system

Abstract

Provide a system. 【Solution means】 Means for measuring the angle of the sun, Means for measuring the light quantity, Means for obtaining weather information, Means for measuring the wind speed, Means for receiving the data obtained from each of the above means and analyzing the data, Means for generating a control command for optimally adjusting the orientation, angle, and area of the solar panel based on the result of the data analysis, Means for physically adjusting the solar panel based on the control command, 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 performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In conventional fixed solar panels, it was often impossible to cope with changes in the position of the sun, the amount of light, and the weather, resulting in a frequent decrease in power generation efficiency. In addition, there was a problem that panels were frequently damaged due to natural disasters such as strong winds and snowfall, increasing the cost of repair and replacement. The present invention aims to solve these problems, improve the efficiency and safety of solar power generation, reduce the power cost, and reduce the environmental load.

Means for Solving the Problems

[0005] The present invention solves the above problems by the following means.

[0006] The system includes means for measuring the angle of the sun, means for measuring light intensity, means for acquiring weather information, and means for measuring wind speed, and means for receiving and analyzing the data acquired from each means. Furthermore, the system includes means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the data analysis, and means for physically adjusting the solar panels based on the control commands. The data analysis means uses an AI analysis module to calculate the optimal orientation, angle, and area of ​​the solar panels, and the control command generation means generates protective commands to move the panels horizontally during strong winds and vertically during snowfall.

[0007]

[0008] "The angle of the sun" refers to the angle at which the sun is located in the sky, and is information used to measure the angle of incidence of solar radiation.

[0009] "Light intensity" refers to the strength of sunlight, and is the amount of light energy emitted per unit of time.

[0010] "Weather information" refers to data indicating weather conditions (sunny, cloudy, rainy, etc.) and is information used to understand the environmental conditions related to solar power generation.

[0011] "Wind speed" refers to the speed of the wind and is information used to understand the effects of wind.

[0012] "Data analysis" is the process of processing various collected data to determine the optimal conditions for solar power generation.

[0013] The "AI analysis module" is a software module that uses artificial intelligence technology to analyze data and calculate the optimal placement of solar panels.

[0014] A "control command" is an instruction generated based on the results of data analysis, and it is a command to adjust the orientation, angle, and area of ​​the solar panels.

[0015] A "solar panel" is a device for converting solar energy into electricity and generates electricity when receiving sunlight.

[0016] A "protection instruction" is an instruction generated to protect a solar panel from natural disasters such as strong winds and snowfalls, and is an order to adjust the position of the panel to a safe state.

Brief Description of Drawings

[0017] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0021] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0022] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0023] 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).

[0024] 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."

[0025] [First Embodiment]

[0026] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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".

[0038] This invention relates to an AI-powered smart solar power generation system that enhances the efficiency and safety of solar power generation systems. This system utilizes numerous sensors and real-time AI data analysis to automatically and optimally control the orientation, angle, and area of ​​solar panels. Specific embodiments of this system are described below.

[0039] Data collection

[0040] sensor

[0041] The sensors measure the sun's angle, light intensity, weather, and wind speed in real time. This data is crucial for optimizing solar power generation.

[0042] Data analysis and control command generation

[0043] server

[0044] The server receives data collected from sensors and analyzes it using an AI analysis module. Based on the data analysis, it calculates the optimal orientation, angle, and area of ​​solar panels for solar power generation. It also generates commands to protect the panels in response to wind speed and weather fluctuations.

[0045] Program processing

[0046] 1. Data Collection

[0047] The sensor measures data on the sun's angle, light intensity, weather, and wind speed in real time and transmits it to the server.

[0048] 2. Data Analysis

[0049] The server receives the collected data and inputs it into the AI ​​analysis module. The AI ​​analysis module analyzes the data and calculates the optimal placement of the solar panels.

[0050] 3. Control command generation

[0051] The server generates control commands to adjust the orientation, angle, and area of ​​the solar panels based on the analysis results. It also generates commands to protect the panels in response to changes in wind speed and weather conditions.

[0052] 4. Panel adjustment

[0053] The terminal receives control commands and physically adjusts the orientation, angle, and area of ​​the solar panels. This optimizes power generation and improves energy efficiency.

[0054] 5. Status Monitoring

[0055] The server monitors the current status of the panel and notifies the user if an anomaly is detected.

[0056] Specific example

[0057] For example, consider a scenario where strong winds of 15 m / s are predicted at 12:00 PM on a given day. In this case, the sensor sends wind speed data to the server. The server inputs this data into an AI analysis module, which then generates an analysis result if strong winds are predicted. The server generates a protective command to position the panels horizontally and sends it to the terminal. The terminal receives this command, and the panel control module activates a motor to move the panels horizontally. This entire process prevents damage to the panels due to strong winds, extending the lifespan and enhancing the safety of the entire system.

[0058] Thus, the AI ​​smart solar power generation system of the present invention maximizes the efficiency and safety of solar power generation through the steps of data collection, data analysis, control command generation, panel adjustment, and condition monitoring.

[0059] The following describes the processing flow.

[0060] Step 1: Data Collection

[0061] The sensor measures the angle of the sun. The sensor measures the amount of light (illuminance). The sensor acquires weather information (sunny, cloudy, rainy, etc.). The sensor measures wind speed. Each sensor sends the collected data to the server.

[0062] Step 2: Data aggregation and preprocessing

[0063] The server receives data transmitted from each sensor. The server cleans the received data, processing for missing or outlier values. The server saves the pre-processed data to data storage.

[0064] Step 3: Data Analysis

[0065] The server inputs the stored data into the AI ​​analysis module. The AI ​​analysis module calculates the predicted position of the sun. The AI ​​analysis module calculates the optimal panel orientation, angle, and area. Based on wind speed and weather information, the AI ​​analysis module determines whether to generate a protection command.

[0066] Step 4: Control command generation

[0067] The server receives calculation results from the AI ​​analysis module. The server generates control commands to optimize the orientation, angle, and area of ​​the solar panels. The server generates protection commands based on wind and snowfall forecasts. The server sends the generated control and protection commands to the terminal.

[0068] Step 5: Panel Position Control

[0069] The terminal receives control commands from the server. The terminal sends commands to the panel control module. The panel control module operates the motors to adjust the orientation, angle, and area of ​​the solar panels. If a protection command is received after a forecast of strong winds or snowfall, the panel control module moves the panels horizontally or vertically.

[0070] Step 6: Status Monitoring

[0071] The server monitors the current status of the panel. The server records the panel's operational data (change history of orientation, angle, and area). If the server detects an anomaly, it generates an alert and notifies the user.

[0072] (Example 1)

[0073] 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."

[0074] To improve the efficiency and safety of solar power generation systems, optimal panel placement based on real-time weather information and the angle of the sun is required. However, current systems require manual adjustments, resulting in low efficiency and an increased risk of panel damage during extreme weather conditions such as strong winds and snowfall. Furthermore, the lack of a mechanism to immediately notify users when an anomaly occurs makes it difficult to respond quickly.

[0075] 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.

[0076] In this invention, the server includes means for measuring the angle of the sun, means for measuring light intensity, means for acquiring weather information, means for measuring wind speed, means for receiving data acquired from each of the means and storing it in a database, means including an AI analysis module for analyzing the data, means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the data analysis, means for physically adjusting the solar panels via a servo motor according to the control commands, and means for monitoring the current state of the solar panels and notifying the user if an abnormality is detected. This enables real-time automatic adjustment, improving the efficiency and safety of solar power generation, as well as enabling a rapid response in the event of an abnormality.

[0077] "Means for measuring the angle of the sun" refers to instruments that measure the current position and altitude angle of the sun. Specifically, this includes sensors for accurately determining the sun's position.

[0078] "Means for measuring light intensity" refers to devices that measure the intensity of ambient sunlight. Specifically, this includes devices that measure light intensity using photoelectric sensors or photodiodes.

[0079] "Means of obtaining weather information" refers to systems or services for obtaining meteorological data. Specifically, this includes APIs for obtaining information from external meteorological data providers and weather stations established independently.

[0080] "Means for measuring wind speed" refers to equipment for measuring wind speed. Specifically, this includes devices for measuring wind speed using an anemometer (wind speed meter), etc.

[0081] "Means for receiving data and storing it in a database" refers to a system for acquiring data from sensors, transferring it to a central computer, and storing it for long-term use. Specifically, this includes communication modules and data storage (e.g., MySQL, MongoDB).

[0082] An "AI analysis module" is an artificial intelligence system for analyzing acquired data. Specifically, it includes a software module that uses machine learning and deep learning algorithms to calculate the optimal panel arrangement.

[0083] "Means for generating control commands" refers to a device or software that creates commands for appropriately controlling solar panels based on the results of data analysis. Specifically, this includes a system that generates control signals using a programmed algorithm.

[0084] A "servo motor" is a drive device used to adjust the orientation and angle of solar panels in response to control commands. Specifically, it includes motors capable of precise rotation and angle adjustment.

[0085] "Means for monitoring status and detecting anomalies" refers to a system that constantly monitors the current operating state of a system and issues warnings when abnormal conditions or operations are detected. Specifically, this includes an alert system that analyzes data from sensors and detects abnormal values.

[0086] "Means of notifying users" refers to methods for informing users of system abnormalities or important information. Specifically, this includes communication methods such as email notifications, SMS, and push notifications.

[0087] This invention relates to an AI-powered smart solar power system that enhances the efficiency and safety of solar power generation systems. This system is configured to automatically and optimally control the orientation, angle, and area of ​​solar panels by utilizing numerous sensors and real-time AI data analysis.

[0088] Data collection

[0089] The sensors measure information on the sun's angle, light intensity, weather, and wind speed in real time. This includes the following sensors:

[0090] Optical sensor for measuring the angle of the sun

[0091] Photoelectric sensor for measuring light intensity

[0092] A system for acquiring weather information from weather sensors or external data providers.

[0093] An anemometer (wind speed meter) for measuring wind speed

[0094] Data reception and storage

[0095] The server receives data transmitted from the sensors and stores it in a database. Examples of databases used include MySQL and MongoDB. This ensures that the latest data is always updated and used for subsequent analysis.

[0096] Data Analysis

[0097] The server receives and stores data, which is then input into an AI analysis module. Specifically, an AI analysis module using deep learning frameworks such as TensorFlow or PyTorch analyzes the data and calculates the optimal orientation, angle, and area of ​​the solar panels.

[0098] Control command generation

[0099] The server generates control commands to optimize the orientation, angle, and area of ​​the solar panels based on the analysis results of the AI ​​analysis module. It also generates protective commands to move the panels horizontally or vertically if the wind speed exceeds a certain value or if snowfall is observed.

[0100] Control command transmission

[0101] The server sends the generated control commands to the terminal. MQTT or HTTP protocols are used for communication.

[0102] Panel adjustment

[0103] The terminal drives servo motors to adjust the orientation and angle of the solar panels based on the control commands it receives. For example, if strong winds are predicted, the panels will be moved horizontally.

[0104] Status Monitoring

[0105] The server constantly monitors the current status of the solar panels and sends a notification to the user if an anomaly is detected. Notifications are sent via email or push notifications.

[0106] Specific example

[0107] For example, if strong winds of 15 m / s are predicted at 12:00 on a given day, the system will operate in the following manner:

[0108] 1. The sensor measures wind speed data and sends it to the server.

[0109] 2. The server receives the data and inputs it into the AI ​​analysis module.

[0110] 3. The AI ​​analysis module analyzes the data and determines that strong winds are predicted.

[0111] 4. The server generates a protective command to position the panel horizontally and sends it to the terminal.

[0112] 5. The terminal receives the command and drives the servo motor to move the panel horizontally.

[0113] This series of processes prevents damage to panels caused by strong winds, thereby improving safety. Furthermore, the system can quickly detect and notify users of any abnormalities, allowing them to respond promptly.

[0114] Examples of prompts to input into a generative AI model:

[0115] "Please explain how the AI ​​smart solar power system works based on the following conditions: It is 12:00 PM on a day when strong winds of 15 m / s are predicted."

[0116] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0117] Step 1:

[0118] Data collection

[0119] The sensor measures data on the sun's angle, light intensity, weather, and wind speed in real time and transmits it to the server. Specifically, the sensor measures the sun's angle and light intensity every second and the wind speed every minute. The input data consists of the sun's angle, light intensity, weather information, and wind speed, and this data is packaged with a timestamp when transmitted. The output is the measurement data transmitted to the server.

[0120] Step 2:

[0121] Data reception and storage

[0122] The server receives data transmitted from the sensor and stores it in a database. The input is measurement data transmitted from the sensor, which the server receives and stores in a database, for example, using MySQL or MongoDB. Specifically, the received data is converted into a format that is easy to analyze and inserted into the corresponding field in the database. The output is the measurement data stored in the database.

[0123] Step 3:

[0124] Data Analysis

[0125] The server inputs data collected from the database into the AI ​​analysis module. The input is the latest measurement data obtained from the database, which the AI ​​analysis module (e.g., a deep learning model using TensorFlow or PyTorch) analyzes. Specifically, the data is fed into the model to calculate the optimal orientation, angle, and area of ​​the solar panels. The output is the parameters for the optimal orientation, angle, and area.

[0126] Step 4:

[0127] Control command generation

[0128] The server generates control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the analysis results of the AI ​​analysis module. The input is the data analysis results, and the server constructs the control commands based on this. Specifically, this includes commands such as positioning the panels horizontally when it is determined that the wind speed exceeds 10 m / s. The generated control commands are packaged in JSON format, etc. The output is the generated control commands.

[0129] Step 5:

[0130] Control command transmission

[0131] The server sends the generated control commands to the terminal. The input is the generated control commands, which are sent to the terminal using protocols such as MQTT or HTTP. Specifically, the command packets are converted into a format suitable for the communication protocol and sent to the terminal. The output is the control commands sent to the terminal.

[0132] Step 6:

[0133] Panel adjustment

[0134] The terminal drives a servo motor to adjust the orientation and angle of the solar panel based on the control commands it receives. The input is a control command sent from the server, which the terminal receives and sends commands to the servo motor. Specifically, it sends signals to the motor to control the rotation angle and direction. For example, if it is determined that the wind speed exceeds 10 m / s, the motor rotates to position the panel horizontally. The output is the physical position of the adjusted solar panel.

[0135] Step 7:

[0136] Status Monitoring

[0137] The server constantly monitors the current status of the solar panels and sends a notification to the user if an anomaly is detected. The input is the adjusted panel status data, which the server monitors to detect anomalies. Specifically, it uses data from angle sensors and temperature sensors to generate an alert if the values ​​differ from the set values. The output is an anomaly notification sent to the user, which is sent via email or push notification.

[0138] (Application Example 1)

[0139] 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."

[0140] Existing solar power generation systems suffer from reduced power generation efficiency due to the lack of real-time data analysis to optimally adjust the orientation and angle of solar panels. Furthermore, they struggle to respond quickly to extreme weather events such as strong winds and snowfall, raising concerns about panel damage and system safety. Additionally, they lack the functionality to remotely monitor the system status and manually control it as needed, even when the user is not on-site.

[0141] 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.

[0142] In this invention, the server includes means for measuring the angle of the sun, means for measuring light intensity, means for acquiring weather information, means for measuring wind speed, means for receiving data acquired from each of the means and analyzing the data, means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the data analysis, means for physically adjusting the solar panels based on the control commands, means for displaying the results on a smart device in real time, and means for the user to manually control the panels using voice commands or touch gestures. This enhances the power generation efficiency and safety of the solar power generation system, and enables remote monitoring and control by the user.

[0143] "Means for measuring the angle of the sun" refers to a sensor device that detects the angle of the sun in real time according to its position.

[0144] "Means for measuring light intensity" refers to a sensor device used to measure the current intensity of sunlight.

[0145] "Means of acquiring weather information" refer to sensors and external data provision services for collecting current temperature, humidity, precipitation, etc.

[0146] "Means for measuring wind speed" refers to a sensor device for measuring wind speed in real time.

[0147] "Means for analyzing data" refers to an AI analysis module that uses data collected from sensors to evaluate the situation and generate necessary control commands.

[0148] "Means for generating control commands" refers to a device or software that generates commands to optimally adjust the orientation, angle, and area of ​​solar panels based on the results of data analysis.

[0149] "Means for physically adjusting solar panels" refer to motors and actuators that automatically change the orientation and angle of the panels according to control commands.

[0150] "Means for displaying results in real time on smart devices" refers to communication and display devices for notifying smart devices (smart glasses, smartphones) of analysis results and data from sensors.

[0151] "Means for manually controlling the panel using voice commands or touch gestures" refers to an interface that allows users to manually adjust the solar panels using voice or physical operations.

[0152] System Overview

[0153] This invention provides an AI-powered smart control system to enhance the efficiency and safety of solar power generation systems. This system collects data from multiple sensors, analyzes it in real time, and optimally adjusts the orientation, angle, and area of ​​the solar panels.

[0154] Hardware configuration

[0155] Sensor equipment: Includes sensors that measure the angle of the sun, light intensity, weather information, and wind speed. The data collected from these sensors forms the foundation of the entire system.

[0156] Server device: Performs data analysis and generates control commands. Equipped with an AI analysis module, it analyzes collected data in real time.

[0157] Solar panel control device: Includes motors and actuators that physically adjust the orientation and angle of the panels based on analysis results.

[0158] Software Configuration

[0159] Data Analysis Module: This is an AI analysis module built using Python and TensorFlow. It analyzes data from sensors and calculates the optimal placement of solar panels.

[0160] Communication software: Software for receiving data from sensors and sending it to a server. It uses real-time streaming technology.

[0161] User Interface: An interface for displaying analysis results on smart glasses or smartphones. Users can monitor and manually control the system through this interface.

[0162] Processing flow

[0163] Data collection

[0164] The server receives data from sensors that measure the sun's angle, light intensity, weather information, and wind speed in real time. This data is stored in a database on the server.

