system

Abstract

We provide the system. [Solution] A means for inputting building design information and analyzing solar radiation based on said information, A means for optimizing the installation of a solar energy generation system based on the analyzed solar radiation, A method for analyzing the surplus of generated electricity and predicting electricity sales revenue based on market prices, A means for optimizing the charging schedule of energy-consuming devices and automatically controlling charging, A means of managing the progress of construction work and dynamically adjusting resource allocation, A means of providing residents with the optimal power generation system and electricity sales strategy using smartphones, A system that includes this.

Description

Technical Field

[0005]

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is 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 character of the chatbot, 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 context of global warming and the depletion of energy resources, the introduction of renewable energy in houses has become an urgent task. However, the effective placement of solar energy power generation devices, the maximization of profits from power surplus trading in the market, and the efficient charging management of energy-consuming devices are complex and difficult for many house owners. In addition, the smooth progress management of construction work and the waste-free allocation of construction resources are also important issues.

Means for Solving the Problems

[0005] This invention provides a means to analyze solar radiation based on design information and support the optimization of the installation of solar energy generation equipment. Furthermore, it includes a function to predict electricity sales revenue considering market prices for the analyzed surplus electricity. In addition, it optimizes charging schedules for energy-consuming equipment, and in particular, improves cost-effectiveness by selecting times when electricity rates are low for charging electric vehicles. During construction, it improves construction efficiency by managing progress and automatically adjusting resource allocation.

[0006] "Building design information" refers to data related to the optimal use of solar energy, such as the building's structure, dimensions, orientation, and roof slope angle.

[0007] "Solar radiation" refers to the total amount of sunlight received at a specific location over a certain period of time, and is a major factor that affects the efficiency of solar energy conversion.

[0008] A "solar energy generation system" is a device that converts sunlight into electricity, and typically includes solar panels and associated systems.

[0009] "Installation optimization" refers to the process of adjusting the placement of solar energy generation equipment to ensure the most efficient arrangement, taking into account factors such as the angle and orientation of the light-receiving surface.

[0010] "Electricity surplus" refers to the portion of generated electricity that is not consumed, and this electricity may be sold on the market.

[0011] "Electricity sales revenue" refers to the profits earned by selling surplus electricity to power companies and other entities.

[0012] "Energy-consuming equipment" refers to all equipment that consumes electricity, and in this invention, it specifically includes electric vehicles.

[0013] A "charging schedule" is a plan for systematically setting the time periods and durations for charging energy-consuming devices.

[0014] "The progress of construction work" is an indicator showing how far a construction project has progressed compared to the scheduled schedule.

[0015] "Resource allocation" is a process that means appropriately allocating the personnel, materials, and time required for construction work.

Brief Explanation of Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It 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] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one 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.

[0020] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0022] 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).

[0023] 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."

[0024] [First Embodiment]

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

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0031] 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.

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

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] This invention is a system that predicts solar radiation based on building design information and supports the optimal installation of solar energy generation equipment. This system enables efficient energy management of buildings and focuses particularly on optimizing solar power generation and electricity consumption.

[0038] The user provides building design information to the server. Based on this design information, the server uses historical weather data and simulation models to analyze solar radiation. Utilizing the resulting solar radiation data, the server generates a layout plan to optimize the installation of solar energy generation equipment. This optimization process takes into account factors such as roof shape, angle, and orientation, aiming to maximize power generation.

[0039] Next, the server analyzes the surplus electricity generated in accordance with market conditions and predicts revenue from selling the electricity. This prediction helps users evaluate the payback period of their investment and understand the economic benefits of the installation. It also takes into account fluctuations in electricity prices and suggests to users that they sell the surplus electricity during the most profitable time of day.

[0040] Furthermore, if the user owns energy-consuming equipment, especially electric vehicles, the terminal will create a charging schedule. This schedule is provided by the server, which selects and manages the charging process automatically, taking advantage of times when electricity rates are low. This feature can reduce energy costs and improve ease of use.

[0041] During construction work, terminals transmit progress data from the construction site to a server. The server monitors the construction status in real time and immediately adjusts resource allocation if delays occur in the schedule. In this way, the efficiency of the construction is increased, and the smooth progress of the construction is guaranteed.

[0042] As a concrete example, for a user's south-facing roof, the server analyzes solar radiation and proposes the optimal placement of power generation equipment. It also predicts that approximately 1,000 kWh of surplus electricity can be sold each month, generating an income of 50,000 yen, and notifies the user. Furthermore, the charging of electric vehicles is automated to begin at 2 AM, ensuring that the minimum charge is incurred.

[0043] Thus, the present invention can maximize the use of solar energy and achieve cost-effective energy management.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] The user inputs building design information into the server. This information includes the building's dimensions, location, roof slope angle, and orientation.

[0047] Step 2:

[0048] The server analyzes the input design information and retrieves solar radiation data from the relevant regional weather database. Based on this data, the server simulates the annual solar radiation at specific points in the building.

[0049] Step 3:

[0050] The server calculates the optimal placement of solar energy generation equipment based on the predicted amount of solar radiation. In doing so, it takes into account the shape and orientation of the roof to generate a layout plan that maximizes power generation.

[0051] Step 4:

[0052] The server provides the user with feedback on the generated optimal placement plan and asks for confirmation of the installation plan. The user approves or modifies the proposed placement and makes a final decision.

[0053] Step 5:

[0054] The server analyzes the user's power consumption patterns and uses this information to predict the revenue from selling surplus electricity generated. The server also performs electricity sales simulations that take market prices into account.

[0055] Step 6:

[0056] If the user has energy-consuming devices, the terminal shares their operating status and charging schedule with the server.

[0057] Step 7:

[0058] The server analyzes the times of day when electricity rates are lower and optimizes the charging schedule for energy-consuming devices. Based on the schedule, the devices automatically start and stop charging at the specified times.

[0059] Step 8:

[0060] The terminal reports the progress of the construction work from the site in real time and sends the data to the server.

[0061] Step 9:

[0062] The server monitors the progress of the construction and dynamically adjusts resource allocation as needed to optimize the construction schedule.

[0063] Step 10:

[0064] Users can centrally monitor the overall energy management status, electricity sales revenue, and construction status to achieve optimal energy management.

[0065] (Example 1)

[0066] 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."

[0067] In recent years, there has been a growing demand for the expanded use of renewable energy, with solar power generation attracting particular attention. However, effective installation and operation of solar power generation systems require accurate analysis of solar radiation, maximization of economic benefits, and efficient operation of power consumption equipment. Furthermore, to improve the efficiency of these processes, progress management of construction work and optimization of resource allocation are necessary. This invention aims to solve these problems.

[0068] 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.

[0069] In this invention, the server includes means for inputting building design information and analyzing the amount of sunlight based on said information, means for optimizing the placement of solar power generation equipment based on the analyzed amount of sunlight, and means for analyzing the surplus of generated electricity and predicting electricity sales profits based on market conditions. This enables optimal utilization of solar energy and maximization of economic benefits.

[0070] A "building" is a structure designed for human use, such as a residence or commercial facility.

[0071] "Design information" refers to data that shows details such as the structure, layout, shape, and orientation of a building.

[0072] "Amount of sunlight" refers to information about the intensity and duration of sunlight at a specific location.

[0073] "Solar power generation equipment" refers to equipment that converts sunlight into electricity, and includes solar panels and related facilities.

[0074] "Placement" refers to the act of arranging objects based on specific criteria, particularly the optimal location in buildings and equipment.

[0075] "Surplus electricity" refers to electricity that is not consumed and can be supplied externally.

[0076] "Market conditions" refer to the economic situation and price trends at a specific time and place.

[0077] A "consumer device" is a machine or piece of equipment that operates using electricity.

[0078] A "charging schedule" is a plan for supplying power to devices in order to ensure efficient operation of power-consuming equipment.

[0079] "Work progress" refers to the extent to which a particular project or construction work is progressing according to plan.

[0080] "Resource allocation" refers to the appropriate distribution of personnel, equipment, materials, and other resources necessary for a task or project.

[0081] This invention relates to a system for optimizing the design and operation of solar power generation systems in buildings. This system consists of a server and terminals as its main components and operates based on user input information.

[0082] The user provides design information to the server via their terminal. This information includes the building's location, shape, roof angle, and orientation. Based on this design information, the server uses software such as WeatherAPI and Radiance to acquire historical weather data and analyze the amount of sunlight.

[0083] The server creates a simulation model based on the analyzed amount of sunlight and determines the optimal placement of the solar power generation equipment. This placement decision takes into account the roof angle and orientation to maximize power generation. This allows users to efficiently proceed with their installation planning.

[0084] Next, the server analyzes market conditions based on the amount of electricity that can be generated and uses software such as OpenEnergyPlatform to predict the profits from selling the electricity. These predictions are provided to the user, who can use them to make decisions that maximize their economic benefits.

[0085] Furthermore, if a user owns an electric vehicle as a power-consuming device, the terminal automatically sets a charging schedule considering the off-peak hours offered by the server. This process is designed to charge during off-peak hours when electricity rates are low, such as late at night, thereby reducing energy costs.

[0086] Furthermore, during the construction phase, the terminals transmit progress data acquired from the construction site to the server. The server monitors this data in real time and dynamically adjusts resource allocation according to the progress, thereby improving construction efficiency.

[0087] For example, if a user enters a prompt such as, "Please calculate the optimal installation method and economic effect of the solar power generation system in my home," the server will perform analysis and optimization according to the procedure described above and present the user with a specific installation plan and its economic effect.

[0088] In this way, this system efficiently manages the use of solar energy and provides economic value to users.

[0089] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0090] Step 1:

[0091] Users input building design information into the server via a terminal. This design information includes the building's location, roof shape, angles, and orientation. This input information is stored in the server's database and serves as the basic data for solar radiation analysis.

[0092] Step 2:

[0093] The server uses design information received from the user to acquire weather data from an external source. During this process, it collects historical weather data using the WeatherAPI and generates a simulation model using Radiance to predict the amount of sunlight at each location on the roof. The input design information and weather data are combined to calculate the predicted annual solar radiation, which is then stored in a database.

[0094] Step 3:

[0095] The server calculates the optimal placement of solar power generation equipment based on the calculated solar radiation data. This process takes into account the roof angle and orientation to maximize power generation and performs multiple placement simulations. This predicts the maximum power generation at each installation location and derives the optimal placement plan.

[0096] Step 4:

[0097] The server analyzes electricity market trends based on the optimal deployment plan and predicted power generation, and uses OpenEnergyPlatform to predict electricity sales revenue. This analysis determines the optimal timing for selling electricity based on market prices and supply volume, and calculates the resulting economic benefits. The final prediction results are notified to the user.

[0098] Step 5:

[0099] If a user owns an electric vehicle, the terminal automatically sets a charging schedule based on information about cheaper time slots obtained from the server. This process adjusts the user's power usage and power supply time, specifically targeting charging during off-peak hours when rates are lower.

[0100] Step 6:

[0101] The terminal periodically sends progress data from the construction site to the server. Based on the received progress data, the server monitors delays and problems in the construction schedule in real time and dynamically adjusts the allocation of resources and personnel as needed to support the smooth progress of the construction.

[0102] (Application Example 1)

[0103] 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."

[0104] Conventional solar energy generation systems have faced challenges in efficiently generating energy and optimizing electricity sales because they cannot fully utilize the design information and solar radiation data specific to each building. Furthermore, the automation of charging schedule management for energy-consuming devices such as electric vehicles is insufficient, making it difficult to optimize energy costs.

[0105] 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.

[0106] In this invention, the server includes means for analyzing solar radiation based on building design information, means for optimizing the installation of a solar energy generation system based on the analysis results, and means for predicting revenue from selling surplus generated electricity based on market prices. This makes it possible to introduce an optimal power generation system for each building and maximize economic benefits through efficient energy management.

[0107] "Building design information" refers to information that affects the efficiency of solar power generation, such as the building's structure, shape, and orientation.

[0108] "Methods for analyzing solar radiation" refer to techniques that use historical weather data and simulation models to calculate the amount of sunlight irradiating a specific building.

[0109] "Methods for optimizing the installation of solar energy generation equipment" refers to technologies for installing equipment in the optimal location to maximize power generation efficiency, based on the results of solar radiation analysis.

[0110] "Methods for predicting electricity sales revenue based on market prices" refer to techniques that analyze the market price of electricity when selling generated electricity and estimate the revenue.

[0111] "Means for optimizing the charging schedule of energy-consuming devices" refers to technologies that determine the optimal time for charging in order to minimize the cost of energy consumption.

[0112] "Means for managing the progress of construction work and dynamically adjusting resource allocation" refers to technologies that monitor the progress of construction projects in real time and make the necessary adjustments to efficiently utilize resources.

[0113] "A means of providing residents with the optimal power generation system and electricity sales strategy using smartphones" refers to a technology that analyzes power generation status and profitability to users via mobile devices and proposes appropriate strategies.

[0114] The system for implementing this invention begins with the user providing building design information to a server. The server then uses historical weather data and simulation models to perform a detailed analysis of the amount of solar radiation on the building. Based on this analysis, the server determines the optimal location for installing the solar energy generation equipment.

[0115] Next, the server analyzes the surplus of generated electricity and predicts sales revenue by comparing it with market electricity prices. This allows users to see the economic benefits of the power generation system.

[0116] Furthermore, the system also manages the charging schedules for energy-consuming devices, especially electric vehicles. The server identifies periods with lower electricity rates and automatically initiates charging, minimizing energy consumption costs.

[0117] For construction site management, terminals send construction progress data to a server, which then monitors the progress in real time. This allows for quick adjustment of resource allocation even if delays occur in the schedule.

[0118] One concrete example is an application that uses a smartphone to determine the optimal placement of solar power generation equipment to be installed on the roof of a user's home. This allows for the suggestion of a power sales strategy tailored to the characteristics of the region, enabling the user to maximize their profits.

