system

Abstract

Provide a system. 【Solution means】 Analyze the design information of the building and determine the optimal arrangement of the solar power generation panels, Solar radiation amount prediction means, Panel arrangement optimization means, Means for predicting the power sales income based on the power sales reference information, Means for monitoring the construction progress in real time and managing the construction resources, Means for automatically optimizing the charging schedule of electric vehicles, Means for monitoring the performance of the panels and performing fault prediction, A system including the above.

Description

【Technical Field】 【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 and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Unexamined Patent Application Publication No. 2022 - 180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 Conventionally, in order to efficiently introduce a solar power generation system and an electric vehicle charging facility in a newly constructed house, it has been necessary to combine separate technologies and systems, which has led to complication of construction and increase in cost. In addition, technical elements related to the optimal installation of solar power generation and advanced analysis for predicting the selling income of electric power have been developed separately, making integrated management and optimization difficult. As a result, problems have remained in maximizing the effect of solar power generation and improving the charging efficiency of electric vehicles. 【Means for Solving the Problems】 【0005】 This invention provides a solar radiation prediction means that analyzes building design information to determine the optimal placement of solar power generation panels, and further introduces an analysis means linked to power sales reference information to optimize panel placement and predict power sales revenue. It also includes an implementation for monitoring construction progress in real time and efficiently managing construction resources. Furthermore, it provides a management system that integrates these technologies by integrating a charging management means that automatically optimizes the charging schedule of electric vehicles to achieve both low cost and high efficiency, as well as a means for monitoring panel performance and predicting failures. This makes it possible to maximize the effect of solar power generation, improve the charging efficiency of electric vehicles, and smoothly proceed with the entire process from construction to operation. 【0006】 "Architectural design information" refers to drawings and data that contain detailed information about the structure and layout of a building. 【0007】 A "solar power generation panel" is a device that converts sunlight into electricity, and is usually installed on roofs or other similar structures. 【0008】 "Solar radiation prediction means" refers to technologies and devices for predicting the amount of sunlight irradiating a specific location according to the time of day and season. 【0009】 "Panel placement optimization means" refers to calculation methods or systems for determining the effective placement of solar power generation panels. 【0010】 "Electricity sales reference information" refers to data that shows market electricity prices and trading trends, and is used as a reference when selling electricity. 【0011】 "Methods for predicting electricity sales revenue" refer to technologies and methods for calculating the revenue obtained from selling generated electricity based on market data and power generation forecasts. 【0012】 "A means of monitoring construction progress in real time and managing construction resources" refers to a system that allows for immediate understanding of the progress at a construction site and efficient allocation of necessary resources. 【0013】 "Means for automatically optimizing electric vehicle charging schedules" refers to a system that automatically plans the time of day and amount of charge for the most efficient and economical charging of electric vehicles. 【0014】 "Means for monitoring panel performance and predicting failures" refer to technologies and devices that continuously check the operating status of solar power generation panels and predict when maintenance should be performed as needed. [Brief explanation of the drawing] 【0015】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] 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 Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined. 【Mode for Carrying Out the Invention】 【0016】 Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0017】 First, the language used in the following description will be explained. 【0018】 In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), etc. 【0019】 In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0020】 In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes. 【0021】 In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark). 【0022】 In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or." 【0023】 [First Embodiment] 【0024】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0025】 As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server. 【0026】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0027】 The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52. 【0028】 The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input. 【0029】 The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor. 【0030】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54. 【0031】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0032】 As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30. 【0033】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0034】 In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0035】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0036】 The present invention aims to streamline and optimize the installation of solar power generation panels and the charging management of electric vehicles in buildings. The embodiments of this system are described below. 【0037】 First, the user uploads the building's blueprints to the system. The blueprints are provided in digitized drawing or data format. Based on this design information, the server analyzes the building's roof shape, orientation, and area. The analyzed information is used for solar radiation forecasting, and the server predicts the amount of solar radiation throughout the year by referring to geographical and meteorological data. 【0038】 Based on this information, the server calculates the optimal placement of solar panels and determines the installation angle and arrangement pattern. The results of this placement optimization are provided to the construction management team, enabling efficient construction. 【0039】 Furthermore, the server retrieves electricity sales reference information from the power market and combines it with predicted power generation to simulate electricity sales revenue. This simulation result is useful for determining the economic feasibility of the power generation system. In addition, construction progress is reported in real time from the terminals, and the server monitors the progress of construction and optimizes resource allocation as needed. 【0040】 For electric vehicle charging, users input their desired charging schedule into the system. Based on this schedule, the server analyzes power usage and provides the optimal charging time. Charging is performed automatically during low-cost periods, promoting efficient energy use. 【0041】 Furthermore, the server constantly monitors panel performance and predicts signs of failure. If performance deteriorates, the system sends an alert to the user, allowing for early maintenance. This proactive maintenance ensures long-term operational stability while maintaining power generation efficiency. 【0042】 As a concrete example, in a certain housing project, using this system allowed the server to streamline the entire process from the design stage to construction management and operation, resulting in high power generation efficiency and economic benefits. 【0043】 The following describes the processing flow. 【0044】 Step 1: 【0045】 The user uploads the building's blueprints to the system in digital format. The server receives this data and activates the building's shape analysis module. 【0046】 Step 2: 【0047】 The server analyzes the blueprints to identify the building's roof shape, orientation, and area. Based on the acquired structural data, it uses a solar radiation prediction module to simulate the amount of solar radiation throughout the year. 【0048】 Step 3: 【0049】 The server references geographic information systems and weather data to correct for solar radiation at specific building locations. This data is then used as a basis for determining the optimal placement of solar power panels. 【0050】 Step 4: 【0051】 The server executes an optimal panel placement algorithm to determine the installation angle and placement pattern. This optimal placement information is sent to the construction team to assist in accurate installation on-site. 【0052】 Step 5: 【0053】 The terminal updates the progress status in real time from the construction site and sends the progress data to the server. The server receives this data, manages construction resources, and optimizes them as needed. 【0054】 Step 6: 【0055】 Users set their electric vehicle charging schedule, entering their desired charging time slots and capacities. Based on this information, the server analyzes power usage and suggests an efficient charging schedule. 【0056】 Step 7: 【0057】 The server constantly monitors panel performance and executes a failure prediction algorithm when an anomaly is detected. If necessary, it sends maintenance notifications to users to encourage early action. 【0058】 Step 8: 【0059】 The server retrieves electricity sales reference information from the power market and integrates it with the results of power generation simulations to predict annual electricity sales revenue. Based on this prediction, it provides users with information to make economic decisions. 【0060】 (Example 1) 【0061】 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." 【0062】 In today's environment, the introduction and management of solar power generation are crucial for achieving sustainable energy use. However, the placement of power generation equipment in buildings, on-site management, and subsequent optimization of energy use require considerable effort and specialized knowledge. Furthermore, there is a need for appropriate market information analysis to maintain power generation efficiency and maximize economic benefits, as well as for the efficient use of electricity. The problem lies in the lack of systems that address these challenges. 【0063】 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. 【0064】 In this invention, the server includes means for analyzing design information and determining the optimal placement of power generation equipment, means for predicting solar radiation, means for optimizing the placement of power generation equipment, means for predicting electricity revenue based on market information, means for monitoring construction progress in real time and managing construction resources, means for automatically optimizing the charging schedule of mobile units, and means for monitoring the performance of power generation equipment and predicting failures. This improves the efficiency of the series of processes and makes it possible to achieve high power generation efficiency and economic convenience. 【0065】 "Design information" refers to digital information related to the design of a building, and specifically includes data on the building's roof shape, orientation, and area. 【0066】 A "power generation device" is a device that converts solar energy into electricity, and specifically refers to a solar power generation panel. 【0067】 "Solar radiation" refers to the amount of solar energy received over a certain period of time at a specific geographical location. 【0068】 "Market information" refers to data related to the buying and selling of electricity in the energy market, and specifically includes information such as electricity supply and demand, and electricity selling prices. 【0069】 "Construction resources" is a general term for the personnel, equipment, materials, and other resources necessary to carry out the installation work of power generation equipment in a building. 【0070】 "Mobile vehicles" refer to vehicles such as automobiles that need to store energy and be charged. 【0071】 "Performance monitoring" is a process of continuously checking the operating status of power generation equipment and evaluating whether it is functioning properly. 【0072】 "Failure prediction" refers to a technology that analyzes data from power generation equipment to detect in advance the possibility of future malfunctions or abnormalities. 【0073】 The present invention aims to efficiently introduce and manage solar power generation in buildings. This system comprehensively performs tasks ranging from analysis of design information and optimal placement of power generation equipment to energy market analysis, construction management, optimization of mobile equipment charging, and performance monitoring of power generation equipment through multiple means. 【0074】 First, the user uploads detailed design information of the building to the system in digital format. This information is then sent to the server, and the analysis begins. The server uses CAD software to analyze the design data and extract the roof shape, orientation, and area. Based on this extracted information, the server predicts the amount of solar radiation by referring to geographic and meteorological databases. 【0075】 Based on solar radiation predictions, the server uses solar power simulation software (e.g., PVsyst) to calculate the optimal placement of power generation equipment. Based on the calculation results, it proposes the optimal installation method for the power generation equipment and provides it to the construction management team. This improves the efficiency of construction work. 【0076】 Furthermore, the server uses energy market information to simulate the economics of selling electricity and presents this to the user. Regarding the charging of mobile devices such as electric vehicles, it optimally manages the supply and demand of electricity based on the charging schedule set by the user. This automatically ensures that charging takes place during off-peak hours when costs are lower. 【0077】 Furthermore, the server constantly monitors the performance of the power generation equipment and predicts signs of failure using a generated AI model. If the output of the power generation equipment decreases, the server sends an alert to the user to encourage early maintenance. This enables the long-term stable operation of the power generation equipment. 【0078】 As a concrete example, the use of this system in a housing project allowed the server to integrate and manage the entire process from the construction phase to the operation phase, achieving high power generation efficiency. As a result, the economic benefits were maximized. 【0079】 An example of a prompt for the generating AI model is, "Based on the house blueprints, calculate the optimal placement of solar panels and maximize power generation efficiency." This prompt prompts the server to automatically generate an efficient placement plan. 【0080】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0081】 Step 1: 【0082】 Users upload building design information to the system in digital format. This provides information about the building's roof shape, orientation, and area. Based on this input data, the server receives the design data and enables subsequent analysis. 【0083】 Step 2: 【0084】 The server analyzes the received design information. Specifically, it uses CAD software to analyze the design data and extract the roof shape, orientation, and area. This data analysis yields meaningful features from the design information. 【0085】 Step 3: 【0086】 The server predicts solar radiation by referencing geographic and meteorological databases. Input data includes roof information and geographical coordinates obtained in step 2. Based on this data, the annual solar radiation calculation is performed. 【0087】 Step 4: 【0088】 The server uses solar power simulation software to calculate the optimal placement of power generation equipment. This process takes predicted solar radiation as input, determines the optimal panel angles and placement patterns, and provides the results to the construction management team. 【0089】 Step 5: 【0090】 The server simulates electricity sales revenue based on market information collected from the energy market. Inputs include predicted power generation and market price data. This allows the user to see the economic potential of the power generation system. 【0091】 Step 6: 【0092】 The terminals report the progress of construction in real time from the site. Using this information, the server monitors the construction status and optimizes the allocation of construction resources as needed. This improves the efficiency of construction. 【0093】 Step 7: 【0094】 The user enters the electric vehicle charging schedule into the system. The server then references this schedule and power demand data to calculate the optimal charging time. This ensures that charging takes place during cost-effective hours. 【0095】 Step 8: 【0096】 The server continuously monitors the performance of the power generation equipment and uses a generative AI model to predict signs of failure. Input includes real-time output data acquired from the power generation equipment. When a performance degradation is detected, an alert is sent to the user, enabling prompt maintenance. 【0097】 (Application Example 1) 【0098】 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." 【0099】 Balancing environmental protection and energy efficiency in modern buildings is a crucial challenge. Existing systems struggle to optimize energy conversion devices from the design stage, and there's a lack of methods to directly help residents understand energy efficiency. Therefore, there's a need for precise placement of energy conversion devices, optimization of charging resources, and systems that allow residents to easily experience efficient energy use. 【0100】 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. 【0101】 In this invention, the server includes means for analyzing building design information and determining the optimal placement of energy conversion devices, means for monitoring construction progress in real time and managing construction resources, and means for visualizing energy efficiency on information terminals for residents. This enables sustainable and efficient energy utilization from the design stage to the operation stage of the building. 【0102】 "Building design information" refers to a collection of detailed design drawings and data concerning the structure and function of a building, and serves as the basis for determining the optimal placement of energy conversion devices. 【0103】 An "energy conversion device" is a device that converts natural energy sources such as solar and wind power into other forms of energy, such as electricity. 【0104】 A "solar radiation prediction means" is a device or method that predicts the amount of solar radiation obtained in a given area based on the location of a building and environmental data. 【0105】 "Energy conversion device placement optimization means" refers to a device or method that performs calculations and analyses to determine the optimal placement of energy conversion devices based on the shape and orientation of a building. 【0106】 "Electricity trading information" refers to information regarding the market price of electricity, supply, and demand, and serves as basic data for determining the optimal timing for selling electricity. 【0107】 "Means for monitoring construction progress in real time and managing construction resources" refers to a device or method for tracking the construction process of a building in real time and efficiently allocating the necessary resources. 【0108】 "Means for automatically optimizing a vehicle's charging schedule" refers to a device or method that automatically sets the time and method for efficiently charging a vehicle based on power demand and cost. 【0109】 "Means for monitoring the performance of an energy conversion device and predicting failures" refers to a device or method that constantly monitors the operating status of an energy conversion device and predicts and notifies of failures before abnormalities occur. 【0110】 "Means of visualizing energy efficiency on information terminals for residents" refers to a device or application that displays energy usage and efficiency in an easy-to-understand manner for residents. 【0111】 The system of this invention is designed to maximize energy efficiency in buildings and allow residents to experience its benefits. The server receives building design information and uses AI technology to calculate the optimal placement of energy conversion devices. In this process, meteorological data and geographic information are combined for solar radiation prediction, and Google® Earth Engine is used. Furthermore, since complex data analysis is required to optimize the placement of conversion devices, a high-performance cloud-based tool is used. 【0112】 During the construction process, the server monitors the progress in real time and optimally allocates resources as needed. This involves collecting data from IoT sensors and managing construction resources using Amazon AWS® IoT Core. 【0113】 Furthermore, regarding energy trading data, the server analyzes market trends and notifies users of the optimal timing for electricity trading. Users receive this information using smartphones or smart glasses, and the system is designed to be intuitively understandable. 