[0165] Data Analysis

[0166] The server uses an AI analysis module to analyze the collected data in real time. Based on the analysis results, it generates control commands to optimally adjust the orientation, angle, and area of ​​the solar panels.

[0167] Transmission and execution of control commands

[0168] Control commands generated from the server are sent to the solar panel control unit. The control unit then physically adjusts the orientation and angle of the panels according to the commands.

[0169] Monitoring and user notifications

[0170] The server monitors the current status of the solar panels in real time. If an anomaly is detected, it sends a notification to a smart device and issues a visual or audible warning.

[0171] Manual operation by the user

[0172] Users can monitor the system via smart glasses or a smartphone and manually control the solar panels using voice commands or touch gestures as needed.

[0173] Specific example

[0174] For example, if strong winds of 18 m / s are predicted, the sensor sends wind speed data to the server. The server quickly inputs this data into the AI ​​analysis module, and if strong winds are predicted, an analysis result is generated. Based on this result, the server generates a protective command to position the panels horizontally and sends it to the solar panel control unit. The control unit executes this command and moves the panels horizontally to prevent damage from strong winds.

[0175] Example of a prompt

[0176] Applying the following invention, create a prototype of a solar power system monitoring application to be installed on smart glasses. This application will have the functions of real-time data display, anomaly detection notification, and manual control.

[0177] 1. Data is collected from sensors on solar panels.

[0178] 2. Analyze the data using the AI ​​analysis module.

[0179] 3. Data and analysis results are visually displayed on smart glasses.

[0180] 4. Control the panel using voice or touch gestures.

[0181] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0182] Step 1:

[0183] The server receives data from sensors that measure the sun's angle, light intensity, weather information, and wind speed in real time. Specifically, the data acquired by the sensor devices is temporarily stored in the server's database. The input data includes the sun's angle, light intensity values, weather data such as temperature and humidity, and wind speed values. After acquiring this data, the server proceeds to the next analysis step.

[0184] Step 2:

[0185] The server inputs the data collected in Step 1 into the AI ​​analysis module. The AI ​​analysis module (using TensorFlow) analyzes this data and calculates the optimal orientation, angle, and area of ​​the solar panels. Based on the input data of the sun's angle, light intensity, weather, and wind speed, the AI ​​performs analysis and generates optimal placement parameters for the solar panels as output.

[0186] Step 3:

[0187] The server generates control commands based on the analysis results from Step 2. Specifically, it creates control commands according to the optimal orientation, angle, and area of ​​the solar panels calculated by the AI ​​analysis module. Furthermore, it generates special commands to protect the panels during strong winds or snowfall. The input data is the analysis results from the AI ​​analysis module, and the output data is the control commands related to the orientation, angle, and area of ​​the panels.

[0188] Step 4:

[0189] The terminal executes control commands received from the server. Specifically, the terminal sends commands to the solar panel control device, causing motors and actuators to physically adjust the orientation and angle of the panels. The input data is the control commands from the server, and the output is the actual physical change in the placement of the solar panels.

[0190] Step 5:

[0191] The server monitors the current status of the solar panels in real time. If an anomaly is detected (for example, if the wind speed exceeds a certain level), the server generates an anomaly notification and sends it to the user's smart device. The input data is real-time status data from the solar panels, and the output data is the anomaly notification message.

[0192] Step 6:

[0193] Users monitor the system status via smart glasses or smartphones. In particular, when an anomaly notification is displayed, users can manually control the system using voice commands or touch gestures. Input data includes anomaly notifications from the server and user voice commands and touch gestures, while output data consists of user feedback and response instructions.

[0194] 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.

[0195] This invention relates to an AI-powered smart solar power generation system that enhances the efficiency and safety of solar power generation systems. This system utilizes numerous sensors and real-time AI data analysis to automatically and optimally control the orientation, angle, and area of ​​solar panels. Furthermore, it incorporates an emotion engine that recognizes user emotions to improve user satisfaction. Specific embodiments of this system are described below.

[0196] Data collection

[0197] sensor

[0198] The sensors measure the sun's angle, light intensity (illuminance), weather information (sunny, cloudy, rainy, etc.), and wind speed in real time. This data is crucial for optimizing solar power generation.

[0199] Emotional Engine

[0200] The emotion engine analyzes the user's facial expressions and voice through input devices such as cameras and microphones to recognize the user's emotions. The emotion data is then sent to a server.

[0201] Data analysis and control command generation

[0202] server

[0203] The server receives data collected from sensors and the emotion engine, and analyzes it using an AI analysis module. Based on the data analysis, it calculates the optimal orientation, angle, and area of ​​solar panels for solar power generation. Furthermore, it takes user emotion data into consideration and performs solar panel placement and other system operations in a way that satisfies the user.

[0204] Program processing

[0205] 1. Data Collection

[0206] Sensors measure data on the sun's angle, light intensity, weather, and wind speed in real time and send it to the server. The emotion engine collects user emotion data and sends it to the server.

[0207] 2. Data Analysis

[0208] The server receives the collected data and inputs it into the AI ​​analysis module. The AI ​​analysis module analyzes the data and calculates the optimal placement of solar panels. Furthermore, it analyzes emotional data and generates control commands that will satisfy the user.

[0209] 3. Control command generation

[0210] The server generates control commands to adjust the orientation, angle, and area of ​​the solar panels based on the analysis results. It also generates commands to protect the panels in response to wind speed and weather fluctuations. Based on emotional data, it also considers placement and operation according to the user's preferences.

[0211] 4. Panel adjustment

[0212] The terminal receives control commands and physically adjusts the orientation, angle, and area of ​​the solar panels. This optimizes power generation and improves energy efficiency. Adjustments may also be made based on emotional data.

[0213] 5. Status Monitoring

[0214] The server monitors the current state of the panel and records the data. If an anomaly is detected, it generates an alert and notifies the user. The user's emotional state is also continuously monitored.

[0215] Specific example

[0216] For example, consider a scenario where strong winds of 15 m / s are predicted for 12:00 PM on a given day. In this case, a sensor sends wind speed data to a server. The server inputs this data into an AI analysis module, which then outputs an analysis result if strong winds are predicted. The server generates a protective command to position the panels horizontally and sends it to the terminal. The terminal receives this command, and the panel control module activates a motor to move the panels horizontally. Meanwhile, if the emotion engine recognizes that the user's stress level is high, the system takes action to provide the user with a relaxing environment (for example, by changing the panel position or adjusting the timing of notifications). This series of processes prevents damage to the panels due to strong winds, enhances safety, and improves user satisfaction.

[0217] Thus, the AI ​​smart solar power generation system of the present invention maximizes the efficiency and safety of solar power generation through the steps of data collection, data analysis, control command generation, panel adjustment, and condition monitoring, and further optimizes the system's operation while also taking into account the user's emotions.

[0218] The following describes the processing flow.

[0219] Step 1: Data Collection

[0220] A sensor measures the angle of the sun. A sensor measures the amount of light (illuminance). A sensor acquires weather information (sunny, cloudy, rainy, etc.). A sensor measures wind speed. Each sensor sends this data to the server. The emotion engine analyzes the user's facial expressions and voice through the camera and microphone, acquires the user's emotion data, and sends it to the server.

[0221] Step 2: Data aggregation and preprocessing

[0222] The server receives data transmitted from each sensor and emotion engine. The server cleans the received data, processing for missing or outlier values. The server stores the pre-processed data in data storage.

[0223] Step 3: Data Analysis

[0224] The server inputs the stored data into the AI ​​analysis module. The AI ​​analysis module calculates the predicted position of the sun. The AI ​​analysis module calculates the optimal panel orientation, angle, and area. The AI ​​analysis module analyzes the user's emotional data and calculates the optimal placement and operation to satisfy the user.

[0225] Step 4: Control command generation

[0226] The server receives calculation results from the AI ​​analysis module. The server generates control commands to optimize the orientation, angle, and area of ​​the solar panels. The server generates protection commands based on wind and snowfall forecasts. It also considers placement and operation according to user preferences based on sentiment data. The server sends the generated control and protection commands to the terminal.

[0227] Step 5: Panel Position Control

[0228] The terminal receives control commands from the server. The terminal sends commands to the panel control module. The panel control module operates the motors to adjust the orientation, angle, and area of ​​the solar panels. If a protection command is received after a forecast of strong winds or snowfall, the panel control module moves the panels horizontally or vertically. Depending on the user's emotional data, relaxing placements and actions may be performed.

[0229] Step 6: Status Monitoring

[0230] The server monitors the panel's current state. The server records the panel's operational data (change history of orientation, angle, and area). If the server detects an anomaly, it generates an alert and notifies the user. The server also continuously monitors the user's emotional state and provides feedback as needed.

[0231] (Example 2)

[0232] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0233] Conventional solar power generation systems typically maximize efficiency by considering only sunlight intensity and panel angle. However, this can sometimes come at the expense of user satisfaction and safety. In particular, protective measures for panels during strong winds and snowfall are insufficient, and system operation that takes user feelings into consideration has yet to be realized. There is a need to solve these problems.

[0234] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for measuring the angle of the sun, means for measuring the amount of light, means for acquiring weather information, means for measuring wind speed, means for analyzing the user's emotions, means for receiving data acquired from each of the means and analyzing the data, means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the data analysis, means for physically adjusting the solar panels based on the control commands, means for monitoring the state of the solar panels, and means for detecting abnormalities and notifying the user. This makes it possible to maximize the efficiency and safety of solar power generation and further optimize the operation of the system while also considering the user's emotions.

[0235] "Means for measuring the angle of the sun" refers to devices or techniques for accurately measuring the position and angle of the sun.

[0236] "Means for measuring light intensity" refers to devices or technologies for measuring the intensity or illuminance of sunlight.

[0237] "Means for acquiring weather information" refers to devices or technologies for collecting weather conditions (such as sunny, cloudy, or rainy).

[0238] "Means for measuring wind speed" refers to a device or technology for measuring the speed of wind.

[0239] "Means for analyzing user emotions" refers to devices or technologies that analyze a user's facial expressions and voice to determine their emotional and psychological state.

[0240] "Means for receiving data acquired from each of the above means and analyzing the said data" refers to a device or technology for receiving various sensor data and emotional data and analyzing them.

[0241] "Means for generating control commands to optimally adjust the orientation, angle, and area of ​​solar panels" refers to an apparatus or technology for determining the optimal orientation, angle, and area of ​​solar panels based on analysis results, and generating control commands based on those results.

[0242] "Means for physically adjusting solar panels" refers to devices or technologies for actually adjusting the physical arrangement and angle of solar panels based on control commands.

[0243] "Means for monitoring the status of solar panels" refers to devices or technologies for monitoring the current status of solar panels (position, angle, power generation, etc.) in real time.

[0244] "Means for detecting anomalies and notifying users" refers to devices or technologies that inform users of anomalies detected during system monitoring in the form of alerts or notifications.

[0245] This invention relates to an AI-powered smart solar power generation system that enhances the efficiency and safety of solar power generation systems. This system utilizes numerous sensors and real-time AI data analysis to automatically and optimally control the orientation, angle, and area of ​​solar panels. Furthermore, by incorporating an emotion engine that recognizes user emotions, it aims to improve user satisfaction.

[0246] Data collection

[0247] The server uses multiple sensors to measure the angle of the sun, light intensity (illuminance), weather information (sunny, cloudy, rainy, etc.), and wind speed. The data acquired from these sensors is transmitted to the server in real time. It also uses an emotion engine to collect user emotion data. The emotion engine analyzes the user's facial expressions and voice through input devices such as cameras and microphones to recognize the user's emotions.

[0248] Data analysis and control command generation

[0249] The server receives data collected from sensors and the emotion engine and analyzes it using an AI analysis module. Based on the data analysis, it calculates the optimal orientation, angle, and area of ​​solar panels for solar power generation. Furthermore, it takes user emotion data into consideration and performs solar panel placement and other system operations in a way that satisfies the user.

[0250] Specific example

[0251] For example, consider a scenario where strong winds of 15 m / s are predicted for 12:00 PM on a given day. In this case, a sensor sends wind speed data to a server. The server inputs this data into an AI analysis module, which then outputs an analysis result if strong winds are predicted. The server generates a protective command to position the panels horizontally and sends it to the terminal. The terminal receives this command, and the panel control module activates a motor to move the panels horizontally. Meanwhile, if the emotion engine recognizes that the user's stress level is high, the system takes action to provide the user with a relaxing environment (for example, by changing the panel position or adjusting the timing of notifications). This series of processes prevents damage to the panels due to strong winds, enhances safety, and improves user satisfaction.

[0252] Examples of prompt statements

[0253] Enter the following prompt into the generative AI model:

[0254] "Please explain how the AI ​​smart solar power system protects the panels when strong winds of 15 m / s are predicted. Also, please explain how the system responds when the user is under high stress."

[0255] Based on this prompt, the generated response will provide details on how the system collects and analyzes data, how it actually adjusts the panel, and how it responds based on user sentiment data.

[0256] The AI ​​smart solar power generation system of the present invention maximizes the efficiency and safety of solar power generation through the steps of data collection, data analysis, control command generation, panel adjustment, and condition monitoring, and further optimizes the system's operation while also taking into account the user's emotions.

[0257] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0258] Step 1: Data Collection

[0259] The server receives real-time data from numerous sensors regarding the angle of the sun, light intensity (illuminance), weather information (sunny, cloudy, rainy, etc.), and wind speed. Users provide emotional data through their cameras and microphones. An emotion engine analyzes the user's facial expressions and voice to generate emotional data. This data is the input data sent to the server. Specifically, the sensors measure data every minute and send it to the server.

[0260] Step 2: Data Analysis

[0261] The server receives data collected from sensors and the emotion engine. This data is preprocessed to ensure consistency and fill in any gaps. Next, the server inputs this preprocessed data into the AI ​​analysis module. The AI ​​analysis module analyzes the data to calculate the optimal orientation, angle, and area of ​​the solar panels. Furthermore, it generates control commands that will satisfy the user based on the user's emotion data. Specifically, the AI ​​analysis module inputs the dataset into a model and performs analysis using an optimization algorithm.

[0262] Step 3: Generation of control commands

[0263] The server assembles specific control commands to adjust the orientation, angle, and area of ​​the solar panels based on the analysis results from the AI ​​analysis module. These control commands determine the optimal placement and operation of the solar panels and also include protective commands against wind speed and weather fluctuations. For example, it generates commands such as, "If the wind speed is 15 m / s or higher, position the panels horizontally."

[0264] Step 4: Sending control commands

[0265] The server sends the generated control command to the terminal. The terminal receives this control command and prepares to control the panel according to the settings. Specifically, the server sends command data to the terminal via the network.

[0266] Step 5: Panel adjustment

[0267] The terminal receives control commands sent from the server and physically adjusts the orientation and angle of the solar panels based on them. It drives motors and actuators to move the panels to the optimal position. Specifically, the terminal executes a motor control program to tilt the panels horizontally.

[0268] Step 6: Status Monitoring

[0269] The server monitors the current status of the solar panels in real time and records the data. It also generates an alert and notifies the user if an anomaly is detected. The user can then take the necessary actions after receiving the notification. Specifically, the server periodically checks the panel's position, angle, power generation, etc., and sends email or application notifications if any anomalies are detected.

[0270] (Application Example 2)

[0271] 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".

[0272] Conventional solar power generation systems optimize power generation efficiency based solely on environmental data, without considering comprehensive energy management in logistics facilities or optimizing the emotional well-being of workers. Furthermore, irregular energy consumption in logistics centers often leads to employee stress and problems with the working environment. This presents a challenge: simultaneously improving energy efficiency and working conditions.

[0273] 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.

[0274] In this invention, the server includes means for measuring the angle of the sun, means for measuring light intensity, means for acquiring weather information, means for measuring wind speed, means for measuring the energy consumption of the logistics center, means for analyzing the emotions of employees, means for receiving and analyzing data acquired from each of the means, means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the data analysis, means for physically adjusting the solar panels based on the control commands, means for optimizing the energy consumption pattern of the logistics center, and means for optimizing the working environment of employees based on the results of the emotion analysis. This makes it possible to improve energy efficiency and optimize the working environment of employees in the logistics center.

[0275] "Means for measuring the angle of the sun" refers to devices and sensor sets used to measure the position and angle of the sun in real time.

[0276] "Means for measuring light intensity" refers to devices or sensors used to measure the amount of ambient light.

[0277] "Means for acquiring weather information" refers to means of communication with sensors and databases used to acquire weather conditions (sunny, cloudy, rainy, etc.).

[0278] "Means for measuring wind speed" refers to devices or sensors for measuring wind speed in real time.

[0279] "Means for measuring the energy consumption of a logistics center" refers to devices or systems for measuring the consumed energy in a logistics facility in real time.

[0280] "Means for analyzing employees' emotions" refers to systems or algorithms for analyzing employees' facial expressions and voice data to recognize their emotional states.

[0281] "Means for receiving data obtained from each of the above means and analyzing the data" refers to devices or programs for receiving data transmitted from sensors or devices and analyzing the data with an AI analysis module.

[0282] "Means for generating a control command for optimally adjusting the orientation, angle, and area of a solar panel based on the result of the data analysis" refers to systems or programs for generating a command to instruct an optimal setting of a solar panel based on the analysis result.

[0283] "Means for physically adjusting a solar panel based on the control command" refers to machines or devices for physically adjusting the orientation and angle of a solar panel upon receiving the control command.

[0284] "Means for optimizing the energy consumption pattern of a logistics center" refers to systems or programs for efficiently managing and optimizing the energy consumption of a logistics center.

[0285] "Means for optimizing employees' working environment based on the result of the emotion analysis" refers to systems or programs for improving the working environment by reflecting the result of employees' emotion analysis.

[0286] The present invention is a system for realizing energy management and optimization of the working environment in a logistics center. The following will explain the detailed configuration and operation for implementing the present invention.