[0119] Using a generative AI model, entering a prompt like the following will suggest the optimal installation strategy: "Generate the optimal solar power plant layout based on building design information and weather data, and calculate the economic benefits."

[0120] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0121] Step 1:

[0122] The server receives building design information entered by the user. This input includes information such as the orientation, angle, and location of the building's roof. The server uses this information to store it as basic data for analyzing the amount of solar radiation on the building.

[0123] Step 2:

[0124] The server retrieves historical weather data from a weather database and analyzes solar radiation in combination with design information. Specifically, it uses a simulation model to calculate the average solar radiation for a specific period. Based on these calculation results, it generates the data necessary to ensure maximum power generation.

[0125] Step 3:

[0126] The server uses the analyzed solar radiation data to determine the optimal location and orientation for the solar energy generation equipment. This generates a layout plan to maximize power generation. Users can receive this plan and use it in their own equipment planning.

[0127] Step 4:

[0128] The server analyzes the surplus electricity generated by the power generators and predicts electricity sales revenue by comparing it with market price data. This process obtains current market price information in real time and multiplies it with the predicted power generation value to output the expected electricity sales revenue.

[0129] Step 5:

[0130] The server optimizes the charging schedule for the user's energy-consuming devices. It automatically selects time periods with lower electricity rates and schedules the start of charging accordingly. As a result, the user achieves cost-effective and efficient energy consumption.

[0131] Step 6:

[0132] The terminal transmits progress information from the construction site to the server. The server analyzes the received progress data and adjusts the schedule and resource allocation in real time based on this analysis. This process prevents delays and ensures the project progresses efficiently.

[0133] 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.

[0134] This invention relates to a system that recognizes the emotional state of a user and optimizes building energy management and the operation of energy-consuming equipment. By taking user emotions into consideration, this system provides a more user-friendly interface and performance.

[0135] First, the user inputs building design information, and the server analyzes the amount of solar radiation based on this information. The server then uses local weather data to predict power generation and calculates the optimal placement of solar energy generation equipment. This maximizes power generation and enables efficient energy use.

[0136] Next, the server analyzes the surplus of generated electricity and predicts electricity sales revenue based on market prices. Users can then use this information to make energy management decisions.

[0137] Furthermore, if the user owns energy-consuming devices, especially electric vehicles, the terminal will create a charging schedule. This schedule helps with economical energy management by having the server automatically control charging during off-peak hours when electricity rates are lower.

[0138] The emotion engine recognizes the user's emotional state through user input and interaction. The server analyzes the data from the emotion engine and dynamically adjusts the operating priority of energy-consuming devices. For example, if the user is stressed, the server adjusts lighting and air conditioning settings to improve comfort. The terminal also provides an interface that responds to the user's emotional state, supporting the user in finding the system easier to use.

[0139] For example, if the emotion engine detects that a user has returned home earlier than usual and is feeling tired, the device will instruct the server to soften the lighting and play music to create a relaxing environment the moment the user arrives home. Furthermore, as energy management advice, it will suggest and notify the user of the best time to sell surplus electricity.

[0140] As a result, the present invention can improve the quality of life by providing ease of use and flexibility that takes into account the user's emotional state, in addition to effective energy management.

[0141] The following describes the processing flow.

[0142] Step 1:

[0143] The user inputs building design information into the server. This information includes the building's dimensions, location, roof slope angle, and orientation.

[0144] Step 2:

[0145] The server analyzes the input design information and retrieves solar radiation data from the relevant regional weather database. It then uses this data to simulate the annual solar radiation at specific points within the building.

[0146] Step 3:

[0147] The server calculates the optimal placement of solar energy generation equipment based on the results of solar radiation simulations. It considers the shape and orientation of the roof to generate a placement plan that maximizes power generation efficiency.

[0148] Step 4:

[0149] The server analyzes the surplus of generated electricity and predicts revenue from selling it in the market. Using electricity market price data, the server develops the most profitable electricity sales plan and reports it to the user.

[0150] Step 5:

[0151] If a user owns an energy-consuming device, such as an electric vehicle, they register the charging schedule for that device with the server.

[0152] Step 6:

[0153] The server analyzes the times of day when electricity rates are low and sets a charging schedule for energy-consuming devices. The terminal automatically controls the charging process according to the schedule and notifies the user when charging is complete.

[0154] Step 7:

[0155] The emotion engine analyzes the user's emotional state from their actions and inputs. Based on this data, the server adjusts the operational priority of energy-consuming devices and implements optimal settings to improve user comfort.

[0156] Step 8:

[0157] The device provides an interface that responds to the user's emotional state, supporting the user in operating the system more intuitively. The interface dynamically adjusts its color scheme and design to match the user's mood.

[0158] Step 9:

[0159] When the user returns home and the emotion engine detects that they are tired, the device instructs the server to change the lighting to a warmer color and play healing music to create a relaxing environment.

[0160] Step 10:

[0161] The server acquires construction progress data in real time and dynamically adjusts resource allocation as needed, thereby improving construction efficiency. This allows users to enjoy both optimal energy management and a comfortable living environment.

[0162] (Example 2)

[0163] 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."

[0164] Existing energy management systems lack the technology to optimize energy use in buildings, and in particular, they do not provide flexible control that takes into account individual emotional states. Furthermore, since the charging plans for energy-consuming devices are rarely automatically optimized to take into account lifestyle patterns and fluctuations in the electricity market, there is a need to provide a comfortable and economical environment for users.

[0165] 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.

[0166] In this invention, the server includes means for inputting building design information and analyzing solar radiation based on said information; means for optimizing the installation of energy conversion devices based on the analyzed solar radiation; means for analyzing the surplus of generated electricity and predicting income based on market value; means for recognizing an individual's emotional state and dynamically adjusting the operation priority of energy consumption devices based on that data; and means for providing an interface that adjusts the environment so that the user feels comfortable. This enables more efficient energy management and improved user comfort.

[0167] "Design information" refers to detailed data regarding the structure, layout, materials, and specifications of a building.

[0168] "Solar radiation" refers to the intensity or amount of sunlight that a particular area or building receives during a specific time period.

[0169] The term "energy conversion device" refers to any equipment used to convert natural energy into electricity.

[0170] "Surplus electricity" refers to the portion of electricity produced that is not consumed and remains unused.

[0171] "Market value" refers to the monetary value that energy and electricity have when they are bought and sold in the market.

[0172] "Energy-consuming devices" refers to all household appliances and equipment that operate using electricity.

[0173] "Emotional state" refers to the user's current psychological and emotional state, which includes stress, relaxation, happiness, etc.

[0174] "Operational priority" refers to the criteria used to determine which functions or installations should be prioritized in energy management and equipment control.

[0175] An "interface" refers to the points of contact or means of exchanging information and instructions between a system and its user.

[0176] This system is designed to optimize energy management in buildings and processes various types of information depending on its application. The following describes the hardware and software used, as well as their specific operating procedures.

[0177] Users input building design information using a terminal. This includes drawings, layout information, and material properties. The input information is sent to a server. The server refers to a weather database and analyzes the amount of solar radiation in the area. High-precision simulation software is used for this analysis.

[0178] Based on the analysis results, the server calculates the optimal placement of energy conversion devices, such as solar power panels. During this process, numerical analysis algorithms are used to adjust the arrangement to achieve maximum power generation efficiency.

[0179] For any surplus electricity produced, the server uses market data to calculate its market value and predict potential revenue. Real-time fluctuating electricity market value data is obtained from online price information services.

[0180] If a user owns a mobile device that consumes energy, the terminal automatically creates a charging schedule. The server identifies times when electricity rates are lower and sends this information to the terminal, thereby enabling efficient energy use.

[0181] Furthermore, the interface, equipped with an emotion engine, recognizes the user's emotional state through user input data and information obtained from sensors. The server dynamically optimizes the control of energy consumption devices according to the user's emotions. For example, if the user is feeling stressed, it adjusts the color temperature of the lighting to provide a relaxing environment.

[0182] For example, if the emotion engine recognizes that a user is in a specific emotional state upon returning home, the device instructs the server to provide a comfortable environment through measures such as adjusting the lighting or playing music. This can improve the user's quality of life.

[0183] An example of a prompt message could be: "Please suggest home environment settings for a user who has returned home early and is tired. Specifically, please show how to create a relaxing environment by considering lighting and music settings." This message can then be input into a generative AI model to obtain appropriate suggestions.

[0184] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0185] Step 1:

[0186] The user inputs building design information into a terminal. This input includes design drawings, layout information, and material properties. This information is transmitted from the terminal to the server in a digital format. The server analyzes the received information and registers it in a database.

[0187] Step 2:

[0188] The server retrieves meteorological data from a weather forecasting service and analyzes solar radiation. This analysis uses high-precision simulation software to calculate solar radiation that varies depending on the building's location and orientation. The inputs are meteorological data and design information, and the output is the result of the solar radiation analysis.

[0189] Step 3:

[0190] The server calculates the optimal placement of energy conversion devices based on the analysis results. The input is the analysis results of solar radiation, and the output is the optimal placement plan. This process uses an optimization algorithm to determine the placement that aims for maximum power generation efficiency.

[0191] Step 4:

[0192] The server analyzes power production data to identify surplus power. The inputs are current power consumption and generation data, and the output is the amount of surplus power. Based on this information, it references market data to predict potential revenue from sales.

[0193] Step 5:

[0194] If the user has a mobile device, the terminal manages the charging schedule. The server uses market value data to select the time of day when electricity rates are lowest and sends it to the terminal. The input is past consumption patterns and market data, and the output is an optimized charging schedule.

[0195] Step 6:

[0196] The emotion engine recognizes the user's emotional state using data from the interface and sensors. Inputs are the user's biometric information and usage data, while output is the recognized emotional state. The server dynamically changes the device's operating settings based on the emotional data.

[0197] Step 7:

[0198] The device provides an interface that responds to the user's emotional state. The input is the user's emotional state, and the output is a customized interface (e.g., lighting color adjustment or music playback). This allows the system to automatically create an environment that the user finds comfortable.

[0199] (Application Example 2)

[0200] 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 device 14 will be referred to as the "terminal."

[0201] In modern architecture, achieving both efficient energy management and improved user comfort is a crucial challenge. In particular, technologies that actively utilize users' emotional states to dynamically adjust energy consumption devices and interfaces are still not fully established. Therefore, the challenge lies in how to achieve both optimized energy efficiency and improved quality of life.

[0202] 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.

[0203] In this invention, the server includes means for inputting building configuration information and analyzing light energy based on said information, means for optimizing the placement of solar energy generators based on the analyzed light energy, and means for analyzing the user's emotional state and dynamically adjusting the operating priority of energy-consuming devices based on the emotional state. This enables efficient energy utilization and comfortable environment adjustment based on the user's emotions.

[0204] "Building structure information" refers to information related to the building's design, such as its shape, layout, materials, and design details.

[0205] "Light energy" is energy obtained from natural energy sources such as sunlight, and is converted into electricity through power generation equipment.

[0206] A "solar energy generating device" is a device that converts sunlight into electricity, and generally includes solar panels.

[0207] "User's emotional state" refers to the emotions a user is currently experiencing, and includes mental states such as stress, relaxation, and anxiety.

[0208] "Energy-consuming equipment" refers to all devices that operate using electricity, including lighting, air conditioners, and home appliances.

[0209] "Operation priority" refers to the criteria used by a system to determine the order or instructions for which devices to prioritize control under specific conditions.

[0210] "Dynamic adjustment" refers to adaptively changing system settings and operations in response to real-time data and conditions.

[0211] The system implementing this invention starts by inputting information about the building's structure. Based on this information, a server performs a light energy analysis to optimize the placement of solar power generation equipment. The analyzed data is combined with local weather information using specific software, such as an environmental data analysis tool. Furthermore, a generative AI model is used to analyze the user's emotional state. This analysis uses voice and facial expression data collected from the user and employs a machine learning platform, such as TENSORFLOW®. This makes it possible to recognize the user's emotional state and dynamically adjust the priority operation of energy-consuming equipment.

[0212] Furthermore, the device provides users with an emotionally responsive interface, presenting specific experiences and information more appropriately. For example, if a user is feeling stressed, the system adjusts the lighting to softer tones and recommends relaxing music.

[0213] As a concrete example, when a user returns home after experiencing stress at work, the system automatically adjusts various devices in the home to create a relaxing environment. A possible prompt input to the generating AI model might be: "When a user is stressed, how can we most effectively adjust their energy system?"

[0214] Thus, the present invention improves both quality of life and energy efficiency simultaneously by realizing energy management that responds to the user's emotional state.

[0215] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0216] Step 1:

[0217] The server receives building configuration information from the user. Based on this information, it imports local weather data and performs a light energy analysis. In this analysis, the software uses a simulation model to evaluate sunlight conditions and optimizes the placement of solar power generation equipment, taking into account the environmental conditions around the building. The input is building configuration information and weather data, and the output is an optimized placement plan.

[0218] Step 2:

[0219] The server uses a generative AI model to analyze the user's emotional state, taking voice and facial expression data collected from the user as input. Specifically, it employs image recognition and voice analysis technologies to perform inference processing on a machine learning platform such as TensorFlow. The emotion analysis algorithm evaluates multiple emotional states and calculates the user's stress level and happiness level in real time. The output is data related to the user's emotional state.

[0220] Step 3:

[0221] The device dynamically adjusts the operational priority of energy-consuming devices based on the results of emotion analysis. For example, if the user is feeling stressed, the artificial intelligence will improve comfort by adjusting the room lighting and optimizing the air conditioning settings. In this case, the prompt message used is, "How can we most effectively adjust the energy system when the user is feeling stressed?" The input is the user's emotional state data, and the output is the device's control signal.