【0114】 Regarding the performance monitoring of energy conversion equipment, the server constantly checks the operating status of the equipment and predicts failures before any abnormalities occur, sending alerts to the user. This prevents future decreases in power generation and equipment failures, promoting smooth system operation. 【0115】 As a concrete example, the implementation of this system in a certain smart city resulted in residents reducing their monthly electricity costs by approximately 15% and optimizing their energy use. The information terminals for residents are equipped with a function to visualize energy efficiency, allowing residents to check their energy usage in real time. 【0116】 An example of a prompt using a generative AI model is, "Perform real-time data analysis on optimizing solar power generation and present the most cost-effective option for residents." In this way, support is provided in a way that is easy for users to understand. 【0117】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0118】 Step 1: 【0119】 The server receives building design information from the user. The input design information is provided in digital drawing format. The server analyzes this information and extracts the building's roof shape and orientation. This generates the basic data necessary for planning the placement of energy conversion devices. 【0120】 Step 2: 【0121】 The server combines geographical and meteorological data to predict solar radiation. Specifically, it uses Google Earth Engine to predict solar radiation throughout the year. The inputs used are roof shape and location information based on design data, and the output is predicted solar radiation data. 【0122】 Step 3: 【0123】 The server calculates the optimal placement of energy conversion devices based on solar radiation forecast data. AI technology is used in the processing to determine the most efficient panel installation angles and placement patterns. The input is solar radiation forecast data, and the output is the optimal placement plan. 【0124】 Step 4: 【0125】 The server monitors construction progress in real time and manages construction resources. It collects data from IoT sensors and uses Amazon AWS IoT Core to understand the condition of the construction site. This minimizes waste during the construction process. 【0126】 Step 5: 【0127】 The server collects electricity market transaction information and analyzes the optimal timing for electricity trading. Market data is used as input, and the output is recommended information on the most suitable time for trading. Users receive this information via smart devices. 【0128】 Step 6: 【0129】 The terminal visualizes energy efficiency on a resident information display. Energy usage and economic effects are visualized using graphs and other visuals, presented in a format easily understood by residents. Input is energy data from a server, and output is a visualized interface. 【0130】 Step 7: 【0131】 The server constantly monitors the performance of the energy conversion device and predicts failures. It analyzes sensor data and sends alerts to user terminals when an anomaly is detected. This enables rapid response and stable system operation. 【0132】 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. 【0133】 This invention provides an energy management system that not only improves the efficiency of solar power generation and electric vehicle charging in buildings, but also takes user sentiment into consideration. The system begins with an analysis of the roof shape based on design information, and then achieves optimal placement of solar panels and maximizes power generation efficiency. Furthermore, it improves economic efficiency by analyzing electricity market information and predicting appropriate electricity sales revenue. It also includes a function to monitor construction progress in real time and optimize resource management. 【0134】 Furthermore, this system incorporates an emotion engine to analyze the user's emotional state, aiming to optimize energy management. The server uses an emotion recognition algorithm to analyze the user's emotions from voice and image data, and automatically adjusts the energy settings within the home based on the results. For example, if the system detects that the user is stressed, the emotion engine will change the lighting and air conditioning settings to provide a more comfortable environment. 【0135】 Furthermore, the server adjusts the electric vehicle's charging schedule according to the user's emotional state. For example, if the user is relaxed, the charging is set to energy-saving mode and optimized to charge at a comfortable pace. This function reduces energy consumption and contributes to long-term cost savings. 【0136】 Furthermore, the solar power generation system uses the analysis results of the emotion engine to detect energy surpluses and shortages in real time, and predicts and optimizes power consumption. This allows for flexible responses to energy usage patterns within the home, which is expected to improve user satisfaction. 【0137】 This system comprehensively supports the entire energy management process, from the design phase to the operation of buildings, enabling a smarter and more emotionally resonant lifestyle. 【0138】 The following describes the processing flow. 【0139】 Step 1: 【0140】 The user operates a device to input audio and image data into the system. This data is used to understand the user's emotional state. 【0141】 Step 2: 【0142】 The server activates an emotion recognition algorithm and analyzes the captured audio and image data. Based on factors such as voice tone, facial expressions, and posture, it identifies the current emotional state. 【0143】 Step 3: 【0144】 The server uses the analysis results to calculate energy settings appropriate for the user's emotional state. For example, to alleviate stress, it adjusts the color and intensity of the lighting and changes the air conditioning settings. 【0145】 Step 4: 【0146】 If a user is planning to charge their electric vehicle, the server will reset the optimal charging schedule based on the emotion recognition results. If the user needs to relax, it will recommend charging in energy-saving mode. 【0147】 Step 5: 【0148】 The server retrieves the latest information from the electricity market and adjusts the timing of electricity sales. Since energy supply and demand change depending on emotional states, it devises the optimal electricity sales plan. 【0149】 Step 6: 【0150】 The terminal integrates progress information from the construction site with user residency information and transmits the data to the server in real time. This data is used for construction management and energy management. 【0151】 Step 7: 【0152】 The server monitors the performance of the solar panels and, if an anomaly is detected, promptly develops a maintenance plan. It also considers data from the emotion engine to determine the most impactful time to take action. 【0153】 Step 8: 【0154】 The server oversees overall energy usage, incorporates insights from the emotion engine, and then executes optimization algorithms to manage and maintain the living environment in the most comfortable way possible at all times. 【0155】 (Example 2) 【0156】 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." 【0157】 In conventional energy management systems, it was difficult to simultaneously achieve maximum efficiency in solar power generation, real-time management of construction progress, effective charging management of electric vehicles, and optimization of the operating environment while considering user sentiment. As a result, this often led to energy waste, increased costs, and decreased user satisfaction. 【0158】 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. 【0159】 In this invention, the server includes means for analyzing design information and determining the optimal placement of power generation equipment, means for predicting solar radiation, means for optimizing the placement, means for predicting electricity sales revenue based on electricity sales reference information, means for monitoring construction progress in real time and managing construction resources, means for analyzing the user's emotional state using an emotion recognition algorithm and automatically optimizing the operating environment, means for optimizing the electric vehicle charging schedule according to the emotional state, and means for monitoring the performance of power generation equipment and performing fault prediction. This enables more efficient energy management, improved user comfort, and cost reduction. 【0160】 "Design information" is a general term for detailed information such as drawings, specifications, materials, and dimensions necessary for the construction of a building. 【0161】 A "power generation device" is a device that generates electricity using sunlight, and mainly refers to solar panels. 【0162】 "Solar radiation" refers to the amount of solar energy that reaches a surface per unit time. 【0163】 "Placement" refers to the location and method for properly installing solar panels and other equipment. 【0164】 "Electricity sales reference information" refers to information regarding trends in the electricity market and electricity prices. 【0165】 "Construction progress" refers to information indicating the current status of a construction project. 【0166】 "Construction resources" is a general term for the personnel, materials, equipment, and other resources necessary for a construction project. 【0167】 An "emotion recognition algorithm" is a computational processing method for analyzing a person's emotional state based on audio or image data. 【0168】 "Operating environment" refers to the physical conditions such as lighting, temperature, and acoustics in the space where the user lives or uses the space. 【0169】 An "electric vehicle" is a vehicle that moves using electricity as its power source, and mainly refers to an electric car. 【0170】 A "charging schedule" is a plan for systematically determining the time and speed at which electric vehicle batteries are charged. 【0171】 "Failure prediction" is a technology that analyzes equipment operation data to estimate signs of failure and the timing of failures in advance. 【0172】 In embodiments of the present invention, the energy management system integrates multiple technologies to achieve efficient energy use in buildings. In this system, a server plays a central role in collecting and analyzing information from various data sources. 【0173】 The server first receives design information. This design information includes building blueprints and specifications, and the server analyzes the roof shape and area based on this information. The server then uses 3D modeling software (e.g., AutoCAD) to perform simulations to determine the optimal placement of solar panels. During this process, it refers to an external database containing weather data to predict solar radiation. 【0174】 The server also gathers information about the electricity market and uses it to predict electricity sales revenue. This prediction is made using data analysis algorithms, providing the optimal electricity sales strategy based on historical electricity price trends and demand curves. 【0175】 IoT sensors are installed at construction sites, transmitting real-time information on construction progress to a server. The server uses this information to optimize the allocation of construction resources and improve construction efficiency. 【0176】 To enhance user comfort, the server implements an emotion recognition algorithm that analyzes the user's voice and image data. This allows it to determine whether the user is stressed or relaxed. For example, if the user is stressed, the server adjusts the lighting and air conditioning settings to provide a more comfortable environment. 【0177】 Furthermore, the server manages electric vehicle charging, flexibly adjusting the charging schedule according to the user's emotional state. For example, it can set the charging schedule to nighttime hours to encourage efficient charging during times of low electricity demand. 【0178】 Furthermore, the server monitors the performance of the power generation equipment and predicts failures as needed. This function helps prevent mechanical problems and contributes to improving the long-term reliability of the system. 【0179】 As a concrete example, when emotion recognition determines that a user is "feeling stressed," the server can respond by dimming the lights and playing music to provide a comfortable environment. 【0180】 Examples of prompt messages are as follows: 【0181】 "How can I optimize the lighting settings in this residential system when users experience stress?" 【0182】 Thus, the system of the present invention simultaneously achieves improved energy efficiency and enhanced quality of life for users through the integration of technologies. 【0183】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0184】 Step 1: 【0185】 The server receives building design information. A 3D design software file is provided as input. The server analyzes this file and extracts data such as roof shape, area, and orientation. Analysis data necessary for solar panel placement is generated as output. 3D modeling software (e.g., general-purpose design software) is used for the analysis. 【0186】 Step 2: 【0187】 The server retrieves data from a weather database to predict solar radiation. Location information and weather data are provided as input. The server uses a solar radiation calculation algorithm to calculate the predicted daily solar radiation. This data calculation includes calculating sunshine duration based on location information. The output is predicted solar radiation data. 【0188】 Step 3: 【0189】 The server calculates the optimal placement of solar panels based on design information and solar radiation data. Roof shape data and solar radiation data are used as input. The server utilizes simulation tools to generate a placement plan that takes shading into account. The output includes a panel placement diagram and data showing the maximum power generation efficiency. In this process, the shading simulation takes into account environmental information surrounding the building. 【0190】 Step 4: 【0191】 The server collects electricity market information and predicts electricity sales revenue. It requires market price data and demand data as input. The server uses a machine learning model to calculate the optimal electricity sales strategy based on this data. The output is predicted electricity sales revenue data. 【0192】 Step 5: 【0193】 The server receives real-time sensor data from the construction site and manages the construction progress. The input is data from IoT sensors installed at the construction site. The server uses a resource management algorithm to analyze the construction progress and allocate resources efficiently. The output is an optimized construction schedule. 【0194】 Step 6: 【0195】 The server collects user emotion data from the microphone and camera and analyzes it using an emotion recognition algorithm. Audio and image data are provided as input. The server uses an emotion analysis model to determine the user's emotional state. Data indicating the emotional state is generated as output. This data is used in the next step. 【0196】 Step 7: 【0197】 The server optimizes the operating environment within the home based on the user's emotional state. Emotional state data is used as input. The server automatically adjusts the air conditioning and lighting settings to create an environment that the user finds comfortable. The output is the adjusted air conditioning and lighting settings. 【0198】 Step 8: 【0199】 The server optimizes the electric vehicle's charging schedule based on the user's emotional state. The input requires user emotional data and the vehicle's charging status. Based on this data, the server creates an efficient charging plan that aligns with the user's lifestyle. The output is the optimized charging schedule. 【0200】 Step 9: 【0201】 The server monitors the performance of the power generation equipment and performs fault prediction as needed. Operational data from the generator is provided as input. The server utilizes a fault prediction model to detect equipment abnormalities in advance. The output is risk data indicating the likelihood of failure. This data is used in maintenance planning. 【0202】 (Application Example 2) 【0203】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal". 【0204】 Conventional energy management systems have not adequately achieved the efficiency of solar energy collection in buildings and energy supply to electric transportation equipment, and in particular, they lack systematic management that takes into account the impact of users' emotional states on energy consumption. Therefore, there has been a challenge in optimizing energy use. 【0205】 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. 【0206】 In this invention, the server includes means for analyzing building design information and determining the optimal placement of solar energy collection devices, means for predicting solar radiation energy, means for optimizing the placement of energy collection devices, means for predicting electricity trading revenue based on electricity trading reference information, means for monitoring construction progress in real time and managing construction resources, means for automatically optimizing the energy supply schedule for electric transport equipment, means for analyzing the user's emotional state and adjusting energy management based on the results, means for detecting energy surplus or deficit based on emotional analysis and performing electricity usage prediction and optimization, and means for monitoring the performance of energy collection devices and performing failure prediction. This enables flexible and efficient energy management that takes user emotions into consideration. 【0207】 "Analyzing building design information" means analyzing detailed information about the structure and layout of a building to help improve energy efficiency. 【0208】 A "solar energy collection device" is a device that efficiently converts sunlight into energy, and is usually installed on the roof or exterior wall of a building. 【0209】 "Optimizing the placement of energy collection devices" is the process of calculating and adjusting the shape, position, angle, and other factors necessary for energy collection devices to function as efficiently as possible. 【0210】 "Solar radiation energy forecasting" involves predicting the amount of radiant energy from the sun and providing information to maximize the operational efficiency of energy collection devices. 【0211】 "Electricity trading reference information" refers to information about transactions in the electricity market, including electricity prices, demand, and supply conditions. 【0212】 "Optimizing the energy replenishment schedule for electric transport equipment" means developing a charging plan that ensures electric transport equipment is charged efficiently and energy consumption is minimized. 【0213】 "Analyzing emotional states" involves analyzing a user's emotional state based on their voice, facial expressions, and actions, and then utilizing the results as data. 【0214】 "Detecting energy surplus or deficit based on emotion analysis" is a method for identifying energy surplus or deficit based on the user's emotions and achieving optimal energy management. 【0215】 "Monitoring the performance of energy collection devices" is a process that constantly checks whether the collection devices are functioning correctly and enables immediate action if any problems arise. 【0216】 This invention is a system for optimizing energy efficiency in buildings. The server executes software that determines the optimal placement of solar energy collection devices based on the building's design information and performs solar radiation energy prediction. This software takes the design information as input and performs the necessary analysis to maximize solar energy collection efficiency. Furthermore, it performs simulations to optimize the placement of the collection devices and calculates their position and angle. 【0217】 The device uses voice analysis APIs and facial recognition APIs to analyze the user's emotional state. Specifically, the device collects voice and image data and sends the data to the server to reveal the user's emotional state. For example, it uses Microsoft® Azure® Face API to analyze the user's facial expressions and estimate their emotional state. 【0218】 Subsequently, the server automatically adjusts energy management based on the user's emotional state. For example, if the user is relaxed, it will change the lighting color to a warmer tone and set the air conditioning temperature to a comfortable range. It will also flexibly adjust the energy replenishment schedule for electric transport equipment to optimize energy consumption. 【0219】 This system achieves optimal energy management by analyzing energy usage data and applying predictive algorithms to detect energy surpluses and deficits based on emotion analysis. Thus, in this embodiment, energy management that takes user emotions into account is comprehensively supported. 【0220】 An example of a prompt would be, "Please tell me the appropriate energy setting for you when you are relaxing." This prompt allows the generating AI model to suggest an appropriate energy management method. 【0221】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0222】 Step 1: 【0223】 The server analyzes the building's design information to determine the optimal placement of solar energy harvesting devices. The input to this process is the building's blueprint, and the output is the specific location information of each harvesting device. Based on the input data, simulation software is used to calculate the optimal placement that maximizes harvesting efficiency. 