[0287] Data collection

[0288] 1. Measurement of solar angle:

[0289] · Hardware used: Solar angle sensor

[0290] · Measure the position and angle of the sun in real time and send the data to the server.

[0291] 2. Measurement of light intensity:

[0292] · Hardware used: Light sensor

[0293] · Measure the amount of ambient light and send the data to the server.

[0294] 3. Acquisition of weather information:

[0295] · Hardware used: Weather sensor, Internet connection

[0296] · Acquire the weather situation in real time and send the data to the server.

[0297] 4. Measurement of wind speed:

[0298] · Hardware used: Wind speed sensor

[0299] · Measure the wind speed and send the data to the server.

[0300] 5. Measurement of energy consumption:

[0301] · Hardware used: Energy meter, RFID tag, GPS

[0302] ·Collect the energy consumption data within the logistics center and send it to the server.

[0303] 6. Sentiment Analysis:

[0304] ·Hardware used: Camera, microphone

[0305] ·Software used: Sentiment analysis engine (e.g., OpenCV)

[0306] ·Analyze the expressions and voices of employees and send the sentiment data to the server.

[0307] Data Analysis and Control Command Generation

[0308] 1. Data Reception:

[0309] ·The server receives data from each sensor and the sentiment analysis engine.

[0310] 2. AI Analysis Module:

[0311] ·Software used: TensorFlow, PyTorch

[0312] ·The server inputs the received data into the AI analysis module to calculate the optimal orientation, angle, and area of the solar panels.

[0313] ·Calculate the pattern for optimizing the energy consumption of the logistics center.

[0314] 3. Control Command Generation:

[0315] ·The server generates control commands based on the AI analysis results.

[0316] ·Send commands for physical adjustment of the solar panels and optimization of the energy consumption pattern. <{0000996}><{0000997}><{0000998}>·Based on the sentiment data, also generate commands to optimize the working environment of employees.

[0318] Panel adjustment and energy management

[0319] 1. Panel adjustment:

[0320] Hardware used: Solar panel angle adjustment mechanism, motor

[0321] Based on control commands, the orientation and angle of the solar panels are physically adjusted.

[0322] 2. Energy Management:

[0323] • Software used: Energy Management System

[0324] • Optimize the energy consumption patterns of logistics centers in real time.

[0325] 3. Optimizing the working environment:

[0326] Hardware used: Lighting, air conditioning system

[0327] • Optimize the working environment for employees based on control commands.

[0328] Status Monitoring

[0329] 1. Monitoring:

[0330] The server constantly monitors the current status of each device.

[0331] 2. Anomaly detection:

[0332] • If an anomaly is detected, an alert will be generated and the user will be notified.

[0333] Specific example

[0334] 1. How to respond during strong winds:

[0335] • Hardware used: Wind speed sensor, solar panel angle adjustment mechanism

[0336] When the wind speed sensor measures 15 m / s, the server inputs the wind speed data into the AI ​​analysis module and generates commands to cope with strong winds. A command is issued to position the solar panels horizontally, and the motor moves the panels.

[0337] Example of a prompt:

[0338] 1. Environmental data collection:

[0339] "Collect light intensity data in real time from the sensor device during sunny conditions and transmit it to the data server."

[0340] 2. Emotion analysis:

[0341] "We analyze employees' facial images in real time to assess their stress levels."

[0342] 3. Control command generation:

[0343] "Protect the solar panels to a safe horizontal position, given the current wind speed of 15 m / s."

[0344] 4. Anomaly monitoring:

[0345] "Continuously monitor the panel status and issue an immediate alert if any abnormal values ​​are detected."

[0346] In this way, the system will perform panel adjustments, optimize energy consumption, and improve the working environment by collecting data from various sensors and analyzing it with AI.

[0347] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0348] Step 1:

[0349] Collect energy data

[0350] Inputs: Sun angle sensor, light sensor, weather sensor, wind speed sensor, energy meter, camera and microphone

[0351] The server collects data from the above sensors and devices in real time.

[0352] Output: Data from each sensor (sun angle, light intensity, weather information, wind speed, energy consumption, emotion data)

[0353] Specific operation: The server periodically receives data transmitted from sensors and saves it to local storage. In addition, the emotion engine analyzes employees' facial expressions and voices and saves their emotional state as data.

[0354] Step 2:

[0355] Preprocessing of data

[0356] Input: Raw data collected in Step 1

[0357] The server cleanses the raw data it collects, removing outliers and noise.

[0358] Output: Cleansed data

[0359] Specific operation: The server uses a database management system to format and normalize data, generating a clean dataset. For example, it filters out abnormal values ​​from temperature sensors (such as sudden fluctuations).

[0360] Step 3:

[0361] Data Analysis

[0362] Input: Clean data obtained in Step 2

[0363] The server uses AI analysis modules such as TensorFlow and PyTorch to analyze data and calculate the optimal settings for the orientation, angle, and area of ​​solar panels. It also analyzes energy consumption patterns and employee sentiment data to generate instructions for setting up the optimal work environment.

[0364] Output: Analysis results (optimal solar panel settings, energy consumption patterns, work environment settings)

[0365] Specific operation: Data is input into the AI ​​model, and the optimal numerical settings are calculated as a result of the analysis. For example, based on the angle of the sun at 3 PM, the panel angle is calculated to be 30 degrees. At the same time, if an employee is working for a long time, a command prompting them to take a break is generated.

[0366] Step 4:

[0367] Generation of control commands

[0368] Input: Analysis results obtained in Step 3

[0369] The server sends control commands to each sensor and device based on the analysis results.

[0370] Output: Control commands (adjustment of solar panel angle, change of energy consumption pattern, adjustment of working environment)

[0371] Specific operation: The server sends a control signal to the solar panel control unit, for example, "Adjust the panel to 30 degrees." At the same time, it sends a command to the lighting system to "Switch to an energy-saving mode."

[0372] Step 5:

[0373] Control implementation

[0374] Input: Control command from step 4

[0375] The terminal receives control commands and physically adjusts the orientation and angle of the solar panels. It also changes the settings of lighting and air conditioning systems.

[0376] Output: Actual adjustment results (orientation and angle of solar panels, changes in working environment)

[0377] Specific operation: The solar panel control unit drives a motor to adjust the panels to the specified angle. It also optimizes energy consumption and automatically switches between lighting and air conditioning.

[0378] Step 6:

[0379] Status Monitoring

[0380] Input: Real-time data from each source

[0381] The server constantly monitors the current status of each system and immediately generates an alert if an anomaly occurs.

[0382] Output: Anomaly detection alert, system log

[0383] Specific operation: The server monitors sensor data at regular intervals and detects abnormal values ​​(e.g., excessive temperature changes). If an abnormality is found, it sends an email or SMS notification to the administrator. It also logs all data.

[0384] 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.

[0385] 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.

[0386] 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.

[0387] [Second Embodiment]

[0388] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0389] 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.

[0390] 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).

[0391] 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.

[0392] 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.

[0393] 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).

[0394] 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.

[0395] 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.

[0396] 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.

[0397] 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.

[0398] 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.

[0399] 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".

[0400] This invention relates to an AI-powered smart solar power generation system that enhances the efficiency and safety of solar power generation systems. This system utilizes numerous sensors and real-time AI data analysis to automatically and optimally control the orientation, angle, and area of ​​solar panels. Specific embodiments of this system are described below.

[0401] Data collection

[0402] sensor

[0403] The sensors measure the sun's angle, light intensity, weather, and wind speed in real time. This data is crucial for optimizing solar power generation.

[0404] Data analysis and control command generation

[0405] server

[0406] The server receives data collected from sensors and analyzes it using an AI analysis module. Based on the data analysis, it calculates the optimal orientation, angle, and area of ​​solar panels for solar power generation. It also generates commands to protect the panels in response to wind speed and weather fluctuations.

[0407] Program processing

[0408] 1. Data Collection

[0409] The sensor measures data on the sun's angle, light intensity, weather, and wind speed in real time and transmits it to the server.

[0410] 2. Data Analysis

[0411] The server receives the collected data and inputs it into the AI ​​analysis module. The AI ​​analysis module analyzes the data and calculates the optimal placement of the solar panels.

[0412] 3. Control command generation

[0413] The server generates control commands to adjust the orientation, angle, and area of ​​the solar panels based on the analysis results. It also generates commands to protect the panels in response to changes in wind speed and weather conditions.

[0414] 4. Panel adjustment

[0415] The terminal receives control commands and physically adjusts the orientation, angle, and area of ​​the solar panels. This optimizes power generation and improves energy efficiency.

[0416] 5. Status Monitoring

[0417] The server monitors the current status of the panel and notifies the user if an anomaly is detected.

[0418] Specific example

[0419] For example, consider a scenario where strong winds of 15 m / s are predicted at 12:00 PM on a given day. In this case, the sensor sends wind speed data to the server. The server inputs this data into an AI analysis module, which then generates an analysis result if strong winds are predicted. The server generates a protective command to position the panels horizontally and sends it to the terminal. The terminal receives this command, and the panel control module activates a motor to move the panels horizontally. This entire process prevents damage to the panels due to strong winds, extending the lifespan and enhancing the safety of the entire system.

[0420] Thus, the AI ​​smart solar power generation system of the present invention maximizes the efficiency and safety of solar power generation through the steps of data collection, data analysis, control command generation, panel adjustment, and condition monitoring.

[0421] The following describes the processing flow.

[0422] Step 1: Data Collection

[0423] The sensor measures the angle of the sun. The sensor measures the amount of light (illuminance). The sensor acquires weather information (sunny, cloudy, rainy, etc.). The sensor measures wind speed. Each sensor sends the collected data to the server.

[0424] Step 2: Data aggregation and preprocessing

[0425] The server receives data transmitted from each sensor. The server cleans the received data, processing for missing or outlier values. The server saves the pre-processed data to data storage.

[0426] Step 3: Data Analysis

[0427] The server inputs the stored data into the AI ​​analysis module. The AI ​​analysis module calculates the predicted position of the sun. The AI ​​analysis module calculates the optimal panel orientation, angle, and area. Based on wind speed and weather information, the AI ​​analysis module determines whether to generate a protection command.

[0428] Step 4: Control command generation

[0429] The server receives calculation results from the AI ​​analysis module. The server generates control commands to optimize the orientation, angle, and area of ​​the solar panels. The server generates protection commands based on wind and snowfall forecasts. The server sends the generated control and protection commands to the terminal.

[0430] Step 5: Panel Position Control

[0431] The terminal receives control commands from the server. The terminal sends commands to the panel control module. The panel control module operates the motors to adjust the orientation, angle, and area of ​​the solar panels. If a protection command is received after a forecast of strong winds or snowfall, the panel control module moves the panels horizontally or vertically.

[0432] Step 6: Status Monitoring

[0433] The server monitors the current status of the panel. The server records the panel's operational data (change history of orientation, angle, and area). If the server detects an anomaly, it generates an alert and notifies the user.

[0434] (Example 1)

[0435] 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".

[0436] To improve the efficiency and safety of solar power generation systems, optimal panel placement based on real-time weather information and the angle of the sun is required. However, current systems require manual adjustments, resulting in low efficiency and an increased risk of panel damage during extreme weather conditions such as strong winds and snowfall. Furthermore, the lack of a mechanism to immediately notify users when an anomaly occurs makes it difficult to respond quickly.

[0437] 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.

[0438] In this invention, the server includes means for measuring the angle of the sun, means for measuring light intensity, means for acquiring weather information, means for measuring wind speed, means for receiving data acquired from each of the means and storing it in a database, means including an AI analysis module for analyzing the data, means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the data analysis, means for physically adjusting the solar panels via a servo motor according to the control commands, and means for monitoring the current state of the solar panels and notifying the user if an abnormality is detected. This enables real-time automatic adjustment, improving the efficiency and safety of solar power generation, as well as enabling a rapid response in the event of an abnormality.

[0439] "Means for measuring the angle of the sun" refers to instruments that measure the current position and altitude angle of the sun. Specifically, this includes sensors for accurately determining the sun's position.

[0440] "Means for measuring light intensity" refers to devices that measure the intensity of ambient sunlight. Specifically, this includes devices that measure light intensity using photoelectric sensors or photodiodes.

[0441] "Means of obtaining weather information" refers to systems or services for obtaining meteorological data. Specifically, this includes APIs for obtaining information from external meteorological data providers and weather stations established independently.

[0442] "Means for measuring wind speed" refers to equipment for measuring wind speed. Specifically, this includes devices for measuring wind speed using an anemometer (wind speed meter), etc.

[0443] "Means for receiving data and storing it in a database" refers to a system for acquiring data from sensors, transferring it to a central computer, and storing it for long-term use. Specifically, this includes communication modules and data storage (e.g., MySQL, MongoDB).

[0444] An "AI analysis module" is an artificial intelligence system for analyzing acquired data. Specifically, it includes a software module that uses machine learning and deep learning algorithms to calculate the optimal panel arrangement.

[0445] "Means for generating control commands" refers to a device or software that creates commands for appropriately controlling solar panels based on the results of data analysis. Specifically, this includes a system that generates control signals using a programmed algorithm.

[0446] A "servo motor" is a drive device used to adjust the orientation and angle of solar panels in response to control commands. Specifically, it includes motors capable of precise rotation and angle adjustment.

[0447] "Means for monitoring status and detecting anomalies" refers to a system that constantly monitors the current operating state of a system and issues warnings when abnormal conditions or operations are detected. Specifically, this includes an alert system that analyzes data from sensors and detects abnormal values.

[0448] "Means of notifying users" refers to methods for informing users of system abnormalities or important information. Specifically, this includes communication methods such as email notifications, SMS, and push notifications.

[0449] This invention relates to an AI-powered smart solar power system that enhances the efficiency and safety of solar power generation systems. This system is configured to automatically and optimally control the orientation, angle, and area of ​​solar panels by utilizing numerous sensors and real-time AI data analysis.

[0450] Data collection

[0451] The sensors measure information on the sun's angle, light intensity, weather, and wind speed in real time. This includes the following sensors:

[0452] Optical sensor for measuring the angle of the sun

[0453] Photoelectric sensor for measuring light intensity

[0454] A system for acquiring weather information from weather sensors or external data providers.

[0455] An anemometer (wind speed meter) for measuring wind speed

[0456] Data reception and storage

[0457] The server receives data transmitted from the sensors and stores it in a database. Examples of databases used include MySQL and MongoDB. This ensures that the latest data is always updated and used for subsequent analysis.

[0458] Data Analysis

[0459] The server receives and stores data, which is then input into an AI analysis module. Specifically, an AI analysis module using deep learning frameworks such as TensorFlow or PyTorch analyzes the data and calculates the optimal orientation, angle, and area of ​​the solar panels.

[0460] Control command generation

[0461] The server generates control commands to optimize the orientation, angle, and area of ​​the solar panels based on the analysis results of the AI ​​analysis module. It also generates protective commands to move the panels horizontally or vertically if the wind speed exceeds a certain value or if snowfall is observed.

[0462] Control command transmission

[0463] The server sends the generated control commands to the terminal. MQTT or HTTP protocols are used for communication.

[0464] Panel adjustment

[0465] The terminal drives servo motors to adjust the orientation and angle of the solar panels based on the control commands it receives. For example, if strong winds are predicted, the panels will be moved horizontally.

[0466] Status Monitoring

[0467] The server constantly monitors the current status of the solar panels and sends a notification to the user if an anomaly is detected. Notifications are sent via email or push notifications.

[0468] Specific example

[0469] For example, if strong winds of 15 m / s are predicted at 12:00 on a given day, the system will operate in the following manner:

[0470] 1. The sensor measures wind speed data and sends it to the server.

[0471] 2. The server receives the data and inputs it into the AI ​​analysis module.

[0472] 3. The AI ​​analysis module analyzes the data and determines that strong winds are predicted.

[0473] 4. The server generates a protective command to position the panel horizontally and sends it to the terminal.

[0474] 5. The terminal receives the command and drives the servo motor to move the panel horizontally.

[0475] This series of processes prevents damage to panels caused by strong winds, thereby improving safety. Furthermore, the system can quickly detect and notify users of any abnormalities, allowing them to respond promptly.

[0476] Examples of prompts to input into a generative AI model:

[0477] "Please explain how the AI ​​smart solar power system works based on the following conditions: It is 12:00 PM on a day when strong winds of 15 m / s are predicted."

[0478] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0479] Step 1:

[0480] Data collection

[0481] The sensor measures data on the sun's angle, light intensity, weather, and wind speed in real time and transmits it to the server. Specifically, the sensor measures the sun's angle and light intensity every second and the wind speed every minute. The input data consists of the sun's angle, light intensity, weather information, and wind speed, and this data is packaged with a timestamp when transmitted. The output is the measurement data transmitted to the server.

[0482] Step 2:

[0483] Data reception and storage

[0484] The server receives data transmitted from the sensor and stores it in a database. The input is measurement data transmitted from the sensor, which the server receives and stores in a database, for example, using MySQL or MongoDB. Specifically, the received data is converted into a format that is easy to analyze and inserted into the corresponding field in the database. The output is the measurement data stored in the database.

[0485] Step 3:

[0486] Data Analysis

[0487] The server inputs data collected from the database into the AI ​​analysis module. The input is the latest measurement data obtained from the database, which the AI ​​analysis module (e.g., a deep learning model using TensorFlow or PyTorch) analyzes. Specifically, the data is fed into the model to calculate the optimal orientation, angle, and area of ​​the solar panels. The output is the parameters for the optimal orientation, angle, and area.

[0488] Step 4:

[0489] Control command generation

[0490] The server generates control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the analysis results of the AI ​​analysis module. The input is the data analysis results, and the server constructs the control commands based on this. Specifically, this includes commands such as positioning the panels horizontally when it is determined that the wind speed exceeds 10 m / s. The generated control commands are packaged in JSON format, etc. The output is the generated control commands.

