of future power consumption.

[0402] Step 6:

[0403] The server uses sentiment analysis data to generate individually optimized power usage plans, with particular consideration given to the user's emotional state. Inputs are consumption forecast data and sentiment evaluation data, while output is the optimized power usage plan.

[0404] Step 7:

[0405] The server generates prompt messages using a generative AI model and sends them to the user. These prompt messages include suggestions tailored to the user's current situation. The input is the user's emotional state and optimization plan, and the output is a customized prompt message.

[0406] Step 8:

[0407] Users review the power usage plan and suggestions presented in the smartphone app and adjust the plan as needed. The input is the plan and suggestions sent from the server, and the output is the final adjusted power usage plan.

[0408] 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.

[0409] 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.

[0410] 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.

[0411] [Third Embodiment]

[0412] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0413] 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.

[0414] 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).

[0415] 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.

[0416] 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.

[0417] 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).

[0418] 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.

[0419] 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.

[0420] 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.

[0421] 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.

[0422] 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.

[0423] 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".

[0424] The system of this invention possesses advanced information processing technology to achieve efficient and safe power supply in homes and businesses. The system mainly consists of a server and terminals, and optimizes power supply according to the following procedure.

[0425] First, the device acquires consumption information in real time from electricity meters in each home and business. This data is measured, for example, every 5 minutes and includes current electricity usage and past consumption history. Weather information is also continuously acquired from external weather information services.

[0426] Next, the server receives this data and stores it in a database. There, it analyzes data from the past few weeks to months to generate consumption patterns. Machine learning algorithms are applied to this consumption pattern analysis, and by analyzing past consumption trends and seasonal fluctuations in particular, it makes highly accurate future predictions.

[0427] Furthermore, based on the generated consumption patterns, the AI ​​agent proposes an optimal power usage plan for each household or business. This plan includes specific actions to reduce peak power consumption, such as "setting the washing machine timer to increase power consumption in the morning" or "adjusting the office air conditioning temperature during specific time periods."

[0428] In terms of communication, the server uses quantum communication technology to securely transfer data to power companies and power plants. This reduces the risk of unauthorized acquisition of transmitted power consumption information and supply and demand adjustment instructions, allowing for secure data management.

[0429] Finally, the servers and terminals monitor the electricity demand of each household and business, and automatically adjust the balance of power supply whenever possible. This adjustment enables immediate feedback on power supply and demand, increasing efficiency in maximizing the use of renewable energy. This reduces wasted electricity use while ensuring a stable power supply.

[0430] Based on the above, the present invention is a system that provides efficient use and safe supply of electricity, thereby reducing the electricity burden on households and businesses.

[0431] The following describes the processing flow.

[0432] Step 1:

[0433] The terminal acquires real-time electricity consumption data from home and business electricity meters. This data is measured every 5 minutes and sent to the server, along with past consumption information.

[0434] Step 2:

[0435] The device accesses external weather information services to obtain current weather and forecast data. This weather data is also updated regularly and sent to the server.

[0436] Step 3:

[0437] The server stores the received power consumption data and weather data in a database. This creates a comprehensive dataset covering the past and present.

[0438] Step 4:

[0439] The server uses machine learning algorithms to analyze consumption patterns. This analysis takes into account past consumption trends and seasonal fluctuations to build a model that predicts future consumption behavior.

[0440] Step 5:

[0441] The AI ​​agent generates an optimal power usage plan for each household or business based on consumption patterns obtained from the server. The plan includes specific actions to avoid peak consumption.

[0442] Step 6:

[0443] The server transmits the generated power usage plan to terminals in each home and business. This process utilizes quantum communication technology to ensure secure data transfer.

[0444] Step 7:

[0445] The server monitors power demand in real time and adjusts the supply balance as needed. This maximizes the use of renewable energy and reduces wasteful consumption.

[0446] (Example 1)

[0447] 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."

[0448] In modern society, efficient and stable electricity consumption is a critical issue. Excessive electricity consumption and unpredictable fluctuations in demand lead to wasteful energy resources, unstable supply, and increased environmental burden. Furthermore, the secure management and transmission of collected electricity consumption information is also a challenge, as the unauthorized acquisition of this information could lead to privacy violations and economic losses.

[0449] 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.

[0450] In this invention, the server includes a device for acquiring power consumption information, a device for collecting weather information from an external information source, and a computing device for analyzing and predicting consumption patterns based on past power consumption information. This enables improved efficiency and stable supply of power consumption, as well as enhanced security of data communications.

[0451] A "device for acquiring power consumption information" is a machine that continuously and accurately collects power usage data from measuring instruments installed in homes and businesses.

[0452] A "device for collecting weather information from external sources" is a device for obtaining weather condition data from external data services via the internet.

[0453] A "computational device for analyzing and predicting consumption patterns" is a computer system that calculates and predicts future power consumption based on collected power consumption data and historical data.

[0454] A "planning device for generating power usage plans" is a device that creates an optimal power consumption schedule based on analyzed consumption patterns.

[0455] A "communication device using quantum communication technology" is a communication device that utilizes quantum key distribution technology to ensure high security in data transmission and reception.

[0456] A "control device that adjusts the balance between power supply and consumption in real time" is a device that monitors the energy supply and demand situation and adjusts the power supply as needed, thereby enabling efficient energy management.

[0457] The system of this invention is intended to promote efficient and safe power supply in homes and businesses. This system mainly consists of a server and terminals and uses data from measuring instruments installed in each home and business, as well as from external information sources.

[0458] The terminal is a device for obtaining real-time power consumption information from power meters. For example, it uses a smart meter to measure power usage every five minutes and transmits the data to a server. The terminal also connects to external information sources and obtains weather information via APIs. This allows for real-time monitoring of weather conditions that may affect power consumption.

[0459] The server is a system that receives data provided by terminals and stores it in a database. Using a database management system (e.g., MySQL, PostgreSQL), it integrates hourly consumption data and weather information, and stores it over long periods. Based on this data, the server uses machine learning algorithms to analyze power consumption patterns and predict future consumption.

[0460] Furthermore, the server uses an AI agent to suggest an optimal power usage plan to the user based on the analyzed consumption patterns. This plan includes specific actions to reduce power consumption during peak hours. For example, it might suggest "use the washing machine in the morning and reduce power usage during the afternoon peak." Users receive these suggestions through a smartphone app or web interface.

[0461] In this system, the server uses quantum communication technology to securely transmit data to power companies and power plants. Quantum key distribution technology is used for data encryption and decryption, enhancing communication security. Therefore, it is possible to prevent the unauthorized acquisition of power consumption information and supply and demand adjustment instructions.

[0462] For example, when a user utilizes this system in a smart home environment, the AI ​​agent automatically adjusts the operating schedule of home appliances according to the proposed power usage plan, optimizing energy efficiency. This allows the user to reduce electricity costs while maintaining a comfortable living environment.

[0463] Examples of prompts to input into a generative AI model:

[0464] "Based on current electricity consumption data and weather information, please propose the optimal electricity usage plan for this week."