【0224】 Step 2: 【0225】 The device collects user voice and image data and sends it to a cloud server for emotional state analysis. The input is the user's voice and image, and the output is analyzed emotional information. Data processing is performed using voice analysis APIs and facial recognition APIs to estimate emotions. 【0226】 Step 3: 【0227】 The server adjusts the indoor environment's energy settings based on the emotional state. The input at this stage is the emotional information obtained in step 2, and the output is the parameters for the new energy settings. Specifically, it uses a generative AI model to determine instructions such as changing the lighting color or adjusting the air conditioning temperature. 【0228】 Step 4: 【0229】 The server optimizes the energy replenishment schedule for electric transport equipment, taking emotional information into consideration. The input is the emotional state and current energy supply status, while the output is the adjusted charging schedule. It analyzes power supply conditions and usage patterns to schedule the optimal charging timing and mode. 【0230】 Step 5: 【0231】 The server detects energy surpluses and shortages based on collected energy usage data and optimizes energy management. The input is historical energy usage data, and the output is a future energy management plan. A predictive algorithm is applied to propose feasible supply plans and energy-saving measures. 【0232】 In this way, energy management that is sensitive to the user's emotions is implemented throughout the processing steps. 【0233】 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. 【0234】 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. 【0235】 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. 【0236】 [Second Embodiment] 【0237】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0238】 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. 【0239】 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). 【0240】 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. 【0241】 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. 【0242】 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). 【0243】 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. 【0244】 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. 【0245】 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. 【0246】 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. 【0247】 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. 【0248】 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". 【0249】 The present invention aims to streamline and optimize the installation of solar power generation panels and the charging management of electric vehicles in buildings. The embodiments of this system are described below. 【0250】 First, the user uploads the building's blueprints to the system. The blueprints are provided in digitized drawing or data format. Based on this design information, the server analyzes the building's roof shape, orientation, and area. The analyzed information is used for solar radiation forecasting, and the server predicts the amount of solar radiation throughout the year by referring to geographical and meteorological data. 【0251】 Based on this information, the server calculates the optimal placement of solar panels and determines the installation angle and arrangement pattern. The results of this placement optimization are provided to the construction management team, enabling efficient construction. 【0252】 Furthermore, the server retrieves electricity sales reference information from the power market and combines it with predicted power generation to simulate electricity sales revenue. This simulation result is useful for determining the economic feasibility of the power generation system. In addition, construction progress is reported in real time from the terminals, and the server monitors the progress of construction and optimizes resource allocation as needed. 【0253】 For electric vehicle charging, users input their desired charging schedule into the system. Based on this schedule, the server analyzes power usage and provides the optimal charging time. Charging is performed automatically during low-cost periods, promoting efficient energy use. 【0254】 Furthermore, the server constantly monitors panel performance and predicts signs of failure. If performance deteriorates, the system sends an alert to the user, allowing for early maintenance. This proactive maintenance ensures long-term operational stability while maintaining power generation efficiency. 【0255】 As a concrete example, in a certain housing project, using this system allowed the server to streamline the entire process from the design stage to construction management and operation, resulting in high power generation efficiency and economic benefits. 【0256】 The following describes the processing flow. 【0257】 Step 1: 【0258】 The user uploads the building's blueprints to the system in digital format. The server receives this data and activates the building's shape analysis module. 【0259】 Step 2: 【0260】 The server analyzes the blueprints to identify the building's roof shape, orientation, and area. Based on the acquired structural data, it uses a solar radiation prediction module to simulate the amount of solar radiation throughout the year. 【0261】 Step 3: 【0262】 The server references geographic information systems and weather data to correct for solar radiation at specific building locations. This data is then used as a basis for determining the optimal placement of solar power panels. 【0263】 Step 4: 【0264】 The server executes an optimal panel placement algorithm to determine the installation angle and placement pattern. This optimal placement information is sent to the construction team to assist in accurate installation on-site. 【0265】 Step 5: 【0266】 The terminal updates the progress status in real time from the construction site and sends the progress data to the server. The server receives this data, manages construction resources, and optimizes them as needed. 【0267】 Step 6: 【0268】 Users set their electric vehicle charging schedule, entering their desired charging time slots and capacities. Based on this information, the server analyzes power usage and suggests an efficient charging schedule. 【0269】 Step 7: 【0270】 The server constantly monitors panel performance and executes a failure prediction algorithm when an anomaly is detected. If necessary, it sends maintenance notifications to users to encourage early action. 【0271】 Step 8: 【0272】 The server retrieves electricity sales reference information from the power market and integrates it with the results of power generation simulations to predict annual electricity sales revenue. Based on this prediction, it provides users with information to make economic decisions. 【0273】 (Example 1) 【0274】 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". 【0275】 In today's environment, the introduction and management of solar power generation are crucial for achieving sustainable energy use. However, the placement of power generation equipment in buildings, on-site management, and subsequent optimization of energy use require considerable effort and specialized knowledge. Furthermore, there is a need for appropriate market information analysis to maintain power generation efficiency and maximize economic benefits, as well as for the efficient use of electricity. The problem lies in the lack of systems that address these challenges. 【0276】 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. 【0277】 In this invention, the server includes means for analyzing design information and determining the optimal placement of power generation equipment, means for predicting solar radiation, means for optimizing the placement of power generation equipment, means for predicting electricity revenue based on market information, means for monitoring construction progress in real time and managing construction resources, means for automatically optimizing the charging schedule of mobile units, and means for monitoring the performance of power generation equipment and predicting failures. This improves the efficiency of the series of processes and makes it possible to achieve high power generation efficiency and economic convenience. 【0278】 "Design information" refers to digital information related to the design of a building, and specifically includes data on the building's roof shape, orientation, and area. 【0279】 The "power generation device" is a device for converting solar energy into electricity, specifically referring to a solar power generation panel. 【0280】 The "solar radiation amount" indicates the amount of solar energy received at a specific geographical location over a certain period. 【0281】 The "market information" refers to data related to the sale and purchase of electricity in the energy market, specifically including information such as the supply and demand of electricity and the selling price of electricity. 【0282】 The "construction resources" is a general term for the personnel, equipment, materials, etc. required to carry out the installation work of the power generation device in a building. 【0283】 The "mobile object" refers to vehicles such as automobiles that store energy and require charging. 【0284】 The "performance monitoring" is a process of continuously checking the operating status of the power generation device and evaluating whether it is functioning normally. 【0285】 The "fault prediction" refers to a technology that analyzes the data of the power generation device to detect in advance the possibility of future function stops or abnormalities. 【0286】 The system of the present invention aims at the efficient introduction and management of solar power generation in a building. This system comprehensively performs, by means of a plurality of means, from the analysis of design information to the optimal arrangement of the power generation device, the analysis of the energy market, construction management, optimization of charging of mobile objects, and performance monitoring of the power generation device. 【0287】 First, the user uploads the detailed design information of the building to the system in digital form. As a result, this information is transmitted to the server and the analysis is started. The server analyzes the design data using CAD software and extracts the shape, orientation, and area of the roof. Based on this extracted information, the server predicts the solar radiation amount by referring to the geographical database and the meteorological database. 【0288】 Based on solar radiation predictions, the server uses solar power simulation software (e.g., PVsyst) to calculate the optimal placement of power generation equipment. Based on the calculation results, it proposes the optimal installation method for the power generation equipment and provides it to the construction management team. This improves the efficiency of construction work. 【0289】 Furthermore, the server uses energy market information to simulate the economics of selling electricity and presents this to the user. Regarding the charging of mobile devices such as electric vehicles, it optimally manages the supply and demand of electricity based on the charging schedule set by the user. This automatically ensures that charging takes place during off-peak hours when costs are lower. 【0290】 Furthermore, the server constantly monitors the performance of the power generation equipment and predicts signs of failure using a generated AI model. If the output of the power generation equipment decreases, the server sends an alert to the user to encourage early maintenance. This enables the long-term stable operation of the power generation equipment. 【0291】 As a concrete example, the use of this system in a housing project allowed the server to integrate and manage the entire process from the construction phase to the operation phase, achieving high power generation efficiency. As a result, the economic benefits were maximized. 【0292】 An example of a prompt for the generating AI model is, "Based on the house blueprints, calculate the optimal placement of solar panels and maximize power generation efficiency." This prompt prompts the server to automatically generate an efficient placement plan. 【0293】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0294】 Step 1: 【0295】 Users upload building design information to the system in digital format. This provides information about the building's roof shape, orientation, and area. Based on this input data, the server receives the design data and enables subsequent analysis. 【0296】 Step 2: 【0297】 The server analyzes the received design information. Specifically, it uses CAD software to analyze the design data and extract the roof shape, orientation, and area. This data analysis yields meaningful features from the design information. 【0298】 Step 3: 【0299】 The server predicts solar radiation by referencing geographic and meteorological databases. Input data includes roof information and geographical coordinates obtained in step 2. Based on this data, the annual solar radiation calculation is performed. 【0300】 Step 4: 【0301】 The server uses solar power simulation software to calculate the optimal placement of power generation equipment. This process takes predicted solar radiation as input, determines the optimal panel angles and placement patterns, and provides the results to the construction management team. 【0302】 Step 5: 【0303】 The server simulates electricity sales revenue based on market information collected from the energy market. Inputs include predicted power generation and market price data. This allows the user to see the economic potential of the power generation system. 【0304】 Step 6: 【0305】 The terminals report the progress of construction in real time from the site. Using this information, the server monitors the construction status and optimizes the allocation of construction resources as needed. This improves the efficiency of construction. 【0306】 Step 7: 【0307】 The user inputs the charging schedule of the electric vehicle into the system. The server refers to this schedule and the power demand data to calculate the optimal charging timing. As a result, charging is performed during a cost-effective time period. 【0308】 Step 8: 【0309】 The server constantly monitors the performance of the power generation device and uses a generated AI model to predict signs of failure. The input includes real-time output data obtained from the power generation device. When a performance degradation is detected, an alert is sent to the user. As a result, prompt maintenance becomes possible. 【0310】 (Application Example 1) 【0311】 Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal". 【0312】 In modern buildings, it is an important issue to achieve both environmental protection and energy efficiency. In existing systems, it is difficult to optimize energy conversion devices from the building design stage, and there is also a problem that there is a lack of a method to directly make residents understand energy efficiency. Therefore, there is a need for a system that can precisely arrange energy conversion devices, optimize charging resources, and enable residents to easily experience efficient energy use. 【0313】 [[ID=?]] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0314】 In this invention, the server includes means for analyzing the design information of the building to determine the optimal arrangement of energy conversion devices, means for monitoring the construction progress in real time and managing construction resources, and means for visualizing energy efficiency on the information terminal for residents. As a result, sustainable and efficient energy utilization is possible from the building design stage to the operation stage. 【0315】 It seems there is a formatting issue with the "? " in the original text where the tag is located. I've left it as is in the translation. If this was an error in the original, please correct it for a more accurate translation."Building design information" refers to a collection of detailed design drawings and data concerning the structure and function of a building, and serves as the basis for determining the optimal placement of energy conversion devices. 【0316】 An "energy conversion device" is a device that converts natural energy sources such as solar and wind power into other forms of energy, such as electricity. 【0317】 A "solar radiation prediction means" is a device or method that predicts the amount of solar radiation obtained in a given area based on the location of a building and environmental data. 【0318】 "Energy conversion device placement optimization means" refers to a device or method that performs calculations and analyses to determine the optimal placement of energy conversion devices based on the shape and orientation of a building. 【0319】 "Electricity trading information" refers to information regarding the market price of electricity, supply, and demand, and serves as basic data for determining the optimal timing for selling electricity. 【0320】 "Means for monitoring construction progress in real time and managing construction resources" refers to a device or method for tracking the construction process of a building in real time and efficiently allocating the necessary resources. 【0321】 "Means for automatically optimizing a vehicle's charging schedule" refers to a device or method that automatically sets the time and method for efficiently charging a vehicle based on power demand and cost. 【0322】 "Means for monitoring the performance of an energy conversion device and predicting failures" refers to a device or method that constantly monitors the operating status of an energy conversion device and predicts and notifies of failures before abnormalities occur. 【0323】 "Means of visualizing energy efficiency on information terminals for residents" refers to a device or application that displays energy usage and efficiency in an easy-to-understand manner for residents. 【0324】 This invention's system is designed to maximize energy efficiency in buildings, allowing residents to experience its benefits. The server receives building design information and uses AI technology to calculate the optimal placement of energy conversion devices. This process combines weather and geographical data for solar radiation prediction and utilizes Google Earth Engine. Furthermore, because optimizing the placement of conversion devices requires complex data analysis, a high-performance cloud-based tool is employed. 【0325】 During the construction process, the server monitors the progress in real time and optimally allocates resources as needed. This involves collecting data from IoT sensors and managing construction resources using Amazon AWS IoT Core. 【0326】 Furthermore, regarding energy trading data, the server analyzes market trends and notifies users of the optimal timing for electricity trading. Users receive this information using smartphones or smart glasses, and the system is designed to be intuitively understandable. 【0327】 Regarding the performance monitoring of energy conversion equipment, the server constantly checks the operating status of the equipment and predicts failures before any abnormalities occur, sending alerts to the user. This prevents future decreases in power generation and equipment failures, promoting smooth system operation. 【0328】 As a concrete example, the implementation of this system in a certain smart city resulted in residents reducing their monthly electricity costs by approximately 15% and optimizing their energy use. The information terminals for residents are equipped with a function to visualize energy efficiency, allowing residents to check their energy usage in real time. 【0329】 An example of a prompt using a generative AI model is, "Perform real-time data analysis on optimizing solar power generation and present the most cost-effective option for residents." In this way, support is provided in a way that is easy for users to understand. 【0330】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0331】 Step 1: 【0332】 The server receives building design information from the user. The input design information is provided in digital drawing format. The server analyzes this information and extracts the building's roof shape and orientation. This generates the basic data necessary for planning the placement of energy conversion devices. 【0333】 Step 2: 【0334】 The server combines geographical and meteorological data to predict solar radiation. Specifically, it uses Google Earth Engine to predict solar radiation throughout the year. The inputs used are roof shape and location information based on design data, and the output is predicted solar radiation data. 【0335】 Step 3: 【0336】 The server calculates the optimal placement of energy conversion devices based on solar radiation forecast data. AI technology is used in the processing to determine the most efficient panel installation angles and placement patterns. The input is solar radiation forecast data, and the output is the optimal placement plan. 【0337】 Step 4: 【0338】 The server monitors construction progress in real time and manages construction resources. It collects data from IoT sensors and uses Amazon AWS IoT Core to understand the condition of the construction site. This minimizes waste during the construction process. 【0339】 Step 5: 【0340】 The server collects electricity market transaction information and analyzes the optimal timing for electricity trading. Market data is used as input, and the output is recommended information on the most suitable time for trading. Users receive this information via smart devices. 【0341】 Step 6: 【0342】 The terminal visualizes energy efficiency on a resident information display. Energy usage and economic effects are visualized using graphs and other visuals, presented in a format easily understood by residents. Input is energy data from a server, and output is a visualized interface. 