[0491] Step 5:

[0492] Control command transmission

[0493] The server sends the generated control commands to the terminal. The input is the generated control commands, which are sent to the terminal using protocols such as MQTT or HTTP. Specifically, the command packets are converted into a format suitable for the communication protocol and sent to the terminal. The output is the control commands sent to the terminal.

[0494] Step 6:

[0495] Panel adjustment

[0496] The terminal drives a servo motor to adjust the orientation and angle of the solar panel based on the control commands it receives. The input is a control command sent from the server, which the terminal receives and sends commands to the servo motor. Specifically, it sends signals to the motor to control the rotation angle and direction. For example, if it is determined that the wind speed exceeds 10 m / s, the motor rotates to position the panel horizontally. The output is the physical position of the adjusted solar panel.

[0497] Step 7:

[0498] Status Monitoring

[0499] The server constantly monitors the current status of the solar panels and sends a notification to the user if an anomaly is detected. The input is the adjusted panel status data, which the server monitors to detect anomalies. Specifically, it uses data from angle sensors and temperature sensors to generate an alert if the values ​​differ from the set values. The output is an anomaly notification sent to the user, which is sent via email or push notification.

[0500] (Application Example 1)

[0501] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0502] Existing solar power generation systems suffer from reduced power generation efficiency due to the lack of real-time data analysis to optimally adjust the orientation and angle of solar panels. Furthermore, they struggle to respond quickly to extreme weather events such as strong winds and snowfall, raising concerns about panel damage and system safety. Additionally, they lack the functionality to remotely monitor the system status and manually control it as needed, even when the user is not on-site.

[0503] 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.

[0504] In this invention, the server includes means for measuring the angle of the sun, means for measuring light intensity, means for acquiring weather information, means for measuring wind speed, means for receiving data acquired from each of the means and analyzing the data, means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the data analysis, means for physically adjusting the solar panels based on the control commands, means for displaying the results on a smart device in real time, and means for the user to manually control the panels using voice commands or touch gestures. This enhances the power generation efficiency and safety of the solar power generation system, and enables remote monitoring and control by the user.

[0505] "Means for measuring the angle of the sun" refers to a sensor device that detects the angle of the sun in real time according to its position.

[0506] "Means for measuring light intensity" refers to a sensor device used to measure the current intensity of sunlight.

[0507] "Means of acquiring weather information" refer to sensors and external data provision services for collecting current temperature, humidity, precipitation, etc.

[0508] "Means for measuring wind speed" refers to a sensor device for measuring wind speed in real time.

[0509] "Means for analyzing data" refers to an AI analysis module that uses data collected from sensors to evaluate the situation and generate necessary control commands.

[0510] "Means for generating control commands" refers to a device or software that generates commands to optimally adjust the orientation, angle, and area of ​​solar panels based on the results of data analysis.

[0511] "Means for physically adjusting solar panels" refer to motors and actuators that automatically change the orientation and angle of the panels according to control commands.

[0512] "Means for displaying results in real time on smart devices" refers to communication and display devices for notifying smart devices (smart glasses, smartphones) of analysis results and data from sensors.

[0513] "Means for manually controlling the panel using voice commands or touch gestures" refers to an interface that allows users to manually adjust the solar panels using voice or physical operations.

[0514] System Overview

[0515] This invention provides an AI-powered smart control system to enhance the efficiency and safety of solar power generation systems. This system collects data from multiple sensors, analyzes it in real time, and optimally adjusts the orientation, angle, and area of ​​the solar panels.

[0516] Hardware configuration

[0517] Sensor equipment: Includes sensors that measure the angle of the sun, light intensity, weather information, and wind speed. The data collected from these sensors forms the foundation of the entire system.

[0518] Server device: Performs data analysis and generates control commands. Equipped with an AI analysis module, it analyzes collected data in real time.

[0519] Solar panel control device: Includes motors and actuators that physically adjust the orientation and angle of the panels based on analysis results.

[0520] Software Configuration

[0521] Data Analysis Module: This is an AI analysis module built using Python and TensorFlow. It analyzes data from sensors and calculates the optimal placement of solar panels.

[0522] Communication software: Software for receiving data from sensors and sending it to a server. It uses real-time streaming technology.

[0523] User Interface: An interface for displaying analysis results on smart glasses or smartphones. Users can monitor and manually control the system through this interface.

[0524] Processing flow

[0525] Data collection

[0526] The server receives data from sensors that measure the sun's angle, light intensity, weather information, and wind speed in real time. This data is stored in a database on the server.

[0527] Data Analysis

[0528] The server uses an AI analysis module to analyze the collected data in real time. Based on the analysis results, it generates control commands to optimally adjust the orientation, angle, and area of ​​the solar panels.

[0529] Transmission and execution of control commands

[0530] Control commands generated from the server are sent to the solar panel control unit. The control unit then physically adjusts the orientation and angle of the panels according to the commands.

[0531] Monitoring and user notifications

[0532] The server monitors the current status of the solar panels in real time. If an anomaly is detected, it sends a notification to a smart device and issues a visual or audible warning.

[0533] Manual operation by the user

[0534] Users can monitor the system via smart glasses or a smartphone and manually control the solar panels using voice commands or touch gestures as needed.

[0535] Specific example

[0536] For example, if strong winds of 18 m / s are predicted, the sensor sends wind speed data to the server. The server quickly inputs this data into the AI ​​analysis module, and if strong winds are predicted, an analysis result is generated. Based on this result, the server generates a protective command to position the panels horizontally and sends it to the solar panel control unit. The control unit executes this command and moves the panels horizontally to prevent damage from strong winds.

[0537] Example of a prompt

[0538] Applying the following invention, create a prototype of a solar power system monitoring application to be installed on smart glasses. This application will have the functions of real-time data display, anomaly detection notification, and manual control.

[0539] 1. Data is collected from sensors on solar panels.

[0540] 2. Analyze the data using the AI ​​analysis module.

[0541] 3. Data and analysis results are visually displayed on smart glasses.

[0542] 4. Control the panel using voice or touch gestures.

[0543] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0544] Step 1:

[0545] The server receives data from sensors that measure the sun's angle, light intensity, weather information, and wind speed in real time. Specifically, the data acquired by the sensor devices is temporarily stored in the server's database. The input data includes the sun's angle, light intensity values, weather data such as temperature and humidity, and wind speed values. After acquiring this data, the server proceeds to the next analysis step.

[0546] Step 2:

[0547] The server inputs the data collected in Step 1 into the AI ​​analysis module. The AI ​​analysis module (using TensorFlow) analyzes this data and calculates the optimal orientation, angle, and area of ​​the solar panels. Based on the input data of the sun's angle, light intensity, weather, and wind speed, the AI ​​performs analysis and generates optimal placement parameters for the solar panels as output.

[0548] Step 3:

[0549] The server generates control commands based on the analysis results from Step 2. Specifically, it creates control commands according to the optimal orientation, angle, and area of ​​the solar panels calculated by the AI ​​analysis module. Furthermore, it generates special commands to protect the panels during strong winds or snowfall. The input data is the analysis results from the AI ​​analysis module, and the output data is the control commands related to the orientation, angle, and area of ​​the panels.

[0550] Step 4:

[0551] The terminal executes control commands received from the server. Specifically, the terminal sends commands to the solar panel control device, causing motors and actuators to physically adjust the orientation and angle of the panels. The input data is the control commands from the server, and the output is the actual physical change in the placement of the solar panels.

[0552] Step 5:

[0553] The server monitors the current status of the solar panels in real time. If an anomaly is detected (for example, if the wind speed exceeds a certain level), the server generates an anomaly notification and sends it to the user's smart device. The input data is real-time status data from the solar panels, and the output data is the anomaly notification message.

[0554] Step 6:

[0555] Users monitor the system status via smart glasses or smartphones. In particular, when an anomaly notification is displayed, users can manually control the system using voice commands or touch gestures. Input data includes anomaly notifications from the server and user voice commands and touch gestures, while output data consists of user feedback and response instructions.

[0556] 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.

[0557] This invention relates to an AI-powered smart solar power generation system that enhances the efficiency and safety of solar power generation systems. This system utilizes numerous sensors and real-time AI data analysis to automatically and optimally control the orientation, angle, and area of ​​solar panels. Furthermore, it incorporates an emotion engine that recognizes user emotions to improve user satisfaction. Specific embodiments of this system are described below.

[0558] Data collection

[0559] sensor

[0560] The sensors measure the sun's angle, light intensity (illuminance), weather information (sunny, cloudy, rainy, etc.), and wind speed in real time. This data is crucial for optimizing solar power generation.

[0561] Emotional Engine

[0562] The emotion engine analyzes the user's facial expressions and voice through input devices such as cameras and microphones to recognize the user's emotions. The emotion data is then sent to a server.

[0563] Data analysis and control command generation

[0564] server

[0565] The server receives data collected from sensors and the emotion engine, and analyzes it using an AI analysis module. Based on the data analysis, it calculates the optimal orientation, angle, and area of ​​solar panels for solar power generation. Furthermore, it takes user emotion data into consideration and performs solar panel placement and other system operations in a way that satisfies the user.

[0566] Program processing

[0567] 1. Data Collection

[0568] Sensors measure data on the sun's angle, light intensity, weather, and wind speed in real time and send it to the server. The emotion engine collects user emotion data and sends it to the server.

[0569] 2. Data Analysis

[0570] The server receives the collected data and inputs it into the AI ​​analysis module. The AI ​​analysis module analyzes the data and calculates the optimal placement of solar panels. Furthermore, it analyzes emotional data and generates control commands that will satisfy the user.

[0571] 3. Control command generation

[0572] The server generates control commands to adjust the orientation, angle, and area of ​​the solar panels based on the analysis results. It also generates commands to protect the panels in response to wind speed and weather fluctuations. Based on emotional data, it also considers placement and operation according to the user's preferences.

[0573] 4. Panel adjustment

[0574] The terminal receives control commands and physically adjusts the orientation, angle, and area of ​​the solar panels. This optimizes power generation and improves energy efficiency. Adjustments may also be made based on emotional data.

[0575] 5. Status Monitoring

[0576] The server monitors the current state of the panel and records the data. If an anomaly is detected, it generates an alert and notifies the user. The user's emotional state is also continuously monitored.

[0577] Specific example

[0578] For example, consider a scenario where strong winds of 15 m / s are predicted for 12:00 PM on a given day. In this case, a sensor sends wind speed data to a server. The server inputs this data into an AI analysis module, which then outputs an analysis result if strong winds are predicted. The server generates a protective command to position the panels horizontally and sends it to the terminal. The terminal receives this command, and the panel control module activates a motor to move the panels horizontally. Meanwhile, if the emotion engine recognizes that the user's stress level is high, the system takes action to provide the user with a relaxing environment (for example, by changing the panel position or adjusting the timing of notifications). This series of processes prevents damage to the panels due to strong winds, enhances safety, and improves user satisfaction.

[0579] Thus, the AI ​​smart solar power generation system of the present invention maximizes the efficiency and safety of solar power generation through the steps of data collection, data analysis, control command generation, panel adjustment, and condition monitoring, and further optimizes the system's operation while also taking into account the user's emotions.

[0580] The following describes the processing flow.

[0581] Step 1: Data Collection

[0582] A sensor measures the angle of the sun. A sensor measures the amount of light (illuminance). A sensor acquires weather information (sunny, cloudy, rainy, etc.). A sensor measures wind speed. Each sensor sends this data to the server. The emotion engine analyzes the user's facial expressions and voice through the camera and microphone, acquires the user's emotion data, and sends it to the server.

[0583] Step 2: Data aggregation and preprocessing

[0584] The server receives data transmitted from each sensor and emotion engine. The server cleans the received data, processing for missing or outlier values. The server stores the pre-processed data in data storage.

[0585] Step 3: Data Analysis

[0586] The server inputs the stored data into the AI ​​analysis module. The AI ​​analysis module calculates the predicted position of the sun. The AI ​​analysis module calculates the optimal panel orientation, angle, and area. The AI ​​analysis module analyzes the user's emotional data and calculates the optimal placement and operation to satisfy the user.

[0587] Step 4: Control command generation

[0588] The server receives calculation results from the AI ​​analysis module. The server generates control commands to optimize the orientation, angle, and area of ​​the solar panels. The server generates protection commands based on wind and snowfall forecasts. It also considers placement and operation according to user preferences based on sentiment data. The server sends the generated control and protection commands to the terminal.

[0589] Step 5: Panel Position Control

[0590] The terminal receives control commands from the server. The terminal sends commands to the panel control module. The panel control module operates the motors to adjust the orientation, angle, and area of ​​the solar panels. If a protection command is received after a forecast of strong winds or snowfall, the panel control module moves the panels horizontally or vertically. Depending on the user's emotional data, relaxing placements and actions may be performed.

[0591] Step 6: Status Monitoring

[0592] The server monitors the panel's current state. The server records the panel's operational data (change history of orientation, angle, and area). If the server detects an anomaly, it generates an alert and notifies the user. The server also continuously monitors the user's emotional state and provides feedback as needed.

[0593] (Example 2)

[0594] 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".

[0595] Conventional solar power generation systems typically maximize efficiency by considering only sunlight intensity and panel angle. However, this can sometimes come at the expense of user satisfaction and safety. In particular, protective measures for panels during strong winds and snowfall are insufficient, and system operation that takes user feelings into consideration has yet to be realized. There is a need to solve these problems.

[0596] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for measuring the angle of the sun, means for measuring the amount of light, means for acquiring weather information, means for measuring wind speed, means for analyzing the user's emotions, means for receiving data acquired from each of the means and analyzing the data, means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the data analysis, means for physically adjusting the solar panels based on the control commands, means for monitoring the state of the solar panels, and means for detecting abnormalities and notifying the user. This makes it possible to maximize the efficiency and safety of solar power generation and further optimize the operation of the system while also considering the user's emotions.

[0597] "Means for measuring the angle of the sun" refers to devices or techniques for accurately measuring the position and angle of the sun.

[0598] "Means for measuring light intensity" refers to devices or technologies for measuring the intensity or illuminance of sunlight.

[0599] "Means for acquiring weather information" refers to devices or technologies for collecting weather conditions (such as sunny, cloudy, or rainy).

[0600] "Means for measuring wind speed" refers to a device or technology for measuring the speed of wind.

[0601] "Means for analyzing user emotions" refers to devices or technologies that analyze a user's facial expressions and voice to determine their emotional and psychological state.

[0602] "Means for receiving data acquired from each of the above means and analyzing the said data" refers to a device or technology for receiving various sensor data and emotional data and analyzing them.

[0603] "Means for generating control commands to optimally adjust the orientation, angle, and area of ​​solar panels" refers to an apparatus or technology for determining the optimal orientation, angle, and area of ​​solar panels based on analysis results, and generating control commands based on those results.

[0604] "Means for physically adjusting solar panels" refers to devices or technologies for actually adjusting the physical arrangement and angle of solar panels based on control commands.

[0605] "Means for monitoring the status of solar panels" refers to devices or technologies for monitoring the current status of solar panels (position, angle, power generation, etc.) in real time.

[0606] "Means for detecting anomalies and notifying users" refers to devices or technologies that inform users of anomalies detected during system monitoring in the form of alerts or notifications.

[0607] This invention relates to an AI-powered smart solar power generation system that enhances the efficiency and safety of solar power generation systems. This system utilizes numerous sensors and real-time AI data analysis to automatically and optimally control the orientation, angle, and area of ​​solar panels. Furthermore, by incorporating an emotion engine that recognizes user emotions, it aims to improve user satisfaction.

[0608] Data collection

[0609] The server uses multiple sensors to measure the angle of the sun, light intensity (illuminance), weather information (sunny, cloudy, rainy, etc.), and wind speed. The data acquired from these sensors is transmitted to the server in real time. It also uses an emotion engine to collect user emotion data. The emotion engine analyzes the user's facial expressions and voice through input devices such as cameras and microphones to recognize the user's emotions.

[0610] Data analysis and control command generation

[0611] The server receives data collected from sensors and the emotion engine and analyzes it using an AI analysis module. Based on the data analysis, it calculates the optimal orientation, angle, and area of ​​solar panels for solar power generation. Furthermore, it takes user emotion data into consideration and performs solar panel placement and other system operations in a way that satisfies the user.

[0612] Specific example

[0613] For example, consider a scenario where strong winds of 15 m / s are predicted for 12:00 PM on a given day. In this case, a sensor sends wind speed data to a server. The server inputs this data into an AI analysis module, which then outputs an analysis result if strong winds are predicted. The server generates a protective command to position the panels horizontally and sends it to the terminal. The terminal receives this command, and the panel control module activates a motor to move the panels horizontally. Meanwhile, if the emotion engine recognizes that the user's stress level is high, the system takes action to provide the user with a relaxing environment (for example, by changing the panel position or adjusting the timing of notifications). This series of processes prevents damage to the panels due to strong winds, enhances safety, and improves user satisfaction.

[0614] Examples of prompt statements

[0615] Enter the following prompt into the generative AI model:

[0616] "Please explain how the AI ​​smart solar power system protects the panels when strong winds of 15 m / s are predicted. Also, please explain how the system responds when the user is under high stress."

[0617] Based on this prompt, the generated response will provide details on how the system collects and analyzes data, how it actually adjusts the panel, and how it responds based on user sentiment data.

[0618] The AI ​​smart solar power generation system of the present invention maximizes the efficiency and safety of solar power generation through the steps of data collection, data analysis, control command generation, panel adjustment, and condition monitoring, and further optimizes the system's operation while also taking into account the user's emotions.

[0619] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0620] Step 1: Data Collection

[0621] The server receives real-time data from numerous sensors regarding the angle of the sun, light intensity (illuminance), weather information (sunny, cloudy, rainy, etc.), and wind speed. Users provide emotional data through their cameras and microphones. An emotion engine analyzes the user's facial expressions and voice to generate emotional data. This data is the input data sent to the server. Specifically, the sensors measure data every minute and send it to the server.