[0222] Step 4:

[0223] Users receive recommended interface changes from the server, allowing them to live their daily lives in an improved, more convenient environment. For example, the system automatically adjusts lighting color and brightness, and selects and plays relaxing music to enhance user comfort. This process involves interactive system adjustments that incorporate user feedback. Inputs are operation priorities and environmental data, while output is the user's preferred settings.

[0224] 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.

[0225] 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.

[0226] 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.

[0227] [Second Embodiment]

[0228] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0229] 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.

[0230] 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).

[0231] 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.

[0232] 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.

[0233] 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).

[0234] 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.

[0235] 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.

[0236] 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.

[0237] 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.

[0238] 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.

[0239] 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".

[0240] This invention is a system that predicts solar radiation based on building design information and supports the optimal installation of solar energy generation equipment. This system enables efficient energy management of buildings and focuses particularly on optimizing solar power generation and electricity consumption.

[0241] The user provides building design information to the server. Based on this design information, the server uses historical weather data and simulation models to analyze solar radiation. Utilizing the resulting solar radiation data, the server generates a layout plan to optimize the installation of solar energy generation equipment. This optimization process takes into account factors such as roof shape, angle, and orientation, aiming to maximize power generation.

[0242] Next, the server analyzes the surplus electricity generated in accordance with market conditions and predicts revenue from selling the electricity. This prediction helps users evaluate the payback period of their investment and understand the economic benefits of the installation. It also takes into account fluctuations in electricity prices and suggests to users that they sell the surplus electricity during the most profitable time of day.

[0243] Furthermore, if the user owns energy-consuming equipment, especially electric vehicles, the terminal will create a charging schedule. This schedule is provided by the server, which selects and manages the charging process automatically, taking advantage of times when electricity rates are low. This feature can reduce energy costs and improve ease of use.

[0244] During construction work, terminals transmit progress data from the construction site to a server. The server monitors the construction status in real time and immediately adjusts resource allocation if delays occur in the schedule. In this way, the efficiency of the construction is increased, and the smooth progress of the construction is guaranteed.

[0245] As a concrete example, for a user's south-facing roof, the server analyzes solar radiation and proposes the optimal placement of power generation equipment. It also predicts that approximately 1,000 kWh of surplus electricity can be sold each month, generating an income of 50,000 yen, and notifies the user. Furthermore, the charging of electric vehicles is automated to begin at 2 AM, ensuring that the minimum charge is incurred.

[0246] Thus, the present invention can maximize the use of solar energy and achieve cost-effective energy management.

[0247] The following describes the processing flow.

[0248] Step 1:

[0249] The user inputs building design information into the server. This information includes the building's dimensions, location, roof slope angle, and orientation.

[0250] Step 2:

[0251] The server analyzes the input design information and retrieves solar radiation data from the relevant regional weather database. Based on this data, the server simulates the annual solar radiation at specific points in the building.

[0252] Step 3:

[0253] The server calculates the optimal placement of solar energy generation equipment based on the predicted amount of solar radiation. In doing so, it takes into account the shape and orientation of the roof to generate a layout plan that maximizes power generation.

[0254] Step 4:

[0255] The server provides the user with feedback on the generated optimal placement plan and asks for confirmation of the installation plan. The user approves or modifies the proposed placement and makes a final decision.

[0256] Step 5:

[0257] The server analyzes the user's power consumption patterns and uses this information to predict the revenue from selling surplus electricity generated. The server also performs electricity sales simulations that take market prices into account.

[0258] Step 6:

[0259] If the user has energy-consuming devices, the terminal shares their operating status and charging schedule with the server.

[0260] Step 7:

[0261] The server analyzes the times of day when electricity rates are lower and optimizes the charging schedule for energy-consuming devices. Based on the schedule, the devices automatically start and stop charging at the specified times.

[0262] Step 8:

[0263] The terminal reports the progress of the construction work from the site in real time and sends the data to the server.

[0264] Step 9:

[0265] The server monitors the progress of the construction and dynamically adjusts resource allocation as needed to optimize the construction schedule.

[0266] Step 10:

[0267] Users can centrally monitor the overall energy management status, electricity sales revenue, and construction status to achieve optimal energy management.

[0268] (Example 1)

[0269] 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".

[0270] In recent years, there has been a growing demand for the expanded use of renewable energy, with solar power generation attracting particular attention. However, effective installation and operation of solar power generation systems require accurate analysis of solar radiation, maximization of economic benefits, and efficient operation of power consumption equipment. Furthermore, to improve the efficiency of these processes, progress management of construction work and optimization of resource allocation are necessary. This invention aims to solve these problems.

[0271] 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.

[0272] In this invention, the server includes means for inputting building design information and analyzing the amount of sunlight based on said information, means for optimizing the placement of solar power generation equipment based on the analyzed amount of sunlight, and means for analyzing the surplus of generated electricity and predicting electricity sales profits based on market conditions. This enables optimal utilization of solar energy and maximization of economic benefits.

[0273] A "building" is a structure designed for human use, such as a residence or commercial facility.

[0274] "Design information" refers to data that shows details such as the structure, layout, shape, and orientation of a building.

[0275] "Amount of sunlight" refers to information about the intensity and duration of sunlight at a specific location.

[0276] "Solar power generation equipment" refers to equipment that converts sunlight into electricity, and includes solar panels and related facilities.

[0277] "Placement" refers to the act of arranging objects based on specific criteria, particularly the optimal location in buildings and equipment.

[0278] "Surplus electricity" refers to electricity that is not consumed and can be supplied externally.

[0279] "Market conditions" refer to the economic situation and price trends at a specific time and place.

[0280] A "consumer device" is a machine or piece of equipment that operates using electricity.

[0281] A "charging schedule" is a plan for supplying power to devices in order to ensure efficient operation of power-consuming equipment.

[0282] "Work progress" refers to the extent to which a particular project or construction work is progressing according to plan.

[0283] "Resource allocation" refers to the appropriate allocation of personnel, equipment, materials, etc. required for work or projects in appropriate proportions.

[0284] The present invention is a system for optimizing the design and operation of a solar power generation system in a building. This system has a server and a terminal as main components and operates based on input information from users.

[0285] The user provides design information to the server via the terminal. The provided design information includes the location, shape, roof angle, and azimuth of the building. Based on this design information, the server uses software such as WeatherAPI and Radiance to obtain past weather data and analyze the amount of sunlight.

[0286] Based on the analyzed amount of sunlight, the server creates a simulation model and determines the optimal arrangement of the solar power generation devices. In this arrangement determination, the roof angle and azimuth are considered so that the power generation amount is maximized. As a result, the user can efficiently proceed with the installation plan.

[0287] Next, the server analyzes the market conditions based on the available power and uses software such as OpenEnergyPlatform to predict the profit from selling electricity. This prediction result is provided to the user, and the user can use it as a basis for judgment to maximize economic benefits.

[0288] Also, when the user owns an electric vehicle as an electric power consumption device, the terminal automatically sets the charging schedule considering the time zones with low electricity rates provided by the server. In this process, charging is set to be performed at times when the electricity rate is low, such as late at night, to reduce the energy cost.

[0289] Furthermore, during the construction phase, the terminals transmit progress data acquired from the construction site to the server. The server monitors this data in real time and dynamically adjusts resource allocation according to the progress, thereby improving construction efficiency.

[0290] For example, if a user enters a prompt such as, "Please calculate the optimal installation method and economic effect of the solar power generation system in my home," the server will perform analysis and optimization according to the procedure described above and present the user with a specific installation plan and its economic effect.

[0291] In this way, this system efficiently manages the use of solar energy and provides economic value to users.

[0292] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0293] Step 1:

[0294] Users input building design information into the server via a terminal. This design information includes the building's location, roof shape, angles, and orientation. This input information is stored in the server's database and serves as the basic data for solar radiation analysis.

[0295] Step 2:

[0296] The server uses design information received from the user to acquire weather data from an external source. During this process, it collects historical weather data using the WeatherAPI and generates a simulation model using Radiance to predict the amount of sunlight at each location on the roof. The input design information and weather data are combined to calculate the predicted annual solar radiation, which is then stored in a database.

[0297] Step 3:

[0298] The server calculates the optimal placement of solar power generation equipment based on the calculated solar radiation data. This process takes into account the roof angle and orientation to maximize power generation and performs multiple placement simulations. This predicts the maximum power generation at each installation location and derives the optimal placement plan.

[0299] Step 4:

[0300] The server analyzes electricity market trends based on the optimal deployment plan and predicted power generation, and uses OpenEnergyPlatform to predict electricity sales revenue. This analysis determines the optimal timing for selling electricity based on market prices and supply volume, and calculates the resulting economic benefits. The final prediction results are notified to the user.

[0301] Step 5:

[0302] If a user owns an electric vehicle, the terminal automatically sets a charging schedule based on information about cheaper time slots obtained from the server. This process adjusts the user's power usage and power supply time, specifically targeting charging during off-peak hours when rates are lower.

[0303] Step 6:

[0304] The terminal periodically sends progress data from the construction site to the server. Based on the received progress data, the server monitors delays and problems in the construction schedule in real time and dynamically adjusts the allocation of resources and personnel as needed to support the smooth progress of the construction.

[0305] (Application Example 1)

[0306] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0307] In conventional solar power generation systems, there have been problems such as the inability to fully utilize building-specific design information and solar radiation amounts, making it difficult to achieve efficient energy generation and optimal power sales. Also, regarding the charging schedule management of energy-consuming devices such as electric vehicles, automation has been insufficient, making it difficult to optimize energy costs.

[0308] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0309] In this invention, the server includes means for analyzing the solar radiation amount based on the building design information, means for optimizing the installation of the solar power generation device based on the analysis result, and means for predicting the power sales revenue based on the market price for the surplus of the generated power. Thereby, it becomes possible to maximize the economic merits through the introduction of an optimal power generation system for each building and efficient energy management.

[0310] The "building design information" is information such as the building's structure, shape, orientation, etc., that affects the efficiency of solar power generation.

[0311] The "means for analyzing the solar radiation amount" is a technique for calculating the amount of sunlight irradiation in a specific building using past weather data and simulation models.

[0312] The "means for optimizing the installation of the solar power generation device" is a technique for installing the device in an optimal location to maximize the power generation efficiency based on the analysis result of the solar radiation amount.

[0313] The "means for predicting the power sales revenue based on the market price" is a technique for analyzing the market power price when selling the generated power and estimating the profit.

[0314] The "means for optimizing the charging schedule of the energy-consuming device" is a technique for determining the optimal time for charging in order to minimize the cost of the consumed energy.

[0315] "Means for managing the progress of construction work and dynamically adjusting resource allocation" refers to technologies that monitor the progress of construction projects in real time and make the necessary adjustments to efficiently utilize resources.

[0316] "A means of providing residents with the optimal power generation system and electricity sales strategy using smartphones" refers to a technology that analyzes power generation status and profitability to users via mobile devices and proposes appropriate strategies.

[0317] The system for implementing this invention begins with the user providing building design information to a server. The server then uses historical weather data and simulation models to perform a detailed analysis of the amount of solar radiation on the building. Based on this analysis, the server determines the optimal location for installing the solar energy generation equipment.

[0318] Next, the server analyzes the surplus of generated electricity and predicts sales revenue by comparing it with market electricity prices. This allows users to see the economic benefits of the power generation system.

[0319] Furthermore, the system also manages the charging schedules for energy-consuming devices, especially electric vehicles. The server identifies periods with lower electricity rates and automatically initiates charging, minimizing energy consumption costs.

[0320] For construction site management, terminals send construction progress data to a server, which then monitors the progress in real time. This allows for quick adjustment of resource allocation even if delays occur in the schedule.

[0321] One concrete example is an application that uses a smartphone to determine the optimal placement of solar power generation equipment to be installed on the roof of a user's home. This allows for the suggestion of a power sales strategy tailored to the characteristics of the region, enabling the user to maximize their profits.

[0322] Using a generative AI model, entering a prompt like the following will suggest the optimal installation strategy: "Generate the optimal solar power plant layout based on building design information and weather data, and calculate the economic benefits."

[0323] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0324] Step 1:

[0325] The server receives building design information entered by the user. This input includes information such as the orientation, angle, and location of the building's roof. The server uses this information to store it as basic data for analyzing the amount of solar radiation on the building.

[0326] Step 2:

[0327] The server retrieves historical weather data from a weather database and analyzes solar radiation in combination with design information. Specifically, it uses a simulation model to calculate the average solar radiation for a specific period. Based on these calculation results, it generates the data necessary to ensure maximum power generation.

[0328] Step 3:

[0329] The server uses the analyzed solar radiation data to determine the optimal location and orientation for the solar energy generation equipment. This generates a layout plan to maximize power generation. Users can receive this plan and use it in their own equipment planning.

[0330] Step 4:

[0331] The server analyzes the surplus electricity generated by the power generators and predicts electricity sales revenue by comparing it with market price data. This process obtains current market price information in real time and multiplies it with the predicted power generation value to output the expected electricity sales revenue.

[0332] Step 5:

[0333] The server optimizes the charging schedule for the user's energy-consuming devices. It automatically selects time periods with lower electricity rates and schedules the start of charging accordingly. As a result, the user achieves cost-effective and efficient energy consumption.

[0334] Step 6:

[0335] The terminal transmits progress information from the construction site to the server. The server analyzes the received progress data and adjusts the schedule and resource allocation in real time based on this analysis. This process prevents delays and ensures the project progresses efficiently.

[0336] 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.

[0337] This invention relates to a system that recognizes the emotional state of a user and optimizes building energy management and the operation of energy-consuming equipment. By taking user emotions into consideration, this system provides a more user-friendly interface and performance.