[0465] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0466] Step 1:

[0467] The terminal acquires electricity consumption information from electricity meters in each home and business. This acquisition is performed at 5-minute intervals, collecting the current electricity consumption measured by the smart meter as digital data. The input is numerical data from the meter, and the output is the process of preparing this data as digital data ready to be transmitted to the server in real time.

[0468] Step 2:

[0469] The device accesses an external weather service to obtain weather information. This process uses an API to retrieve data such as current temperature, humidity, and weather conditions, and then formats this data for transmission to the server. The input is raw data from the weather service, and the output is weather information data in a parseable format.

[0470] Step 3:

[0471] The server stores power consumption data and weather information data received from terminals in a database. Specifically, it organizes and records this data appropriately in the database management system. The input is power consumption and weather information transmitted from terminals, and the output is a record as a database entry suitable for long-term storage.

[0472] Step 4:

[0473] The server performs analysis using data stored in the database. In this step, machine learning algorithms are applied to generate consumption patterns. The input consists of historical power consumption data and weather data, and the output is predicted future power consumption trends and patterns.

[0474] Step 5:

[0475] The server uses an AI agent to create an optimal power usage plan based on the generated consumption patterns. The plan includes specific power usage suggestions for each household or business. The input is the consumption patterns extracted in step 4, and the output is the specific power usage schedule proposed to the user.

[0476] Step 6:

[0477] The server securely transmits power consumption information and proposed power usage plans using quantum communication technology. Here, quantum key distribution technology is used to encrypt the communication and ensure security. The input is the plan data, and the output is the securely transmitted plan information.

[0478] Step 7:

[0479] Users receive a proposed power usage plan and provide feedback. They review the information received via a smartphone app or web interface and fine-tune the plan as needed. The input is the plan information received from the server, and the output is the final plan with the user's consent or adjustments.

[0480] (Application Example 1)

[0481] 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."

[0482] In modern homes and businesses, electricity consumption continues to increase, necessitating efficient energy use. Furthermore, there is a lack of systems capable of secure and rapid data communication and providing concrete energy-saving suggestions. Therefore, a means is needed to ensure the stability of the power supply while allowing users to understand the situation in real time and improve energy efficiency.

[0483] 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.

[0484] In this invention, the server includes data acquisition means for acquiring power consumption information, analysis means for analyzing and predicting consumption trends based on past power consumption information, and strategy generation means for generating a power usage plan based on the analyzed consumption trends. This enables real-time optimization of energy consumption in homes and businesses, and allows for safe and efficient power supply.

[0485] "Data acquisition means" refers to a device or function that has the function of collecting electricity consumption information in homes and businesses in real time and transferring the data from each terminal to a server.

[0486] "Analysis means" refers to a device or function that uses collected past electricity consumption information to analyze consumption trends and perform processing to predict future electricity demand.

[0487] A "strategy generation tool" is a device or function that has the function of formulating a plan to achieve efficient power utilization based on analyzed power consumption trends.

[0488] "Information exchange means" refers to a device or function that uses communication technology to ensure secure information transmission to send and receive data, and to perform encryption and decryption.

[0489] "Adjustment means" refers to a device or function that performs the necessary controls to monitor and adjust the balance between power supply and consumption in real time.

[0490] "Information display means" refers to a device or function that has the ability to display information in real time on the screen of a mobile device or similar device, so that users can easily understand the power consumption status of their home or business.

[0491] The system constructed to implement this invention includes data acquisition means, analysis means, strategy generation means, information exchange means, coordination means, and information display means. The server uses these means to improve power consumption efficiency and secure data communication.

[0492] The server collects power consumption data in real time via IoT devices as a data acquisition method. Specifically, it collects data using the MQTT protocol, for example, and manages backend processing with an API that employs the Flask framework. The collected data is analyzed using TensorFlow as an analysis tool to form a model that predicts future power demand based on past consumption trends.

[0493] The strategy generation tool presents users with efficient power usage methods based on the generated analysis results. This functionality is delivered directly to users through a mobile application built using React Native. Users can use this app to monitor their power usage in real time and obtain specific actions to take to save energy.

[0494] As a means of information exchange, the server utilizes quantum communication technology to ensure secure information transmission, encrypting data transmission and reception over the communication network. Furthermore, the adjustment mechanism monitors power supply and consumption in real time, automatically adjusting the supply-demand balance.

[0495] For example, if excessive power consumption is predicted during a specific time of day, the system will send a notification to the user such as, "Please change the washing machine usage time to reduce power consumption during this time." An example of a prompt to be input into the generating AI model might be, "Based on power consumption data from the past month and weather forecast data, predict next week's energy consumption pattern and propose an effective action plan for peak shifting."

[0496] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0497] Step 1:

[0498] The server receives power consumption data in real time from terminals via the MQTT protocol. This input data includes information from electricity meters in specific homes or businesses, and the server stores this data in a database.

[0499] Step 2:

[0500] The server uses stored power consumption data to perform data analysis based on a machine learning model utilizing TensorFlow. It takes historical power consumption data and weather information as input to model consumption trends. As a result of the analysis, a forecast of future power demand is output.

[0501] Step 3:

[0502] The server uses the analysis results to present a power usage plan to a mobile app built with React Native via an AI agent. Input information includes predicted consumption trends, and the output generates specific savings suggestions for the user.

[0503] Step 4:

[0504] Users receive power usage plans and suggestions sent from the server via a mobile app. Based on this information, users can select specific power-saving actions. The suggestions provided might include things like "avoid using electrical appliances during peak hours."

[0505] Step 5:

[0506] The terminal controls each device to adjust power consumption within homes and businesses, following instructions from the server. It receives adjustment instructions from the server as input and controls the operation of the corresponding device as output. This optimizes the balance between power supply and consumption in real time.

[0507] 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.

[0508] The system in this invention formulates an optimal power usage plan based on power consumption information and user emotion information. The system mainly consists of a server, a terminal, and an emotion engine, and is implemented in the following procedure.

[0509] First, the terminal acquires real-time power consumption data from home and business electricity meters. This data is recorded every 5 minutes and sent to the server, and weather information is also obtained from external services and sent to the server.

[0510] Next, the emotion engine analyzes emotional information from the user's voice input and camera input. This analysis determines the user's current emotional state, and the result is sent to the server.

[0511] The server stores received power consumption data, weather information, and sentiment information in a database. Based on this data, machine learning algorithms are used to analyze consumption patterns and predict future power consumption. User sentiment information, in particular, is considered important as a factor influencing consumption behavior and is reflected in the system for individual optimization.

[0512] Next, the AI ​​agent uses the analyzed data to generate an optimized power usage plan for specific emotional states. For example, when the user is relaxed, it adjusts lighting and temperature settings for greater comfort, and when stress levels are high, it suggests things like playing music to reduce stress.

[0513] To ensure privacy and data security, the server uses quantum communication technology to encrypt and decrypt communications while smoothly exchanging data. This ensures that user emotional information and power usage data are managed securely.