[0622] Step 2: Data Analysis

[0623] The server receives data collected from sensors and the emotion engine. This data is preprocessed to ensure consistency and fill in any gaps. Next, the server inputs this preprocessed data into the AI ​​analysis module. The AI ​​analysis module analyzes the data to calculate the optimal orientation, angle, and area of ​​the solar panels. Furthermore, it generates control commands that will satisfy the user based on the user's emotion data. Specifically, the AI ​​analysis module inputs the dataset into a model and performs analysis using an optimization algorithm.

[0624] Step 3: Generation of control commands

[0625] The server assembles specific control commands to adjust the orientation, angle, and area of ​​the solar panels based on the analysis results from the AI ​​analysis module. These control commands determine the optimal placement and operation of the solar panels and also include protective commands against wind speed and weather fluctuations. For example, it generates commands such as, "If the wind speed is 15 m / s or higher, position the panels horizontally."

[0626] Step 4: Sending control commands

[0627] The server sends the generated control command to the terminal. The terminal receives this control command and prepares to control the panel according to the settings. Specifically, the server sends command data to the terminal via the network.

[0628] Step 5: Panel adjustment

[0629] The terminal receives control commands sent from the server and physically adjusts the orientation and angle of the solar panels based on them. It drives motors and actuators to move the panels to the optimal position. Specifically, the terminal executes a motor control program to tilt the panels horizontally.

[0630] Step 6: Status Monitoring

[0631] The server monitors the current status of the solar panels in real time and records the data. It also generates an alert and notifies the user if an anomaly is detected. The user can then take the necessary actions after receiving the notification. Specifically, the server periodically checks the panel's position, angle, power generation, etc., and sends email or application notifications if any anomalies are detected.

[0632] (Application Example 2)

[0633] 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."

[0634] Conventional solar power generation systems optimize power generation efficiency based solely on environmental data, without considering comprehensive energy management in logistics facilities or optimizing the emotional well-being of workers. Furthermore, irregular energy consumption in logistics centers often leads to employee stress and problems with the working environment. This presents a challenge: simultaneously improving energy efficiency and working conditions.

[0635] 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.

[0636] In this invention, the server includes means for measuring the angle of the sun, means for measuring light intensity, means for acquiring weather information, means for measuring wind speed, means for measuring the energy consumption of the logistics center, means for analyzing the emotions of employees, means for receiving and analyzing data acquired from each of the means, means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the data analysis, means for physically adjusting the solar panels based on the control commands, means for optimizing the energy consumption pattern of the logistics center, and means for optimizing the working environment of employees based on the results of the emotion analysis. This makes it possible to improve energy efficiency and optimize the working environment of employees in the logistics center.

[0637] "Means for measuring the angle of the sun" refers to devices and sensor sets used to measure the position and angle of the sun in real time.

[0638] "Means for measuring light intensity" refers to devices or sensors used to measure the amount of ambient light.

[0639] "Means for acquiring weather information" refers to means of communication with sensors and databases used to acquire weather conditions (sunny, cloudy, rainy, etc.).

[0640] "Means for measuring wind speed" refers to devices or sensors used to measure wind speed in real time.

[0641] "Means for measuring energy consumption in a logistics center" refers to devices and systems for measuring energy consumption within a logistics facility in real time.

[0642] "Methods for analyzing employee emotions" refer to systems and algorithms that analyze employees' facial expressions and voice data to recognize their emotional state.

[0643] "Means for receiving data acquired from each of the above means and analyzing the data" refers to devices or programs that receive data transmitted from sensors or devices and analyze that data using an AI analysis module.

[0644] "Means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the data analysis" refers to a system or program that generates commands to instruct the optimal settings of the solar panels based on the analysis results.

[0645] "Means for physically adjusting the solar panels based on the control command" refers to machines or devices that receive a control command and physically adjust the orientation and angle of the solar panels.

[0646] "Means for optimizing the energy consumption patterns of a logistics center" refers to systems and programs for efficiently managing and optimizing the energy consumption of a logistics center.

[0647] "Means for optimizing the working environment of employees based on the results of the aforementioned sentiment analysis" refers to systems or programs for improving the working environment by reflecting the results of the employee sentiment analysis.

[0648] This invention is a system for achieving energy management and optimization of the working environment in a logistics center. The detailed configuration and operation for carrying out this invention are described below.

[0649] Data collection

[0650] 1. Measuring the angle of the sun:

[0651] • Hardware used: Solar angle sensor

[0652] • Measures the position and angle of the sun in real time and transmits the data to the server.

[0653] 2. Measurement of light intensity:

[0654] • Hardware used: Light sensor

[0655] • Measures the amount of ambient light and sends the data to the server.

[0656] 3. Obtaining weather information:

[0657] • Hardware used: Weather sensor, Internet connection

[0658] • Acquire weather conditions in real time and send the data to the server.

[0659] 4. Measuring wind speed:

[0660] • Hardware used: Wind speed sensor

[0661] • Measure wind speed and send the data to the server.

[0662] 5. Measurement of energy consumption:

[0663] Hardware used: energy meter, RFID tag, GPS

[0664] • Collect energy consumption data within the logistics center and send it to the server.

[0665] 6. Emotion analysis:

[0666] • Hardware used: Camera, microphone

[0667] • Software used: Sentiment analysis engine (e.g., OpenCV)

[0668] • Analyzes employees' facial expressions and voices and sends emotional data to the server.

[0669] Data analysis and control command generation

[0670] 1. Data reception:

[0671] The server receives data from each sensor and emotion analysis engine.

[0672] 2. AI Analysis Module:

[0673] • Software used: TensorFlow, PyTorch

[0674] The server inputs the received data into the AI ​​analysis module to calculate the optimal orientation, angle, and area of ​​the solar panels.

[0675] • Calculate patterns to optimize energy consumption at the logistics center.

[0676] 3. Control command generation:

[0677] The server generates control commands based on the AI ​​analysis results.

[0678] • Transmits commands for physical adjustment of solar panels and optimization of energy consumption patterns.

[0679] • It also generates instructions to optimize the employee work environment based on emotional data.

[0680] Panel adjustment and energy management

[0681] 1. Panel adjustment:

[0682] Hardware used: Solar panel angle adjustment mechanism, motor

[0683] Based on control commands, the orientation and angle of the solar panels are physically adjusted.

[0684] 2. Energy Management:

[0685] • Software used: Energy Management System

[0686] • Optimize the energy consumption patterns of logistics centers in real time.

[0687] 3. Optimizing the working environment:

[0688] Hardware used: Lighting, air conditioning system

[0689] • Optimize the working environment for employees based on control commands.

[0690] Status Monitoring

[0691] 1. Monitoring:

[0692] The server constantly monitors the current status of each device.

[0693] 2. Anomaly detection:

[0694] • If an anomaly is detected, an alert will be generated and the user will be notified.

[0695] Specific example

[0696] 1. How to respond during strong winds:

[0697] • Hardware used: Wind speed sensor, solar panel angle adjustment mechanism

[0698] When the wind speed sensor measures 15 m / s, the server inputs the wind speed data into the AI ​​analysis module and generates commands to cope with strong winds. A command is issued to position the solar panels horizontally, and the motor moves the panels.

[0699] Example of a prompt:

[0700] 1. Environmental data collection:

[0701] "Collect light intensity data in real time from the sensor device during sunny conditions and transmit it to the data server."

[0702] 2. Emotion analysis:

[0703] "We analyze employees' facial images in real time to assess their stress levels."

[0704] 3. Control command generation:

[0705] "Protect the solar panels to a safe horizontal position, given the current wind speed of 15 m / s."

[0706] 4. Anomaly monitoring:

[0707] "Continuously monitor the panel status and issue an immediate alert if any abnormal values ​​are detected."

[0708] In this way, the system will perform panel adjustments, optimize energy consumption, and improve the working environment by collecting data from various sensors and analyzing it with AI.

[0709] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0710] Step 1:

[0711] Collect energy data

[0712] Inputs: Sun angle sensor, light sensor, weather sensor, wind speed sensor, energy meter, camera and microphone

[0713] The server collects data from the above sensors and devices in real time.

[0714] Output: Data from each sensor (sun angle, light intensity, weather information, wind speed, energy consumption, emotion data)

[0715] Specific operation: The server periodically receives data transmitted from sensors and saves it to local storage. In addition, the emotion engine analyzes employees' facial expressions and voices and saves their emotional state as data.

[0716] Step 2:

[0717] Preprocessing of data

[0718] Input: Raw data collected in Step 1

[0719] The server cleanses the raw data it collects, removing outliers and noise.

[0720] Output: Cleansed data

[0721] Specific operation: The server uses a database management system to format and normalize data, generating a clean dataset. For example, it filters out abnormal values ​​from temperature sensors (such as sudden fluctuations).

[0722] Step 3:

[0723] Data Analysis

[0724] Input: Clean data obtained in Step 2

[0725] The server uses AI analysis modules such as TensorFlow and PyTorch to analyze data and calculate the optimal settings for the orientation, angle, and area of ​​solar panels. It also analyzes energy consumption patterns and employee sentiment data to generate instructions for setting up the optimal work environment.

[0726] Output: Analysis results (optimal solar panel settings, energy consumption patterns, work environment settings)

[0727] Specific operation: Data is input into the AI ​​model, and the optimal numerical settings are calculated as a result of the analysis. For example, based on the angle of the sun at 3 PM, the panel angle is calculated to be 30 degrees. At the same time, if an employee is working for a long time, a command prompting them to take a break is generated.

[0728] Step 4:

[0729] Generation of control commands

[0730] Input: Analysis results obtained in Step 3

[0731] The server sends control commands to each sensor and device based on the analysis results.

[0732] Output: Control commands (adjustment of solar panel angle, change of energy consumption pattern, adjustment of working environment)

[0733] Specific operation: The server sends a control signal to the solar panel control unit, for example, "Adjust the panel to 30 degrees." At the same time, it sends a command to the lighting system to "Switch to an energy-saving mode."

[0734] Step 5:

[0735] Control implementation

[0736] Input: Control command from step 4

[0737] The terminal receives control commands and physically adjusts the orientation and angle of the solar panels. It also changes the settings of lighting and air conditioning systems.

[0738] Output: Actual adjustment results (orientation and angle of solar panels, changes in working environment)

[0739] Specific operation: The solar panel control unit drives a motor to adjust the panels to the specified angle. It also optimizes energy consumption and automatically switches between lighting and air conditioning.

[0740] Step 6:

[0741] Status Monitoring

[0742] Input: Real-time data from each source

[0743] The server constantly monitors the current status of each system and immediately generates an alert if an anomaly occurs.

[0744] Output: Anomaly detection alert, system log

[0745] Specific operation: The server monitors sensor data at regular intervals and detects abnormal values ​​(e.g., excessive temperature changes). If an abnormality is found, it sends an email or SMS notification to the administrator. It also logs all data.

[0746] 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.

[0747] 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.

[0748] 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.

[0749] [Third Embodiment]

[0750] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0751] 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.

[0752] 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).

[0753] 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.

[0754] 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.

[0755] 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).

[0756] 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.

[0757] 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.

[0758] 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.

[0759] 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.

[0760] 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.

[0761] 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".

[0762] This invention relates to an AI-powered smart solar power generation system that enhances the efficiency and safety of solar power generation systems. This system utilizes numerous sensors and real-time AI data analysis to automatically and optimally control the orientation, angle, and area of ​​solar panels. Specific embodiments of this system are described below.

[0763] Data collection

[0764] sensor

[0765] The sensors measure the sun's angle, light intensity, weather, and wind speed in real time. This data is crucial for optimizing solar power generation.

[0766] Data analysis and control command generation

[0767] server

[0768] The server receives data collected from sensors and analyzes it using an AI analysis module. Based on the data analysis, it calculates the optimal orientation, angle, and area of ​​solar panels for solar power generation. It also generates commands to protect the panels in response to wind speed and weather fluctuations.

[0769] Program processing

[0770] 1. Data Collection

[0771] The sensor measures data on the sun's angle, light intensity, weather, and wind speed in real time and transmits it to the server.

[0772] 2. Data Analysis

[0773] The server receives the collected data and inputs it into the AI ​​analysis module. The AI ​​analysis module analyzes the data and calculates the optimal placement of the solar panels.

[0774] 3. Control command generation

[0775] The server generates control commands to adjust the orientation, angle, and area of ​​the solar panels based on the analysis results. It also generates commands to protect the panels in response to changes in wind speed and weather conditions.

[0776] 4. Panel adjustment

[0777] The terminal receives control commands and physically adjusts the orientation, angle, and area of ​​the solar panels. This optimizes power generation and improves energy efficiency.

[0778] 5. Status Monitoring

[0779] The server monitors the current status of the panel and notifies the user if an anomaly is detected.

[0780] Specific example

[0781] For example, consider a scenario where strong winds of 15 m / s are predicted at 12:00 PM on a given day. In this case, the sensor sends wind speed data to the server. The server inputs this data into an AI analysis module, which then generates an analysis result if strong winds are predicted. The server generates a protective command to position the panels horizontally and sends it to the terminal. The terminal receives this command, and the panel control module activates a motor to move the panels horizontally. This entire process prevents damage to the panels due to strong winds, extending the lifespan and enhancing the safety of the entire system.

[0782] Thus, the AI ​​smart solar power generation system of the present invention maximizes the efficiency and safety of solar power generation through the steps of data collection, data analysis, control command generation, panel adjustment, and condition monitoring.

[0783] The following describes the processing flow.

[0784] Step 1: Data Collection

[0785] The sensor measures the angle of the sun. The sensor measures the amount of light (illuminance). The sensor acquires weather information (sunny, cloudy, rainy, etc.). The sensor measures wind speed. Each sensor sends the collected data to the server.

[0786] Step 2: Data aggregation and preprocessing

[0787] The server receives data transmitted from each sensor. The server cleans the received data, processing for missing or outlier values. The server saves the pre-processed data to data storage.

[0788] Step 3: Data Analysis

[0789] The server inputs the stored data into the AI ​​analysis module. The AI ​​analysis module calculates the predicted position of the sun. The AI ​​analysis module calculates the optimal panel orientation, angle, and area. Based on wind speed and weather information, the AI ​​analysis module determines whether to generate a protection command.

[0790] Step 4: Control command generation

[0791] The server receives calculation results from the AI ​​analysis module. The server generates control commands to optimize the orientation, angle, and area of ​​the solar panels. The server generates protection commands based on wind and snowfall forecasts. The server sends the generated control and protection commands to the terminal.

[0792] Step 5: Panel Position Control

[0793] The terminal receives control commands from the server. The terminal sends commands to the panel control module. The panel control module operates the motors to adjust the orientation, angle, and area of ​​the solar panels. If a protection command is received after a forecast of strong winds or snowfall, the panel control module moves the panels horizontally or vertically.

[0794] Step 6: Status Monitoring

[0795] The server monitors the current status of the panel. The server records the panel's operational data (change history of orientation, angle, and area). If the server detects an anomaly, it generates an alert and notifies the user.

[0796] (Example 1)

[0797] 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."

[0798] To improve the efficiency and safety of solar power generation systems, optimal panel placement based on real-time weather information and the angle of the sun is required. However, current systems require manual adjustments, resulting in low efficiency and an increased risk of panel damage during extreme weather conditions such as strong winds and snowfall. Furthermore, the lack of a mechanism to immediately notify users when an anomaly occurs makes it difficult to respond quickly.

[0799] 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.

[0800] In this invention, the server includes means for measuring the angle of the sun, means for measuring light intensity, means for acquiring weather information, means for measuring wind speed, means for receiving data acquired from each of the means and storing it in a database, means including an AI analysis module for analyzing the data, means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the data analysis, means for physically adjusting the solar panels via a servo motor according to the control commands, and means for monitoring the current state of the solar panels and notifying the user if an abnormality is detected. This enables real-time automatic adjustment, improving the efficiency and safety of solar power generation, as well as enabling a rapid response in the event of an abnormality.

[0801] "Means for measuring the angle of the sun" refers to instruments that measure the current position and altitude angle of the sun. Specifically, this includes sensors for accurately determining the sun's position.

[0802] "Means for measuring light intensity" refers to devices that measure the intensity of ambient sunlight. Specifically, this includes devices that measure light intensity using photoelectric sensors or photodiodes.

[0803] "Means of obtaining weather information" refers to systems or services for obtaining meteorological data. Specifically, this includes APIs for obtaining information from external meteorological data providers and weather stations established independently.

[0804] "Means for measuring wind speed" refers to equipment for measuring wind speed. Specifically, this includes devices for measuring wind speed using an anemometer (wind speed meter), etc.

[0805] "Means for receiving data and storing it in a database" refers to a system for acquiring data from sensors, transferring it to a central computer, and storing it for long-term use. Specifically, this includes communication modules and data storage (e.g., MySQL, MongoDB).

[0806] An "AI analysis module" is an artificial intelligence system for analyzing acquired data. Specifically, it includes a software module that uses machine learning and deep learning algorithms to calculate the optimal panel arrangement.

[0807] "Means for generating control commands" refers to a device or software that creates commands for appropriately controlling solar panels based on the results of data analysis. Specifically, this includes a system that generates control signals using a programmed algorithm.

[0808] A "servo motor" is a drive device used to adjust the orientation and angle of solar panels in response to control commands. Specifically, it includes motors capable of precise rotation and angle adjustment.

[0809] "Means for monitoring status and detecting anomalies" refers to a system that constantly monitors the current operating state of a system and issues warnings when abnormal conditions or operations are detected. Specifically, this includes an alert system that analyzes data from sensors and detects abnormal values.

[0810] "Means of notifying users" refers to methods for informing users of system abnormalities or important information. Specifically, this includes communication methods such as email notifications, SMS, and push notifications.

[0811] This invention relates to an AI-powered smart solar power system that enhances the efficiency and safety of solar power generation systems. This system is configured to automatically and optimally control the orientation, angle, and area of ​​solar panels by utilizing numerous sensors and real-time AI data analysis.