[0338] First, the user inputs building design information, and the server analyzes the amount of solar radiation based on this information. The server then uses local weather data to predict power generation and calculates the optimal placement of solar energy generation equipment. This maximizes power generation and enables efficient energy use.

[0339] Next, the server analyzes the surplus of generated electricity and predicts electricity sales revenue based on market prices. Users can then use this information to make energy management decisions.

[0340] Furthermore, if the user owns energy-consuming devices, especially electric vehicles, the terminal will create a charging schedule. This schedule helps with economical energy management by having the server automatically control charging during off-peak hours when electricity rates are lower.

[0341] The emotion engine recognizes the user's emotional state through user input and interaction. The server analyzes the data from the emotion engine and dynamically adjusts the operating priority of energy-consuming devices. For example, if the user is stressed, the server adjusts lighting and air conditioning settings to improve comfort. The terminal also provides an interface that responds to the user's emotional state, supporting the user in finding the system easier to use.

[0342] For example, if the emotion engine detects that a user has returned home earlier than usual and is feeling tired, the device will instruct the server to soften the lighting and play music to create a relaxing environment the moment the user arrives home. Furthermore, as energy management advice, it will suggest and notify the user of the best time to sell surplus electricity.

[0343] As a result, the present invention can improve the quality of life by providing ease of use and flexibility that takes into account the user's emotional state, in addition to effective energy management.

[0344] The following describes the processing flow.

[0345] Step 1:

[0346] The user inputs building design information into the server. This information includes the building's dimensions, location, roof slope angle, and orientation.

[0347] Step 2:

[0348] The server analyzes the input design information and retrieves solar radiation data from the relevant regional weather database. It then uses this data to simulate the annual solar radiation at specific points within the building.

[0349] Step 3:

[0350] The server calculates the optimal placement of solar energy generation equipment based on the results of solar radiation simulations. It considers the shape and orientation of the roof to generate a placement plan that maximizes power generation efficiency.

[0351] Step 4:

[0352] The server analyzes the surplus of generated electricity and predicts revenue from selling it in the market. Using electricity market price data, the server develops the most profitable electricity sales plan and reports it to the user.

[0353] Step 5:

[0354] If a user owns an energy-consuming device, such as an electric vehicle, they register the charging schedule for that device with the server.

[0355] Step 6:

[0356] The server analyzes the times of day when electricity rates are low and sets a charging schedule for energy-consuming devices. The terminal automatically controls the charging process according to the schedule and notifies the user when charging is complete.

[0357] Step 7:

[0358] The emotion engine analyzes the user's emotional state from their actions and inputs. Based on this data, the server adjusts the operational priority of energy-consuming devices and implements optimal settings to improve user comfort.

[0359] Step 8:

[0360] The device provides an interface that responds to the user's emotional state, supporting the user in operating the system more intuitively. The interface dynamically adjusts its color scheme and design to match the user's mood.

[0361] Step 9:

[0362] When the user returns home and the emotion engine detects that they are tired, the device instructs the server to change the lighting to a warmer color and play healing music to create a relaxing environment.

[0363] Step 10:

[0364] The server acquires construction progress data in real time and dynamically adjusts resource allocation as needed, thereby improving construction efficiency. This allows users to enjoy both optimal energy management and a comfortable living environment.

[0365] (Example 2)

[0366] 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".

[0367] Existing energy management systems lack the technology to optimize energy use in buildings, and in particular, they do not provide flexible control that takes into account individual emotional states. Furthermore, since the charging plans for energy-consuming devices are rarely automatically optimized to take into account lifestyle patterns and fluctuations in the electricity market, there is a need to provide a comfortable and economical environment for users.

[0368] 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.

[0369] In this invention, the server includes means for inputting building design information and analyzing solar radiation based on said information; means for optimizing the installation of energy conversion devices based on the analyzed solar radiation; means for analyzing the surplus of generated electricity and predicting income based on market value; means for recognizing an individual's emotional state and dynamically adjusting the operation priority of energy consumption devices based on that data; and means for providing an interface that adjusts the environment so that the user feels comfortable. This enables more efficient energy management and improved user comfort.

[0370] "Design information" refers to detailed data regarding the structure, layout, materials, and specifications of a building.

[0371] "Solar radiation" refers to the intensity or amount of sunlight that a particular area or building receives during a specific time period.

[0372] The term "energy conversion device" refers to any equipment used to convert natural energy into electricity.

[0373] "Surplus electricity" refers to the portion of electricity produced that is not consumed and remains unused.

[0374] "Market value" refers to the monetary value that energy and electricity have when they are bought and sold in the market.

[0375] "Energy-consuming devices" refers to all household appliances and equipment that operate using electricity.

[0376] "Emotional state" refers to the user's current psychological and emotional state, which includes stress, relaxation, happiness, etc.

[0377] "Operational priority" refers to the criteria used to determine which functions or installations should be prioritized in energy management and equipment control.

[0378] An "interface" refers to the points of contact or means of exchanging information and instructions between a system and its user.

[0379] This system is designed to optimize energy management in buildings and processes various types of information depending on its application. The following describes the hardware and software used, as well as their specific operating procedures.

[0380] Users input building design information using a terminal. This includes drawings, layout information, and material properties. The input information is sent to a server. The server refers to a weather database and analyzes the amount of solar radiation in the area. High-precision simulation software is used for this analysis.

[0381] Based on the analysis results, the server calculates the optimal placement of energy conversion devices, such as solar power panels. During this process, numerical analysis algorithms are used to adjust the arrangement to achieve maximum power generation efficiency.

[0382] For any surplus electricity produced, the server uses market data to calculate its market value and predict potential revenue. Real-time fluctuating electricity market value data is obtained from online price information services.

[0383] If a user owns a mobile device that consumes energy, the terminal automatically creates a charging schedule. The server identifies times when electricity rates are lower and sends this information to the terminal, thereby enabling efficient energy use.

[0384] Furthermore, the interface, equipped with an emotion engine, recognizes the user's emotional state through user input data and information obtained from sensors. The server dynamically optimizes the control of energy consumption devices according to the user's emotions. For example, if the user is feeling stressed, it adjusts the color temperature of the lighting to provide a relaxing environment.

[0385] For example, if the emotion engine recognizes that a user is in a specific emotional state upon returning home, the device instructs the server to provide a comfortable environment through measures such as adjusting the lighting or playing music. This can improve the user's quality of life.

[0386] An example of a prompt message could be: "Please suggest home environment settings for a user who has returned home early and is tired. Specifically, please show how to create a relaxing environment by considering lighting and music settings." This message can then be input into a generative AI model to obtain appropriate suggestions.

[0387] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0388] Step 1:

[0389] The user inputs building design information into a terminal. This input includes design drawings, layout information, and material properties. This information is transmitted from the terminal to the server in a digital format. The server analyzes the received information and registers it in a database.

[0390] Step 2:

[0391] The server retrieves meteorological data from a weather forecasting service and analyzes solar radiation. This analysis uses high-precision simulation software to calculate solar radiation that varies depending on the building's location and orientation. The inputs are meteorological data and design information, and the output is the result of the solar radiation analysis.

[0392] Step 3:

[0393] The server calculates the optimal placement of energy conversion devices based on the analysis results. The input is the analysis results of solar radiation, and the output is the optimal placement plan. This process uses an optimization algorithm to determine the placement that aims for maximum power generation efficiency.

[0394] Step 4:

[0395] The server analyzes power production data to identify surplus power. The inputs are current power consumption and generation data, and the output is the amount of surplus power. Based on this information, it references market data to predict potential revenue from sales.

[0396] Step 5:

[0397] If the user has a mobile device, the terminal manages the charging schedule. The server uses market value data to select the time of day when electricity rates are lowest and sends it to the terminal. The input is past consumption patterns and market data, and the output is an optimized charging schedule.

[0398] Step 6:

[0399] The emotion engine recognizes the user's emotional state using data from the interface and sensors. Inputs are the user's biometric information and usage data, while output is the recognized emotional state. The server dynamically changes the device's operating settings based on the emotional data.

[0400] Step 7:

[0401] The device provides an interface that responds to the user's emotional state. The input is the user's emotional state, and the output is a customized interface (e.g., lighting color adjustment or music playback). This allows the system to automatically create an environment that the user finds comfortable.

[0402] (Application Example 2)

[0403] 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 will be referred to as the "terminal."

[0404] In modern architecture, achieving both efficient energy management and improved user comfort is a crucial challenge. In particular, technologies that actively utilize users' emotional states to dynamically adjust energy consumption devices and interfaces are still not fully established. Therefore, the challenge lies in how to achieve both optimized energy efficiency and improved quality of life.

[0405] 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.

[0406] In this invention, the server includes means for inputting building configuration information and analyzing light energy based on said information, means for optimizing the placement of solar energy generators based on the analyzed light energy, and means for analyzing the user's emotional state and dynamically adjusting the operating priority of energy-consuming devices based on the emotional state. This enables efficient energy utilization and comfortable environment adjustment based on the user's emotions.

[0407] "Building structure information" refers to information related to the building's design, such as its shape, layout, materials, and design details.

[0408] "Light energy" is energy obtained from natural energy sources such as sunlight, and is converted into electricity through power generation equipment.

[0409] A "solar energy generating device" is a device that converts sunlight into electricity, and generally includes solar panels.

[0410] "User's emotional state" refers to the emotions a user is currently experiencing, and includes mental states such as stress, relaxation, and anxiety.

[0411] "Energy-consuming equipment" refers to all devices that operate using electricity, including lighting, air conditioners, and home appliances.

[0412] "Operation priority" refers to the criteria used by a system to determine the order or instructions for which devices to prioritize control under specific conditions.

[0413] "Dynamic adjustment" refers to adaptively changing system settings and operations in response to real-time data and conditions.

[0414] The system implementing this invention starts by inputting information about the building's structure. Based on this information, a server performs a light energy analysis to optimize the placement of solar power generation equipment. The analyzed data is combined with local weather information using specific software, such as an environmental data analysis tool. Furthermore, a generative AI model is used to analyze the user's emotional state. This analysis uses voice and facial expression data collected from the user and employs a machine learning platform, such as TensorFlow. This makes it possible to recognize the user's emotional state and dynamically adjust the priority operation of energy-consuming equipment.

[0415] Furthermore, the device provides users with an emotionally responsive interface, presenting specific experiences and information more appropriately. For example, if a user is feeling stressed, the system adjusts the lighting to softer tones and recommends relaxing music.

[0416] As a concrete example, when a user returns home after experiencing stress at work, the system automatically adjusts various devices in the home to create a relaxing environment. A possible prompt input to the generating AI model might be: "When a user is stressed, how can we most effectively adjust their energy system?"

[0417] Thus, the present invention improves both quality of life and energy efficiency simultaneously by realizing energy management that responds to the user's emotional state.

[0418] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0419] Step 1:

[0420] The server receives building configuration information from the user. Based on this information, it imports local weather data and performs a light energy analysis. In this analysis, the software uses a simulation model to evaluate sunlight conditions and optimizes the placement of solar power generation equipment, taking into account the environmental conditions around the building. The input is building configuration information and weather data, and the output is an optimized placement plan.

[0421] Step 2:

[0422] The server uses a generative AI model to analyze the user's emotional state, taking voice and facial expression data collected from the user as input. Specifically, it employs image recognition and voice analysis technologies to perform inference processing on a machine learning platform such as TensorFlow. The emotion analysis algorithm evaluates multiple emotional states and calculates the user's stress level and happiness level in real time. The output is data related to the user's emotional state.

[0423] Step 3:

[0424] The device dynamically adjusts the operational priority of energy-consuming devices based on the results of emotion analysis. For example, if the user is feeling stressed, the artificial intelligence will improve comfort by adjusting the room lighting and optimizing the air conditioning settings. In this case, the prompt message used is, "How can we most effectively adjust the energy system when the user is feeling stressed?" The input is the user's emotional state data, and the output is the device's control signal.

[0425] Step 4:

[0426] Users receive recommended interface changes from the server, allowing them to live their daily lives in an improved, more convenient environment. For example, the system automatically adjusts lighting color and brightness, and selects and plays relaxing music to enhance user comfort. This process involves interactive system adjustments that incorporate user feedback. Inputs are operation priorities and environmental data, while output is the user's preferred settings.

[0427] 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.

[0428] 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.

[0429] 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.

[0430] [Third Embodiment]

[0431] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0432] 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.

[0433] 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).

[0434] 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.

[0435] 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.

[0436] 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).

[0437] 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.

[0438] 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.

[0439] 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.

[0440] 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.

[0441] 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.

[0442] 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".

[0443] This invention is a system that predicts solar radiation based on building design information and supports the optimal installation of solar energy generation equipment. This system enables efficient energy management of buildings and focuses particularly on optimizing solar power generation and electricity consumption.

[0444] The user provides building design information to the server. Based on this design information, the server uses historical weather data and simulation models to analyze solar radiation. Utilizing the resulting solar radiation data, the server generates a layout plan to optimize the installation of solar energy generation equipment. This optimization process takes into account factors such as roof shape, angle, and orientation, aiming to maximize power generation.

[0445] Next, the server analyzes the surplus electricity generated in accordance with market conditions and predicts revenue from selling the electricity. This prediction helps users evaluate the payback period of their investment and understand the economic benefits of the installation. It also takes into account fluctuations in electricity prices and suggests to users that they sell the surplus electricity during the most profitable time of day.

[0446] Furthermore, if the user owns energy-consuming equipment, especially electric vehicles, the terminal will create a charging schedule. This schedule is provided by the server, which selects and manages the charging process automatically, taking advantage of times when electricity rates are low. This feature can reduce energy costs and improve ease of use.

[0447] During construction work, terminals transmit progress data from the construction site to a server. The server monitors the construction status in real time and immediately adjusts resource allocation if delays occur in the schedule. In this way, the efficiency of the construction is increased, and the smooth progress of the construction is guaranteed.