【0343】 Step 7: 【0344】 The server constantly monitors the performance of the energy conversion device and predicts failures. It analyzes sensor data and sends alerts to user terminals when an anomaly is detected. This enables rapid response and stable system operation. 【0345】 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. 【0346】 This invention provides an energy management system that not only improves the efficiency of solar power generation and electric vehicle charging in buildings, but also takes user sentiment into consideration. The system begins with an analysis of the roof shape based on design information, and then achieves optimal placement of solar panels and maximizes power generation efficiency. Furthermore, it improves economic efficiency by analyzing electricity market information and predicting appropriate electricity sales revenue. It also includes a function to monitor construction progress in real time and optimize resource management. 【0347】 Furthermore, this system incorporates an emotion engine to analyze the user's emotional state, aiming to optimize energy management. The server uses an emotion recognition algorithm to analyze the user's emotions from voice and image data, and automatically adjusts the energy settings within the home based on the results. For example, if the system detects that the user is stressed, the emotion engine will change the lighting and air conditioning settings to provide a more comfortable environment. 【0348】 Furthermore, the server adjusts the electric vehicle's charging schedule according to the user's emotional state. For example, if the user is relaxed, the charging is set to energy-saving mode and optimized to charge at a comfortable pace. This function reduces energy consumption and contributes to long-term cost savings. 【0349】 Furthermore, the solar power generation system uses the analysis results of the emotion engine to detect energy surpluses and shortages in real time, and predicts and optimizes power consumption. This allows for flexible responses to energy usage patterns within the home, which is expected to improve user satisfaction. 【0350】 This system comprehensively supports the entire energy management process, from the design phase to the operation of buildings, enabling a smarter and more emotionally resonant lifestyle. 【0351】 The following describes the processing flow. 【0352】 Step 1: 【0353】 The user operates a device to input audio and image data into the system. This data is used to understand the user's emotional state. 【0354】 Step 2: 【0355】 The server activates an emotion recognition algorithm and analyzes the captured audio and image data. Based on factors such as voice tone, facial expressions, and posture, it identifies the current emotional state. 【0356】 Step 3: 【0357】 The server uses the analysis results to calculate energy settings appropriate for the user's emotional state. For example, to alleviate stress, it adjusts the color and intensity of the lighting and changes the air conditioning settings. 【0358】 Step 4: 【0359】 If a user is planning to charge their electric vehicle, the server will reset the optimal charging schedule based on the emotion recognition results. If the user needs to relax, it will recommend charging in energy-saving mode. 【0360】 Step 5: 【0361】 The server retrieves the latest information from the electricity market and adjusts the timing of electricity sales. Since energy supply and demand change depending on emotional states, it devises the optimal electricity sales plan. 【0362】 Step 6: 【0363】 The terminal integrates progress information from the construction site with user residency information and transmits the data to the server in real time. This data is used for construction management and energy management. 【0364】 Step 7: 【0365】 The server monitors the performance of the solar panels and, if an anomaly is detected, promptly develops a maintenance plan. It also considers data from the emotion engine to determine the most impactful time to take action. 【0366】 Step 8: 【0367】 The server oversees overall energy usage, incorporates insights from the emotion engine, and then executes optimization algorithms to manage and maintain the living environment in the most comfortable way possible at all times. 【0368】 (Example 2) 【0369】 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". 【0370】 In conventional energy management systems, it was difficult to simultaneously achieve maximum efficiency in solar power generation, real-time management of construction progress, effective charging management of electric vehicles, and optimization of the operating environment while considering user sentiment. As a result, this often led to energy waste, increased costs, and decreased user satisfaction. 【0371】 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. 【0372】 In this invention, the server includes means for analyzing design information and determining the optimal placement of power generation equipment, means for predicting solar radiation, means for optimizing the placement, means for predicting electricity sales revenue based on electricity sales reference information, means for monitoring construction progress in real time and managing construction resources, means for analyzing the user's emotional state using an emotion recognition algorithm and automatically optimizing the operating environment, means for optimizing the electric vehicle charging schedule according to the emotional state, and means for monitoring the performance of power generation equipment and performing fault prediction. This enables more efficient energy management, improved user comfort, and cost reduction. 【0373】 "Design information" is a general term for detailed information such as drawings, specifications, materials, and dimensions necessary for the construction of a building. 【0374】 A "power generation device" is a device that generates electricity using sunlight, and mainly refers to solar panels. 【0375】 "Solar radiation" refers to the amount of solar energy that reaches a surface per unit time. 【0376】 "Placement" refers to the location and method for properly installing solar panels and other equipment. 【0377】 "Electricity sales reference information" refers to information regarding trends in the electricity market and electricity prices. 【0378】 "Construction progress" refers to information indicating the current status of a construction project. 【0379】 "Construction resources" is a general term for the personnel, materials, equipment, and other resources necessary for a construction project. 【0380】 An "emotion recognition algorithm" is a computational processing method for analyzing a person's emotional state based on audio or image data. 【0381】 "Operating environment" refers to the physical conditions such as lighting, temperature, and acoustics in the space where the user lives or uses the space. 【0382】 An "electric vehicle" is a vehicle that moves using electricity as its power source, and mainly refers to an electric car. 【0383】 A "charging schedule" is a plan for systematically determining the time and speed at which electric vehicle batteries are charged. 【0384】 "Failure prediction" is a technology that analyzes equipment operation data to estimate signs of failure and the timing of failures in advance. 【0385】 In embodiments of the present invention, the energy management system integrates multiple technologies to achieve efficient energy use in buildings. In this system, a server plays a central role in collecting and analyzing information from various data sources. 【0386】 The server first receives design information. This design information includes building blueprints and specifications, and the server analyzes the roof shape and area based on this information. The server then uses 3D modeling software (e.g., AutoCAD) to perform simulations to determine the optimal placement of solar panels. During this process, it refers to an external database containing weather data to predict solar radiation. 【0387】 The server also gathers information about the electricity market and uses it to predict electricity sales revenue. This prediction is made using data analysis algorithms, providing the optimal electricity sales strategy based on historical electricity price trends and demand curves. 【0388】 IoT sensors are installed at construction sites, transmitting real-time information on construction progress to a server. The server uses this information to optimize the allocation of construction resources and improve construction efficiency. 【0389】 To enhance user comfort, the server implements an emotion recognition algorithm that analyzes the user's voice and image data. This allows it to determine whether the user is stressed or relaxed. For example, if the user is stressed, the server adjusts the lighting and air conditioning settings to provide a more comfortable environment. 【0390】 Furthermore, the server manages electric vehicle charging, flexibly adjusting the charging schedule according to the user's emotional state. For example, it can set the charging schedule to nighttime hours to encourage efficient charging during times of low electricity demand. 【0391】 Furthermore, the server monitors the performance of the power generation equipment and predicts failures as needed. This function helps prevent mechanical problems and contributes to improving the long-term reliability of the system. 【0392】 As a concrete example, when emotion recognition determines that a user is "feeling stressed," the server can respond by dimming the lights and playing music to provide a comfortable environment. 【0393】 Examples of prompt messages are as follows: 【0394】 "How can I optimize the lighting settings in this residential system when users experience stress?" 【0395】 Thus, the system of the present invention simultaneously achieves improved energy efficiency and enhanced quality of life for users through the integration of technologies. 【0396】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0397】 Step 1: 【0398】 The server receives building design information. A 3D design software file is provided as input. The server analyzes this file and extracts data such as roof shape, area, and orientation. Analysis data necessary for solar panel placement is generated as output. 3D modeling software (e.g., general-purpose design software) is used for the analysis. 【0399】 Step 2: 【0400】 The server retrieves data from a weather database to predict solar radiation. Location information and weather data are provided as input. The server uses a solar radiation calculation algorithm to calculate the predicted daily solar radiation. This data calculation includes calculating sunshine duration based on location information. The output is predicted solar radiation data. 【0401】 Step 3: 【0402】 The server calculates the optimal placement of solar panels based on design information and solar radiation data. Roof shape data and solar radiation data are used as input. The server utilizes simulation tools to generate a placement plan that takes shading into account. The output includes a panel placement diagram and data showing the maximum power generation efficiency. In this process, the shading simulation takes into account environmental information surrounding the building. 【0403】 Step 4: 【0404】 The server collects electricity market information and predicts electricity sales revenue. It requires market price data and demand data as input. The server uses a machine learning model to calculate the optimal electricity sales strategy based on this data. The output is predicted electricity sales revenue data. 【0405】 Step 5: 【0406】 The server receives real-time sensor data from the construction site and manages the construction progress. The input is data from IoT sensors installed at the construction site. The server uses a resource management algorithm to analyze the construction progress and allocate resources efficiently. The output is an optimized construction schedule. 【0407】 Step 6: 【0408】 The server collects user emotion data from the microphone and camera and analyzes it using an emotion recognition algorithm. Audio and image data are provided as input. The server uses an emotion analysis model to determine the user's emotional state. Data indicating the emotional state is generated as output. This data is used in the next step. 【0409】 Step 7: 【0410】 The server optimizes the operating environment within the home based on the user's emotional state. Emotional state data is used as input. The server automatically adjusts the air conditioning and lighting settings to create an environment that the user finds comfortable. The output is the adjusted air conditioning and lighting settings. 【0411】 Step 8: 【0412】 The server optimizes the electric vehicle's charging schedule based on the user's emotional state. The input requires user emotional data and the vehicle's charging status. Based on this data, the server creates an efficient charging plan that aligns with the user's lifestyle. The output is the optimized charging schedule. 【0413】 Step 9: 【0414】 The server monitors the performance of the power generation equipment and performs fault prediction as needed. Operational data from the generator is provided as input. The server utilizes a fault prediction model to detect equipment abnormalities in advance. The output is risk data indicating the likelihood of failure. This data is used in maintenance planning. 【0415】 (Application Example 2) 【0416】 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." 【0417】 Conventional energy management systems have not adequately achieved the efficiency of solar energy collection in buildings and energy supply to electric transportation equipment, and in particular, they lack systematic management that takes into account the impact of users' emotional states on energy consumption. Therefore, there has been a challenge in optimizing energy use. 【0418】 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. 【0419】 In this invention, the server includes means for analyzing building design information and determining the optimal placement of solar energy collection devices, means for predicting solar radiation energy, means for optimizing the placement of energy collection devices, means for predicting electricity trading revenue based on electricity trading reference information, means for monitoring construction progress in real time and managing construction resources, means for automatically optimizing the energy supply schedule for electric transport equipment, means for analyzing the user's emotional state and adjusting energy management based on the results, means for detecting energy surplus or deficit based on emotional analysis and performing electricity usage prediction and optimization, and means for monitoring the performance of energy collection devices and performing failure prediction. This enables flexible and efficient energy management that takes user emotions into consideration. 【0420】 "Analyzing building design information" means analyzing detailed information about the structure and layout of a building to help improve energy efficiency. 【0421】 A "solar energy collection device" is a device that efficiently converts sunlight into energy, and is usually installed on the roof or exterior wall of a building. 【0422】 "Optimizing the placement of energy collection devices" is the process of calculating and adjusting the shape, position, angle, and other factors necessary for energy collection devices to function as efficiently as possible. 【0423】 "Solar radiation energy forecasting" involves predicting the amount of radiant energy from the sun and providing information to maximize the operational efficiency of energy collection devices. 【0424】 "Electricity trading reference information" refers to information about transactions in the electricity market, including electricity prices, demand, and supply conditions. 【0425】 "Optimizing the energy replenishment schedule for electric transport equipment" means developing a charging plan that ensures electric transport equipment is charged efficiently and energy consumption is minimized. 【0426】 "Analyzing emotional states" involves analyzing a user's emotional state based on their voice, facial expressions, and actions, and then utilizing the results as data. 【0427】 "Detecting energy surplus or deficit based on emotion analysis" is a method for identifying energy surplus or deficit based on the user's emotions and achieving optimal energy management. 【0428】 "Monitoring the performance of energy collection devices" is a process that constantly checks whether the collection devices are functioning correctly and enables immediate action if any problems arise. 【0429】 This invention is a system for optimizing energy efficiency in buildings. The server executes software that determines the optimal placement of solar energy collection devices based on the building's design information and performs solar radiation energy prediction. This software takes the design information as input and performs the necessary analysis to maximize solar energy collection efficiency. Furthermore, it performs simulations to optimize the placement of the collection devices and calculates their position and angle. 【0430】 The device uses voice analysis APIs and facial recognition APIs to analyze the user's emotional state. Specifically, the device collects voice and image data and sends the data to the server to reveal the user's emotional state. For example, it uses the Microsoft Azure Face API to analyze the user's facial expressions and estimate their emotional state. 【0431】 Subsequently, the server automatically adjusts energy management based on the user's emotional state. For example, if the user is relaxed, it will change the lighting color to a warmer tone and set the air conditioning temperature to a comfortable range. It will also flexibly adjust the energy replenishment schedule for electric transport equipment to optimize energy consumption. 【0432】 This system achieves optimal energy management by analyzing energy usage data and applying predictive algorithms to detect energy surpluses and deficits based on emotion analysis. Thus, in this embodiment, energy management that takes user emotions into account is comprehensively supported. 【0433】 An example of a prompt would be, "Please tell me the appropriate energy setting for you when you are relaxing." This prompt allows the generating AI model to suggest an appropriate energy management method. 【0434】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0435】 Step 1: 【0436】 The server analyzes the building's design information to determine the optimal placement of solar energy harvesting devices. The input to this process is the building's blueprint, and the output is the specific location information of each harvesting device. Based on the input data, simulation software is used to calculate the optimal placement that maximizes harvesting efficiency. 【0437】 Step 2: 【0438】 The device collects user voice and image data and sends it to a cloud server for emotional state analysis. The input is the user's voice and image, and the output is analyzed emotional information. Data processing is performed using voice analysis APIs and facial recognition APIs to estimate emotions. 【0439】 Step 3: 【0440】 The server adjusts the indoor environment's energy settings based on the emotional state. The input at this stage is the emotional information obtained in step 2, and the output is the parameters for the new energy settings. Specifically, it uses a generative AI model to determine instructions such as changing the lighting color or adjusting the air conditioning temperature. 【0441】 Step 4: 【0442】 The server optimizes the energy replenishment schedule for electric transport equipment, taking emotional information into consideration. The input is the emotional state and current energy supply status, while the output is the adjusted charging schedule. It analyzes power supply conditions and usage patterns to schedule the optimal charging timing and mode. 【0443】 Step 5: 【0444】 The server detects energy surpluses and shortages based on collected energy usage data and optimizes energy management. The input is historical energy usage data, and the output is a future energy management plan. A predictive algorithm is applied to propose feasible supply plans and energy-saving measures. 【0445】 In this way, energy management that is sensitive to the user's emotions is implemented throughout the processing steps. 【0446】 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. 【0447】 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. 【0448】 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. 【0449】 [Third Embodiment] 【0450】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0451】 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. 【0452】 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). 【0453】 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. 【0454】 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. 【0455】 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). 【0456】 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. 【0457】 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. 【0458】 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. 【0459】 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. 【0460】 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. 【0461】 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". 【0462】 The present invention aims to streamline and optimize the installation of solar power generation panels and the charging management of electric vehicles in buildings. The embodiments of this system are described below. 