[0812] Data collection

[0813] The sensors measure information on the sun's angle, light intensity, weather, and wind speed in real time. This includes the following sensors:

[0814] Optical sensor for measuring the angle of the sun

[0815] Photoelectric sensor for measuring light intensity

[0816] A system for acquiring weather information from weather sensors or external data providers.

[0817] An anemometer (wind speed meter) for measuring wind speed

[0818] Data reception and storage

[0819] The server receives data transmitted from the sensors and stores it in a database. Examples of databases used include MySQL and MongoDB. This ensures that the latest data is always updated and used for subsequent analysis.

[0820] Data Analysis

[0821] The server receives and stores data, which is then input into an AI analysis module. Specifically, an AI analysis module using deep learning frameworks such as TensorFlow or PyTorch analyzes the data and calculates the optimal orientation, angle, and area of ​​the solar panels.

[0822] Control command generation

[0823] The server generates control commands to optimize the orientation, angle, and area of ​​the solar panels based on the analysis results of the AI ​​analysis module. It also generates protective commands to move the panels horizontally or vertically if the wind speed exceeds a certain value or if snowfall is observed.

[0824] Control command transmission

[0825] The server sends the generated control commands to the terminal. MQTT or HTTP protocols are used for communication.

[0826] Panel adjustment

[0827] The terminal drives servo motors to adjust the orientation and angle of the solar panels based on the control commands it receives. For example, if strong winds are predicted, the panels will be moved horizontally.

[0828] Status Monitoring

[0829] The server constantly monitors the current status of the solar panels and sends a notification to the user if an anomaly is detected. Notifications are sent via email or push notifications.

[0830] Specific example

[0831] For example, if strong winds of 15 m / s are predicted at 12:00 on a given day, the system will operate in the following manner:

[0832] 1. The sensor measures wind speed data and sends it to the server.

[0833] 2. The server receives the data and inputs it into the AI ​​analysis module.

[0834] 3. The AI ​​analysis module analyzes the data and determines that strong winds are predicted.

[0835] 4. The server generates a protective command to position the panel horizontally and sends it to the terminal.

[0836] 5. The terminal receives the command and drives the servo motor to move the panel horizontally.

[0837] This series of processes prevents damage to panels caused by strong winds, thereby improving safety. Furthermore, the system can quickly detect and notify users of any abnormalities, allowing them to respond promptly.

[0838] Examples of prompts to input into a generative AI model:

[0839] "Please explain how the AI ​​smart solar power system works based on the following conditions: It is 12:00 PM on a day when strong winds of 15 m / s are predicted."

[0840] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0841] Step 1:

[0842] Data collection

[0843] The sensor measures data on the sun's angle, light intensity, weather, and wind speed in real time and transmits it to the server. Specifically, the sensor measures the sun's angle and light intensity every second and the wind speed every minute. The input data consists of the sun's angle, light intensity, weather information, and wind speed, and this data is packaged with a timestamp when transmitted. The output is the measurement data transmitted to the server.

[0844] Step 2:

[0845] Data reception and storage

[0846] The server receives data transmitted from the sensor and stores it in a database. The input is measurement data transmitted from the sensor, which the server receives and stores in a database, for example, using MySQL or MongoDB. Specifically, the received data is converted into a format that is easy to analyze and inserted into the corresponding field in the database. The output is the measurement data stored in the database.

[0847] Step 3:

[0848] Data Analysis

[0849] The server inputs data collected from the database into the AI ​​analysis module. The input is the latest measurement data obtained from the database, which the AI ​​analysis module (e.g., a deep learning model using TensorFlow or PyTorch) analyzes. Specifically, the data is fed into the model to calculate the optimal orientation, angle, and area of ​​the solar panels. The output is the parameters for the optimal orientation, angle, and area.

[0850] Step 4:

[0851] Control command generation

[0852] The server generates control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the analysis results of the AI ​​analysis module. The input is the data analysis results, and the server constructs the control commands based on this. Specifically, this includes commands such as positioning the panels horizontally when it is determined that the wind speed exceeds 10 m / s. The generated control commands are packaged in JSON format, etc. The output is the generated control commands.

[0853] Step 5:

[0854] Control command transmission

[0855] The server sends the generated control commands to the terminal. The input is the generated control commands, which are sent to the terminal using protocols such as MQTT or HTTP. Specifically, the command packets are converted into a format suitable for the communication protocol and sent to the terminal. The output is the control commands sent to the terminal.

[0856] Step 6:

[0857] Panel adjustment

[0858] The terminal drives a servo motor to adjust the orientation and angle of the solar panel based on the control commands it receives. The input is a control command sent from the server, which the terminal receives and sends commands to the servo motor. Specifically, it sends signals to the motor to control the rotation angle and direction. For example, if it is determined that the wind speed exceeds 10 m / s, the motor rotates to position the panel horizontally. The output is the physical position of the adjusted solar panel.

[0859] Step 7:

[0860] Status Monitoring

[0861] The server constantly monitors the current status of the solar panels and sends a notification to the user if an anomaly is detected. The input is the adjusted panel status data, which the server monitors to detect anomalies. Specifically, it uses data from angle sensors and temperature sensors to generate an alert if the values ​​differ from the set values. The output is an anomaly notification sent to the user, which is sent via email or push notification.

[0862] (Application Example 1)

[0863] 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."

[0864] Existing solar power generation systems suffer from reduced power generation efficiency due to the lack of real-time data analysis to optimally adjust the orientation and angle of solar panels. Furthermore, they struggle to respond quickly to extreme weather events such as strong winds and snowfall, raising concerns about panel damage and system safety. Additionally, they lack the functionality to remotely monitor the system status and manually control it as needed, even when the user is not on-site.

[0865] 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.

[0866] In this invention, the server includes means for measuring the angle of the sun, means for measuring light intensity, means for acquiring weather information, means for measuring wind speed, means for receiving data acquired from each of the means and analyzing the data, means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the data analysis, means for physically adjusting the solar panels based on the control commands, means for displaying the results on a smart device in real time, and means for the user to manually control the panels using voice commands or touch gestures. This enhances the power generation efficiency and safety of the solar power generation system, and enables remote monitoring and control by the user.

[0867] "Means for measuring the angle of the sun" refers to a sensor device that detects the angle of the sun in real time according to its position.

[0868] "Means for measuring light intensity" refers to a sensor device used to measure the current intensity of sunlight.

[0869] "Means of acquiring weather information" refer to sensors and external data provision services for collecting current temperature, humidity, precipitation, etc.

[0870] "Means for measuring wind speed" refers to a sensor device for measuring wind speed in real time.

[0871] "Means for analyzing data" refers to an AI analysis module that uses data collected from sensors to evaluate the situation and generate necessary control commands.

[0872] "Means for generating control commands" refers to a device or software that generates commands to optimally adjust the orientation, angle, and area of ​​solar panels based on the results of data analysis.

[0873] "Means for physically adjusting solar panels" refer to motors and actuators that automatically change the orientation and angle of the panels according to control commands.

[0874] "Means for displaying results in real time on smart devices" refers to communication and display devices for notifying smart devices (smart glasses, smartphones) of analysis results and data from sensors.

[0875] "Means for manually controlling the panel using voice commands or touch gestures" refers to an interface that allows users to manually adjust the solar panels using voice or physical operations.

[0876] System Overview

[0877] This invention provides an AI-powered smart control system to enhance the efficiency and safety of solar power generation systems. This system collects data from multiple sensors, analyzes it in real time, and optimally adjusts the orientation, angle, and area of ​​the solar panels.

[0878] Hardware configuration

[0879] Sensor equipment: Includes sensors that measure the angle of the sun, light intensity, weather information, and wind speed. The data collected from these sensors forms the foundation of the entire system.

[0880] Server device: Performs data analysis and generates control commands. Equipped with an AI analysis module, it analyzes collected data in real time.

[0881] Solar panel control device: Includes motors and actuators that physically adjust the orientation and angle of the panels based on analysis results.

[0882] Software Configuration

[0883] Data Analysis Module: This is an AI analysis module built using Python and TensorFlow. It analyzes data from sensors and calculates the optimal placement of solar panels.

[0884] Communication software: Software for receiving data from sensors and sending it to a server. It uses real-time streaming technology.

[0885] User Interface: An interface for displaying analysis results on smart glasses or smartphones. Users can monitor and manually control the system through this interface.

[0886] Processing flow

[0887] Data collection

[0888] The server receives data from sensors that measure the sun's angle, light intensity, weather information, and wind speed in real time. This data is stored in a database on the server.

[0889] Data Analysis

[0890] The server uses an AI analysis module to analyze the collected data in real time. Based on the analysis results, it generates control commands to optimally adjust the orientation, angle, and area of ​​the solar panels.

[0891] Transmission and execution of control commands

[0892] Control commands generated from the server are sent to the solar panel control unit. The control unit then physically adjusts the orientation and angle of the panels according to the commands.

[0893] Monitoring and user notifications

[0894] The server monitors the current status of the solar panels in real time. If an anomaly is detected, it sends a notification to a smart device and issues a visual or audible warning.

[0895] Manual operation by the user

[0896] Users can monitor the system via smart glasses or a smartphone and manually control the solar panels using voice commands or touch gestures as needed.

[0897] Specific example

[0898] For example, if strong winds of 18 m / s are predicted, the sensor sends wind speed data to the server. The server quickly inputs this data into the AI ​​analysis module, and if strong winds are predicted, an analysis result is generated. Based on this result, the server generates a protective command to position the panels horizontally and sends it to the solar panel control unit. The control unit executes this command and moves the panels horizontally to prevent damage from strong winds.

[0899] Example of a prompt

[0900] Applying the following invention, create a prototype of a solar power system monitoring application to be installed on smart glasses. This application will have the functions of real-time data display, anomaly detection notification, and manual control.

[0901] 1. Data is collected from sensors on solar panels.

[0902] 2. Analyze the data using the AI ​​analysis module.

[0903] 3. Data and analysis results are visually displayed on smart glasses.

[0904] 4. Control the panel using voice or touch gestures.

[0905] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0906] Step 1:

[0907] The server receives data from sensors that measure the sun's angle, light intensity, weather information, and wind speed in real time. Specifically, the data acquired by the sensor devices is temporarily stored in the server's database. The input data includes the sun's angle, light intensity values, weather data such as temperature and humidity, and wind speed values. After acquiring this data, the server proceeds to the next analysis step.

[0908] Step 2:

[0909] The server inputs the data collected in Step 1 into the AI ​​analysis module. The AI ​​analysis module (using TensorFlow) analyzes this data and calculates the optimal orientation, angle, and area of ​​the solar panels. Based on the input data of the sun's angle, light intensity, weather, and wind speed, the AI ​​performs analysis and generates optimal placement parameters for the solar panels as output.

[0910] Step 3:

[0911] The server generates control commands based on the analysis results from Step 2. Specifically, it creates control commands according to the optimal orientation, angle, and area of ​​the solar panels calculated by the AI ​​analysis module. Furthermore, it generates special commands to protect the panels during strong winds or snowfall. The input data is the analysis results from the AI ​​analysis module, and the output data is the control commands related to the orientation, angle, and area of ​​the panels.

[0912] Step 4:

[0913] The terminal executes control commands received from the server. Specifically, the terminal sends commands to the solar panel control device, causing motors and actuators to physically adjust the orientation and angle of the panels. The input data is the control commands from the server, and the output is the actual physical change in the placement of the solar panels.

[0914] Step 5:

[0915] The server monitors the current status of the solar panels in real time. If an anomaly is detected (for example, if the wind speed exceeds a certain level), the server generates an anomaly notification and sends it to the user's smart device. The input data is real-time status data from the solar panels, and the output data is the anomaly notification message.

[0916] Step 6:

[0917] Users monitor the system status via smart glasses or smartphones. In particular, when an anomaly notification is displayed, users can manually control the system using voice commands or touch gestures. Input data includes anomaly notifications from the server and user voice commands and touch gestures, while output data consists of user feedback and response instructions.

[0918] 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.

[0919] This invention relates to an AI-powered smart solar power generation system that enhances the efficiency and safety of solar power generation systems. This system utilizes numerous sensors and real-time AI data analysis to automatically and optimally control the orientation, angle, and area of ​​solar panels. Furthermore, it incorporates an emotion engine that recognizes user emotions to improve user satisfaction. Specific embodiments of this system are described below.

[0920] Data collection

[0921] sensor

[0922] The sensors measure the sun's angle, light intensity (illuminance), weather information (sunny, cloudy, rainy, etc.), and wind speed in real time. This data is crucial for optimizing solar power generation.

[0923] Emotional Engine

[0924] The emotion engine analyzes the user's facial expressions and voice through input devices such as cameras and microphones to recognize the user's emotions. The emotion data is then sent to a server.

[0925] Data analysis and control command generation

[0926] server

[0927] The server receives data collected from sensors and the emotion engine, and analyzes it using an AI analysis module. Based on the data analysis, it calculates the optimal orientation, angle, and area of ​​solar panels for solar power generation. Furthermore, it takes user emotion data into consideration and performs solar panel placement and other system operations in a way that satisfies the user.

[0928] Program processing

[0929] 1. Data Collection

[0930] Sensors measure data on the sun's angle, light intensity, weather, and wind speed in real time and send it to the server. The emotion engine collects user emotion data and sends it to the server.

[0931] 2. Data Analysis

[0932] The server receives the collected data and inputs it into the AI ​​analysis module. The AI ​​analysis module analyzes the data and calculates the optimal placement of solar panels. Furthermore, it analyzes emotional data and generates control commands that will satisfy the user.

[0933] 3. Control command generation

[0934] The server generates control commands to adjust the orientation, angle, and area of ​​the solar panels based on the analysis results. It also generates commands to protect the panels in response to wind speed and weather fluctuations. Based on emotional data, it also considers placement and operation according to the user's preferences.

[0935] 4. Panel adjustment

[0936] The terminal receives control commands and physically adjusts the orientation, angle, and area of ​​the solar panels. This optimizes power generation and improves energy efficiency. Adjustments may also be made based on emotional data.

[0937] 5. Status Monitoring

[0938] The server monitors the current state of the panel and records the data. If an anomaly is detected, it generates an alert and notifies the user. The user's emotional state is also continuously monitored.

[0939] Specific example

[0940] For example, consider a scenario where strong winds of 15 m / s are predicted for 12:00 PM on a given day. In this case, a sensor sends wind speed data to a server. The server inputs this data into an AI analysis module, which then outputs an analysis result if strong winds are predicted. The server generates a protective command to position the panels horizontally and sends it to the terminal. The terminal receives this command, and the panel control module activates a motor to move the panels horizontally. Meanwhile, if the emotion engine recognizes that the user's stress level is high, the system takes action to provide the user with a relaxing environment (for example, by changing the panel position or adjusting the timing of notifications). This series of processes prevents damage to the panels due to strong winds, enhances safety, and improves user satisfaction.

[0941] Thus, the AI ​​smart solar power generation system of the present invention maximizes the efficiency and safety of solar power generation through the steps of data collection, data analysis, control command generation, panel adjustment, and condition monitoring, and further optimizes the system's operation while also taking into account the user's emotions.

[0942] The following describes the processing flow.

[0943] Step 1: Data Collection

[0944] A sensor measures the angle of the sun. A sensor measures the amount of light (illuminance). A sensor acquires weather information (sunny, cloudy, rainy, etc.). A sensor measures wind speed. Each sensor sends this data to the server. The emotion engine analyzes the user's facial expressions and voice through the camera and microphone, acquires the user's emotion data, and sends it to the server.

[0945] Step 2: Data aggregation and preprocessing

[0946] The server receives data transmitted from each sensor and emotion engine. The server cleans the received data, processing for missing or outlier values. The server stores the pre-processed data in data storage.

[0947] Step 3: Data Analysis

[0948] The server inputs the stored data into the AI ​​analysis module. The AI ​​analysis module calculates the predicted position of the sun. The AI ​​analysis module calculates the optimal panel orientation, angle, and area. The AI ​​analysis module analyzes the user's emotional data and calculates the optimal placement and operation to satisfy the user.

[0949] Step 4: Control command generation

[0950] The server receives calculation results from the AI ​​analysis module. The server generates control commands to optimize the orientation, angle, and area of ​​the solar panels. The server generates protection commands based on wind and snowfall forecasts. It also considers placement and operation according to user preferences based on sentiment data. The server sends the generated control and protection commands to the terminal.

[0951] Step 5: Panel Position Control

[0952] The terminal receives control commands from the server. The terminal sends commands to the panel control module. The panel control module operates the motors to adjust the orientation, angle, and area of ​​the solar panels. If a protection command is received after a forecast of strong winds or snowfall, the panel control module moves the panels horizontally or vertically. Depending on the user's emotional data, relaxing placements and actions may be performed.

[0953] Step 6: Status Monitoring

[0954] The server monitors the panel's current state. The server records the panel's operational data (change history of orientation, angle, and area). If the server detects an anomaly, it generates an alert and notifies the user. The server also continuously monitors the user's emotional state and provides feedback as needed.

[0955] (Example 2)

[0956] 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."

[0957] Conventional solar power generation systems typically maximize efficiency by considering only sunlight intensity and panel angle. However, this can sometimes come at the expense of user satisfaction and safety. In particular, protective measures for panels during strong winds and snowfall are insufficient, and system operation that takes user feelings into consideration has yet to be realized. There is a need to solve these problems.

[0958] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for measuring the angle of the sun, means for measuring the amount of light, means for acquiring weather information, means for measuring wind speed, means for analyzing the user's emotions, means for receiving data acquired from each of the means and analyzing the data, means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the data analysis, means for physically adjusting the solar panels based on the control commands, means for monitoring the state of the solar panels, and means for detecting abnormalities and notifying the user. This makes it possible to maximize the efficiency and safety of solar power generation and further optimize the operation of the system while also considering the user's emotions.

[0959] "Means for measuring the angle of the sun" refers to devices or techniques for accurately measuring the position and angle of the sun.