[0514] Finally, users can review the proposed electricity usage plan on their smartphone app or device. They can then accept the system's proposal or adjust the plan as needed to achieve energy management tailored to their individual needs.

[0515] This embodiment enables the efficient and safe supply of electricity, making the user's living environment more comfortable.

[0516] The following describes the processing flow.

[0517] Step 1:

[0518] The terminal acquires real-time power consumption data from home and business electricity meters. This data is sent to the server at 5-minute intervals. The terminal also acquires weather data from weather information services and sends it to the server in the same manner.

[0519] Step 2:

[0520] The emotion engine acquires user audio and video data from the microphone and camera connected to the device. It analyzes this data to identify the user's current emotional state. This emotional information is then sent to the server.

[0521] Step 3:

[0522] The server integrates the received power consumption data, weather data, and sentiment information and stores it in a database. This creates a foundational dataset for comprehensively understanding the situation.

[0523] Step 4:

[0524] The server uses machine learning algorithms to analyze past consumption data and sentiment information. This allows it to more accurately predict future electricity demand and user behavior.

[0525] Step 5:

[0526] The AI ​​agent generates a power usage plan tailored to the user's emotional state, based on data predicted by the server. This plan may include lighting and air conditioning settings to improve comfort.

[0527] Step 6:

[0528] The server transmits the generated power usage plan to terminals in each home and business. Quantum communication technology is used to ensure the security and privacy of the communication.

[0529] Step 7:

[0530] Users review suggestions from the AI ​​agent via their device or smartphone app. Based on these suggestions, users can adjust their actual power usage and operate according to a plan that also reflects emotional information.

[0531] (Example 2)

[0532] 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."

[0533] Managing electricity consumption efficiently in modern society and creating optimal power usage plans tailored to the emotional state of individual users presents a significant challenge. Furthermore, there is a need to balance power supply and consumption in real time while ensuring privacy and data security. Conventional systems are insufficient to address these challenges.

[0534] 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.

[0535] In this invention, the server includes data acquisition means for acquiring power consumption information and weather information, emotion analysis means for analyzing user emotion information and determining the emotional state, and consumption analysis means for analyzing and predicting consumption patterns based on past power consumption information and emotion information. This makes it possible to generate and securely manage power usage plans optimized for each individual user.

[0536] "Data acquisition means" refers to a device or method for acquiring power consumption information and weather information in real time.

[0537] "Emotion analysis means" refers to a technology or device for identifying a user's emotional state based on the user's voice input or camera footage.

[0538] A "consumption analysis tool" is a method or program for analyzing consumption patterns from past electricity consumption information and emotional information to predict future consumption.

[0539] "Plan generation means" refers to a technology or device for creating an optimal power usage plan for individual users based on predicted consumption patterns and emotional information.

[0540] "Secure communication means" refers to a method or device for encrypting and decrypting data using quantum communication technology and for securely transmitting and receiving it.

[0541] "Balance control means" refers to a technology or device that adjusts the balance between power supply and consumption in real time to maintain the efficiency and stability of the entire system.

[0542] This invention is a system that formulates an optimal power usage plan based on power consumption information and user emotion information. This system mainly consists of a server, terminals, and an emotion engine.

[0543] The terminal uses smart electricity meters to obtain real-time electricity consumption information from homes and businesses. Furthermore, weather information is obtained from external information services via an internet connection. This data is updated every five minutes and transmitted to the server.

[0544] The emotion engine analyzes emotional information using the user's voice and video input from the camera. A voice emotion analysis algorithm is used for voice analysis, and facial recognition technology is used for facial expression analysis. The analyzed emotional information is sent to the server.

[0545] The server aggregates power consumption information, weather information, and emotional information received from the terminal and the emotion engine, and stores it in a database. Based on the stored data, it uses machine learning algorithms to analyze consumption patterns and predict future power consumption. For example, the server might suggest a plan to adjust the lighting to warmer colors and maintain a comfortable room temperature during a relaxed weekend afternoon. It might also suggest playing healing music.

[0546] The AI ​​agent generates an optimal power usage plan based on data analyzed by the server, tailored to the user's emotional state. This plan is particularly effective when the user is relaxed and includes settings for comfortable lighting and temperature.

[0547] To ensure privacy, the server uses quantum communication technology to encrypt and decrypt data, ensuring secure data transmission. Furthermore, user emotional information and power consumption data are highly protected.

[0548] Ultimately, users can review, accept, or adjust the power usage plan generated by the AI ​​agent through a smartphone app or dedicated device. In this way, users can achieve comfortable and efficient energy management tailored to their individual needs.

[0549] An example of a prompt for a generative AI model is: "Please suggest an optimal power usage plan for when the user is relaxing. Include specific suggestions regarding lighting, temperature settings, and music playback."

[0550] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0551] Step 1:

[0552] The terminal acquires electricity consumption information from smart electricity meters for homes and businesses. Input data includes information on power consumption and time of day. This data is updated every 5 minutes and transmitted to a server via the internet. The output, electricity consumption information, is then transferred to the server for management.

[0553] Step 2:

[0554] The terminal obtains weather information from external information services. Input data includes current temperature, humidity, and probability of precipitation. This information is obtained via the internet and transmitted to the server. The latest weather information data is stored on the server as output.

[0555] Step 3:

[0556] The emotion engine performs emotion analysis using voice input and camera footage from the user. Input data includes voice tone and facial expressions. Using voice emotion analysis algorithms and facial recognition technology, it identifies the user's emotional state. The analyzed emotional state is then sent to the server as output.

[0557] Step 4:

[0558] The server centrally manages power consumption information, weather information, and emotion information received from terminals and the emotion engine, storing them in a database. Various types of information are included in the input and stored in the database. No output is generated at this stage, but data is accumulated in preparation for subsequent analysis.

[0559] Step 5:

[0560] The server uses machine learning algorithms to analyze stored data. Input data includes previously stored power consumption information, weather information, and sentiment information. Based on this data, it analyzes consumption patterns and predicts future power consumption. The output is the predicted consumption pattern.

[0561] Step 6:

[0562] The AI ​​agent generates an optimal power usage plan based on consumption patterns and current emotional state. Input data includes analyzed consumption patterns and emotional information. The AI ​​uses a generative AI model to create a specific usage plan. The output is a customized power usage plan tailored to the user.

[0563] Step 7:

[0564] The server uses quantum communication technology to encrypt and decrypt data, securely transmitting the plan to the terminal. The input data includes the generated power usage plan. The output is encrypted data delivered to the terminal, allowing the user to receive the information securely.

[0565] Step 8:

[0566] Users can view the provided electricity usage plan through a smartphone app or dedicated terminal. The input includes decrypted plan information. Users can view the plan, adjust it as needed, and apply it. The output is the electricity usage schedule customized by the user, which is then put into action.

[0567] (Application Example 2)

[0568] 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."

[0569] In modern society, efficient energy management is essential, but conventional electricity usage plans are based solely on consumption patterns and do not take into account the emotional state of users or the optimization of electricity distribution across the entire city. This can lead to problems such as oversupply and decreased resident satisfaction. As a result, efficiency improvements in electricity supply and improvements in quality of life are hindered.