【0463】 First, the user uploads the building's blueprints to the system. The blueprints are provided in digitized drawing or data format. Based on this design information, the server analyzes the building's roof shape, orientation, and area. The analyzed information is used for solar radiation forecasting, and the server predicts the amount of solar radiation throughout the year by referring to geographical and meteorological data. 【0464】 Based on this information, the server calculates the optimal placement of solar panels and determines the installation angle and arrangement pattern. The results of this placement optimization are provided to the construction management team, enabling efficient construction. 【0465】 Furthermore, the server retrieves electricity sales reference information from the power market and combines it with predicted power generation to simulate electricity sales revenue. This simulation result is useful for determining the economic feasibility of the power generation system. In addition, construction progress is reported in real time from the terminals, and the server monitors the progress of construction and optimizes resource allocation as needed. 【0466】 For electric vehicle charging, users input their desired charging schedule into the system. Based on this schedule, the server analyzes power usage and provides the optimal charging time. Charging is performed automatically during low-cost periods, promoting efficient energy use. 【0467】 Furthermore, the server constantly monitors panel performance and predicts signs of failure. If performance deteriorates, the system sends an alert to the user, allowing for early maintenance. This proactive maintenance ensures long-term operational stability while maintaining power generation efficiency. 【0468】 As a concrete example, in a certain housing project, using this system allowed the server to streamline the entire process from the design stage to construction management and operation, resulting in high power generation efficiency and economic benefits. 【0469】 The following describes the processing flow. 【0470】 Step 1: 【0471】 The user uploads the building's blueprints to the system in digital format. The server receives this data and activates the building's shape analysis module. 【0472】 Step 2: 【0473】 The server analyzes the blueprints to identify the building's roof shape, orientation, and area. Based on the acquired structural data, it uses a solar radiation prediction module to simulate the amount of solar radiation throughout the year. 【0474】 Step 3: 【0475】 The server references geographic information systems and weather data to correct for solar radiation at specific building locations. This data is then used as a basis for determining the optimal placement of solar power panels. 【0476】 Step 4: 【0477】 The server executes an optimal panel placement algorithm to determine the installation angle and placement pattern. This optimal placement information is sent to the construction team to assist in accurate installation on-site. 【0478】 Step 5: 【0479】 The terminal updates the progress status in real time from the construction site and sends the progress data to the server. The server receives this data, manages construction resources, and optimizes them as needed. 【0480】 Step 6: 【0481】 Users set their electric vehicle charging schedule, entering their desired charging time slots and capacities. Based on this information, the server analyzes power usage and suggests an efficient charging schedule. 【0482】 Step 7: 【0483】 The server constantly monitors panel performance and executes a failure prediction algorithm when an anomaly is detected. If necessary, it sends maintenance notifications to users to encourage early action. 【0484】 Step 8: 【0485】 The server retrieves electricity sales reference information from the power market and integrates it with the results of power generation simulations to predict annual electricity sales revenue. Based on this prediction, it provides users with information to make economic decisions. 【0486】 (Example 1) 【0487】 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." 【0488】 In today's environment, the introduction and management of solar power generation are crucial for achieving sustainable energy use. However, the placement of power generation equipment in buildings, on-site management, and subsequent optimization of energy use require considerable effort and specialized knowledge. Furthermore, there is a need for appropriate market information analysis to maintain power generation efficiency and maximize economic benefits, as well as for the efficient use of electricity. The problem lies in the lack of systems that address these challenges. 【0489】 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. 【0490】 In this invention, the server includes means for analyzing design information and determining the optimal placement of power generation equipment, means for predicting solar radiation, means for optimizing the placement of power generation equipment, means for predicting electricity revenue based on market information, means for monitoring construction progress in real time and managing construction resources, means for automatically optimizing the charging schedule of mobile units, and means for monitoring the performance of power generation equipment and predicting failures. This improves the efficiency of the series of processes and makes it possible to achieve high power generation efficiency and economic convenience. 【0491】 "Design information" refers to digital information related to the design of a building, and specifically includes data on the building's roof shape, orientation, and area. 【0492】 A "power generation device" is a device that converts solar energy into electricity, and specifically refers to a solar power generation panel. 【0493】 "Solar radiation" refers to the amount of solar energy received over a certain period of time at a specific geographical location. 【0494】 "Market information" refers to data related to the buying and selling of electricity in the energy market, and specifically includes information such as electricity supply and demand, and electricity selling prices. 【0495】 "Construction resources" is a general term for the personnel, equipment, materials, and other resources necessary to carry out the installation work of power generation equipment in a building. 【0496】 "Mobile vehicles" refer to vehicles such as automobiles that need to store energy and be charged. 【0497】 "Performance monitoring" is a process of continuously checking the operating status of power generation equipment and evaluating whether it is functioning properly. 【0498】 "Failure prediction" refers to a technology that analyzes data from power generation equipment to detect in advance the possibility of future malfunctions or abnormalities. 【0499】 The present invention aims to efficiently introduce and manage solar power generation in buildings. This system comprehensively performs tasks ranging from analysis of design information and optimal placement of power generation equipment to energy market analysis, construction management, optimization of mobile equipment charging, and performance monitoring of power generation equipment through multiple means. 【0500】 First, the user uploads detailed design information of the building to the system in digital format. This information is then sent to the server, and the analysis begins. The server uses CAD software to analyze the design data and extract the roof shape, orientation, and area. Based on this extracted information, the server predicts the amount of solar radiation by referring to geographic and meteorological databases. 【0501】 Based on solar radiation predictions, the server uses solar power simulation software (e.g., PVsyst) to calculate the optimal placement of power generation equipment. Based on the calculation results, it proposes the optimal installation method for the power generation equipment and provides it to the construction management team. This improves the efficiency of construction work. 【0502】 Furthermore, the server uses energy market information to simulate the economics of selling electricity and presents this to the user. Regarding the charging of mobile devices such as electric vehicles, it optimally manages the supply and demand of electricity based on the charging schedule set by the user. This automatically ensures that charging takes place during off-peak hours when costs are lower. 【0503】 Furthermore, the server constantly monitors the performance of the power generation equipment and predicts signs of failure using a generated AI model. If the output of the power generation equipment decreases, the server sends an alert to the user to encourage early maintenance. This enables the long-term stable operation of the power generation equipment. 【0504】 As a concrete example, the use of this system in a housing project allowed the server to integrate and manage the entire process from the construction phase to the operation phase, achieving high power generation efficiency. As a result, the economic benefits were maximized. 【0505】 An example of a prompt for the generating AI model is, "Based on the house blueprints, calculate the optimal placement of solar panels and maximize power generation efficiency." This prompt prompts the server to automatically generate an efficient placement plan. 【0506】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0507】 Step 1: 【0508】 Users upload building design information to the system in digital format. This provides information about the building's roof shape, orientation, and area. Based on this input data, the server receives the design data and enables subsequent analysis. 【0509】 Step 2: 【0510】 The server analyzes the received design information. Specifically, it uses CAD software to analyze the design data and extract the roof shape, orientation, and area. This data analysis yields meaningful features from the design information. 【0511】 Step 3: 【0512】 The server predicts solar radiation by referencing geographic and meteorological databases. Input data includes roof information and geographical coordinates obtained in step 2. Based on this data, the annual solar radiation calculation is performed. 【0513】 Step 4: 【0514】 The server uses solar power simulation software to calculate the optimal placement of power generation equipment. This process takes predicted solar radiation as input, determines the optimal panel angles and placement patterns, and provides the results to the construction management team. 【0515】 Step 5: 【0516】 The server simulates electricity sales revenue based on market information collected from the energy market. Inputs include predicted power generation and market price data. This allows the user to see the economic potential of the power generation system. 【0517】 Step 6: 【0518】 The terminals report the progress of construction in real time from the site. Using this information, the server monitors the construction status and optimizes the allocation of construction resources as needed. This improves the efficiency of construction. 【0519】 Step 7: 【0520】 The user enters the electric vehicle charging schedule into the system. The server then references this schedule and power demand data to calculate the optimal charging time. This ensures that charging takes place during cost-effective hours. 【0521】 Step 8: 【0522】 The server continuously monitors the performance of the power generation equipment and uses a generative AI model to predict signs of failure. Input includes real-time output data acquired from the power generation equipment. When a performance degradation is detected, an alert is sent to the user, enabling prompt maintenance. 【0523】 (Application Example 1) 【0524】 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." 【0525】 Balancing environmental protection and energy efficiency in modern buildings is a crucial challenge. Existing systems struggle to optimize energy conversion devices from the design stage, and there's a lack of methods to directly help residents understand energy efficiency. Therefore, there's a need for precise placement of energy conversion devices, optimization of charging resources, and systems that allow residents to easily experience efficient energy use. 【0526】 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. 【0527】 In this invention, the server includes means for analyzing building design information and determining the optimal placement of energy conversion devices, means for monitoring construction progress in real time and managing construction resources, and means for visualizing energy efficiency on information terminals for residents. This enables sustainable and efficient energy utilization from the design stage to the operation stage of the building. 【0528】 "Building design information" refers to a collection of detailed design drawings and data concerning the structure and function of a building, and serves as the basis for determining the optimal placement of energy conversion devices. 【0529】 An "energy conversion device" is a device that converts natural energy sources such as solar and wind power into other forms of energy, such as electricity. 【0530】 A "solar radiation prediction means" is a device or method that predicts the amount of solar radiation obtained in a given area based on the location of a building and environmental data. 【0531】 "Energy conversion device placement optimization means" refers to a device or method that performs calculations and analyses to determine the optimal placement of energy conversion devices based on the shape and orientation of a building. 【0532】 "Electricity trading information" refers to information regarding the market price of electricity, supply, and demand, and serves as basic data for determining the optimal timing for selling electricity. 【0533】 "Means for monitoring construction progress in real time and managing construction resources" refers to a device or method for tracking the construction process of a building in real time and efficiently allocating the necessary resources. 【0534】 "Means for automatically optimizing a vehicle's charging schedule" refers to a device or method that automatically sets the time and method for efficiently charging a vehicle based on power demand and cost. 【0535】 "Means for monitoring the performance of an energy conversion device and predicting failures" refers to a device or method that constantly monitors the operating status of an energy conversion device and predicts and notifies of failures before abnormalities occur. 【0536】 "Means of visualizing energy efficiency on information terminals for residents" refers to a device or application that displays energy usage and efficiency in an easy-to-understand manner for residents. 【0537】 This invention's system is designed to maximize energy efficiency in buildings, allowing residents to experience its benefits. The server receives building design information and uses AI technology to calculate the optimal placement of energy conversion devices. This process combines weather and geographical data for solar radiation prediction and utilizes Google Earth Engine. Furthermore, because optimizing the placement of conversion devices requires complex data analysis, a high-performance cloud-based tool is employed. 【0538】 During the construction process, the server monitors the progress in real time and optimally allocates resources as needed. This involves collecting data from IoT sensors and managing construction resources using Amazon AWS IoT Core. 【0539】 Furthermore, regarding energy trading data, the server analyzes market trends and notifies users of the optimal timing for electricity trading. Users receive this information using smartphones or smart glasses, and the system is designed to be intuitively understandable. 【0540】 Regarding the performance monitoring of energy conversion equipment, the server constantly checks the operating status of the equipment and predicts failures before any abnormalities occur, sending alerts to the user. This prevents future decreases in power generation and equipment failures, promoting smooth system operation. 【0541】 As a concrete example, the implementation of this system in a certain smart city resulted in residents reducing their monthly electricity costs by approximately 15% and optimizing their energy use. The information terminals for residents are equipped with a function to visualize energy efficiency, allowing residents to check their energy usage in real time. 【0542】 An example of a prompt using a generative AI model is, "Perform real-time data analysis on optimizing solar power generation and present the most cost-effective option for residents." In this way, support is provided in a way that is easy for users to understand. 【0543】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0544】 Step 1: 【0545】 The server receives building design information from the user. The input design information is provided in digital drawing format. The server analyzes this information and extracts the building's roof shape and orientation. This generates the basic data necessary for planning the placement of energy conversion devices. 【0546】 Step 2: 【0547】 The server combines geographical and meteorological data to predict solar radiation. Specifically, it uses Google Earth Engine to predict solar radiation throughout the year. The inputs used are roof shape and location information based on design data, and the output is predicted solar radiation data. 【0548】 Step 3: 【0549】 The server calculates the optimal placement of energy conversion devices based on solar radiation forecast data. AI technology is used in the processing to determine the most efficient panel installation angles and placement patterns. The input is solar radiation forecast data, and the output is the optimal placement plan. 【0550】 Step 4: 【0551】 The server monitors construction progress in real time and manages construction resources. It collects data from IoT sensors and uses Amazon AWS IoT Core to understand the condition of the construction site. This minimizes waste during the construction process. 【0552】 Step 5: 【0553】 The server collects electricity market transaction information and analyzes the optimal timing for electricity trading. Market data is used as input, and the output is recommended information on the most suitable time for trading. Users receive this information via smart devices. 【0554】 Step 6: 【0555】 The terminal visualizes energy efficiency on a resident information display. Energy usage and economic effects are visualized using graphs and other visuals, presented in a format easily understood by residents. Input is energy data from a server, and output is a visualized interface. 【0556】 Step 7: 【0557】 The server constantly monitors the performance of the energy conversion device and predicts failures. It analyzes sensor data and sends alerts to user terminals when an anomaly is detected. This enables rapid response and stable system operation. 【0558】 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. 【0559】 This invention provides an energy management system that not only improves the efficiency of solar power generation and electric vehicle charging in buildings, but also takes user sentiment into consideration. The system begins with an analysis of the roof shape based on design information, and then achieves optimal placement of solar panels and maximizes power generation efficiency. Furthermore, it improves economic efficiency by analyzing electricity market information and predicting appropriate electricity sales revenue. It also includes a function to monitor construction progress in real time and optimize resource management. 【0560】 Furthermore, this system incorporates an emotion engine to analyze the user's emotional state, aiming to optimize energy management. The server uses an emotion recognition algorithm to analyze the user's emotions from voice and image data, and automatically adjusts the energy settings within the home based on the results. For example, if the system detects that the user is stressed, the emotion engine will change the lighting and air conditioning settings to provide a more comfortable environment. 【0561】 Furthermore, the server adjusts the electric vehicle's charging schedule according to the user's emotional state. For example, if the user is relaxed, the charging is set to energy-saving mode and optimized to charge at a comfortable pace. This function reduces energy consumption and contributes to long-term cost savings. 【0562】 Furthermore, the solar power generation system uses the analysis results of the emotion engine to detect energy surpluses and shortages in real time, and predicts and optimizes power consumption. This allows for flexible responses to energy usage patterns within the home, which is expected to improve user satisfaction. 【0563】 This system comprehensively supports the entire energy management process, from the design phase to the operation of buildings, enabling a smarter and more emotionally resonant lifestyle. 【0564】 The following describes the processing flow. 【0565】 Step 1: 【0566】 The user operates a device to input audio and image data into the system. This data is used to understand the user's emotional state. 【0567】 Step 2: 【0568】 The server activates an emotion recognition algorithm and analyzes the captured audio and image data. Based on factors such as voice tone, facial expressions, and posture, it identifies the current emotional state. 【0569】 Step 3: 【0570】 The server uses the analysis results to calculate energy settings appropriate for the user's emotional state. For example, to alleviate stress, it adjusts the color and intensity of the lighting and changes the air conditioning settings. 【0571】 Step 4: 【0572】 If a user is planning to charge their electric vehicle, the server will reset the optimal charging schedule based on the emotion recognition results. If the user needs to relax, it will recommend charging in energy-saving mode. 