[0448] As a concrete example, for a user's south-facing roof, the server analyzes solar radiation and proposes the optimal placement of power generation equipment. It also predicts that approximately 1,000 kWh of surplus electricity can be sold each month, generating an income of 50,000 yen, and notifies the user. Furthermore, the charging of electric vehicles is automated to begin at 2 AM, ensuring that the minimum charge is incurred.

[0449] Thus, the present invention can maximize the use of solar energy and achieve cost-effective energy management.

[0450] The following describes the processing flow.

[0451] Step 1:

[0452] The user inputs building design information into the server. This information includes the building's dimensions, location, roof slope angle, and orientation.

[0453] Step 2:

[0454] The server analyzes the input design information and retrieves solar radiation data from the relevant regional weather database. Based on this data, the server simulates the annual solar radiation at specific points in the building.

[0455] Step 3:

[0456] The server calculates the optimal placement of solar energy generation equipment based on the predicted amount of solar radiation. In doing so, it takes into account the shape and orientation of the roof to generate a layout plan that maximizes power generation.

[0457] Step 4:

[0458] The server provides the user with feedback on the generated optimal placement plan and asks for confirmation of the installation plan. The user approves or modifies the proposed placement and makes a final decision.

[0459] Step 5:

[0460] The server analyzes the user's power consumption patterns and uses this information to predict the revenue from selling surplus electricity generated. The server also performs electricity sales simulations that take market prices into account.

[0461] Step 6:

[0462] If the user has energy-consuming devices, the terminal shares their operating status and charging schedule with the server.

[0463] Step 7:

[0464] The server analyzes the times of day when electricity rates are lower and optimizes the charging schedule for energy-consuming devices. Based on the schedule, the devices automatically start and stop charging at the specified times.

[0465] Step 8:

[0466] The terminal reports the progress of the construction work from the site in real time and sends the data to the server.

[0467] Step 9:

[0468] The server monitors the progress of the construction and dynamically adjusts resource allocation as needed to optimize the construction schedule.

[0469] Step 10:

[0470] Users can centrally monitor the overall energy management status, electricity sales revenue, and construction status to achieve optimal energy management.

[0471] (Example 1)

[0472] 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."

[0473] In recent years, there has been a growing demand for the expanded use of renewable energy, with solar power generation attracting particular attention. However, effective installation and operation of solar power generation systems require accurate analysis of solar radiation, maximization of economic benefits, and efficient operation of power consumption equipment. Furthermore, to improve the efficiency of these processes, progress management of construction work and optimization of resource allocation are necessary. This invention aims to solve these problems.

[0474] 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.

[0475] In this invention, the server includes means for inputting building design information and analyzing the amount of sunlight based on said information, means for optimizing the placement of solar power generation equipment based on the analyzed amount of sunlight, and means for analyzing the surplus of generated electricity and predicting electricity sales profits based on market conditions. This enables optimal utilization of solar energy and maximization of economic benefits.

[0476] A "building" is a structure designed for human use, such as a residence or commercial facility.

[0477] "Design information" refers to data that shows details such as the structure, layout, shape, and orientation of a building.

[0478] "Amount of sunlight" refers to information about the intensity and duration of sunlight at a specific location.

[0479] "Solar power generation equipment" refers to equipment that converts sunlight into electricity, and includes solar panels and related facilities.

[0480] "Placement" refers to the act of arranging objects based on specific criteria, particularly the optimal location in buildings and equipment.

[0481] "Surplus electricity" refers to electricity that is not consumed and can be supplied externally.

[0482] "Market conditions" refer to the economic situation and price trends at a specific time and place.

[0483] A "consumer device" is a machine or piece of equipment that operates using electricity.

[0484] A "charging schedule" is a plan for supplying power to devices in order to ensure efficient operation of power-consuming equipment.

[0485] "Work progress" refers to the extent to which a particular project or construction work is progressing according to plan.

[0486] "Resource allocation" refers to the appropriate distribution of personnel, equipment, materials, and other resources necessary for a task or project.

[0487] This invention relates to a system for optimizing the design and operation of solar power generation systems in buildings. This system consists of a server and terminals as its main components and operates based on user input information.

[0488] The user provides design information to the server via their terminal. This information includes the building's location, shape, roof angle, and orientation. Based on this design information, the server uses software such as WeatherAPI and Radiance to acquire historical weather data and analyze the amount of sunlight.

[0489] The server creates a simulation model based on the analyzed amount of sunlight and determines the optimal placement of the solar power generation equipment. This placement decision takes into account the roof angle and orientation to maximize power generation. This allows users to efficiently proceed with their installation planning.

[0490] Next, the server analyzes market conditions based on the amount of electricity that can be generated and uses software such as OpenEnergyPlatform to predict the profits from selling the electricity. These predictions are provided to the user, who can use them to make decisions that maximize their economic benefits.

[0491] Furthermore, if a user owns an electric vehicle as a power-consuming device, the terminal automatically sets a charging schedule considering the off-peak hours offered by the server. This process is designed to charge during off-peak hours when electricity rates are low, such as late at night, thereby reducing energy costs.

[0492] Furthermore, during the construction phase, the terminals transmit progress data acquired from the construction site to the server. The server monitors this data in real time and dynamically adjusts resource allocation according to the progress, thereby improving construction efficiency.

[0493] For example, if a user enters a prompt such as, "Please calculate the optimal installation method and economic effect of the solar power generation system in my home," the server will perform analysis and optimization according to the procedure described above and present the user with a specific installation plan and its economic effect.

[0494] In this way, this system efficiently manages the use of solar energy and provides economic value to users.

[0495] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0496] Step 1:

[0497] Users input building design information into the server via a terminal. This design information includes the building's location, roof shape, angles, and orientation. This input information is stored in the server's database and serves as the basic data for solar radiation analysis.

[0498] Step 2:

[0499] The server uses design information received from the user to acquire weather data from an external source. During this process, it collects historical weather data using the WeatherAPI and generates a simulation model using Radiance to predict the amount of sunlight at each location on the roof. The input design information and weather data are combined to calculate the predicted annual solar radiation, which is then stored in a database.

[0500] Step 3:

[0501] The server calculates the optimal placement of solar power generation equipment based on the calculated solar radiation data. This process takes into account the roof angle and orientation to maximize power generation and performs multiple placement simulations. This predicts the maximum power generation at each installation location and derives the optimal placement plan.

[0502] Step 4:

[0503] The server analyzes electricity market trends based on the optimal deployment plan and predicted power generation, and uses OpenEnergyPlatform to predict electricity sales revenue. This analysis determines the optimal timing for selling electricity based on market prices and supply volume, and calculates the resulting economic benefits. The final prediction results are notified to the user.

[0504] Step 5:

[0505] If a user owns an electric vehicle, the terminal automatically sets a charging schedule based on information about cheaper time slots obtained from the server. This process adjusts the user's power usage and power supply time, specifically targeting charging during off-peak hours when rates are lower.

[0506] Step 6:

[0507] The terminal periodically sends progress data from the construction site to the server. Based on the received progress data, the server monitors delays and problems in the construction schedule in real time and dynamically adjusts the allocation of resources and personnel as needed to support the smooth progress of the construction.

[0508] (Application Example 1)

[0509] 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."

[0510] Conventional solar energy generation systems have faced challenges in efficiently generating energy and optimizing electricity sales because they cannot fully utilize the design information and solar radiation data specific to each building. Furthermore, the automation of charging schedule management for energy-consuming devices such as electric vehicles is insufficient, making it difficult to optimize energy costs.

[0511] 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.

[0512] In this invention, the server includes means for analyzing solar radiation based on building design information, means for optimizing the installation of a solar energy generation system based on the analysis results, and means for predicting revenue from selling surplus generated electricity based on market prices. This makes it possible to introduce an optimal power generation system for each building and maximize economic benefits through efficient energy management.

[0513] "Building design information" refers to information that affects the efficiency of solar power generation, such as the building's structure, shape, and orientation.

[0514] "Methods for analyzing solar radiation" refer to techniques that use historical weather data and simulation models to calculate the amount of sunlight irradiating a specific building.

[0515] "Methods for optimizing the installation of solar energy generation equipment" refers to technologies for installing equipment in the optimal location to maximize power generation efficiency, based on the results of solar radiation analysis.

[0516] "Methods for predicting electricity sales revenue based on market prices" refer to techniques that analyze the market price of electricity when selling generated electricity and estimate the revenue.

[0517] "Means for optimizing the charging schedule of energy-consuming devices" refers to technologies that determine the optimal time for charging in order to minimize the cost of energy consumption.

[0518] "Means for managing the progress of construction work and dynamically adjusting resource allocation" refers to technologies that monitor the progress of construction projects in real time and make the necessary adjustments to efficiently utilize resources.

[0519] "A means of providing residents with the optimal power generation system and electricity sales strategy using smartphones" refers to a technology that analyzes power generation status and profitability to users via mobile devices and proposes appropriate strategies.

[0520] The system for implementing this invention begins with the user providing building design information to a server. The server then uses historical weather data and simulation models to perform a detailed analysis of the amount of solar radiation on the building. Based on this analysis, the server determines the optimal location for installing the solar energy generation equipment.

[0521] Next, the server analyzes the surplus of generated electricity and predicts sales revenue by comparing it with market electricity prices. This allows users to see the economic benefits of the power generation system.

[0522] Furthermore, the system also manages the charging schedules for energy-consuming devices, especially electric vehicles. The server identifies periods with lower electricity rates and automatically initiates charging, minimizing energy consumption costs.

[0523] For construction site management, terminals send construction progress data to a server, which then monitors the progress in real time. This allows for quick adjustment of resource allocation even if delays occur in the schedule.

[0524] One concrete example is an application that uses a smartphone to determine the optimal placement of solar power generation equipment to be installed on the roof of a user's home. This allows for the suggestion of a power sales strategy tailored to the characteristics of the region, enabling the user to maximize their profits.

[0525] Using a generative AI model, entering a prompt like the following will suggest the optimal installation strategy: "Generate the optimal solar power plant layout based on building design information and weather data, and calculate the economic benefits."

[0526] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0527] Step 1:

[0528] The server receives building design information entered by the user. This input includes information such as the orientation, angle, and location of the building's roof. The server uses this information to store it as basic data for analyzing the amount of solar radiation on the building.

[0529] Step 2:

[0530] The server retrieves historical weather data from a weather database and analyzes solar radiation in combination with design information. Specifically, it uses a simulation model to calculate the average solar radiation for a specific period. Based on these calculation results, it generates the data necessary to ensure maximum power generation.

[0531] Step 3:

[0532] The server uses the analyzed solar radiation data to determine the optimal location and orientation for the solar energy generation equipment. This generates a layout plan to maximize power generation. Users can receive this plan and use it in their own equipment planning.

[0533] Step 4:

[0534] The server analyzes the surplus electricity generated by the power generators and predicts electricity sales revenue by comparing it with market price data. This process obtains current market price information in real time and multiplies it with the predicted power generation value to output the expected electricity sales revenue.

[0535] Step 5:

[0536] The server optimizes the charging schedule for the user's energy-consuming devices. It automatically selects time periods with lower electricity rates and schedules the start of charging accordingly. As a result, the user achieves cost-effective and efficient energy consumption.

[0537] Step 6:

[0538] The terminal transmits progress information from the construction site to the server. The server analyzes the received progress data and adjusts the schedule and resource allocation in real time based on this analysis. This process prevents delays and ensures the project progresses efficiently.

[0539] 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.

[0540] This invention relates to a system that recognizes the emotional state of a user and optimizes building energy management and the operation of energy-consuming equipment. By taking user emotions into consideration, this system provides a more user-friendly interface and performance.

[0541] First, the user inputs building design information, and the server analyzes the amount of solar radiation based on this information. The server then uses local weather data to predict power generation and calculates the optimal placement of solar energy generation equipment. This maximizes power generation and enables efficient energy use.

[0542] Next, the server analyzes the surplus of generated electricity and predicts electricity sales revenue based on market prices. Users can then use this information to make energy management decisions.

[0543] Furthermore, if the user owns energy-consuming devices, especially electric vehicles, the terminal will create a charging schedule. This schedule helps with economical energy management by having the server automatically control charging during off-peak hours when electricity rates are lower.

[0544] The emotion engine recognizes the user's emotional state through user input and interaction. The server analyzes the data from the emotion engine and dynamically adjusts the operating priority of energy-consuming devices. For example, if the user is stressed, the server adjusts lighting and air conditioning settings to improve comfort. The terminal also provides an interface that responds to the user's emotional state, supporting the user in finding the system easier to use.

[0545] For example, if the emotion engine detects that a user has returned home earlier than usual and is feeling tired, the device will instruct the server to soften the lighting and play music to create a relaxing environment the moment the user arrives home. Furthermore, as energy management advice, it will suggest and notify the user of the best time to sell surplus electricity.

[0546] As a result, the present invention can improve the quality of life by providing ease of use and flexibility that takes into account the user's emotional state, in addition to effective energy management.

[0547] The following describes the processing flow.

[0548] Step 1:

[0549] The user inputs building design information into the server. This information includes the building's dimensions, location, roof slope angle, and orientation.

[0550] Step 2:

[0551] The server analyzes the input design information and retrieves solar radiation data from the relevant regional weather database. It then uses this data to simulate the annual solar radiation at specific points within the building.

[0552] Step 3:

[0553] The server calculates the optimal placement of solar energy generation equipment based on the results of solar radiation simulations. It considers the shape and orientation of the roof to generate a placement plan that maximizes power generation efficiency.

[0554] Step 4:

[0555] The server analyzes the surplus of generated electricity and predicts revenue from selling it in the market. Using electricity market price data, the server develops the most profitable electricity sales plan and reports it to the user.