[0570] 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.

[0571] In this invention, the server includes information acquisition means for acquiring power consumption information, analysis means for analyzing and predicting consumption patterns based on past power consumption information, plan generation means for generating a power usage plan based on the analyzed consumption patterns, communication means for securely transmitting and receiving data using quantum communication technology, control means for adjusting the balance between power supply and consumption in real time, emotion analysis means for optimizing the power usage plan by considering factors based on the emotional state of the user, and urban optimization means for optimizing the power distribution of the entire city. This makes it possible to generate and implement a more accurate power usage plan that takes into account the emotional state of the user and the power distribution of the entire city.

[0572] "Electricity consumption information" refers to data on the amount of electricity used by households and businesses.

[0573] "Information acquisition means" refers to a device or procedure for collecting electricity consumption information.

[0574] "Analysis means" refers to the process of analyzing past power consumption information, extracting patterns, and predicting future consumption.

[0575] "Plan generation means" refers to a method or function for creating an efficient power usage plan based on analyzed data.

[0576] "Quantum communication technology" is a communication technology that uses the properties of quantum mechanics to ensure the security of data.

[0577] "Communication means" refers to a method, device, or technology for sending and receiving data.

[0578] A "control system" is a system or process that makes adjustments in real time to balance the supply and consumption of power.

[0579] "Emotional analysis means" refers to a function that evaluates the emotional state of users and reflects it in the power usage plan.

[0580] "Urban optimization methods" are methods and technologies designed to optimize the distribution of electricity throughout a city.

[0581] The system for implementing this invention mainly consists of a server, a terminal, and an emotion analysis engine. The terminal is responsible for acquiring power consumption information from electricity meters in each home and business and transmitting it to the server. Furthermore, the terminal accesses external weather information services and transmits that data to the server as well. The server stores the received power consumption information and weather information in a database and applies machine learning algorithms to analyze past data and identify consumption patterns.

[0582] The emotion analysis engine uses data input from the user's voice and camera to analyze the user's emotional state. This result is sent to a server and used to optimize the power usage plan. Based on the analyzed consumption data, weather information, and emotion information, the server uses an AI agent to generate a individually optimized power usage plan. The server uses quantum communication technology to securely transmit the generated plan to the user's terminal.

[0583] This process includes suggestions for adjusting lighting and music, and changing air conditioning settings, based on the user's emotional state. Simultaneously, city-level power distribution plans are considered to optimize overall city power consumption. Users can review the suggestions provided by this system via a smartphone app and accept or adjust the plans.

[0584] As a concrete example, the system might suggest softening the lighting in the living space when the user is relaxed, or streaming calming music when the user is stressed. Furthermore, prompts such as, "How are you feeling today? Shall we play some music you like to help you relax and enjoy yourself?" are input into the AI ​​model to enable appropriate responses to the user. Using these prompts allows the system to provide more personalized and accurate suggestions.

[0585] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0586] Step 1:

[0587] The terminal acquires power consumption data from the power meter. This data is sampled every 5 minutes and sent to the server in real time. The input is raw data from the power meter, and the output is power consumption information every 5 minutes.

[0588] Step 2:

[0589] The terminal retrieves weather information from an external service and sends it to the server. The input is real-time data from the weather information service, and the output is information about current weather conditions.

[0590] Step 3:

[0591] The emotion analysis engine collects emotion data from the user's voice and camera and analyzes the user's emotional state. The input is the user's voice and image data, and the output is evaluation data representing the user's emotional state.

[0592] Step 4:

[0593] The server integrates received power consumption information, weather information, and sentiment rating data and stores it in a database. The input is the integrated data from the previous step, and the output is the stored data.

[0594] Step 5:

[0595] The server uses machine learning algorithms to analyze consumption patterns based on historical data and predict future power consumption. The inputs are historical power consumption information and weather information, and the output is a forecast of future power consumption.

[0596] Step 6:

[0597] The server uses sentiment analysis data to generate individually optimized power usage plans, with particular consideration given to the user's emotional state. Inputs are consumption forecast data and sentiment evaluation data, while output is the optimized power usage plan.

[0598] Step 7:

[0599] The server generates prompt messages using a generative AI model and sends them to the user. These prompt messages include suggestions tailored to the user's current situation. The input is the user's emotional state and optimization plan, and the output is a customized prompt message.

[0600] Step 8:

[0601] Users review the power usage plan and suggestions presented in the smartphone app and adjust the plan as needed. The input is the plan and suggestions sent from the server, and the output is the final adjusted power usage plan.

[0602] 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.

[0603] 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.

[0604] 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.

[0605] [Fourth Embodiment]

[0606] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0607] 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.

[0608] 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).

[0609] 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.

[0610] 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.

[0611] 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).

[0612] 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.

[0613] 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.

[0614] 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.

[0615] 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.

[0616] 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.

[0617] 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.

[0618] 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".

[0619] The system of this invention possesses advanced information processing technology to achieve efficient and safe power supply in homes and businesses. The system mainly consists of a server and terminals, and optimizes power supply according to the following procedure.

[0620] First, the device acquires consumption information in real time from electricity meters in each home and business. This data is measured, for example, every 5 minutes and includes current electricity usage and past consumption history. Weather information is also continuously acquired from external weather information services.

[0621] Next, the server receives this data and stores it in a database. There, it analyzes data from the past few weeks to months to generate consumption patterns. Machine learning algorithms are applied to this consumption pattern analysis, and by analyzing past consumption trends and seasonal fluctuations in particular, it makes highly accurate future predictions.

[0622] Furthermore, based on the generated consumption patterns, the AI ​​agent proposes an optimal power usage plan for each household or business. This plan includes specific actions to reduce peak power consumption, such as "setting the washing machine timer to increase power consumption in the morning" or "adjusting the office air conditioning temperature during specific time periods."

[0623] In terms of communication, the server uses quantum communication technology to securely transfer data to power companies and power plants. This reduces the risk of unauthorized acquisition of transmitted power consumption information and supply and demand adjustment instructions, allowing for secure data management.

[0624] Finally, the servers and terminals monitor the electricity demand of each household and business, and automatically adjust the balance of power supply whenever possible. This adjustment enables immediate feedback on power supply and demand, increasing efficiency in maximizing the use of renewable energy. This reduces wasted electricity use while ensuring a stable power supply.

[0625] Based on the above, the present invention is a system that provides efficient use and safe supply of electricity, thereby reducing the electricity burden on households and businesses.

[0626] The following describes the processing flow.

[0627] Step 1:

[0628] The terminal acquires real-time electricity consumption data from home and business electricity meters. This data is measured every 5 minutes and sent to the server, along with past consumption information.

[0629] Step 2:

[0630] The device accesses external weather information services to obtain current weather and forecast data. This weather data is also updated regularly and sent to the server.

[0631] Step 3:

[0632] The server stores the received power consumption data and weather data in a database. This creates a comprehensive dataset covering the past and present.