【0573】 Step 5: 【0574】 The server retrieves the latest information from the electricity market and adjusts the timing of electricity sales. Since energy supply and demand change depending on emotional states, it devises the optimal electricity sales plan. 【0575】 Step 6: 【0576】 The terminal integrates progress information from the construction site with user residency information and transmits the data to the server in real time. This data is used for construction management and energy management. 【0577】 Step 7: 【0578】 The server monitors the performance of the solar panels and, if an anomaly is detected, promptly develops a maintenance plan. It also considers data from the emotion engine to determine the most impactful time to take action. 【0579】 Step 8: 【0580】 The server oversees overall energy usage, incorporates insights from the emotion engine, and then executes optimization algorithms to manage and maintain the living environment in the most comfortable way possible at all times. 【0581】 (Example 2) 【0582】 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." 【0583】 In conventional energy management systems, it was difficult to simultaneously achieve maximum efficiency in solar power generation, real-time management of construction progress, effective charging management of electric vehicles, and optimization of the operating environment while considering user sentiment. As a result, this often led to energy waste, increased costs, and decreased user satisfaction. 【0584】 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. 【0585】 In this invention, the server includes means for analyzing design information and determining the optimal placement of power generation equipment, means for predicting solar radiation, means for optimizing the placement, means for predicting electricity sales revenue based on electricity sales reference information, means for monitoring construction progress in real time and managing construction resources, means for analyzing the user's emotional state using an emotion recognition algorithm and automatically optimizing the operating environment, means for optimizing the electric vehicle charging schedule according to the emotional state, and means for monitoring the performance of power generation equipment and performing fault prediction. This enables more efficient energy management, improved user comfort, and cost reduction. 【0586】 "Design information" is a general term for detailed information such as drawings, specifications, materials, and dimensions necessary for the construction of a building. 【0587】 A "power generation device" is a device that generates electricity using sunlight, and mainly refers to solar panels. 【0588】 "Solar radiation" refers to the amount of solar energy that reaches a surface per unit time. 【0589】 "Placement" refers to the location and method for properly installing solar panels and other equipment. 【0590】 "Electricity sales reference information" refers to information regarding trends in the electricity market and electricity prices. 【0591】 "Construction progress" refers to information indicating the current status of a construction project. 【0592】 "Construction resources" is a general term for the personnel, materials, equipment, and other resources necessary for a construction project. 【0593】 An "emotion recognition algorithm" is a computational processing method for analyzing a person's emotional state based on audio or image data. 【0594】 "Operating environment" refers to the physical conditions such as lighting, temperature, and acoustics in the space where the user lives or uses the space. 【0595】 An "electric vehicle" is a vehicle that moves using electricity as its power source, and mainly refers to an electric car. 【0596】 A "charging schedule" is a plan for systematically determining the time and speed at which to charge the batteries of an electric vehicle. 【0597】 "Failure prediction" is a technology that analyzes equipment operation data to estimate signs of failure and the timing of failures in advance. 【0598】 In embodiments of the present invention, the energy management system integrates multiple technologies to achieve efficient energy use in buildings. In this system, a server plays a central role in collecting and analyzing information from various data sources. 【0599】 The server first receives design information. This design information includes building blueprints and specifications, and the server analyzes the roof shape and area based on this information. The server then uses 3D modeling software (e.g., AutoCAD) to perform simulations to determine the optimal placement of solar panels. During this process, it refers to an external database containing weather data to predict solar radiation. 【0600】 The server also gathers information about the electricity market and uses it to predict electricity sales revenue. This prediction is made using data analysis algorithms, providing the optimal electricity sales strategy based on historical electricity price trends and demand curves. 【0601】 IoT sensors are installed at construction sites, transmitting real-time information on construction progress to a server. The server uses this information to optimize the allocation of construction resources and improve construction efficiency. 【0602】 To enhance user comfort, the server implements an emotion recognition algorithm that analyzes the user's voice and image data. This allows it to determine whether the user is stressed or relaxed. For example, if the user is stressed, the server adjusts the lighting and air conditioning settings to provide a more comfortable environment. 【0603】 Furthermore, the server manages electric vehicle charging, flexibly adjusting the charging schedule according to the user's emotional state. For example, it can set the charging schedule to nighttime hours to encourage efficient charging during times of low electricity demand. 【0604】 Furthermore, the server monitors the performance of the power generation equipment and predicts failures as needed. This function helps prevent mechanical problems and contributes to improving the long-term reliability of the system. 【0605】 As a concrete example, when emotion recognition determines that a user is "feeling stressed," the server can respond by dimming the lights and playing music to provide a comfortable environment. 【0606】 Examples of prompt messages are as follows: 【0607】 "How can I optimize the lighting settings in this residential system when users experience stress?" 【0608】 Thus, the system of the present invention simultaneously achieves improved energy efficiency and enhanced quality of life for users through the integration of technologies. 【0609】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0610】 Step 1: 【0611】 The server receives building design information. A 3D design software file is provided as input. The server analyzes this file and extracts data such as roof shape, area, and orientation. Analysis data necessary for solar panel placement is generated as output. 3D modeling software (e.g., general-purpose design software) is used for the analysis. 【0612】 Step 2: 【0613】 The server retrieves data from a weather database to predict solar radiation. Location information and weather data are provided as input. The server uses a solar radiation calculation algorithm to calculate the predicted daily solar radiation. This data calculation includes calculating sunshine duration based on location information. The output is predicted solar radiation data. 【0614】 Step 3: 【0615】 The server calculates the optimal placement of solar panels based on design information and solar radiation data. Roof shape data and solar radiation data are used as input. The server utilizes simulation tools to generate a placement plan that takes shading into account. The output includes a panel placement diagram and data showing the maximum power generation efficiency. In this process, the shading simulation takes into account environmental information surrounding the building. 【0616】 Step 4: 【0617】 The server collects electricity market information and predicts electricity sales revenue. It requires market price data and demand data as input. The server uses a machine learning model to calculate the optimal electricity sales strategy based on this data. The output is predicted electricity sales revenue data. 【0618】 Step 5: 【0619】 The server receives real-time sensor data from the construction site and manages the construction progress. The input is data from IoT sensors installed at the construction site. The server uses a resource management algorithm to analyze the construction progress and allocate resources efficiently. The output is an optimized construction schedule. 【0620】 Step 6: 【0621】 The server collects user emotion data from the microphone and camera and analyzes it using an emotion recognition algorithm. Audio and image data are provided as input. The server uses an emotion analysis model to determine the user's emotional state. Data indicating the emotional state is generated as output. This data is used in the next step. 【0622】 Step 7: 【0623】 The server optimizes the operating environment within the home based on the user's emotional state. Emotional state data is used as input. The server automatically adjusts the air conditioning and lighting settings to create an environment that the user finds comfortable. The output is the adjusted air conditioning and lighting settings. 【0624】 Step 8: 【0625】 The server optimizes the electric vehicle's charging schedule based on the user's emotional state. The input requires user emotional data and the vehicle's charging status. Based on this data, the server creates an efficient charging plan that aligns with the user's lifestyle. The output is the optimized charging schedule. 【0626】 Step 9: 【0627】 The server monitors the performance of the power generation equipment and performs fault prediction as needed. Operational data from the generator is provided as input. The server utilizes a fault prediction model to detect equipment abnormalities in advance. The output is risk data indicating the likelihood of failure. This data is used in maintenance planning. 【0628】 (Application Example 2) 【0629】 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." 【0630】 Conventional energy management systems have not adequately achieved the efficiency of solar energy collection in buildings and energy supply to electric transportation equipment, and in particular, they lack systematic management that takes into account the impact of users' emotional states on energy consumption. Therefore, there has been a challenge in optimizing energy use. 【0631】 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. 【0632】 In this invention, the server includes means for analyzing building design information and determining the optimal placement of solar energy collection devices, means for predicting solar radiation energy, means for optimizing the placement of energy collection devices, means for predicting electricity trading revenue based on electricity trading reference information, means for monitoring construction progress in real time and managing construction resources, means for automatically optimizing the energy supply schedule for electric transport equipment, means for analyzing the user's emotional state and adjusting energy management based on the results, means for detecting energy surplus or deficit based on emotional analysis and performing electricity usage prediction and optimization, and means for monitoring the performance of energy collection devices and performing failure prediction. This enables flexible and efficient energy management that takes user emotions into consideration. 【0633】 "Analyzing building design information" means analyzing detailed information about the structure and layout of a building to help improve energy efficiency. 【0634】 A "solar energy collection device" is a device that efficiently converts sunlight into energy, and is usually installed on the roof or exterior wall of a building. 【0635】 "Optimizing the placement of energy collection devices" is the process of calculating and adjusting the shape, position, angle, and other factors necessary for energy collection devices to function as efficiently as possible. 【0636】 "Solar radiation energy forecasting" involves predicting the amount of radiant energy from the sun and providing information to maximize the operational efficiency of energy collection devices. 【0637】 "Electricity trading reference information" refers to information about transactions in the electricity market, including electricity prices, demand, and supply conditions. 【0638】 "Optimizing the energy replenishment schedule for electric transport equipment" means developing a charging plan that ensures electric transport equipment is charged efficiently and energy consumption is minimized. 【0639】 "Analyzing emotional states" involves analyzing a user's emotional state based on their voice, facial expressions, and actions, and then utilizing the results as data. 【0640】 "Detecting energy surplus or deficit based on emotion analysis" is a method for identifying energy surplus or deficit based on the user's emotions and achieving optimal energy management. 【0641】 "Monitoring the performance of energy collection devices" is a process that constantly checks whether the collection devices are functioning correctly and enables immediate action if any problems arise. 【0642】 This invention is a system for optimizing energy efficiency in buildings. The server executes software that determines the optimal placement of solar energy collection devices based on the building's design information and performs solar radiation energy prediction. This software takes the design information as input and performs the necessary analysis to maximize solar energy collection efficiency. Furthermore, it performs simulations to optimize the placement of the collection devices and calculates their position and angle. 【0643】 The device uses voice analysis APIs and facial recognition APIs to analyze the user's emotional state. Specifically, the device collects voice and image data and sends the data to the server to reveal the user's emotional state. For example, it uses the Microsoft Azure Face API to analyze the user's facial expressions and estimate their emotional state. 【0644】 Subsequently, the server automatically adjusts energy management based on the user's emotional state. For example, if the user is relaxed, it will change the lighting color to a warmer tone and set the air conditioning temperature to a comfortable range. It will also flexibly adjust the energy replenishment schedule for electric transport equipment to optimize energy consumption. 【0645】 This system achieves optimal energy management by analyzing energy usage data and applying predictive algorithms to detect energy surpluses and deficits based on emotion analysis. Thus, in this embodiment, energy management that takes user emotions into account is comprehensively supported. 【0646】 An example of a prompt would be, "Please tell me the appropriate energy setting for you when you are relaxing." This prompt allows the generating AI model to suggest an appropriate energy management method. 【0647】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0648】 Step 1: 【0649】 The server analyzes the building's design information to determine the optimal placement of solar energy harvesting devices. The input to this process is the building's blueprint, and the output is the specific location information of each harvesting device. Based on the input data, simulation software is used to calculate the optimal placement that maximizes harvesting efficiency. 【0650】 Step 2: 【0651】 The device collects user voice and image data and sends it to a cloud server for emotional state analysis. The input is the user's voice and image, and the output is analyzed emotional information. Data processing is performed using voice analysis APIs and facial recognition APIs to estimate emotions. 【0652】 Step 3: 【0653】 The server adjusts the indoor environment's energy settings based on the emotional state. The input at this stage is the emotional information obtained in step 2, and the output is the parameters for the new energy settings. Specifically, it uses a generative AI model to determine instructions such as changing the lighting color or adjusting the air conditioning temperature. 【0654】 Step 4: 【0655】 The server optimizes the energy replenishment schedule for electric transport equipment, taking emotional information into consideration. The input is the emotional state and current energy supply status, while the output is the adjusted charging schedule. It analyzes power supply conditions and usage patterns to schedule the optimal charging timing and mode. 【0656】 Step 5: 【0657】 The server detects energy surpluses and shortages based on collected energy usage data and optimizes energy management. The input is historical energy usage data, and the output is a future energy management plan. A predictive algorithm is applied to propose feasible supply plans and energy-saving measures. 【0658】 In this way, energy management that is sensitive to the user's emotions is implemented throughout the processing steps. 【0659】 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. 【0660】 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. 【0661】 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. 【0662】 [Fourth Embodiment] 【0663】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0664】 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. 【0665】 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). 【0666】 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. 【0667】 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. 【0668】 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). 【0669】 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. 【0670】 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. 【0671】 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. 【0672】 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. 【0673】 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. 【0674】 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. 【0675】 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". 【0676】 The present invention aims to streamline and optimize the installation of solar power generation panels and the charging management of electric vehicles in buildings. The embodiments of this system are described below. 【0677】 First, the user uploads the building's blueprints to the system. The blueprints are provided in digitized drawing or data format. Based on this design information, the server analyzes the building's roof shape, orientation, and area. The analyzed information is used for solar radiation forecasting, and the server predicts the amount of solar radiation throughout the year by referring to geographical and meteorological data. 【0678】 Based on this information, the server calculates the optimal placement of solar panels and determines the installation angle and arrangement pattern. The results of this placement optimization are provided to the construction management team, enabling efficient construction. 【0679】 Furthermore, the server retrieves electricity sales reference information from the power market and combines it with predicted power generation to simulate electricity sales revenue. This simulation result is useful for determining the economic feasibility of the power generation system. In addition, construction progress is reported in real time from the terminals, and the server monitors the progress of construction and optimizes resource allocation as needed. 【0680】 For electric vehicle charging, users input their desired charging schedule into the system. Based on this schedule, the server analyzes power usage and provides the optimal charging time. Charging is performed automatically during low-cost periods, promoting efficient energy use. 【0681】 Furthermore, the server constantly monitors panel performance and predicts signs of failure. If performance deteriorates, the system sends an alert to the user, allowing for early maintenance. This proactive maintenance ensures long-term operational stability while maintaining power generation efficiency. 【0682】 As a concrete example, in a certain housing project, using this system allowed the server to streamline the entire process from the design stage to construction management and operation, resulting in high power generation efficiency and economic benefits. 【0683】 The following describes the processing flow. 【0684】 Step 1: 【0685】 The user uploads the building's blueprints to the system in digital format. The server receives this data and activates the building's shape analysis module. 【0686】 Step 2: 【0687】 The server analyzes the blueprints to identify the building's roof shape, orientation, and area. Based on the acquired structural data, it uses a solar radiation prediction module to simulate the amount of solar radiation throughout the year. 【0688】 Step 3: 【0689】 The server references geographic information systems and weather data to correct for solar radiation at specific building locations. This data is then used as a basis for determining the optimal placement of solar power panels. 【0690】 Step 4: 【0691】 The server executes an optimal panel placement algorithm to determine the installation angle and placement pattern. This optimal placement information is sent to the construction team to assist in accurate installation on-site. 【0692】 Step 5: 【0693】 The terminal updates the progress status in real time from the construction site and sends the progress data to the server. The server receives this data, manages construction resources, and optimizes them as needed. 【0694】 Step 6: 【0695】 Users set their electric vehicle charging schedule, entering their desired charging time slots and capacities. Based on this information, the server analyzes power usage and suggests an efficient charging schedule. 