[0960] "Means for measuring light intensity" refers to devices or technologies for measuring the intensity or illuminance of sunlight.

[0961] "Means for acquiring weather information" refers to devices or technologies for collecting weather conditions (such as sunny, cloudy, or rainy).

[0962] "Means for measuring wind speed" refers to a device or technology for measuring the speed of wind.

[0963] "Means for analyzing user emotions" refers to devices or technologies that analyze a user's facial expressions and voice to determine their emotional and psychological state.

[0964] "Means for receiving data acquired from each of the above means and analyzing the said data" refers to a device or technology for receiving various sensor data and emotional data and analyzing them.

[0965] "Means for generating control commands to optimally adjust the orientation, angle, and area of ​​solar panels" refers to an apparatus or technology for determining the optimal orientation, angle, and area of ​​solar panels based on analysis results, and generating control commands based on those results.

[0966] "Means for physically adjusting solar panels" refers to devices or technologies for actually adjusting the physical arrangement and angle of solar panels based on control commands.

[0967] "Means for monitoring the status of solar panels" refers to devices or technologies for monitoring the current status of solar panels (position, angle, power generation, etc.) in real time.

[0968] "Means for detecting anomalies and notifying users" refers to devices or technologies that inform users of anomalies detected during system monitoring in the form of alerts or notifications.

[0969] This invention relates to an AI-powered smart solar power generation system that enhances the efficiency and safety of solar power generation systems. This system utilizes numerous sensors and real-time AI data analysis to automatically and optimally control the orientation, angle, and area of ​​solar panels. Furthermore, by incorporating an emotion engine that recognizes user emotions, it aims to improve user satisfaction.

[0970] Data collection

[0971] The server uses multiple sensors to measure the angle of the sun, light intensity (illuminance), weather information (sunny, cloudy, rainy, etc.), and wind speed. The data acquired from these sensors is transmitted to the server in real time. It also uses an emotion engine to collect user emotion data. The emotion engine analyzes the user's facial expressions and voice through input devices such as cameras and microphones to recognize the user's emotions.

[0972] Data analysis and control command generation

[0973] The server receives data collected from sensors and the emotion engine and analyzes it using an AI analysis module. Based on the data analysis, it calculates the optimal orientation, angle, and area of ​​solar panels for solar power generation. Furthermore, it takes user emotion data into consideration and performs solar panel placement and other system operations in a way that satisfies the user.

[0974] Specific example

[0975] For example, consider a scenario where strong winds of 15 m / s are predicted for 12:00 PM on a given day. In this case, a sensor sends wind speed data to a server. The server inputs this data into an AI analysis module, which then outputs an analysis result if strong winds are predicted. The server generates a protective command to position the panels horizontally and sends it to the terminal. The terminal receives this command, and the panel control module activates a motor to move the panels horizontally. Meanwhile, if the emotion engine recognizes that the user's stress level is high, the system takes action to provide the user with a relaxing environment (for example, by changing the panel position or adjusting the timing of notifications). This series of processes prevents damage to the panels due to strong winds, enhances safety, and improves user satisfaction.

[0976] Examples of prompt statements

[0977] Enter the following prompt into the generative AI model:

[0978] "Please explain how the AI ​​smart solar power system protects the panels when strong winds of 15 m / s are predicted. Also, please explain how the system responds when the user is under high stress."

[0979] Based on this prompt, the generated response will provide details on how the system collects and analyzes data, how it actually adjusts the panel, and how it responds based on user sentiment data.

[0980] The AI ​​smart solar power generation system of the present invention maximizes the efficiency and safety of solar power generation through the steps of data collection, data analysis, control command generation, panel adjustment, and condition monitoring, and further optimizes the system's operation while also taking into account the user's emotions.

[0981] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0982] Step 1: Data Collection

[0983] The server receives real-time data from numerous sensors regarding the angle of the sun, light intensity (illuminance), weather information (sunny, cloudy, rainy, etc.), and wind speed. Users provide emotional data through their cameras and microphones. An emotion engine analyzes the user's facial expressions and voice to generate emotional data. This data is the input data sent to the server. Specifically, the sensors measure data every minute and send it to the server.

[0984] Step 2: Data Analysis

[0985] The server receives data collected from sensors and the emotion engine. This data is preprocessed to ensure consistency and fill in any gaps. Next, the server inputs this preprocessed data into the AI ​​analysis module. The AI ​​analysis module analyzes the data to calculate the optimal orientation, angle, and area of ​​the solar panels. Furthermore, it generates control commands that will satisfy the user based on the user's emotion data. Specifically, the AI ​​analysis module inputs the dataset into a model and performs analysis using an optimization algorithm.

[0986] Step 3: Generation of control commands

[0987] The server assembles specific control commands to adjust the orientation, angle, and area of ​​the solar panels based on the analysis results from the AI ​​analysis module. These control commands determine the optimal placement and operation of the solar panels and also include protective commands against wind speed and weather fluctuations. For example, it generates commands such as, "If the wind speed is 15 m / s or higher, position the panels horizontally."

[0988] Step 4: Sending control commands

[0989] The server sends the generated control command to the terminal. The terminal receives this control command and prepares to control the panel according to the settings. Specifically, the server sends command data to the terminal via the network.

[0990] Step 5: Panel adjustment

[0991] The terminal receives control commands sent from the server and physically adjusts the orientation and angle of the solar panels based on them. It drives motors and actuators to move the panels to the optimal position. Specifically, the terminal executes a motor control program to tilt the panels horizontally.

[0992] Step 6: Status Monitoring

[0993] The server monitors the current status of the solar panels in real time and records the data. It also generates an alert and notifies the user if an anomaly is detected. The user can then take the necessary actions after receiving the notification. Specifically, the server periodically checks the panel's position, angle, power generation, etc., and sends email or application notifications if any anomalies are detected.

[0994] (Application Example 2)

[0995] 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."

[0996] Conventional solar power generation systems optimize power generation efficiency based solely on environmental data, without considering comprehensive energy management in logistics facilities or optimizing the emotional well-being of workers. Furthermore, irregular energy consumption in logistics centers often leads to employee stress and problems with the working environment. This presents a challenge: simultaneously improving energy efficiency and working conditions.

[0997] 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.

[0998] In this invention, the server includes means for measuring the angle of the sun, means for measuring light intensity, means for acquiring weather information, means for measuring wind speed, means for measuring the energy consumption of the logistics center, means for analyzing the emotions of employees, means for receiving and analyzing data acquired from each of the means, means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the data analysis, means for physically adjusting the solar panels based on the control commands, means for optimizing the energy consumption pattern of the logistics center, and means for optimizing the working environment of employees based on the results of the emotion analysis. This makes it possible to improve energy efficiency and optimize the working environment of employees in the logistics center.

[0999] "Means for measuring the angle of the sun" refers to devices and sensor sets used to measure the position and angle of the sun in real time.

[1000] "Means for measuring light intensity" refers to devices or sensors used to measure the amount of ambient light.

[1001] "Means for acquiring weather information" refers to means of communication with sensors and databases used to acquire weather conditions (sunny, cloudy, rainy, etc.).

[1002] "Means for measuring wind speed" refers to devices or sensors used to measure wind speed in real time.

[1003] "Means for measuring energy consumption in a logistics center" refers to devices and systems for measuring energy consumption within a logistics facility in real time.

[1004] "Methods for analyzing employee emotions" refer to systems and algorithms that analyze employees' facial expressions and voice data to recognize their emotional state.

[1005] "Means for receiving data acquired from each of the above means and analyzing the data" refers to devices or programs that receive data transmitted from sensors or devices and analyze that data using an AI analysis module.

[1006] "Means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the data analysis" refers to a system or program that generates commands to instruct the optimal settings of the solar panels based on the analysis results.

[1007] "Means for physically adjusting the solar panels based on the control command" refers to machines or devices that receive a control command and physically adjust the orientation and angle of the solar panels.

[1008] "Means for optimizing the energy consumption patterns of a logistics center" refers to systems and programs for efficiently managing and optimizing the energy consumption of a logistics center.

[1009] "Means for optimizing the working environment of employees based on the results of the aforementioned sentiment analysis" refers to systems or programs for improving the working environment by reflecting the results of the employee sentiment analysis.

[1010] This invention is a system for achieving energy management and optimization of the working environment in a logistics center. The detailed configuration and operation for carrying out this invention are described below.

[1011] Data collection

[1012] 1. Measuring the angle of the sun:

[1013] • Hardware used: Solar angle sensor

[1014] • Measures the position and angle of the sun in real time and transmits the data to the server.

[1015] 2. Measurement of light intensity:

[1016] • Hardware used: Light sensor

[1017] • Measures the amount of ambient light and sends the data to the server.

[1018] 3. Obtaining weather information:

[1019] • Hardware used: Weather sensor, Internet connection

[1020] • Acquire weather conditions in real time and send the data to the server.

[1021] 4. Measuring wind speed:

[1022] • Hardware used: Wind speed sensor

[1023] • Measure wind speed and send the data to the server.

[1024] 5. Measurement of energy consumption:

[1025] Hardware used: energy meter, RFID tag, GPS

[1026] • Collect energy consumption data within the logistics center and send it to the server.

[1027] 6. Emotion analysis:

[1028] • Hardware used: Camera, microphone

[1029] • Software used: Sentiment analysis engine (e.g., OpenCV)

[1030] • Analyzes employees' facial expressions and voices and sends emotional data to the server.

[1031] Data analysis and control command generation

[1032] 1. Data reception:

[1033] The server receives data from each sensor and emotion analysis engine.

[1034] 2. AI Analysis Module:

[1035] • Software used: TensorFlow, PyTorch

[1036] The server inputs the received data into the AI ​​analysis module to calculate the optimal orientation, angle, and area of ​​the solar panels.

[1037] • Calculate patterns to optimize energy consumption at the logistics center.

[1038] 3. Control command generation:

[1039] The server generates control commands based on the AI ​​analysis results.

[1040] • Transmits commands for physical adjustment of solar panels and optimization of energy consumption patterns.

[1041] • It also generates instructions to optimize the employee work environment based on emotional data.

[1042] Panel adjustment and energy management

[1043] 1. Panel adjustment:

[1044] Hardware used: Solar panel angle adjustment mechanism, motor

[1045] Based on control commands, the orientation and angle of the solar panels are physically adjusted.

[1046] 2. Energy Management:

[1047] • Software used: Energy Management System

[1048] • Optimize the energy consumption patterns of logistics centers in real time.

[1049] 3. Optimizing the working environment:

[1050] Hardware used: Lighting, air conditioning system

[1051] • Optimize the working environment for employees based on control commands.

[1052] Status Monitoring

[1053] 1. Monitoring:

[1054] The server constantly monitors the current status of each device.

[1055] 2. Anomaly detection:

[1056] • If an anomaly is detected, an alert will be generated and the user will be notified.

[1057] Specific example

[1058] 1. How to respond during strong winds:

[1059] • Hardware used: Wind speed sensor, solar panel angle adjustment mechanism

[1060] When the wind speed sensor measures 15 m / s, the server inputs the wind speed data into the AI ​​analysis module and generates commands to cope with strong winds. A command is issued to position the solar panels horizontally, and the motor moves the panels.

[1061] Example of a prompt:

[1062] 1. Environmental data collection:

[1063] "Collect light intensity data in real time from the sensor device during sunny conditions and transmit it to the data server."

[1064] 2. Emotion analysis:

[1065] "We analyze employees' facial images in real time to assess their stress levels."

[1066] 3. Control command generation:

[1067] "Protect the solar panels to a safe horizontal position, given the current wind speed of 15 m / s."

[1068] 4. Anomaly monitoring:

[1069] "Continuously monitor the panel status and issue an immediate alert if any abnormal values ​​are detected."

[1070] In this way, the system will perform panel adjustments, optimize energy consumption, and improve the working environment by collecting data from various sensors and analyzing it with AI.

[1071] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1072] Step 1:

[1073] Collect energy data

[1074] Inputs: Sun angle sensor, light sensor, weather sensor, wind speed sensor, energy meter, camera and microphone

[1075] The server collects data from the above sensors and devices in real time.

[1076] Output: Data from each sensor (sun angle, light intensity, weather information, wind speed, energy consumption, emotion data)

[1077] Specific operation: The server periodically receives data transmitted from sensors and saves it to local storage. In addition, the emotion engine analyzes employees' facial expressions and voices and saves their emotional state as data.

[1078] Step 2:

[1079] Preprocessing of data

[1080] Input: Raw data collected in Step 1

[1081] The server cleanses the raw data it collects, removing outliers and noise.

[1082] Output: Cleansed data

[1083] Specific operation: The server uses a database management system to format and normalize data, generating a clean dataset. For example, it filters out abnormal values ​​from temperature sensors (such as sudden fluctuations).

[1084] Step 3:

[1085] Data Analysis

[1086] Input: Clean data obtained in Step 2

[1087] The server uses AI analysis modules such as TensorFlow and PyTorch to analyze data and calculate the optimal settings for the orientation, angle, and area of ​​solar panels. It also analyzes energy consumption patterns and employee sentiment data to generate instructions for setting up the optimal work environment.

[1088] Output: Analysis results (optimal solar panel settings, energy consumption patterns, work environment settings)

[1089] Specific operation: Data is input into the AI ​​model, and the optimal numerical settings are calculated as a result of the analysis. For example, based on the angle of the sun at 3 PM, the panel angle is calculated to be 30 degrees. At the same time, if an employee is working for a long time, a command prompting them to take a break is generated.

[1090] Step 4:

[1091] Generation of control commands

[1092] Input: Analysis results obtained in Step 3

[1093] The server sends control commands to each sensor and device based on the analysis results.

[1094] Output: Control commands (adjustment of solar panel angle, change of energy consumption pattern, adjustment of working environment)

[1095] Specific operation: The server sends a control signal to the solar panel control unit, for example, "Adjust the panel to 30 degrees." At the same time, it sends a command to the lighting system to "Switch to an energy-saving mode."

[1096] Step 5:

[1097] Control implementation

[1098] Input: Control command from step 4

[1099] The terminal receives control commands and physically adjusts the orientation and angle of the solar panels. It also changes the settings of lighting and air conditioning systems.

[1100] Output: Actual adjustment results (orientation and angle of solar panels, changes in working environment)

[1101] Specific operation: The solar panel control unit drives a motor to adjust the panels to the specified angle. It also optimizes energy consumption and automatically switches between lighting and air conditioning.

[1102] Step 6:

[1103] Status Monitoring

[1104] Input: Real-time data from each source

[1105] The server constantly monitors the current status of each system and immediately generates an alert if an anomaly occurs.

[1106] Output: Anomaly detection alert, system log

[1107] Specific operation: The server monitors sensor data at regular intervals and detects abnormal values ​​(e.g., excessive temperature changes). If an abnormality is found, it sends an email or SMS notification to the administrator. It also logs all data.

[1108] 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.

[1109] 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.

[1110] 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.

[1111] [Fourth Embodiment]

[1112] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1113] 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.

[1114] 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).

[1115] 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.

[1116] 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.

[1117] 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).

[1118] 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.

[1119] 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.

[1120] 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.

[1121] 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.

[1122] 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.

[1123] 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.

[1124] 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".

[1125] This invention relates to an AI-powered smart solar power generation system that enhances the efficiency and safety of solar power generation systems. This system utilizes numerous sensors and real-time AI data analysis to automatically and optimally control the orientation, angle, and area of ​​solar panels. Specific embodiments of this system are described below.

[1126] Data collection

[1127] sensor

[1128] The sensors measure the sun's angle, light intensity, weather, and wind speed in real time. This data is crucial for optimizing solar power generation.

[1129] Data analysis and control command generation

[1130] server

[1131] The server receives data collected from sensors and analyzes it using an AI analysis module. Based on the data analysis, it calculates the optimal orientation, angle, and area of ​​solar panels for solar power generation. It also generates commands to protect the panels in response to wind speed and weather fluctuations.

[1132] Program processing

[1133] 1. Data Collection

[1134] The sensor measures data on the sun's angle, light intensity, weather, and wind speed in real time and transmits it to the server.

[1135] 2. Data Analysis

[1136] The server receives the collected data and inputs it into the AI ​​analysis module. The AI ​​analysis module analyzes the data and calculates the optimal placement of the solar panels.

[1137] 3. Control command generation

[1138] The server generates control commands to adjust the orientation, angle, and area of ​​the solar panels based on the analysis results. It also generates commands to protect the panels in response to changes in wind speed and weather conditions.

[1139] 4. Panel adjustment

[1140] The terminal receives control commands and physically adjusts the orientation, angle, and area of ​​the solar panels. This optimizes power generation and improves energy efficiency.

[1141] 5. Status Monitoring

[1142] The server monitors the current status of the panel and notifies the user if an anomaly is detected.

[1143] Specific example

[1144] For example, consider a scenario where strong winds of 15 m / s are predicted at 12:00 PM on a given day. In this case, the sensor sends wind speed data to the server. The server inputs this data into an AI analysis module, which then generates an analysis result if strong winds are predicted. The server generates a protective command to position the panels horizontally and sends it to the terminal. The terminal receives this command, and the panel control module activates a motor to move the panels horizontally. This entire process prevents damage to the panels due to strong winds, extending the lifespan and enhancing the safety of the entire system.

[1145] Thus, the AI ​​smart solar power generation system of the present invention maximizes the efficiency and safety of solar power generation through the steps of data collection, data analysis, control command generation, panel adjustment, and condition monitoring.

[1146] The following describes the processing flow.

[1147] Step 1: Data Collection

[1148] The sensor measures the angle of the sun. The sensor measures the amount of light (illuminance). The sensor acquires weather information (sunny, cloudy, rainy, etc.). The sensor measures wind speed. Each sensor sends the collected data to the server.

[1149] Step 2: Data aggregation and preprocessing

[1150] The server receives data transmitted from each sensor. The server cleans the received data, processing for missing or outlier values. The server saves the pre-processed data to data storage.