[0633] Step 4:

[0634] The server uses machine learning algorithms to analyze consumption patterns. This analysis takes into account past consumption trends and seasonal fluctuations to build a model that predicts future consumption behavior.

[0635] Step 5:

[0636] The AI ​​agent generates an optimal power usage plan for each household or business based on consumption patterns obtained from the server. The plan includes specific actions to avoid peak consumption.

[0637] Step 6:

[0638] The server transmits the generated power usage plan to terminals in each home and business. This process utilizes quantum communication technology to ensure secure data transfer.

[0639] Step 7:

[0640] The server monitors power demand in real time and adjusts the supply balance as needed. This maximizes the use of renewable energy and reduces wasteful consumption.

[0641] (Example 1)

[0642] 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".

[0643] In modern society, efficient and stable electricity consumption is a critical issue. Excessive electricity consumption and unpredictable fluctuations in demand lead to wasteful energy resources, unstable supply, and increased environmental burden. Furthermore, the secure management and transmission of collected electricity consumption information is also a challenge, as the unauthorized acquisition of this information could lead to privacy violations and economic losses.

[0644] 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.

[0645] In this invention, the server includes a device for acquiring power consumption information, a device for collecting weather information from an external information source, and a computing device for analyzing and predicting consumption patterns based on past power consumption information. This enables improved efficiency and stable supply of power consumption, as well as enhanced security of data communications.

[0646] A "device for acquiring power consumption information" is a machine that continuously and accurately collects power usage data from measuring instruments installed in homes and businesses.

[0647] A "device for collecting weather information from external sources" is a device for obtaining weather condition data from external data services via the internet.

[0648] A "computational device for analyzing and predicting consumption patterns" is a computer system that calculates and predicts future power consumption based on collected power consumption data and historical data.

[0649] A "planning device for generating power usage plans" is a device that creates an optimal power consumption schedule based on analyzed consumption patterns.

[0650] A "communication device using quantum communication technology" is a communication device that utilizes quantum key distribution technology to ensure high security in data transmission and reception.

[0651] A "control device that adjusts the balance between power supply and consumption in real time" is a device that monitors the energy supply and demand situation and adjusts the power supply as needed, thereby enabling efficient energy management.

[0652] The system of this invention is intended to promote efficient and safe power supply in homes and businesses. This system mainly consists of a server and terminals and uses data from measuring instruments installed in each home and business, as well as from external information sources.

[0653] The terminal is a device for obtaining real-time power consumption information from power meters. For example, it uses a smart meter to measure power usage every five minutes and transmits the data to a server. The terminal also connects to external information sources and obtains weather information via APIs. This allows for real-time monitoring of weather conditions that may affect power consumption.

[0654] The server is a system that receives data provided by terminals and stores it in a database. Using a database management system (e.g., MySQL, PostgreSQL), it integrates hourly consumption data and weather information, and stores it over long periods. Based on this data, the server uses machine learning algorithms to analyze power consumption patterns and predict future consumption.

[0655] Furthermore, the server uses an AI agent to suggest an optimal power usage plan to the user based on the analyzed consumption patterns. This plan includes specific actions to reduce power consumption during peak hours. For example, it might suggest "use the washing machine in the morning and reduce power usage during the afternoon peak." Users receive these suggestions through a smartphone app or web interface.

[0656] In this system, the server uses quantum communication technology to securely transmit data to power companies and power plants. Quantum key distribution technology is used for data encryption and decryption, enhancing communication security. Therefore, it is possible to prevent the unauthorized acquisition of power consumption information and supply and demand adjustment instructions.

[0657] For example, when a user utilizes this system in a smart home environment, the AI ​​agent automatically adjusts the operating schedule of home appliances according to the proposed power usage plan, optimizing energy efficiency. This allows the user to reduce electricity costs while maintaining a comfortable living environment.

[0658] Examples of prompts to input into a generative AI model:

[0659] "Based on current electricity consumption data and weather information, please propose the optimal electricity usage plan for this week."

[0660] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0661] Step 1:

[0662] The terminal acquires electricity consumption information from electricity meters in each home and business. This acquisition is performed at 5-minute intervals, collecting the current electricity consumption measured by the smart meter as digital data. The input is numerical data from the meter, and the output is the process of preparing this data as digital data ready to be transmitted to the server in real time.

[0663] Step 2:

[0664] The device accesses an external weather service to obtain weather information. This process uses an API to retrieve data such as current temperature, humidity, and weather conditions, and then formats this data for transmission to the server. The input is raw data from the weather service, and the output is weather information data in a parseable format.

[0665] Step 3:

[0666] The server stores power consumption data and weather information data received from terminals in a database. Specifically, it organizes and records this data appropriately in the database management system. The input is power consumption and weather information transmitted from terminals, and the output is a record as a database entry suitable for long-term storage.

[0667] Step 4:

[0668] The server performs analysis using data stored in the database. In this step, machine learning algorithms are applied to generate consumption patterns. The input consists of historical power consumption data and weather data, and the output is predicted future power consumption trends and patterns.

[0669] Step 5:

[0670] The server uses an AI agent to create an optimal power usage plan based on the generated consumption patterns. The plan includes specific power usage suggestions for each household or business. The input is the consumption patterns extracted in step 4, and the output is the specific power usage schedule proposed to the user.

[0671] Step 6:

[0672] The server securely transmits power consumption information and proposed power usage plans using quantum communication technology. Here, quantum key distribution technology is used to encrypt the communication and ensure security. The input is the plan data, and the output is the securely transmitted plan information.

[0673] Step 7:

[0674] Users receive a proposed power usage plan and provide feedback. They review the information received via a smartphone app or web interface and fine-tune the plan as needed. The input is the plan information received from the server, and the output is the final plan with the user's consent or adjustments.

[0675] (Application Example 1)

[0676] 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".

[0677] In modern homes and businesses, electricity consumption continues to increase, necessitating efficient energy use. Furthermore, there is a lack of systems capable of secure and rapid data communication and providing concrete energy-saving suggestions. Therefore, a means is needed to ensure the stability of the power supply while allowing users to understand the situation in real time and improve energy efficiency.

[0678] 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.

[0679] In this invention, the server includes data acquisition means for acquiring power consumption information, analysis means for analyzing and predicting consumption trends based on past power consumption information, and strategy generation means for generating a power usage plan based on the analyzed consumption trends. This enables real-time optimization of energy consumption in homes and businesses, and allows for safe and efficient power supply.

[0680] "Data acquisition means" refers to a device or function that has the function of collecting electricity consumption information in homes and businesses in real time and transferring the data from each terminal to a server.

[0681] "Analysis means" refers to a device or function that uses collected past electricity consumption information to analyze consumption trends and perform processing to predict future electricity demand.

[0682] A "strategy generation tool" is a device or function that has the function of formulating a plan to achieve efficient power utilization based on analyzed power consumption trends.

[0683] "Information exchange means" refers to a device or function that uses communication technology to ensure secure information transmission to send and receive data, and to perform encryption and decryption.