【0696】 Step 7: 【0697】 The server constantly monitors panel performance and executes a failure prediction algorithm when an anomaly is detected. If necessary, it sends maintenance notifications to users to encourage early action. 【0698】 Step 8: 【0699】 The server retrieves electricity sales reference information from the power market and integrates it with the results of power generation simulations to predict annual electricity sales revenue. Based on this prediction, it provides users with information to make economic decisions. 【0700】 (Example 1) 【0701】 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". 【0702】 In today's environment, the introduction and management of solar power generation are crucial for achieving sustainable energy use. However, the placement of power generation equipment in buildings, on-site management, and subsequent optimization of energy use require considerable effort and specialized knowledge. Furthermore, there is a need for appropriate market information analysis to maintain power generation efficiency and maximize economic benefits, as well as for the efficient use of electricity. The problem lies in the lack of systems that address these challenges. 【0703】 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. 【0704】 In this invention, the server includes means for analyzing design information and determining the optimal placement of power generation equipment, means for predicting solar radiation, means for optimizing the placement of power generation equipment, means for predicting electricity revenue based on market information, means for monitoring construction progress in real time and managing construction resources, means for automatically optimizing the charging schedule of mobile units, and means for monitoring the performance of power generation equipment and predicting failures. This improves the efficiency of the series of processes and makes it possible to achieve high power generation efficiency and economic convenience. 【0705】 "Design information" refers to digital information related to the design of a building, and specifically includes data on the building's roof shape, orientation, and area. 【0706】 A "power generation device" is a device that converts solar energy into electricity, and specifically refers to a solar power generation panel. 【0707】 "Solar radiation" refers to the amount of solar energy received over a certain period of time at a specific geographical location. 【0708】 "Market information" refers to data related to the buying and selling of electricity in the energy market, and specifically includes information such as electricity supply and demand, and electricity selling prices. 【0709】 "Construction resources" is a general term for the personnel, equipment, materials, and other resources necessary to carry out the installation work of power generation equipment in a building. 【0710】 "Mobile vehicles" refer to vehicles such as automobiles that need to store energy and be charged. 【0711】 "Performance monitoring" is a process of continuously checking the operating status of power generation equipment and evaluating whether it is functioning properly. 【0712】 "Failure prediction" refers to a technology that analyzes data from power generation equipment to detect in advance the possibility of future malfunctions or abnormalities. 【0713】 The present invention aims to efficiently introduce and manage solar power generation in buildings. This system comprehensively performs tasks ranging from analysis of design information and optimal placement of power generation equipment to energy market analysis, construction management, optimization of mobile equipment charging, and performance monitoring of power generation equipment through multiple means. 【0714】 First, the user uploads detailed design information of the building to the system in digital format. This information is then sent to the server, and the analysis begins. The server uses CAD software to analyze the design data and extract the roof shape, orientation, and area. Based on this extracted information, the server predicts the amount of solar radiation by referring to geographic and meteorological databases. 【0715】 Based on solar radiation predictions, the server uses solar power simulation software (e.g., PVsyst) to calculate the optimal placement of power generation equipment. Based on the calculation results, it proposes the optimal installation method for the power generation equipment and provides it to the construction management team. This improves the efficiency of construction work. 【0716】 Furthermore, the server uses energy market information to simulate the economics of selling electricity and presents this to the user. Regarding the charging of mobile devices such as electric vehicles, it optimally manages the supply and demand of electricity based on the charging schedule set by the user. This automatically ensures that charging takes place during off-peak hours when costs are lower. 【0717】 Furthermore, the server constantly monitors the performance of the power generation equipment and predicts signs of failure using a generated AI model. If the output of the power generation equipment decreases, the server sends an alert to the user to encourage early maintenance. This enables the long-term stable operation of the power generation equipment. 【0718】 As a concrete example, the use of this system in a housing project allowed the server to integrate and manage the entire process from the construction phase to the operation phase, achieving high power generation efficiency. As a result, the economic benefits were maximized. 【0719】 An example of a prompt for the generating AI model is, "Based on the house blueprints, calculate the optimal placement of solar panels and maximize power generation efficiency." This prompt prompts the server to automatically generate an efficient placement plan. 【0720】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0721】 Step 1: 【0722】 Users upload building design information to the system in digital format. This provides information about the building's roof shape, orientation, and area. Based on this input data, the server receives the design data and enables subsequent analysis. 【0723】 Step 2: 【0724】 The server analyzes the received design information. Specifically, it uses CAD software to analyze the design data and extract the roof shape, orientation, and area. This data analysis yields meaningful features from the design information. 【0725】 Step 3: 【0726】 The server predicts solar radiation by referencing geographic and meteorological databases. Input data includes roof information and geographical coordinates obtained in step 2. Based on this data, the annual solar radiation calculation is performed. 【0727】 Step 4: 【0728】 The server uses solar power simulation software to calculate the optimal placement of power generation equipment. This process takes predicted solar radiation as input, determines the optimal panel angles and placement patterns, and provides the results to the construction management team. 【0729】 Step 5: 【0730】 The server simulates electricity sales revenue based on market information collected from the energy market. Inputs include predicted power generation and market price data. This allows the user to see the economic potential of the power generation system. 【0731】 Step 6: 【0732】 The terminals report the progress of construction in real time from the site. Using this information, the server monitors the construction status and optimizes the allocation of construction resources as needed. This improves the efficiency of construction. 【0733】 Step 7: 【0734】 The user enters the electric vehicle charging schedule into the system. The server then references this schedule and power demand data to calculate the optimal charging time. This ensures that charging takes place during cost-effective hours. 【0735】 Step 8: 【0736】 The server continuously monitors the performance of the power generation equipment and uses a generative AI model to predict signs of failure. Input includes real-time output data acquired from the power generation equipment. When a performance degradation is detected, an alert is sent to the user, enabling prompt maintenance. 【0737】 (Application Example 1) 【0738】 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". 【0739】 Balancing environmental protection and energy efficiency in modern buildings is a crucial challenge. Existing systems struggle to optimize energy conversion devices from the design stage, and there's a lack of methods to directly help residents understand energy efficiency. Therefore, there's a need for precise placement of energy conversion devices, optimization of charging resources, and systems that allow residents to easily experience efficient energy use. 【0740】 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. 【0741】 In this invention, the server includes means for analyzing building design information and determining the optimal placement of energy conversion devices, means for monitoring construction progress in real time and managing construction resources, and means for visualizing energy efficiency on information terminals for residents. This enables sustainable and efficient energy utilization from the design stage to the operation stage of the building. 【0742】 "Building design information" refers to a collection of detailed design drawings and data concerning the structure and function of a building, and serves as the basis for determining the optimal placement of energy conversion devices. 【0743】 An "energy conversion device" is a device that converts natural energy sources such as solar and wind power into other forms of energy, such as electricity. 【0744】 A "solar radiation prediction means" is a device or method that predicts the amount of solar radiation obtained in a given area based on the location of a building and environmental data. 【0745】 "Energy conversion device placement optimization means" refers to a device or method that performs calculations and analyses to determine the optimal placement of energy conversion devices based on the shape and orientation of a building. 【0746】 "Electricity trading information" refers to information regarding the market price of electricity, supply, and demand, and serves as basic data for determining the optimal timing for selling electricity. 【0747】 "Means for monitoring construction progress in real time and managing construction resources" refers to a device or method for tracking the construction process of a building in real time and efficiently allocating the necessary resources. 【0748】 "Means for automatically optimizing a vehicle's charging schedule" refers to a device or method that automatically sets the time and method for efficiently charging a vehicle based on power demand and cost. 【0749】 "Means for monitoring the performance of an energy conversion device and predicting failures" refers to a device or method that constantly monitors the operating status of an energy conversion device and predicts and notifies of failures before abnormalities occur. 【0750】 "Means of visualizing energy efficiency on information terminals for residents" refers to a device or application that displays energy usage and efficiency in an easy-to-understand manner for residents. 【0751】 This invention's system is designed to maximize energy efficiency in buildings, allowing residents to experience its benefits. The server receives building design information and uses AI technology to calculate the optimal placement of energy conversion devices. This process combines weather and geographical data for solar radiation prediction and utilizes Google Earth Engine. Furthermore, because optimizing the placement of conversion devices requires complex data analysis, a high-performance cloud-based tool is employed. 【0752】 During the construction process, the server monitors the progress in real time and optimally allocates resources as needed. This involves collecting data from IoT sensors and managing construction resources using Amazon AWS IoT Core. 【0753】 Furthermore, regarding energy trading data, the server analyzes market trends and notifies users of the optimal timing for electricity trading. Users receive this information using smartphones or smart glasses, and the system is designed to be intuitively understandable. 【0754】 Regarding the performance monitoring of energy conversion equipment, the server constantly checks the operating status of the equipment and predicts failures before any abnormalities occur, sending alerts to the user. This prevents future decreases in power generation and equipment failures, promoting smooth system operation. 【0755】 As a concrete example, the implementation of this system in a certain smart city resulted in residents reducing their monthly electricity costs by approximately 15% and optimizing their energy use. The information terminals for residents are equipped with a function to visualize energy efficiency, allowing residents to check their energy usage in real time. 【0756】 An example of a prompt using a generative AI model is, "Perform real-time data analysis on optimizing solar power generation and present the most cost-effective option for residents." In this way, support is provided in a way that is easy for users to understand. 【0757】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0758】 Step 1: 【0759】 The server receives building design information from the user. The input design information is provided in digital drawing format. The server analyzes this information and extracts the building's roof shape and orientation. This generates the basic data necessary for planning the placement of energy conversion devices. 【0760】 Step 2: 【0761】 The server combines geographical and meteorological data to predict solar radiation. Specifically, it uses Google Earth Engine to predict solar radiation throughout the year. The inputs used are roof shape and location information based on design data, and the output is predicted solar radiation data. 【0762】 Step 3: 【0763】 The server calculates the optimal placement of energy conversion devices based on solar radiation forecast data. AI technology is used in the processing to determine the most efficient panel installation angles and placement patterns. The input is solar radiation forecast data, and the output is the optimal placement plan. 【0764】 Step 4: 【0765】 The server monitors construction progress in real time and manages construction resources. It collects data from IoT sensors and uses Amazon AWS IoT Core to understand the condition of the construction site. This minimizes waste during the construction process. 【0766】 Step 5: 【0767】 The server collects electricity market transaction information and analyzes the optimal timing for electricity trading. Market data is used as input, and the output is recommended information on the most suitable time for trading. Users receive this information via smart devices. 【0768】 Step 6: 【0769】 The terminal visualizes energy efficiency on a resident information display. Energy usage and economic effects are visualized using graphs and other visuals, presented in a format easily understood by residents. Input is energy data from a server, and output is a visualized interface. 【0770】 Step 7: 【0771】 The server constantly monitors the performance of the energy conversion device and predicts failures. It analyzes sensor data and sends alerts to user terminals when an anomaly is detected. This enables rapid response and stable system operation. 【0772】 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. 【0773】 This invention provides an energy management system that not only improves the efficiency of solar power generation and electric vehicle charging in buildings, but also takes user sentiment into consideration. The system begins with an analysis of the roof shape based on design information, and then achieves optimal placement of solar panels and maximizes power generation efficiency. Furthermore, it improves economic efficiency by analyzing electricity market information and predicting appropriate electricity sales revenue. It also includes a function to monitor construction progress in real time and optimize resource management. 【0774】 Furthermore, this system incorporates an emotion engine to analyze the user's emotional state, aiming to optimize energy management. The server uses an emotion recognition algorithm to analyze the user's emotions from voice and image data, and automatically adjusts the energy settings within the home based on the results. For example, if the system detects that the user is stressed, the emotion engine will change the lighting and air conditioning settings to provide a more comfortable environment. 【0775】 Furthermore, the server adjusts the electric vehicle's charging schedule according to the user's emotional state. For example, if the user is relaxed, the charging is set to energy-saving mode and optimized to charge at a comfortable pace. This function reduces energy consumption and contributes to long-term cost savings. 【0776】 Furthermore, the solar power generation system uses the analysis results of the emotion engine to detect energy surpluses and shortages in real time, and predicts and optimizes power consumption. This allows for flexible responses to energy usage patterns within the home, which is expected to improve user satisfaction. 【0777】 This system comprehensively supports the entire energy management process, from the design phase to the operation of buildings, enabling a smarter and more emotionally resonant lifestyle. 【0778】 The following describes the processing flow. 【0779】 Step 1: 【0780】 The user operates a device to input audio and image data into the system. This data is used to understand the user's emotional state. 【0781】 Step 2: 【0782】 The server activates an emotion recognition algorithm and analyzes the captured audio and image data. Based on factors such as voice tone, facial expressions, and posture, it identifies the current emotional state. 【0783】 Step 3: 【0784】 The server uses the analysis results to calculate energy settings appropriate for the user's emotional state. For example, to alleviate stress, it adjusts the color and intensity of the lighting and changes the air conditioning settings. 【0785】 Step 4: 【0786】 If a user is planning to charge their electric vehicle, the server will reset the optimal charging schedule based on the emotion recognition results. If the user needs to relax, it will recommend charging in energy-saving mode. 【0787】 Step 5: 【0788】 The server retrieves the latest information from the electricity market and adjusts the timing of electricity sales. Since energy supply and demand change depending on emotional states, it devises the optimal electricity sales plan. 【0789】 Step 6: 【0790】 The terminal integrates progress information from the construction site with user residency information and transmits the data to the server in real time. This data is used for construction management and energy management. 【0791】 Step 7: 【0792】 The server monitors the performance of the solar panels and, if an anomaly is detected, promptly develops a maintenance plan. It also considers data from the emotion engine to determine the most impactful time to take action. 【0793】 Step 8: 【0794】 The server oversees overall energy usage, incorporates insights from the emotion engine, and then executes optimization algorithms to manage and maintain the living environment in the most comfortable way possible at all times. 【0795】 (Example 2) 【0796】 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". 【0797】 In conventional energy management systems, it was difficult to simultaneously achieve maximum efficiency in solar power generation, real-time management of construction progress, effective charging management of electric vehicles, and optimization of the operating environment while considering user sentiment. As a result, this often led to energy waste, increased costs, and decreased user satisfaction. 【0798】 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. 【0799】 In this invention, the server includes means for analyzing design information and determining the optimal placement of power generation equipment, means for predicting solar radiation, means for optimizing the placement, means for predicting electricity sales revenue based on electricity sales reference information, means for monitoring construction progress in real time and managing construction resources, means for analyzing the user's emotional state using an emotion recognition algorithm and automatically optimizing the operating environment, means for optimizing the electric vehicle charging schedule according to the emotional state, and means for monitoring the performance of power generation equipment and performing fault prediction. This enables more efficient energy management, improved user comfort, and cost reduction. 【0800】 "Design information" is a general term for detailed information such as drawings, specifications, materials, and dimensions necessary for the construction of a building. 【0801】 A "power generation device" is a device that generates electricity using sunlight, and mainly refers to solar panels. 【0802】 "Solar radiation" refers to the amount of solar energy that reaches a surface per unit time. 【0803】 "Placement" refers to the location and method for properly installing solar panels and other equipment. 【0804】 "Electricity sales reference information" refers to information regarding trends in the electricity market and electricity prices. 【0805】 "Construction progress" refers to information indicating the current status of a construction project. 【0806】 "Construction resources" is a general term for the personnel, materials, equipment, and other resources necessary for a construction project. 【0807】 An "emotion recognition algorithm" is a computational processing method for analyzing a person's emotional state based on audio or image data. 