[0556] Step 5:

[0557] If a user owns an energy-consuming device, such as an electric vehicle, they register the charging schedule for that device with the server.

[0558] Step 6:

[0559] The server analyzes the times of day when electricity rates are low and sets a charging schedule for energy-consuming devices. The terminal automatically controls the charging process according to the schedule and notifies the user when charging is complete.

[0560] Step 7:

[0561] The emotion engine analyzes the user's emotional state from their actions and inputs. Based on this data, the server adjusts the operational priority of energy-consuming devices and implements optimal settings to improve user comfort.

[0562] Step 8:

[0563] The device provides an interface that responds to the user's emotional state, supporting the user in operating the system more intuitively. The interface dynamically adjusts its color scheme and design to match the user's mood.

[0564] Step 9:

[0565] When the user returns home and the emotion engine detects that they are tired, the device instructs the server to change the lighting to a warmer color and play healing music to create a relaxing environment.

[0566] Step 10:

[0567] The server acquires construction progress data in real time and dynamically adjusts resource allocation as needed, thereby improving construction efficiency. This allows users to enjoy both optimal energy management and a comfortable living environment.

[0568] (Example 2)

[0569] 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."

[0570] Existing energy management systems lack the technology to optimize energy use in buildings, and in particular, they do not provide flexible control that takes into account individual emotional states. Furthermore, since the charging plans for energy-consuming devices are rarely automatically optimized to take into account lifestyle patterns and fluctuations in the electricity market, there is a need to provide a comfortable and economical environment for users.

[0571] 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.

[0572] In this invention, the server includes means for inputting building design information and analyzing solar radiation based on said information; means for optimizing the installation of energy conversion devices based on the analyzed solar radiation; means for analyzing the surplus of generated electricity and predicting income based on market value; means for recognizing an individual's emotional state and dynamically adjusting the operation priority of energy consumption devices based on that data; and means for providing an interface that adjusts the environment so that the user feels comfortable. This enables more efficient energy management and improved user comfort.

[0573] "Design information" refers to detailed data regarding the structure, layout, materials, and specifications of a building.

[0574] "Solar radiation" refers to the intensity or amount of sunlight that a particular area or building receives during a specific time period.

[0575] The term "energy conversion device" refers to any equipment used to convert natural energy into electricity.

[0576] "Surplus electricity" refers to the portion of electricity produced that is not consumed and remains unused.

[0577] "Market value" refers to the monetary value that energy and electricity have when they are bought and sold in the market.

[0578] "Energy-consuming devices" refers to all household appliances and equipment that operate using electricity.

[0579] "Emotional state" refers to the user's current psychological and emotional state, which includes stress, relaxation, happiness, etc.

[0580] "Operational priority" refers to the criteria used to determine which functions or installations should be prioritized in energy management and equipment control.

[0581] An "interface" refers to the points of contact or means of exchanging information and instructions between a system and its user.

[0582] This system is designed to optimize energy management in buildings and processes various types of information depending on its application. The following describes the hardware and software used, as well as their specific operating procedures.

[0583] Users input building design information using a terminal. This includes drawings, layout information, and material properties. The input information is sent to a server. The server refers to a weather database and analyzes the amount of solar radiation in the area. High-precision simulation software is used for this analysis.

[0584] Based on the analysis results, the server calculates the optimal placement of energy conversion devices, such as solar power panels. During this process, numerical analysis algorithms are used to adjust the arrangement to achieve maximum power generation efficiency.

[0585] For any surplus electricity produced, the server uses market data to calculate its market value and predict potential revenue. Real-time fluctuating electricity market value data is obtained from online price information services.

[0586] If a user owns a mobile device that consumes energy, the terminal automatically creates a charging schedule. The server identifies times when electricity rates are lower and sends this information to the terminal, thereby enabling efficient energy use.

[0587] Furthermore, the interface, equipped with an emotion engine, recognizes the user's emotional state through user input data and information obtained from sensors. The server dynamically optimizes the control of energy consumption devices according to the user's emotions. For example, if the user is feeling stressed, it adjusts the color temperature of the lighting to provide a relaxing environment.

[0588] For example, if the emotion engine recognizes that a user is in a specific emotional state upon returning home, the device instructs the server to provide a comfortable environment through measures such as adjusting the lighting or playing music. This can improve the user's quality of life.

[0589] An example of a prompt message could be: "Please suggest home environment settings for a user who has returned home early and is tired. Specifically, please show how to create a relaxing environment by considering lighting and music settings." This message can then be input into a generative AI model to obtain appropriate suggestions.

[0590] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0591] Step 1:

[0592] The user inputs building design information into a terminal. This input includes design drawings, layout information, and material properties. This information is transmitted from the terminal to the server in a digital format. The server analyzes the received information and registers it in a database.

[0593] Step 2:

[0594] The server retrieves meteorological data from a weather forecasting service and analyzes solar radiation. This analysis uses high-precision simulation software to calculate solar radiation that varies depending on the building's location and orientation. The inputs are meteorological data and design information, and the output is the result of the solar radiation analysis.

[0595] Step 3:

[0596] The server calculates the optimal placement of energy conversion devices based on the analysis results. The input is the analysis results of solar radiation, and the output is the optimal placement plan. This process uses an optimization algorithm to determine the placement that aims for maximum power generation efficiency.

[0597] Step 4:

[0598] The server analyzes power production data to identify surplus power. The inputs are current power consumption and generation data, and the output is the amount of surplus power. Based on this information, it references market data to predict potential revenue from sales.

[0599] Step 5:

[0600] If the user has a mobile device, the terminal manages the charging schedule. The server uses market value data to select the time of day when electricity rates are lowest and sends it to the terminal. The input is past consumption patterns and market data, and the output is an optimized charging schedule.

[0601] Step 6:

[0602] The emotion engine recognizes the user's emotional state using data from the interface and sensors. Inputs are the user's biometric information and usage data, while output is the recognized emotional state. The server dynamically changes the device's operating settings based on the emotional data.

[0603] Step 7:

[0604] The device provides an interface that responds to the user's emotional state. The input is the user's emotional state, and the output is a customized interface (e.g., lighting color adjustment or music playback). This allows the system to automatically create an environment that the user finds comfortable.

[0605] (Application Example 2)

[0606] 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."

[0607] In modern architecture, achieving both efficient energy management and improved user comfort is a crucial challenge. In particular, technologies that actively utilize users' emotional states to dynamically adjust energy consumption devices and interfaces are still not fully established. Therefore, the challenge lies in how to achieve both optimized energy efficiency and improved quality of life.

[0608] 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.

[0609] In this invention, the server includes means for inputting building configuration information and analyzing light energy based on said information, means for optimizing the placement of solar energy generators based on the analyzed light energy, and means for analyzing the user's emotional state and dynamically adjusting the operating priority of energy-consuming devices based on the emotional state. This enables efficient energy utilization and comfortable environment adjustment based on the user's emotions.

[0610] "Building structure information" refers to information related to the building's design, such as its shape, layout, materials, and design details.

[0611] "Light energy" is energy obtained from natural energy sources such as sunlight, and is converted into electricity through power generation equipment.

[0612] A "solar energy generating device" is a device that converts sunlight into electricity, and generally includes solar panels.

[0613] "User's emotional state" refers to the emotions a user is currently experiencing, and includes mental states such as stress, relaxation, and anxiety.

[0614] "Energy-consuming equipment" refers to all devices that operate using electricity, including lighting, air conditioners, and home appliances.

[0615] "Operation priority" refers to the criteria used by a system to determine the order or instructions for which devices to prioritize control under specific conditions.

[0616] "Dynamic adjustment" refers to adaptively changing system settings and operations in response to real-time data and conditions.

[0617] The system implementing this invention starts by inputting information about the building's structure. Based on this information, a server performs a light energy analysis to optimize the placement of solar power generation equipment. The analyzed data is combined with local weather information using specific software, such as an environmental data analysis tool. Furthermore, a generative AI model is used to analyze the user's emotional state. This analysis uses voice and facial expression data collected from the user and employs a machine learning platform, such as TensorFlow. This makes it possible to recognize the user's emotional state and dynamically adjust the priority operation of energy-consuming equipment.

[0618] Furthermore, the device provides users with an emotionally responsive interface, presenting specific experiences and information more appropriately. For example, if a user is feeling stressed, the system adjusts the lighting to softer tones and recommends relaxing music.

[0619] As a concrete example, when a user returns home after experiencing stress at work, the system automatically adjusts various devices in the home to create a relaxing environment. A possible prompt input to the generating AI model might be: "When a user is stressed, how can we most effectively adjust their energy system?"

[0620] Thus, the present invention improves both quality of life and energy efficiency simultaneously by realizing energy management that responds to the user's emotional state.

[0621] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0622] Step 1:

[0623] The server receives building configuration information from the user. Based on this information, it imports local weather data and performs a light energy analysis. In this analysis, the software uses a simulation model to evaluate sunlight conditions and optimizes the placement of solar power generation equipment, taking into account the environmental conditions around the building. The input is building configuration information and weather data, and the output is an optimized placement plan.

[0624] Step 2:

[0625] The server uses a generative AI model to analyze the user's emotional state, taking voice and facial expression data collected from the user as input. Specifically, it employs image recognition and voice analysis technologies to perform inference processing on a machine learning platform such as TensorFlow. The emotion analysis algorithm evaluates multiple emotional states and calculates the user's stress level and happiness level in real time. The output is data related to the user's emotional state.

[0626] Step 3:

[0627] The device dynamically adjusts the operational priority of energy-consuming devices based on the results of emotion analysis. For example, if the user is feeling stressed, the artificial intelligence will improve comfort by adjusting the room lighting and optimizing the air conditioning settings. In this case, the prompt message used is, "How can we most effectively adjust the energy system when the user is feeling stressed?" The input is the user's emotional state data, and the output is the device's control signal.

[0628] Step 4:

[0629] Users receive recommended interface changes from the server, allowing them to live their daily lives in an improved, more convenient environment. For example, the system automatically adjusts lighting color and brightness, and selects and plays relaxing music to enhance user comfort. This process involves interactive system adjustments that incorporate user feedback. Inputs are operation priorities and environmental data, while output is the user's preferred settings.

[0630] 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.

[0631] 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.

[0632] 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.

[0633] [Fourth Embodiment]

[0634] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0635] 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.

[0636] 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).

[0637] 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.

[0638] 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.

[0639] 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).

[0640] 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.

[0641] 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.

[0642] 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.

[0643] 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.

[0644] 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.

[0645] 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.

[0646] 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".

[0647] This invention is a system that predicts solar radiation based on building design information and supports the optimal installation of solar energy generation equipment. This system enables efficient energy management of buildings and focuses particularly on optimizing solar power generation and electricity consumption.

[0648] The user provides building design information to the server. Based on this design information, the server uses historical weather data and simulation models to analyze solar radiation. Utilizing the resulting solar radiation data, the server generates a layout plan to optimize the installation of solar energy generation equipment. This optimization process takes into account factors such as roof shape, angle, and orientation, aiming to maximize power generation.

[0649] Next, the server analyzes the surplus electricity generated in accordance with market conditions and predicts revenue from selling the electricity. This prediction helps users evaluate the payback period of their investment and understand the economic benefits of the installation. It also takes into account fluctuations in electricity prices and suggests to users that they sell the surplus electricity during the most profitable time of day.

[0650] Furthermore, if the user owns energy-consuming equipment, especially electric vehicles, the terminal will create a charging schedule. This schedule is provided by the server, which selects and manages the charging process automatically, taking advantage of times when electricity rates are low. This feature can reduce energy costs and improve ease of use.

[0651] During construction work, terminals transmit progress data from the construction site to a server. The server monitors the construction status in real time and immediately adjusts resource allocation if delays occur in the schedule. In this way, the efficiency of the construction is increased, and the smooth progress of the construction is guaranteed.

[0652] As a concrete example, for a user's south-facing roof, the server analyzes solar radiation and proposes the optimal placement of power generation equipment. It also predicts that approximately 1,000 kWh of surplus electricity can be sold each month, generating an income of 50,000 yen, and notifies the user. Furthermore, the charging of electric vehicles is automated to begin at 2 AM, ensuring that the minimum charge is incurred.

[0653] Thus, the present invention can maximize the use of solar energy and achieve cost-effective energy management.

[0654] The following describes the processing flow.

[0655] Step 1:

[0656] The user inputs building design information into the server. This information includes the building's dimensions, location, roof slope angle, and orientation.

[0657] Step 2:

[0658] The server analyzes the input design information and retrieves solar radiation data from the relevant regional weather database. Based on this data, the server simulates the annual solar radiation at specific points in the building.

[0659] Step 3:

[0660] The server calculates the optimal placement of solar energy generation equipment based on the predicted amount of solar radiation. In doing so, it takes into account the shape and orientation of the roof to generate a layout plan that maximizes power generation.

[0661] Step 4:

[0662] The server provides the user with feedback on the generated optimal placement plan and asks for confirmation of the installation plan. The user approves or modifies the proposed placement and makes a final decision.

[0663] Step 5:

[0664] The server analyzes the user's power consumption patterns and uses this information to predict the revenue from selling surplus electricity generated. The server also performs electricity sales simulations that take market prices into account.

[0665] Step 6:

[0666] If the user has energy-consuming devices, the terminal shares their operating status and charging schedule with the server.

[0667] Step 7:

[0668] The server analyzes the times of day when electricity rates are lower and optimizes the charging schedule for energy-consuming devices. Based on the schedule, the devices automatically start and stop charging at the specified times.

[0669] Step 8:

[0670] The terminal reports the progress of the construction work from the site in real time and sends the data to the server.

[0671] Step 9:

[0672] The server monitors the progress of the construction and dynamically adjusts resource allocation as needed to optimize the construction schedule.