[0684] "Adjustment means" refers to a device or function that performs the necessary controls to monitor and adjust the balance between power supply and consumption in real time.

[0685] "Information display means" refers to a device or function that has the ability to display information in real time on the screen of a mobile device or similar device, so that users can easily understand the power consumption status of their home or business.

[0686] The system constructed to implement this invention includes data acquisition means, analysis means, strategy generation means, information exchange means, coordination means, and information display means. The server uses these means to improve power consumption efficiency and secure data communication.

[0687] The server collects power consumption data in real time via IoT devices as a data acquisition method. Specifically, it collects data using the MQTT protocol, for example, and manages backend processing with an API that employs the Flask framework. The collected data is analyzed using TensorFlow as an analysis tool to form a model that predicts future power demand based on past consumption trends.

[0688] The strategy generation tool presents users with efficient power usage methods based on the generated analysis results. This functionality is delivered directly to users through a mobile application built using React Native. Users can use this app to monitor their power usage in real time and obtain specific actions to take to save energy.

[0689] As a means of information exchange, the server utilizes quantum communication technology to ensure secure information transmission, encrypting data transmission and reception over the communication network. Furthermore, the adjustment mechanism monitors power supply and consumption in real time, automatically adjusting the supply-demand balance.

[0690] For example, if excessive power consumption is predicted during a specific time of day, the system will send a notification to the user such as, "Please change the washing machine usage time to reduce power consumption during this time." An example of a prompt to be input into the generating AI model might be, "Based on power consumption data from the past month and weather forecast data, predict next week's energy consumption pattern and propose an effective action plan for peak shifting."

[0691] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0692] Step 1:

[0693] The server receives power consumption data in real time from terminals via the MQTT protocol. This input data includes information from electricity meters in specific homes or businesses, and the server stores this data in a database.

[0694] Step 2:

[0695] The server uses stored power consumption data to perform data analysis based on a machine learning model utilizing TensorFlow. It takes historical power consumption data and weather information as input to model consumption trends. As a result of the analysis, a forecast of future power demand is output.

[0696] Step 3:

[0697] The server uses the analysis results to present a power usage plan to a mobile app built with React Native via an AI agent. Input information includes predicted consumption trends, and the output generates specific savings suggestions for the user.

[0698] Step 4:

[0699] Users receive power usage plans and suggestions sent from the server via a mobile app. Based on this information, users can select specific power-saving actions. The suggestions provided might include things like "avoid using electrical appliances during peak hours."

[0700] Step 5:

[0701] The terminal controls each device to adjust power consumption within homes and businesses, following instructions from the server. It receives adjustment instructions from the server as input and controls the operation of the corresponding device as output. This optimizes the balance between power supply and consumption in real time.

[0702] 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.

[0703] The system in this invention formulates an optimal power usage plan based on power consumption information and user emotion information. The system mainly consists of a server, a terminal, and an emotion engine, and is implemented in the following procedure.

[0704] First, the terminal acquires real-time power consumption data from home and business electricity meters. This data is recorded every 5 minutes and sent to the server, and weather information is also obtained from external services and sent to the server.

[0705] Next, the emotion engine analyzes emotional information from the user's voice input and camera input. This analysis determines the user's current emotional state, and the result is sent to the server.

[0706] The server stores received power consumption data, weather information, and sentiment information in a database. Based on this data, machine learning algorithms are used to analyze consumption patterns and predict future power consumption. User sentiment information, in particular, is considered important as a factor influencing consumption behavior and is reflected in the system for individual optimization.

[0707] Next, the AI ​​agent uses the analyzed data to generate an optimized power usage plan for specific emotional states. For example, when the user is relaxed, it adjusts lighting and temperature settings for greater comfort, and when stress levels are high, it suggests things like playing music to reduce stress.

[0708] To ensure privacy and data security, the server uses quantum communication technology to encrypt and decrypt communications while smoothly exchanging data. This ensures that user emotional information and power usage data are managed securely.

[0709] Finally, users can review the proposed electricity usage plan on their smartphone app or device. They can then accept the system's proposal or adjust the plan as needed to achieve energy management tailored to their individual needs.

[0710] This embodiment enables the efficient and safe supply of electricity, making the user's living environment more comfortable.

[0711] The following describes the processing flow.

[0712] Step 1:

[0713] The terminal acquires real-time power consumption data from home and business electricity meters. This data is sent to the server at 5-minute intervals. The terminal also acquires weather data from weather information services and sends it to the server in the same manner.

[0714] Step 2:

[0715] The emotion engine acquires user audio and video data from the microphone and camera connected to the device. It analyzes this data to identify the user's current emotional state. This emotional information is then sent to the server.

[0716] Step 3:

[0717] The server integrates the received power consumption data, weather data, and sentiment information and stores it in a database. This creates a foundational dataset for comprehensively understanding the situation.

[0718] Step 4:

[0719] The server uses machine learning algorithms to analyze past consumption data and sentiment information. This allows it to more accurately predict future electricity demand and user behavior.

[0720] Step 5:

[0721] The AI ​​agent generates a power usage plan tailored to the user's emotional state, based on data predicted by the server. This plan may include lighting and air conditioning settings to improve comfort.

[0722] Step 6:

[0723] The server transmits the generated power usage plan to terminals in each home and business. Quantum communication technology is used to ensure the security and privacy of the communication.

[0724] Step 7:

[0725] Users review suggestions from the AI ​​agent via their device or smartphone app. Based on these suggestions, users can adjust their actual power usage and operate according to a plan that also reflects emotional information.

[0726] (Example 2)

[0727] 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".

[0728] Managing electricity consumption efficiently in modern society and creating optimal power usage plans tailored to the emotional state of individual users presents a significant challenge. Furthermore, there is a need to balance power supply and consumption in real time while ensuring privacy and data security. Conventional systems are insufficient to address these challenges.

[0729] 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.

[0730] In this invention, the server includes data acquisition means for acquiring power consumption information and weather information, emotion analysis means for analyzing user emotion information and determining the emotional state, and consumption analysis means for analyzing and predicting consumption patterns based on past power consumption information and emotion information. This makes it possible to generate and securely manage power usage plans optimized for each individual user.

[0731] "Data acquisition means" refers to a device or method for acquiring power consumption information and weather information in real time.

[0732] "Emotion analysis means" refers to a technology or device for identifying a user's emotional state based on the user's voice input or camera footage.

[0733] A "consumption analysis tool" is a method or program for analyzing consumption patterns from past electricity consumption information and emotional information to predict future consumption.

[0734] "Plan generation means" refers to a technology or device for creating an optimal power usage plan for individual users based on predicted consumption patterns and emotional information.

[0735] "Secure communication means" refers to a method or device for encrypting and decrypting data using quantum communication technology and for securely transmitting and receiving it.

[0736] "Balance control means" refers to a technology or device that adjusts the balance between power supply and consumption in real time to maintain the efficiency and stability of the entire system.

[0737] This invention is a system that formulates an optimal power usage plan based on power consumption information and user emotion information. This system mainly consists of a server, terminals, and an emotion engine.