【0808】 "Operating environment" refers to the physical conditions such as lighting, temperature, and acoustics in the space where the user lives or uses the space. 【0809】 An "electric vehicle" is a vehicle that moves using electricity as its power source, and mainly refers to an electric car. 【0810】 A "charging schedule" is a plan for systematically determining the time and speed at which to charge the batteries of an electric vehicle. 【0811】 "Failure prediction" is a technology that analyzes equipment operation data to estimate signs of failure and the timing of failures in advance. 【0812】 In embodiments of the present invention, the energy management system integrates multiple technologies to achieve efficient energy use in buildings. In this system, a server plays a central role in collecting and analyzing information from various data sources. 【0813】 The server first receives design information. This design information includes building blueprints and specifications, and the server analyzes the roof shape and area based on this information. The server then uses 3D modeling software (e.g., AutoCAD) to perform simulations to determine the optimal placement of solar panels. During this process, it refers to an external database containing weather data to predict solar radiation. 【0814】 The server also gathers information about the electricity market and uses it to predict electricity sales revenue. This prediction is made using data analysis algorithms, providing the optimal electricity sales strategy based on historical electricity price trends and demand curves. 【0815】 IoT sensors are installed at construction sites, transmitting real-time information on construction progress to a server. The server uses this information to optimize the allocation of construction resources and improve construction efficiency. 【0816】 To enhance user comfort, the server implements an emotion recognition algorithm that analyzes the user's voice and image data. This allows it to determine whether the user is stressed or relaxed. For example, if the user is stressed, the server adjusts the lighting and air conditioning settings to provide a more comfortable environment. 【0817】 Furthermore, the server manages electric vehicle charging, flexibly adjusting the charging schedule according to the user's emotional state. For example, it can set the charging schedule to nighttime hours to encourage efficient charging during times of low electricity demand. 【0818】 Furthermore, the server monitors the performance of the power generation equipment and predicts failures as needed. This function helps prevent mechanical problems and contributes to improving the long-term reliability of the system. 【0819】 As a concrete example, when emotion recognition determines that a user is "feeling stressed," the server can respond by dimming the lights and playing music to provide a comfortable environment. 【0820】 Examples of prompt messages are as follows: 【0821】 "How can I optimize the lighting settings in this residential system when users experience stress?" 【0822】 Thus, the system of the present invention simultaneously achieves improved energy efficiency and enhanced quality of life for users through the integration of technologies. 【0823】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0824】 Step 1: 【0825】 The server receives building design information. A 3D design software file is provided as input. The server analyzes this file and extracts data such as roof shape, area, and orientation. Analysis data necessary for solar panel placement is generated as output. 3D modeling software (e.g., general-purpose design software) is used for the analysis. 【0826】 Step 2: 【0827】 The server retrieves data from a weather database to predict solar radiation. Location information and weather data are provided as input. The server uses a solar radiation calculation algorithm to calculate the predicted daily solar radiation. This data calculation includes calculating sunshine duration based on location information. The output is predicted solar radiation data. 【0828】 Step 3: 【0829】 The server calculates the optimal placement of solar panels based on design information and solar radiation data. Roof shape data and solar radiation data are used as input. The server utilizes simulation tools to generate a placement plan that takes shading into account. The output includes a panel placement diagram and data showing the maximum power generation efficiency. In this process, the shading simulation takes into account environmental information surrounding the building. 【0830】 Step 4: 【0831】 The server collects electricity market information and predicts electricity sales revenue. It requires market price data and demand data as input. The server uses a machine learning model to calculate the optimal electricity sales strategy based on this data. The output is predicted electricity sales revenue data. 【0832】 Step 5: 【0833】 The server receives real-time sensor data from the construction site and manages the construction progress. The input is data from IoT sensors installed at the construction site. The server uses a resource management algorithm to analyze the construction progress and allocate resources efficiently. The output is an optimized construction schedule. 【0834】 Step 6: 【0835】 The server collects user emotion data from the microphone and camera and analyzes it using an emotion recognition algorithm. Audio and image data are provided as input. The server uses an emotion analysis model to determine the user's emotional state. Data indicating the emotional state is generated as output. This data is used in the next step. 【0836】 Step 7: 【0837】 The server optimizes the operating environment within the home based on the user's emotional state. Emotional state data is used as input. The server automatically adjusts the air conditioning and lighting settings to create an environment that the user finds comfortable. The output is the adjusted air conditioning and lighting settings. 【0838】 Step 8: 【0839】 The server optimizes the electric vehicle's charging schedule based on the user's emotional state. The input requires user emotional data and the vehicle's charging status. Based on this data, the server creates an efficient charging plan that aligns with the user's lifestyle. The output is the optimized charging schedule. 【0840】 Step 9: 【0841】 The server monitors the performance of the power generation equipment and performs fault prediction as needed. Operational data from the generator is provided as input. The server utilizes a fault prediction model to detect equipment abnormalities in advance. The output is risk data indicating the likelihood of failure. This data is used in maintenance planning. 【0842】 (Application Example 2) 【0843】 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". 【0844】 Conventional energy management systems have not adequately achieved the efficiency of solar energy collection in buildings and energy supply to electric transportation equipment, and in particular, they lack systematic management that takes into account the impact of users' emotional states on energy consumption. Therefore, there has been a challenge in optimizing energy use. 【0845】 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. 【0846】 In this invention, the server includes means for analyzing building design information and determining the optimal placement of solar energy collection devices, means for predicting solar radiation energy, means for optimizing the placement of energy collection devices, means for predicting electricity trading revenue based on electricity trading reference information, means for monitoring construction progress in real time and managing construction resources, means for automatically optimizing the energy supply schedule for electric transport equipment, means for analyzing the user's emotional state and adjusting energy management based on the results, means for detecting energy surplus or deficit based on emotional analysis and performing electricity usage prediction and optimization, and means for monitoring the performance of energy collection devices and performing failure prediction. This enables flexible and efficient energy management that takes user emotions into consideration. 【0847】 "Analyzing building design information" means analyzing detailed information about the structure and layout of a building to help improve energy efficiency. 【0848】 A "solar energy collection device" is a device that efficiently converts sunlight into energy, and is usually installed on the roof or exterior wall of a building. 【0849】 "Optimizing the placement of energy collection devices" is the process of calculating and adjusting the shape, position, angle, and other factors necessary for energy collection devices to function as efficiently as possible. 【0850】 "Solar radiation energy forecasting" involves predicting the amount of radiant energy from the sun and providing information to maximize the operational efficiency of energy collection devices. 【0851】 "Electricity trading reference information" refers to information about transactions in the electricity market, including electricity prices, demand, and supply conditions. 【0852】 "Optimizing the energy replenishment schedule for electric transport equipment" means developing a charging plan that ensures electric transport equipment is charged efficiently and energy consumption is minimized. 【0853】 "Analyzing emotional states" involves analyzing a user's emotional state based on their voice, facial expressions, and actions, and then utilizing the results as data. 【0854】 "Detecting energy surplus or deficit based on emotion analysis" is a method for identifying energy surplus or deficit based on the user's emotions and achieving optimal energy management. 【0855】 "Monitoring the performance of energy collection devices" is a process that constantly checks whether the collection devices are functioning correctly and enables immediate action if any problems arise. 【0856】 This invention is a system for optimizing energy efficiency in buildings. The server executes software that determines the optimal placement of solar energy collection devices based on the building's design information and performs solar radiation energy prediction. This software takes the design information as input and performs the necessary analysis to maximize solar energy collection efficiency. Furthermore, it performs simulations to optimize the placement of the collection devices and calculates their position and angle. 【0857】 The device uses voice analysis APIs and facial recognition APIs to analyze the user's emotional state. Specifically, the device collects voice and image data and sends the data to the server to reveal the user's emotional state. For example, it uses the Microsoft Azure Face API to analyze the user's facial expressions and estimate their emotional state. 【0858】 Subsequently, the server automatically adjusts energy management based on the user's emotional state. For example, if the user is relaxed, it will change the lighting color to a warmer tone and set the air conditioning temperature to a comfortable range. It will also flexibly adjust the energy replenishment schedule for electric transport equipment to optimize energy consumption. 【0859】 This system achieves optimal energy management by analyzing energy usage data and applying predictive algorithms to detect energy surpluses and deficits based on emotion analysis. Thus, in this embodiment, energy management that takes user emotions into account is comprehensively supported. 【0860】 An example of a prompt would be, "Please tell me the appropriate energy setting for you when you are relaxing." This prompt allows the generating AI model to suggest an appropriate energy management method. 【0861】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0862】 Step 1: 【0863】 The server analyzes the building's design information to determine the optimal placement of solar energy harvesting devices. The input to this process is the building's blueprint, and the output is the specific location information of each harvesting device. Based on the input data, simulation software is used to calculate the optimal placement that maximizes harvesting efficiency. 【0864】 Step 2: 【0865】 The device collects user voice and image data and sends it to a cloud server for emotional state analysis. The input is the user's voice and image, and the output is analyzed emotional information. Data processing is performed using voice analysis APIs and facial recognition APIs to estimate emotions. 【0866】 Step 3: 【0867】 The server adjusts the indoor environment's energy settings based on the emotional state. The input at this stage is the emotional information obtained in step 2, and the output is the parameters for the new energy settings. Specifically, it uses a generative AI model to determine instructions such as changing the lighting color or adjusting the air conditioning temperature. 【0868】 Step 4: 【0869】 The server optimizes the energy replenishment schedule for electric transport equipment, taking emotional information into consideration. The input is the emotional state and current energy supply status, while the output is the adjusted charging schedule. It analyzes power supply conditions and usage patterns to schedule the optimal charging timing and mode. 【0870】 Step 5: 【0871】 The server detects energy surpluses and shortages based on collected energy usage data and optimizes energy management. The input is historical energy usage data, and the output is a future energy management plan. A predictive algorithm is applied to propose feasible supply plans and energy-saving measures. 【0872】 In this way, energy management that is sensitive to the user's emotions is implemented throughout the processing steps. 【0873】 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. 【0874】 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. 【0875】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414. 【0876】 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. 【0877】 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. 【0878】 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. 【0879】 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. 【0880】 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. 【0881】 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." 【0882】 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. 【0883】 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. 【0884】 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. 【0885】 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. 【0886】 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. 【0887】 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. 【0888】 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 this memory. 【0889】 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. 【0890】 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. 【0891】 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. 【0892】 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. 【0893】 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. 【0894】 The following is further disclosed regarding the embodiments described above. 【0895】 (Claim 1) 【0896】 Analyze the design information of the building to determine the optimal placement of solar power generation panels. 【0897】 Solar radiation prediction method, 【0898】 Panel arrangement optimization means, 【0899】 A method for predicting electricity sales revenue based on electricity sales reference information, 【0900】 A means of monitoring construction progress in real time and managing construction resources, 【0901】 A means to automatically optimize the charging schedule of electric vehicles, 【0902】 A means for monitoring panel performance and performing failure prediction, 【0903】 A system that includes this. 【0904】 (Claim 2) 【0905】 The system according to claim 1, which analyzes the roof shape of a building based on design information and derives the amount of solar radiation. 【0906】 (Claim 3) 【0907】 The system according to claim 1, which analyzes collected market information and recommends the optimal time of day for selling electricity. 【0908】 "Example 1" 【0909】 (Claim 1) 【0910】 A means for analyzing design information and determining the optimal placement of power generation equipment, 【0911】 A means of predicting solar radiation, 【0912】 Means for optimizing the arrangement of power generation equipment, 【0913】 A method for predicting electricity revenue based on market information, 【0914】 A means of monitoring construction progress in real time and managing construction resources, 【0915】 A means for automatically optimizing the charging schedule of a mobile device, 【0916】 A means for monitoring the performance of power generation equipment and predicting failures, 【0917】 A system that includes this. 【0918】 (Claim 2) 【0919】 The system according to claim 1, which analyzes the roof structure of a building based on design information and derives the amount of light. 【0920】 (Claim 3) 【0921】 The system according to claim 1, which analyzes collected market information and recommends the optimal time for selling electricity. 【0922】 "Application Example 1" 【0923】 (Claim 1) 【0924】 Analyze the design information of the building to determine the optimal placement of energy conversion devices. 【0925】 Solar radiation prediction method, 【0926】 Energy conversion device arrangement optimization means, 【0927】 A means of predicting electricity trading revenue based on electricity trading information, 【0928】 A means of monitoring construction progress in real time and managing construction resources, 【0929】 A means to automatically optimize the vehicle's charging schedule, 【0930】 A means for monitoring the performance of an energy conversion device and performing failure prediction, 【0931】 A means of visualizing energy efficiency on information terminals for residents, 【0932】 A system that includes this. 【0933】 (Claim 2) 【0934】 The system according to claim 1, which analyzes the roof shape of a building based on design information and derives the amount of solar radiation. 【0935】 (Claim 3) 【0936】 The system according to claim 1, which analyzes collected market information and recommends the optimal time for electricity trading. 【0937】 "Example 2 of combining an emotion engine" 【0938】 (Claim 1) 【0939】 A means for analyzing design information and determining the optimal placement of power generation equipment, 【0940】 A means of predicting solar radiation, 【0941】 Means for optimizing the arrangement, 【0942】 A method for predicting electricity sales revenue based on electricity sales reference information, 【0943】 A means of monitoring construction progress in real time and managing construction resources, 【0944】 A means of automatically optimizing the operating environment by analyzing the user's emotional state using an emotion recognition algorithm, 【0945】 A means for optimizing the charging schedule of electric vehicles according to emotional state, 【0946】 A means for monitoring the performance of power generation equipment and performing fault prediction, 【0947】 A system that includes this. 【0948】 (Claim 2) 【0949】 The system according to claim 1, which analyzes the shape of a building based on design information and derives the amount of solar radiation. 【0950】 (Claim 3) 【0951】 The system according to claim 1, which analyzes collected market information and recommends the optimal time of day for selling electricity. 【0952】 "Application example 2 when combining with an emotional engine" 【0953】 (Claim 1) 【0954】 Analyze the building's design information to determine the optimal placement of solar energy collection devices. 【0955】 Solar radiation energy prediction method, 【0956】 Means for optimizing the placement of energy collection devices, 【0957】 A means of predicting electricity trading revenue based on electricity trading reference information, 【0958】 A means of monitoring construction progress in real time and managing construction resources, 【0959】 A means for automatically optimizing the energy replenishment schedule of electric transport equipment, 【0960】 A means of analyzing the user's emotional state and adjusting energy management based on the results, 【0961】 A means for detecting energy surpluses and shortages based on emotion analysis, and for predicting and optimizing power usage, 【0962】 A means for monitoring the performance of an energy collection device and performing failure prediction, 【0963】 A system that includes this. 【0964】 (Claim 2) 【0965】 The system according to claim 1, which analyzes the roof shape of a building based on design information and derives solar radiation energy. 【0966】 (Claim 3) 【0967】 The system according to claim 1, which analyzes collected market information and recommends the optimal time for electricity trading. [Explanation of symbols] 【0968】 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

[Claim 1] Analyze the design information of the building to determine the optimal placement of solar power generation panels. Solar radiation prediction method, Panel arrangement optimization means, A method for predicting electricity sales revenue based on electricity sales reference information, A means of monitoring construction progress in real time and managing construction resources, A means to automatically optimize the charging schedule of electric vehicles, A means for monitoring panel performance and performing failure prediction, A system that includes this. [Claim 2] The system according to claim 1, which analyzes the roof shape of a building based on design information and derives the amount of solar radiation. [Claim 3] The system according to claim 1, which analyzes collected market information and recommends the optimal time of day for selling electricity.

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