[0673] Step 10:

[0674] Users can centrally monitor the overall energy management status, electricity sales revenue, and construction status to achieve optimal energy management.

[0675] (Example 1)

[0676] 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".

[0677] In recent years, there has been a growing demand for the expanded use of renewable energy, with solar power generation attracting particular attention. However, effective installation and operation of solar power generation systems require accurate analysis of solar radiation, maximization of economic benefits, and efficient operation of power consumption equipment. Furthermore, to improve the efficiency of these processes, progress management of construction work and optimization of resource allocation are necessary. This invention aims to solve these problems.

[0678] 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.

[0679] In this invention, the server includes means for inputting building design information and analyzing the amount of sunlight based on said information, means for optimizing the placement of solar power generation equipment based on the analyzed amount of sunlight, and means for analyzing the surplus of generated electricity and predicting electricity sales profits based on market conditions. This enables optimal utilization of solar energy and maximization of economic benefits.

[0680] A "building" is a structure designed for human use, such as a residence or commercial facility.

[0681] "Design information" refers to data that shows details such as the structure, layout, shape, and orientation of a building.

[0682] "Amount of sunlight" refers to information about the intensity and duration of sunlight at a specific location.

[0683] "Solar power generation equipment" refers to equipment that converts sunlight into electricity, and includes solar panels and related facilities.

[0684] "Placement" refers to the act of arranging objects based on specific criteria, particularly the optimal location in buildings and equipment.

[0685] "Surplus electricity" refers to electricity that is not consumed and can be supplied externally.

[0686] "Market conditions" refer to the economic situation and price trends at a specific time and place.

[0687] A "consumer device" is a machine or piece of equipment that operates using electricity.

[0688] A "charging schedule" is a plan for supplying power to devices in order to ensure efficient operation of power-consuming equipment.

[0689] "Work progress" refers to the extent to which a particular project or construction work is progressing according to plan.

[0690] "Resource allocation" refers to the appropriate distribution of personnel, equipment, materials, and other resources necessary for a task or project.

[0691] This invention relates to a system for optimizing the design and operation of solar power generation systems in buildings. This system consists of a server and terminals as its main components and operates based on user input information.

[0692] The user provides design information to the server via their terminal. This information includes the building's location, shape, roof angle, and orientation. Based on this design information, the server uses software such as WeatherAPI and Radiance to acquire historical weather data and analyze the amount of sunlight.

[0693] The server creates a simulation model based on the analyzed amount of sunlight and determines the optimal placement of the solar power generation equipment. This placement decision takes into account the roof angle and orientation to maximize power generation. This allows users to efficiently proceed with their installation planning.

[0694] Next, the server analyzes market conditions based on the amount of electricity that can be generated and uses software such as OpenEnergyPlatform to predict the profits from selling the electricity. These predictions are provided to the user, who can use them to make decisions that maximize their economic benefits.

[0695] Furthermore, if a user owns an electric vehicle as a power-consuming device, the terminal automatically sets a charging schedule considering the off-peak hours offered by the server. This process is designed to charge during off-peak hours when electricity rates are low, such as late at night, thereby reducing energy costs.

[0696] Furthermore, during the construction phase, the terminals transmit progress data acquired from the construction site to the server. The server monitors this data in real time and dynamically adjusts resource allocation according to the progress, thereby improving construction efficiency.

[0697] For example, if a user enters a prompt such as, "Please calculate the optimal installation method and economic effect of the solar power generation system in my home," the server will perform analysis and optimization according to the procedure described above and present the user with a specific installation plan and its economic effect.

[0698] In this way, this system efficiently manages the use of solar energy and provides economic value to users.

[0699] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0700] Step 1:

[0701] Users input building design information into the server via a terminal. This design information includes the building's location, roof shape, angles, and orientation. This input information is stored in the server's database and serves as the basic data for solar radiation analysis.

[0702] Step 2:

[0703] The server uses design information received from the user to acquire weather data from an external source. During this process, it collects historical weather data using the WeatherAPI and generates a simulation model using Radiance to predict the amount of sunlight at each location on the roof. The input design information and weather data are combined to calculate the predicted annual solar radiation, which is then stored in a database.

[0704] Step 3:

[0705] The server calculates the optimal placement of solar power generation equipment based on the calculated solar radiation data. This process takes into account the roof angle and orientation to maximize power generation and performs multiple placement simulations. This predicts the maximum power generation at each installation location and derives the optimal placement plan.

[0706] Step 4:

[0707] The server analyzes electricity market trends based on the optimal deployment plan and predicted power generation, and uses OpenEnergyPlatform to predict electricity sales revenue. This analysis determines the optimal timing for selling electricity based on market prices and supply volume, and calculates the resulting economic benefits. The final prediction results are notified to the user.

[0708] Step 5:

[0709] If a user owns an electric vehicle, the terminal automatically sets a charging schedule based on information about cheaper time slots obtained from the server. This process adjusts the user's power usage and power supply time, specifically targeting charging during off-peak hours when rates are lower.

[0710] Step 6:

[0711] The terminal periodically sends progress data from the construction site to the server. Based on the received progress data, the server monitors delays and problems in the construction schedule in real time and dynamically adjusts the allocation of resources and personnel as needed to support the smooth progress of the construction.

[0712] (Application Example 1)

[0713] 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".

[0714] Conventional solar energy generation systems have faced challenges in efficiently generating energy and optimizing electricity sales because they cannot fully utilize the design information and solar radiation data specific to each building. Furthermore, the automation of charging schedule management for energy-consuming devices such as electric vehicles is insufficient, making it difficult to optimize energy costs.

[0715] 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.

[0716] In this invention, the server includes means for analyzing solar radiation based on building design information, means for optimizing the installation of a solar energy generation system based on the analysis results, and means for predicting revenue from selling surplus generated electricity based on market prices. This makes it possible to introduce an optimal power generation system for each building and maximize economic benefits through efficient energy management.

[0717] "Building design information" refers to information that affects the efficiency of solar power generation, such as the building's structure, shape, and orientation.

[0718] "Methods for analyzing solar radiation" refer to techniques that use historical weather data and simulation models to calculate the amount of sunlight irradiating a specific building.

[0719] "Methods for optimizing the installation of solar energy generation equipment" refers to technologies for installing equipment in the optimal location to maximize power generation efficiency, based on the results of solar radiation analysis.

[0720] "Methods for predicting electricity sales revenue based on market prices" refer to techniques that analyze the market price of electricity when selling generated electricity and estimate the revenue.

[0721] "Means for optimizing the charging schedule of energy-consuming devices" refers to technologies that determine the optimal time for charging in order to minimize the cost of energy consumption.

[0722] "Means for managing the progress of construction work and dynamically adjusting resource allocation" refers to technologies that monitor the progress of construction projects in real time and make the necessary adjustments to efficiently utilize resources.

[0723] "A means of providing residents with the optimal power generation system and electricity sales strategy using smartphones" refers to a technology that analyzes power generation status and profitability to users via mobile devices and proposes appropriate strategies.

[0724] The system for implementing this invention begins with the user providing building design information to a server. The server then uses historical weather data and simulation models to perform a detailed analysis of the amount of solar radiation on the building. Based on this analysis, the server determines the optimal location for installing the solar energy generation equipment.

[0725] Next, the server analyzes the surplus of generated electricity and predicts sales revenue by comparing it with market electricity prices. This allows users to see the economic benefits of the power generation system.

[0726] Furthermore, the system also manages the charging schedules for energy-consuming devices, especially electric vehicles. The server identifies periods with lower electricity rates and automatically initiates charging, minimizing energy consumption costs.

[0727] For construction site management, terminals send construction progress data to a server, which then monitors the progress in real time. This allows for quick adjustment of resource allocation even if delays occur in the schedule.

[0728] One concrete example is an application that uses a smartphone to determine the optimal placement of solar power generation equipment to be installed on the roof of a user's home. This allows for the suggestion of a power sales strategy tailored to the characteristics of the region, enabling the user to maximize their profits.

[0729] Using a generative AI model, entering a prompt like the following will suggest the optimal installation strategy: "Generate the optimal solar power plant layout based on building design information and weather data, and calculate the economic benefits."

[0730] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0731] Step 1:

[0732] The server receives building design information entered by the user. This input includes information such as the orientation, angle, and location of the building's roof. The server uses this information to store it as basic data for analyzing the amount of solar radiation on the building.

[0733] Step 2:

[0734] The server retrieves historical weather data from a weather database and analyzes solar radiation in combination with design information. Specifically, it uses a simulation model to calculate the average solar radiation for a specific period. Based on these calculation results, it generates the data necessary to ensure maximum power generation.

[0735] Step 3:

[0736] The server uses the analyzed solar radiation data to determine the optimal location and orientation for the solar energy generation equipment. This generates a layout plan to maximize power generation. Users can receive this plan and use it in their own equipment planning.

[0737] Step 4:

[0738] The server analyzes the surplus electricity generated by the power generators and predicts electricity sales revenue by comparing it with market price data. This process obtains current market price information in real time and multiplies it with the predicted power generation value to output the expected electricity sales revenue.

[0739] Step 5:

[0740] The server optimizes the charging schedule for the user's energy-consuming devices. It automatically selects time periods with lower electricity rates and schedules the start of charging accordingly. As a result, the user achieves cost-effective and efficient energy consumption.

[0741] Step 6:

[0742] The terminal transmits progress information from the construction site to the server. The server analyzes the received progress data and adjusts the schedule and resource allocation in real time based on this analysis. This process prevents delays and ensures the project progresses efficiently.

[0743] 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.

[0744] This invention relates to a system that recognizes the emotional state of a user and optimizes building energy management and the operation of energy-consuming equipment. By taking user emotions into consideration, this system provides a more user-friendly interface and performance.

[0745] First, the user inputs building design information, and the server analyzes the amount of solar radiation based on this information. The server then uses local weather data to predict power generation and calculates the optimal placement of solar energy generation equipment. This maximizes power generation and enables efficient energy use.

[0746] Next, the server analyzes the surplus of generated electricity and predicts electricity sales revenue based on market prices. Users can then use this information to make energy management decisions.

[0747] Furthermore, if the user owns energy-consuming devices, especially electric vehicles, the terminal will create a charging schedule. This schedule helps with economical energy management by having the server automatically control charging during off-peak hours when electricity rates are lower.

[0748] The emotion engine recognizes the user's emotional state through user input and interaction. The server analyzes the data from the emotion engine and dynamically adjusts the operating priority of energy-consuming devices. For example, if the user is stressed, the server adjusts lighting and air conditioning settings to improve comfort. The terminal also provides an interface that responds to the user's emotional state, supporting the user in finding the system easier to use.

[0749] For example, if the emotion engine detects that a user has returned home earlier than usual and is feeling tired, the device will instruct the server to soften the lighting and play music to create a relaxing environment the moment the user arrives home. Furthermore, as energy management advice, it will suggest and notify the user of the best time to sell surplus electricity.

[0750] As a result, the present invention can improve the quality of life by providing ease of use and flexibility that takes into account the user's emotional state, in addition to effective energy management.

[0751] The following describes the processing flow.

[0752] Step 1:

[0753] The user inputs building design information into the server. This information includes the building's dimensions, location, roof slope angle, and orientation.

[0754] Step 2:

[0755] The server analyzes the input design information and retrieves solar radiation data from the relevant regional weather database. It then uses this data to simulate the annual solar radiation at specific points within the building.

[0756] Step 3:

[0757] The server calculates the optimal placement of solar energy generation equipment based on the results of solar radiation simulations. It considers the shape and orientation of the roof to generate a placement plan that maximizes power generation efficiency.

[0758] Step 4:

[0759] The server analyzes the surplus of generated electricity and predicts revenue from selling it in the market. Using electricity market price data, the server develops the most profitable electricity sales plan and reports it to the user.

[0760] Step 5:

[0761] If a user owns an energy-consuming device, such as an electric vehicle, they register the charging schedule for that device with the server.

[0762] Step 6:

[0763] The server analyzes the times of day when electricity rates are low and sets a charging schedule for energy-consuming devices. The terminal automatically controls the charging process according to the schedule and notifies the user when charging is complete.

[0764] Step 7:

[0765] The emotion engine analyzes the user's emotional state from their actions and inputs. Based on this data, the server adjusts the operational priority of energy-consuming devices and implements optimal settings to improve user comfort.

[0766] Step 8:

[0767] The device provides an interface that responds to the user's emotional state, supporting the user in operating the system more intuitively. The interface dynamically adjusts its color scheme and design to match the user's mood.

[0768] Step 9:

[0769] When the user returns home and the emotion engine detects that they are tired, the device instructs the server to change the lighting to a warmer color and play healing music to create a relaxing environment.

[0770] Step 10:

[0771] The server acquires construction progress data in real time and dynamically adjusts resource allocation as needed, thereby improving construction efficiency. This allows users to enjoy both optimal energy management and a comfortable living environment.

[0772] (Example 2)

[0773] 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".

[0774] Existing energy management systems lack the technology to optimize energy use in buildings, and in particular, they do not provide flexible control that takes into account individual emotional states. Furthermore, since the charging plans for energy-consuming devices are rarely automatically optimized to take into account lifestyle patterns and fluctuations in the electricity market, there is a need to provide a comfortable and economical environment for users.

[0775] 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.

[0776] In this invention, the server includes means for inputting building design information and analyzing solar radiation based on said information; means for optimizing the installation of energy conversion devices based on the analyzed solar radiation; means for analyzing the surplus of generated electricity and predicting income based on market value; means for recognizing an individual's emotional state and dynamically adjusting the operation priority of energy consumption devices based on that data; and means for providing an interface that adjusts the environment so that the user feels comfortable. This enables more efficient energy management and improved user comfort.