[0738] The terminal uses smart electricity meters to obtain real-time electricity consumption information from homes and businesses. Furthermore, weather information is obtained from external information services via an internet connection. This data is updated every five minutes and transmitted to the server.

[0739] The emotion engine analyzes emotional information using the user's voice and video input from the camera. A voice emotion analysis algorithm is used for voice analysis, and facial recognition technology is used for facial expression analysis. The analyzed emotional information is sent to the server.

[0740] The server aggregates power consumption information, weather information, and emotional information received from the terminal and the emotion engine, and stores it in a database. Based on the stored data, it uses machine learning algorithms to analyze consumption patterns and predict future power consumption. For example, the server might suggest a plan to adjust the lighting to warmer colors and maintain a comfortable room temperature during a relaxed weekend afternoon. It might also suggest playing healing music.

[0741] The AI ​​agent generates an optimal power usage plan based on data analyzed by the server, tailored to the user's emotional state. This plan is particularly effective when the user is relaxed and includes settings for comfortable lighting and temperature.

[0742] To ensure privacy, the server uses quantum communication technology to encrypt and decrypt data, ensuring secure data transmission. Furthermore, user emotional information and power consumption data are highly protected.

[0743] Ultimately, users can review, accept, or adjust the power usage plan generated by the AI ​​agent through a smartphone app or dedicated device. In this way, users can achieve comfortable and efficient energy management tailored to their individual needs.

[0744] An example of a prompt for a generative AI model is: "Please suggest an optimal power usage plan for when the user is relaxing. Include specific suggestions regarding lighting, temperature settings, and music playback."

[0745] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0746] Step 1:

[0747] The terminal acquires electricity consumption information from smart electricity meters for homes and businesses. Input data includes information on power consumption and time of day. This data is updated every 5 minutes and transmitted to a server via the internet. The output, electricity consumption information, is then transferred to the server for management.

[0748] Step 2:

[0749] The terminal obtains weather information from external information services. Input data includes current temperature, humidity, and probability of precipitation. This information is obtained via the internet and transmitted to the server. The latest weather information data is stored on the server as output.

[0750] Step 3:

[0751] The emotion engine performs emotion analysis using voice input and camera footage from the user. Input data includes voice tone and facial expressions. Using voice emotion analysis algorithms and facial recognition technology, it identifies the user's emotional state. The analyzed emotional state is then sent to the server as output.

[0752] Step 4:

[0753] The server centrally manages power consumption information, weather information, and emotion information received from terminals and the emotion engine, storing them in a database. Various types of information are included in the input and stored in the database. No output is generated at this stage, but data is accumulated in preparation for subsequent analysis.

[0754] Step 5:

[0755] The server uses machine learning algorithms to analyze stored data. Input data includes previously stored power consumption information, weather information, and sentiment information. Based on this data, it analyzes consumption patterns and predicts future power consumption. The output is the predicted consumption pattern.

[0756] Step 6:

[0757] The AI ​​agent generates an optimal power usage plan based on consumption patterns and current emotional state. Input data includes analyzed consumption patterns and emotional information. The AI ​​uses a generative AI model to create a specific usage plan. The output is a customized power usage plan tailored to the user.

[0758] Step 7:

[0759] The server uses quantum communication technology to encrypt and decrypt data, securely transmitting the plan to the terminal. The input data includes the generated power usage plan. The output is encrypted data delivered to the terminal, allowing the user to receive the information securely.

[0760] Step 8:

[0761] Users can view the provided electricity usage plan through a smartphone app or dedicated terminal. The input includes decrypted plan information. Users can view the plan, adjust it as needed, and apply it. The output is the electricity usage schedule customized by the user, which is then put into action.

[0762] (Application Example 2)

[0763] 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".

[0764] In modern society, efficient energy management is essential, but conventional electricity usage plans are based solely on consumption patterns and do not take into account the emotional state of users or the optimization of electricity distribution across the entire city. This can lead to problems such as oversupply and decreased resident satisfaction. As a result, efficiency improvements in electricity supply and improvements in quality of life are hindered.

[0765] 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.

[0766] In this invention, the server includes information acquisition means for acquiring power consumption information, analysis means for analyzing and predicting consumption patterns based on past power consumption information, plan generation means for generating a power usage plan based on the analyzed consumption patterns, communication means for securely transmitting and receiving data using quantum communication technology, control means for adjusting the balance between power supply and consumption in real time, emotion analysis means for optimizing the power usage plan by considering factors based on the emotional state of the user, and urban optimization means for optimizing the power distribution of the entire city. This makes it possible to generate and implement a more accurate power usage plan that takes into account the emotional state of the user and the power distribution of the entire city.

[0767] "Electricity consumption information" refers to data on the amount of electricity used by households and businesses.

[0768] "Information acquisition means" refers to a device or procedure for collecting electricity consumption information.

[0769] "Analysis means" refers to the process of analyzing past power consumption information, extracting patterns, and predicting future consumption.

[0770] "Plan generation means" refers to a method or function for creating an efficient power usage plan based on analyzed data.

[0771] "Quantum communication technology" is a communication technology that uses the properties of quantum mechanics to ensure the security of data.

[0772] "Communication means" refers to a method, device, or technology for sending and receiving data.

[0773] A "control system" is a system or process that makes adjustments in real time to balance the supply and consumption of power.

[0774] "Emotional analysis means" refers to a function that evaluates the emotional state of users and reflects it in the power usage plan.

[0775] "Urban optimization methods" are methods and technologies designed to optimize the distribution of electricity throughout a city.

[0776] The system for implementing this invention mainly consists of a server, a terminal, and an emotion analysis engine. The terminal is responsible for acquiring power consumption information from electricity meters in each home and business and transmitting it to the server. Furthermore, the terminal accesses external weather information services and transmits that data to the server as well. The server stores the received power consumption information and weather information in a database and applies machine learning algorithms to analyze past data and identify consumption patterns.

[0777] The emotion analysis engine uses data input from the user's voice and camera to analyze the user's emotional state. This result is sent to a server and used to optimize the power usage plan. Based on the analyzed consumption data, weather information, and emotion information, the server uses an AI agent to generate a individually optimized power usage plan. The server uses quantum communication technology to securely transmit the generated plan to the user's terminal.

[0778] This process includes suggestions for adjusting lighting and music, and changing air conditioning settings, based on the user's emotional state. Simultaneously, city-level power distribution plans are considered to optimize overall city power consumption. Users can review the suggestions provided by this system via a smartphone app and accept or adjust the plans.

[0779] As a concrete example, the system might suggest softening the lighting in the living space when the user is relaxed, or streaming calming music when the user is stressed. Furthermore, prompts such as, "How are you feeling today? Shall we play some music you like to help you relax and enjoy yourself?" are input into the AI ​​model to enable appropriate responses to the user. Using these prompts allows the system to provide more personalized and accurate suggestions.

[0780] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0781] Step 1:

[0782] The terminal acquires power consumption data from the power meter. This data is sampled every 5 minutes and sent to the server in real time. The input is raw data from the power meter, and the output is power consumption information every 5 minutes.