[0777] "Design information" refers to detailed data regarding the structure, layout, materials, and specifications of a building.

[0778] "Solar radiation" refers to the intensity or amount of sunlight that a particular area or building receives during a specific time period.

[0779] The term "energy conversion device" refers to any equipment used to convert natural energy into electricity.

[0780] "Surplus electricity" refers to the portion of electricity produced that is not consumed and remains unused.

[0781] "Market value" refers to the monetary value that energy and electricity have when they are bought and sold in the market.

[0782] "Energy-consuming devices" refers to all household appliances and equipment that operate using electricity.

[0783] "Emotional state" refers to the user's current psychological and emotional state, which includes stress, relaxation, happiness, etc.

[0784] "Operational priority" refers to the criteria used to determine which functions or installations should be prioritized in energy management and equipment control.

[0785] An "interface" refers to the points of contact or means of exchanging information and instructions between a system and its user.

[0786] This system is designed to optimize energy management in buildings and processes various types of information depending on its application. The following describes the hardware and software used, as well as their specific operating procedures.

[0787] Users input building design information using a terminal. This includes drawings, layout information, and material properties. The input information is sent to a server. The server refers to a weather database and analyzes the amount of solar radiation in the area. High-precision simulation software is used for this analysis.

[0788] Based on the analysis results, the server calculates the optimal placement of energy conversion devices, such as solar power panels. During this process, numerical analysis algorithms are used to adjust the arrangement to achieve maximum power generation efficiency.

[0789] For any surplus electricity produced, the server uses market data to calculate its market value and predict potential revenue. Real-time fluctuating electricity market value data is obtained from online price information services.

[0790] If a user owns a mobile device that consumes energy, the terminal automatically creates a charging schedule. The server identifies times when electricity rates are lower and sends this information to the terminal, thereby enabling efficient energy use.

[0791] Furthermore, the interface, equipped with an emotion engine, recognizes the user's emotional state through user input data and information obtained from sensors. The server dynamically optimizes the control of energy consumption devices according to the user's emotions. For example, if the user is feeling stressed, it adjusts the color temperature of the lighting to provide a relaxing environment.

[0792] For example, if the emotion engine recognizes that a user is in a specific emotional state upon returning home, the device instructs the server to provide a comfortable environment through measures such as adjusting the lighting or playing music. This can improve the user's quality of life.

[0793] An example of a prompt message could be: "Please suggest home environment settings for a user who has returned home early and is tired. Specifically, please show how to create a relaxing environment by considering lighting and music settings." This message can then be input into a generative AI model to obtain appropriate suggestions.

[0794] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0795] Step 1:

[0796] The user inputs building design information into a terminal. This input includes design drawings, layout information, and material properties. This information is transmitted from the terminal to the server in a digital format. The server analyzes the received information and registers it in a database.

[0797] Step 2:

[0798] The server retrieves meteorological data from a weather forecasting service and analyzes solar radiation. This analysis uses high-precision simulation software to calculate solar radiation that varies depending on the building's location and orientation. The inputs are meteorological data and design information, and the output is the result of the solar radiation analysis.

[0799] Step 3:

[0800] The server calculates the optimal placement of energy conversion devices based on the analysis results. The input is the analysis results of solar radiation, and the output is the optimal placement plan. This process uses an optimization algorithm to determine the placement that aims for maximum power generation efficiency.

[0801] Step 4:

[0802] The server analyzes power production data to identify surplus power. The inputs are current power consumption and generation data, and the output is the amount of surplus power. Based on this information, it references market data to predict potential revenue from sales.

[0803] Step 5:

[0804] If the user has a mobile device, the terminal manages the charging schedule. The server uses market value data to select the time of day when electricity rates are lowest and sends it to the terminal. The input is past consumption patterns and market data, and the output is an optimized charging schedule.

[0805] Step 6:

[0806] The emotion engine recognizes the user's emotional state using data from the interface and sensors. Inputs are the user's biometric information and usage data, while output is the recognized emotional state. The server dynamically changes the device's operating settings based on the emotional data.

[0807] Step 7:

[0808] The device provides an interface that responds to the user's emotional state. The input is the user's emotional state, and the output is a customized interface (e.g., lighting color adjustment or music playback). This allows the system to automatically create an environment that the user finds comfortable.

[0809] (Application Example 2)

[0810] 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".

[0811] In modern architecture, achieving both efficient energy management and improved user comfort is a crucial challenge. In particular, technologies that actively utilize users' emotional states to dynamically adjust energy consumption devices and interfaces are still not fully established. Therefore, the challenge lies in how to achieve both optimized energy efficiency and improved quality of life.

[0812] 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.

[0813] In this invention, the server includes means for inputting building configuration information and analyzing light energy based on said information, means for optimizing the placement of solar energy generators based on the analyzed light energy, and means for analyzing the user's emotional state and dynamically adjusting the operating priority of energy-consuming devices based on the emotional state. This enables efficient energy utilization and comfortable environment adjustment based on the user's emotions.

[0814] "Building structure information" refers to information related to the building's design, such as its shape, layout, materials, and design details.

[0815] "Light energy" is energy obtained from natural energy sources such as sunlight, and is converted into electricity through power generation equipment.

[0816] A "solar energy generating device" is a device that converts sunlight into electricity, and generally includes solar panels.

[0817] "User's emotional state" refers to the emotions a user is currently experiencing, and includes mental states such as stress, relaxation, and anxiety.

[0818] "Energy-consuming equipment" refers to all devices that operate using electricity, including lighting, air conditioners, and home appliances.

[0819] "Operation priority" refers to the criteria used by a system to determine the order or instructions for which devices to prioritize control under specific conditions.

[0820] "Dynamic adjustment" refers to adaptively changing system settings and operations in response to real-time data and conditions.

[0821] The system implementing this invention starts by inputting information about the building's structure. Based on this information, a server performs a light energy analysis to optimize the placement of solar power generation equipment. The analyzed data is combined with local weather information using specific software, such as an environmental data analysis tool. Furthermore, a generative AI model is used to analyze the user's emotional state. This analysis uses voice and facial expression data collected from the user and employs a machine learning platform, such as TensorFlow. This makes it possible to recognize the user's emotional state and dynamically adjust the priority operation of energy-consuming equipment.

[0822] Furthermore, the device provides users with an emotionally responsive interface, presenting specific experiences and information more appropriately. For example, if a user is feeling stressed, the system adjusts the lighting to softer tones and recommends relaxing music.

[0823] As a concrete example, when a user returns home after experiencing stress at work, the system automatically adjusts various devices in the home to create a relaxing environment. A possible prompt input to the generating AI model might be: "When a user is stressed, how can we most effectively adjust their energy system?"

[0824] Thus, the present invention improves both quality of life and energy efficiency simultaneously by realizing energy management that responds to the user's emotional state.

[0825] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0826] Step 1:

[0827] The server receives building configuration information from the user. Based on this information, it imports local weather data and performs a light energy analysis. In this analysis, the software uses a simulation model to evaluate sunlight conditions and optimizes the placement of solar power generation equipment, taking into account the environmental conditions around the building. The input is building configuration information and weather data, and the output is an optimized placement plan.

[0828] Step 2:

[0829] The server uses a generative AI model to analyze the user's emotional state, taking voice and facial expression data collected from the user as input. Specifically, it employs image recognition and voice analysis technologies to perform inference processing on a machine learning platform such as TensorFlow. The emotion analysis algorithm evaluates multiple emotional states and calculates the user's stress level and happiness level in real time. The output is data related to the user's emotional state.

[0830] Step 3:

[0831] The device dynamically adjusts the operational priority of energy-consuming devices based on the results of emotion analysis. For example, if the user is feeling stressed, the artificial intelligence will improve comfort by adjusting the room lighting and optimizing the air conditioning settings. In this case, the prompt message used is, "How can we most effectively adjust the energy system when the user is feeling stressed?" The input is the user's emotional state data, and the output is the device's control signal.

[0832] Step 4:

[0833] Users receive recommended interface changes from the server, allowing them to live their daily lives in an improved, more convenient environment. For example, the system automatically adjusts lighting color and brightness, and selects and plays relaxing music to enhance user comfort. This process involves interactive system adjustments that incorporate user feedback. Inputs are operation priorities and environmental data, while output is the user's preferred settings.

[0834] 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.

[0835] 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.

[0836] 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.

[0837] 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.

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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.

[0842] 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."

[0843] 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.

[0844] 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.

[0845] 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.

[0846] 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.

[0847] 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.

[0848] 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.

[0849] 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.

[0850] 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.

[0851] 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.

[0852] 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.

[0853] 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.

[0854] 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.

[0855] The following is further disclosed regarding the embodiments described above.

[0856] (Claim 1)

[0857] A means for inputting building design information and analyzing solar radiation based on said information,

[0858] A means for optimizing the installation of a solar energy generation system based on the analyzed solar radiation,

[0859] A method for analyzing the surplus of generated electricity and predicting electricity sales revenue based on market prices,

[0860] A means for optimizing the charging schedule of energy-consuming devices and automatically controlling charging,

[0861] A means of managing the progress of construction work and dynamically adjusting resource allocation,

[0862] A system that includes this.

[0863] (Claim 2)

[0864] The system according to claim 1, which uses meteorological data to analyze solar radiation and predicts power generation based on said data.

[0865] (Claim 3)

[0866] The system according to claim 1, wherein, when the energy-consuming device is an electric vehicle, the charging schedule is set taking into account the time of day when rates are low.

[0867] "Example 1"

[0868] (Claim 1)

[0869] A means for inputting building design information and analyzing the amount of sunlight based on said information,

[0870] A means for optimizing the arrangement of photovoltaic power generation equipment based on the amount of sunlight analyzed,

[0871] A means of analyzing the surplus of generated electricity and predicting electricity sales profits based on market conditions,

[0872] A means for optimizing the charging schedule of energy-consuming devices and automatically controlling charging,

[0873] A means of monitoring the progress of work and dynamically adjusting resource allocation,

[0874] A system that includes this.

[0875] (Claim 2)

[0876] The system according to claim 1, which uses environmental data to analyze the amount of sunlight and predicts the amount of power generated based on said data.

[0877] (Claim 3)

[0878] The system according to claim 1, wherein, when the energy consumption device is an electric vehicle, the charging schedule is set taking into account periods when charges are low.

[0879] "Application Example 1"

[0880] (Claim 1)

[0881] A means for inputting building design information and analyzing solar radiation based on said information,

[0882] A means for optimizing the installation of a solar energy generation system based on the analyzed solar radiation,

[0883] A method for analyzing the surplus of generated electricity and predicting electricity sales revenue based on market prices,

[0884] A means for optimizing the charging schedule of energy-consuming devices and automatically controlling charging,

[0885] A means of managing the progress of construction work and dynamically adjusting resource allocation,

[0886] A means of providing residents with the optimal power generation system and electricity sales strategy using smartphones,

[0887] A system that includes this.

[0888] (Claim 2)

[0889] The system according to claim 1, which uses meteorological data to analyze solar radiation and predicts power generation based on said data.

[0890] (Claim 3)

[0891] The system according to claim 1, wherein, when the energy-consuming device is an electric vehicle, the charging schedule is set taking into account the time of day when rates are low.

[0892] "Example 2 of combining an emotion engine"

[0893] (Claim 1)

[0894] A means for inputting building design information and analyzing solar radiation based on said information,

[0895] A means for optimizing the installation of an energy conversion device based on the analyzed solar radiation,

[0896] A means of analyzing the surplus of generated electricity and predicting revenue based on market value,

[0897] A means for optimizing and automatically controlling the charging plan of energy-consuming devices,

[0898] A means for recognizing an individual's emotional state and dynamically adjusting the operating priority of energy consumption devices based on that data,

[0899] A means of providing an interface that adjusts the environment so that the user feels comfortable,

[0900] A system that includes this.

[0901] (Claim 2)

[0902] The system according to claim 1, which uses meteorological data to analyze solar radiation and predicts conversion efficiency based on said data.

[0903] (Claim 3)

[0904] The system according to claim 1, which sets a charging plan considering the time of day when the energy-consuming device is a mobile device.

[0905] "Application example 2 when combining with an emotional engine"

[0906] (Claim 1)

[0907] A means for inputting information about the structure of a building and analyzing light energy based on that information,

[0908] A means for optimizing the arrangement of a solar energy generator based on the analyzed light energy,

[0909] A method for analyzing the surplus of generated electricity and predicting electricity sales revenue based on market value,

[0910] A means for optimizing the charging schedule of power-consuming equipment and automatically adjusting charging,

[0911] A means for analyzing the user's emotional state and dynamically adjusting the operating priority of energy-consuming devices based on that emotional state,

[0912] A means of providing an interface that responds to emotional states, and helping users to use the system more comfortably,

[0913] A system that includes this.

[0914] (Claim 2)

[0915] The system according to claim 1, which utilizes meteorological information for the analysis of light energy and predicts the amount of generation based on said information.

[0916] (Claim 3)

[0917] The system according to claim 1, which creates a charging schedule considering the time of day when prices are low, when the power-consuming equipment is an electric mobile device. [Explanation of Symbols]

[0918] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for inputting building design information and analyzing solar radiation based on said information, A means for optimizing the installation of a solar energy generation system based on the analyzed solar radiation, A method for analyzing the surplus of generated electricity and predicting electricity sales revenue based on market prices, A means for optimizing the charging schedule of energy-consuming devices and automatically controlling charging, A means of managing the progress of construction work and dynamically adjusting resource allocation, A means of providing residents with the optimal power generation system and electricity sales strategy using smartphones, A system that includes this.

2. The system according to claim 1, which uses meteorological data to analyze solar radiation and predicts power generation based on said data.

3. The system according to claim 1, wherein, when the energy-consuming device is an electric vehicle, the charging schedule is set taking into account the time of day when charges are low.

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