[0783] Step 2:

[0784] The terminal retrieves weather information from an external service and sends it to the server. The input is real-time data from the weather information service, and the output is information about current weather conditions.

[0785] Step 3:

[0786] The emotion analysis engine collects emotion data from the user's voice and camera and analyzes the user's emotional state. The input is the user's voice and image data, and the output is evaluation data representing the user's emotional state.

[0787] Step 4:

[0788] The server integrates received power consumption information, weather information, and sentiment rating data and stores it in a database. The input is the integrated data from the previous step, and the output is the stored data.

[0789] Step 5:

[0790] The server uses machine learning algorithms to analyze consumption patterns based on historical data and predict future power consumption. The inputs are historical power consumption information and weather information, and the output is a forecast of future power consumption.

[0791] Step 6:

[0792] The server uses sentiment analysis data to generate individually optimized power usage plans, with particular consideration given to the user's emotional state. Inputs are consumption forecast data and sentiment evaluation data, while output is the optimized power usage plan.

[0793] Step 7:

[0794] The server generates prompt messages using a generative AI model and sends them to the user. These prompt messages include suggestions tailored to the user's current situation. The input is the user's emotional state and optimization plan, and the output is a customized prompt message.

[0795] Step 8:

[0796] Users review the power usage plan and suggestions presented in the smartphone app and adjust the plan as needed. The input is the plan and suggestions sent from the server, and the output is the final adjusted power usage plan.

[0797] 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.

[0798] 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.

[0799] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0800] 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.

[0801] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0802] 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.

[0803] 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.

[0804] 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.

[0805] 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."

[0806] 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.

[0807] 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.

[0808] 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.

[0809] 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.

[0810] 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.

[0811] 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.

[0812] 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.

[0813] 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.

[0814] 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.

[0815] 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.

[0816] 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.

[0817] 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.

[0818] The following is further disclosed regarding the embodiments described above.

[0819] (Claim 1)

[0820] Information acquisition means for acquiring power consumption information,

[0821] An analytical means for analyzing and predicting consumption patterns based on past power consumption information,

[0822] A plan generation means that generates a power usage plan based on the analyzed consumption pattern,

[0823] A communication means that uses quantum communication technology to securely transmit and receive data,

[0824] A control means that adjusts the balance between power supply and consumption in real time,

[0825] A system that includes this.

[0826] (Claim 2)

[0827] The system according to claim 1, characterized in that the plan generation means generates a power usage plan taking weather information into consideration.

[0828] (Claim 3)

[0829] The system according to claim 1, characterized in that the communication means ensures the security of the communication by performing encryption and decryption.

[0830] "Example 1"

[0831] (Claim 1)

[0832] A device for acquiring power consumption information,

[0833] A device that collects weather information from external sources,

[0834] A computing device that analyzes and predicts consumption patterns based on past power consumption information,

[0835] A planning device that generates a power usage plan based on the analyzed consumption patterns,

[0836] A communication device that uses quantum communication technology to securely transmit and receive data,

[0837] A control device that adjusts the balance between power supply and consumption in real time,

[0838] A system that includes this.

[0839] (Claim 2)

[0840] The system according to claim 1, characterized in that the planning device generates a power usage plan taking weather information into consideration.

[0841] (Claim 3)

[0842] The system according to claim 1, characterized in that the communication device ensures the security of communications by performing encryption and decryption.

[0843] "Application Example 1"

[0844] (Claim 1)

[0845] A data acquisition method for obtaining power consumption information,

[0846] An analytical method for analyzing and predicting consumption trends based on past electricity consumption information,

[0847] A strategy generation means for generating an electricity usage plan based on analyzed consumption trends,

[0848] An information exchange means that uses communication technology to ensure secure information transmission to perform secure transmission and reception of data,

[0849] A means of adjusting the balance between power supply and consumption in real time,

[0850] An information display device that shows the electricity consumption status of homes and businesses on the user's mobile device and suggests ways to improve energy efficiency,

[0851] A system that includes this.

[0852] (Claim 2)

[0853] The system according to claim 1, wherein the strategy generation means takes weather information into consideration and proposes specific actions to improve energy efficiency based on the results of analysis by AI.

[0854] (Claim 3)

[0855] The system according to claim 1, wherein the information exchange means performs encryption and decryption, and also distributes and provides feedback on data in real time via a communication network.

[0856] "Example 2 of combining an emotion engine"

[0857] (Claim 1)

[0858] A data acquisition means for acquiring power consumption information and weather information,

[0859] An emotion analysis method that analyzes user emotional information to determine emotional state,

[0860] A consumption analysis method that analyzes and predicts consumption patterns based on past power consumption information and emotional information,

[0861] A plan generation means for generating a power usage plan based on predicted consumption patterns and emotional information,

[0862] A secure communication means that uses quantum communication technology to securely transmit and receive data,

[0863] A balance control means that adjusts the balance between power supply and consumption in real time,

[0864] A system that includes this.

[0865] (Claim 2)

[0866] The system according to claim 1, characterized in that the plan generation means generates a power usage plan adapted to a specific emotional state.

[0867] (Claim 3)

[0868] The system according to claim 1, characterized in that the secure communication means ensures the security of communication by performing quantum communication while encrypting and decrypting.

[0869] "Application example 2 when combining with an emotional engine"

[0870] (Claim 1)

[0871] Information acquisition means for acquiring power consumption information,

[0872] An analytical means for analyzing and predicting consumption patterns based on past power consumption information,

[0873] A plan generation means that generates a power usage plan based on the analyzed consumption pattern,

[0874] A communication means that uses quantum communication technology to securely transmit and receive data,

[0875] A control means that adjusts the balance between power supply and consumption in real time,

[0876] An emotion analysis means for optimizing power usage plans by taking into account factors based on the user's emotional state,

[0877] A means of urban optimization for optimizing the power distribution of the entire city,

[0878] A system that includes this.

[0879] (Claim 2)

[0880] The system according to claim 1, characterized in that the plan generation means generates a power usage plan taking weather information into consideration.

[0881] (Claim 3)

[0882] The system according to claim 1, characterized in that the communication means ensures the security of the communication by performing encryption and decryption. [Explanation of Symbols]

[0883] 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 data acquisition method for obtaining power consumption information, An analytical method for analyzing and predicting consumption trends based on past electricity consumption information, A strategy generation means for generating an electricity usage plan based on analyzed consumption trends, An information exchange means that uses communication technology to ensure secure information transmission to perform secure transmission and reception of data, A means of adjusting the balance between power supply and consumption in real time, An information display device that shows the electricity consumption status of homes and businesses on the user's mobile device and suggests ways to improve energy efficiency, A system that includes this.

2. The system according to claim 1, wherein the strategy generation means takes weather information into consideration and proposes specific actions to improve energy efficiency based on the results of AI analysis.

3. The system according to claim 1, wherein the information exchange means performs encryption and decryption, and also distributes and provides feedback on data in real time via a communication network.

Images