[1151] Step 3: Data Analysis

[1152] The server inputs the stored data into the AI ​​analysis module. The AI ​​analysis module calculates the predicted position of the sun. The AI ​​analysis module calculates the optimal panel orientation, angle, and area. Based on wind speed and weather information, the AI ​​analysis module determines whether to generate a protection command.

[1153] Step 4: Control command generation

[1154] The server receives calculation results from the AI ​​analysis module. The server generates control commands to optimize the orientation, angle, and area of ​​the solar panels. The server generates protection commands based on wind and snowfall forecasts. The server sends the generated control and protection commands to the terminal.

[1155] Step 5: Panel Position Control

[1156] The terminal receives control commands from the server. The terminal sends commands to the panel control module. The panel control module operates the motors to adjust the orientation, angle, and area of ​​the solar panels. If a protection command is received after a forecast of strong winds or snowfall, the panel control module moves the panels horizontally or vertically.

[1157] Step 6: Status Monitoring

[1158] The server monitors the current status of the panel. The server records the panel's operational data (change history of orientation, angle, and area). If the server detects an anomaly, it generates an alert and notifies the user.

[1159] (Example 1)

[1160] 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".

[1161] To improve the efficiency and safety of solar power generation systems, optimal panel placement based on real-time weather information and the angle of the sun is required. However, current systems require manual adjustments, resulting in low efficiency and an increased risk of panel damage during extreme weather conditions such as strong winds and snowfall. Furthermore, the lack of a mechanism to immediately notify users when an anomaly occurs makes it difficult to respond quickly.

[1162] 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.

[1163] In this invention, the server includes means for measuring the angle of the sun, means for measuring light intensity, means for acquiring weather information, means for measuring wind speed, means for receiving data acquired from each of the means and storing it in a database, means including an AI analysis module for analyzing the data, means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the data analysis, means for physically adjusting the solar panels via a servo motor according to the control commands, and means for monitoring the current state of the solar panels and notifying the user if an abnormality is detected. This enables real-time automatic adjustment, improving the efficiency and safety of solar power generation, as well as enabling a rapid response in the event of an abnormality.

[1164] "Means for measuring the angle of the sun" refers to instruments that measure the current position and altitude angle of the sun. Specifically, this includes sensors for accurately determining the sun's position.

[1165] "Means for measuring light intensity" refers to devices that measure the intensity of ambient sunlight. Specifically, this includes devices that measure light intensity using photoelectric sensors or photodiodes.

[1166] "Means of obtaining weather information" refers to systems or services for obtaining meteorological data. Specifically, this includes APIs for obtaining information from external meteorological data providers and weather stations established independently.

[1167] "Means for measuring wind speed" refers to equipment for measuring wind speed. Specifically, this includes devices for measuring wind speed using an anemometer (wind speed meter), etc.

[1168] "Means for receiving data and storing it in a database" refers to a system for acquiring data from sensors, transferring it to a central computer, and storing it for long-term use. Specifically, this includes communication modules and data storage (e.g., MySQL, MongoDB).

[1169] An "AI analysis module" is an artificial intelligence system for analyzing acquired data. Specifically, it includes a software module that uses machine learning and deep learning algorithms to calculate the optimal panel arrangement.

[1170] "Means for generating control commands" refers to a device or software that creates commands for appropriately controlling solar panels based on the results of data analysis. Specifically, this includes a system that generates control signals using a programmed algorithm.

[1171] A "servo motor" is a drive device used to adjust the orientation and angle of solar panels in response to control commands. Specifically, it includes motors capable of precise rotation and angle adjustment.

[1172] "Means for monitoring status and detecting anomalies" refers to a system that constantly monitors the current operating state of a system and issues warnings when abnormal conditions or operations are detected. Specifically, this includes an alert system that analyzes data from sensors and detects abnormal values.

[1173] "Means of notifying users" refers to methods for informing users of system abnormalities or important information. Specifically, this includes communication methods such as email notifications, SMS, and push notifications.

[1174] This invention relates to an AI-powered smart solar power system that enhances the efficiency and safety of solar power generation systems. This system is configured to automatically and optimally control the orientation, angle, and area of ​​solar panels by utilizing numerous sensors and real-time AI data analysis.

[1175] Data collection

[1176] The sensors measure information on the sun's angle, light intensity, weather, and wind speed in real time. This includes the following sensors:

[1177] Optical sensor for measuring the angle of the sun

[1178] Photoelectric sensor for measuring light intensity

[1179] A system for acquiring weather information from weather sensors or external data providers.

[1180] An anemometer (wind speed meter) for measuring wind speed

[1181] Data reception and storage

[1182] The server receives data transmitted from the sensors and stores it in a database. Examples of databases used include MySQL and MongoDB. This ensures that the latest data is always updated and used for subsequent analysis.

[1183] Data Analysis

[1184] The server receives and stores data, which is then input into an AI analysis module. Specifically, an AI analysis module using deep learning frameworks such as TensorFlow or PyTorch analyzes the data and calculates the optimal orientation, angle, and area of ​​the solar panels.

[1185] Control command generation

[1186] The server generates control commands to optimize the orientation, angle, and area of ​​the solar panels based on the analysis results of the AI ​​analysis module. It also generates protective commands to move the panels horizontally or vertically if the wind speed exceeds a certain value or if snowfall is observed.

[1187] Control command transmission

[1188] The server sends the generated control commands to the terminal. MQTT or HTTP protocols are used for communication.

[1189] Panel adjustment

[1190] The terminal drives servo motors to adjust the orientation and angle of the solar panels based on the control commands it receives. For example, if strong winds are predicted, the panels will be moved horizontally.

[1191] Status Monitoring

[1192] The server constantly monitors the current status of the solar panels and sends a notification to the user if an anomaly is detected. Notifications are sent via email or push notifications.

[1193] Specific example

[1194] For example, if strong winds of 15 m / s are predicted at 12:00 on a given day, the system will operate in the following manner:

[1195] 1. The sensor measures wind speed data and sends it to the server.

[1196] 2. The server receives the data and inputs it into the AI ​​analysis module.

[1197] 3. The AI ​​analysis module analyzes the data and determines that strong winds are predicted.

[1198] 4. The server generates a protective command to position the panel horizontally and sends it to the terminal.

[1199] 5. The terminal receives the command and drives the servo motor to move the panel horizontally.

[1200] This series of processes prevents damage to panels caused by strong winds, thereby improving safety. Furthermore, the system can quickly detect and notify users of any abnormalities, allowing them to respond promptly.

[1201] Examples of prompts to input into a generative AI model:

[1202] "Please explain how the AI ​​smart solar power system works based on the following conditions: It is 12:00 PM on a day when strong winds of 15 m / s are predicted."

[1203] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1204] Step 1:

[1205] Data collection

[1206] The sensor measures data on the sun's angle, light intensity, weather, and wind speed in real time and transmits it to the server. Specifically, the sensor measures the sun's angle and light intensity every second and the wind speed every minute. The input data consists of the sun's angle, light intensity, weather information, and wind speed, and this data is packaged with a timestamp when transmitted. The output is the measurement data transmitted to the server.

[1207] Step 2:

[1208] Data reception and storage

[1209] The server receives data transmitted from the sensor and stores it in a database. The input is measurement data transmitted from the sensor, which the server receives and stores in a database, for example, using MySQL or MongoDB. Specifically, the received data is converted into a format that is easy to analyze and inserted into the corresponding field in the database. The output is the measurement data stored in the database.

[1210] Step 3:

[1211] Data Analysis

[1212] The server inputs data collected from the database into the AI ​​analysis module. The input is the latest measurement data obtained from the database, which the AI ​​analysis module (e.g., a deep learning model using TensorFlow or PyTorch) analyzes. Specifically, the data is fed into the model to calculate the optimal orientation, angle, and area of ​​the solar panels. The output is the parameters for the optimal orientation, angle, and area.

[1213] Step 4:

[1214] Control command generation

[1215] The server generates control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the analysis results of the AI ​​analysis module. The input is the data analysis results, and the server constructs the control commands based on this. Specifically, this includes commands such as positioning the panels horizontally when it is determined that the wind speed exceeds 10 m / s. The generated control commands are packaged in JSON format, etc. The output is the generated control commands.

[1216] Step 5:

[1217] Control command transmission

[1218] The server sends the generated control commands to the terminal. The input is the generated control commands, which are sent to the terminal using protocols such as MQTT or HTTP. Specifically, the command packets are converted into a format suitable for the communication protocol and sent to the terminal. The output is the control commands sent to the terminal.

[1219] Step 6:

[1220] Panel adjustment

[1221] The terminal drives a servo motor to adjust the orientation and angle of the solar panel based on the control commands it receives. The input is a control command sent from the server, which the terminal receives and sends commands to the servo motor. Specifically, it sends signals to the motor to control the rotation angle and direction. For example, if it is determined that the wind speed exceeds 10 m / s, the motor rotates to position the panel horizontally. The output is the physical position of the adjusted solar panel.

[1222] Step 7:

[1223] Status Monitoring

[1224] The server constantly monitors the current status of the solar panels and sends a notification to the user if an anomaly is detected. The input is the adjusted panel status data, which the server monitors to detect anomalies. Specifically, it uses data from angle sensors and temperature sensors to generate an alert if the values ​​differ from the set values. The output is an anomaly notification sent to the user, which is sent via email or push notification.

[1225] (Application Example 1)

[1226] 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".

[1227] Existing solar power generation systems suffer from reduced power generation efficiency due to the lack of real-time data analysis to optimally adjust the orientation and angle of solar panels. Furthermore, they struggle to respond quickly to extreme weather events such as strong winds and snowfall, raising concerns about panel damage and system safety. Additionally, they lack the functionality to remotely monitor the system status and manually control it as needed, even when the user is not on-site.

[1228] 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.

[1229] In this invention, the server includes means for measuring the angle of the sun, means for measuring light intensity, means for acquiring weather information, means for measuring wind speed, means for receiving data acquired from each of the means and analyzing the data, means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the data analysis, means for physically adjusting the solar panels based on the control commands, means for displaying the results on a smart device in real time, and means for the user to manually control the panels using voice commands or touch gestures. This enhances the power generation efficiency and safety of the solar power generation system, and enables remote monitoring and control by the user.

[1230] "Means for measuring the angle of the sun" refers to a sensor device that detects the angle of the sun in real time according to its position.

[1231] "Means for measuring light intensity" refers to a sensor device used to measure the current intensity of sunlight.

[1232] "Means of acquiring weather information" refer to sensors and external data provision services for collecting current temperature, humidity, precipitation, etc.

[1233] "Means for measuring wind speed" refers to a sensor device for measuring wind speed in real time.

[1234] "Means for analyzing data" refers to an AI analysis module that uses data collected from sensors to evaluate the situation and generate necessary control commands.

[1235] "Means for generating control commands" refers to a device or software that generates commands to optimally adjust the orientation, angle, and area of ​​solar panels based on the results of data analysis.

[1236] "Means for physically adjusting solar panels" refer to motors and actuators that automatically change the orientation and angle of the panels according to control commands.

[1237] "Means for displaying results in real time on smart devices" refers to communication and display devices for notifying smart devices (smart glasses, smartphones) of analysis results and data from sensors.

[1238] "Means for manually controlling the panel using voice commands or touch gestures" refers to an interface that allows users to manually adjust the solar panels using voice or physical operations.

[1239] System Overview

[1240] This invention provides an AI-powered smart control system to enhance the efficiency and safety of solar power generation systems. This system collects data from multiple sensors, analyzes it in real time, and optimally adjusts the orientation, angle, and area of ​​the solar panels.

[1241] Hardware configuration

[1242] Sensor equipment: Includes sensors that measure the angle of the sun, light intensity, weather information, and wind speed. The data collected from these sensors forms the foundation of the entire system.

[1243] Server device: Performs data analysis and generates control commands. Equipped with an AI analysis module, it analyzes collected data in real time.

[1244] Solar panel control device: Includes motors and actuators that physically adjust the orientation and angle of the panels based on analysis results.

[1245] Software Configuration

[1246] Data Analysis Module: This is an AI analysis module built using Python and TensorFlow. It analyzes data from sensors and calculates the optimal placement of solar panels.

[1247] Communication software: Software for receiving data from sensors and sending it to a server. It uses real-time streaming technology.

[1248] User Interface: An interface for displaying analysis results on smart glasses or smartphones. Users can monitor and manually control the system through this interface.

[1249] Processing flow

[1250] Data collection

[1251] The server receives data from sensors that measure the sun's angle, light intensity, weather information, and wind speed in real time. This data is stored in a database on the server.

[1252] Data Analysis

[1253] The server uses an AI analysis module to analyze the collected data in real time. Based on the analysis results, it generates control commands to optimally adjust the orientation, angle, and area of ​​the solar panels.

[1254] Transmission and execution of control commands

[1255] Control commands generated from the server are sent to the solar panel control unit. The control unit then physically adjusts the orientation and angle of the panels according to the commands.

[1256] Monitoring and user notifications

[1257] The server monitors the current status of the solar panels in real time. If an anomaly is detected, it sends a notification to a smart device and issues a visual or audible warning.

[1258] Manual operation by the user

[1259] Users can monitor the system via smart glasses or a smartphone and manually control the solar panels using voice commands or touch gestures as needed.

[1260] Specific example

[1261] For example, if strong winds of 18 m / s are predicted, the sensor sends wind speed data to the server. The server quickly inputs this data into the AI ​​analysis module, and if strong winds are predicted, an analysis result is generated. Based on this result, the server generates a protective command to position the panels horizontally and sends it to the solar panel control unit. The control unit executes this command and moves the panels horizontally to prevent damage from strong winds.

[1262] Example of a prompt

[1263] Applying the following invention, create a prototype of a solar power system monitoring application to be installed on smart glasses. This application will have the functions of real-time data display, anomaly detection notification, and manual control.

[1264] 1. Data is collected from sensors on solar panels.

[1265] 2. Analyze the data using the AI ​​analysis module.

[1266] 3. Data and analysis results are visually displayed on smart glasses.

[1267] 4. Control the panel using voice or touch gestures.

[1268] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1269] Step 1:

[1270] The server receives data from sensors that measure the sun's angle, light intensity, weather information, and wind speed in real time. Specifically, the data acquired by the sensor devices is temporarily stored in the server's database. The input data includes the sun's angle, light intensity values, weather data such as temperature and humidity, and wind speed values. After acquiring this data, the server proceeds to the next analysis step.

[1271] Step 2:

[1272] The server inputs the data collected in Step 1 into the AI ​​analysis module. The AI ​​analysis module (using TensorFlow) analyzes this data and calculates the optimal orientation, angle, and area of ​​the solar panels. Based on the input data of the sun's angle, light intensity, weather, and wind speed, the AI ​​performs analysis and generates optimal placement parameters for the solar panels as output.

[1273] Step 3:

[1274] The server generates control commands based on the analysis results from Step 2. Specifically, it creates control commands according to the optimal orientation, angle, and area of ​​the solar panels calculated by the AI ​​analysis module. Furthermore, it generates special commands to protect the panels during strong winds or snowfall. The input data is the analysis results from the AI ​​analysis module, and the output data is the control commands related to the orientation, angle, and area of ​​the panels.

[1275] Step 4:

[1276] The terminal executes control commands received from the server. Specifically, the terminal sends commands to the solar panel control device, causing motors and actuators to physically adjust the orientation and angle of the panels. The input data is the control commands from the server, and the output is the actual physical change in the placement of the solar panels.

[1277] Step 5:

[1278] The server monitors the current status of the solar panels in real time. If an anomaly is detected (for example, if the wind speed exceeds a certain level), the server generates an anomaly notification and sends it to the user's smart device. The input data is real-time status data from the solar panels, and the output data is the anomaly notification message.

[1279] Step 6:

[1280] Users monitor the system status via smart glasses or smartphones. In particular, when an anomaly notification is displayed, users can manually control the system using voice commands or touch gestures. Input data includes anomaly notifications from the server and user voice commands and touch gestures, while output data consists of user feedback and response instructions.

[1281] 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.

[1282] This invention relates to an AI-powered smart solar power generation system that enhances the efficiency and safety of solar power generation systems. This system utilizes numerous sensors and real-time AI data analysis to automatically and optimally control the orientation, angle, and area of ​​solar panels. Furthermore, it incorporates an emotion engine that recognizes user emotions to improve user satisfaction. Specific embodiments of this system are described below.

[1283] Data collection

[1284] sensor

[1285] The sensors measure the sun's angle, light intensity (illuminance), weather information (sunny, cloudy, rainy, etc.), and wind speed in real time. This data is crucial for optimizing solar power generation.

[1286] Emotional Engine

[1287] The emotion engine analyzes the user's facial expressions and voice through input devices such as cameras and microphones to recognize the user's emotions. The emotion data is then sent to a server.

[1288] Data analysis and control command generation

[1289] server

[1290] The server receives data collected from sensors and the emotion engine, and analyzes it using an AI analysis module. Based on the data analysis, it calculates the optimal orientation, angle, and area of ​​solar panels for solar power generation. Furthermore, it takes user emotion data into consideration and performs solar panel placement and other system operations in a way that satisfies the user.

[1291] Program processing

[1292] 1. Data Collection

[1293] Sensors measure data on the sun's angle, light intensity, weather, and wind speed in real time and send it to the server. The emotion engine collects user emotion data and sends it to the server.

[1294] 2. Data Analysis

[1295] The server receives the collected data and inputs it into the AI ​​analysis module. The AI ​​analysis module analyzes the data and calculates the optimal placement of solar panels. Furthermore, it analyzes emotional data and generates control commands that will satisfy the user.

[1296] 3. Control command generation

[1297] The server generates control commands to adjust the orientation, angle, and area of ​​the solar panels based on the analysis results. It also generates commands to protect the panels in response to wind speed and weather fluctuations. Based on emotional data, it also considers placement and operation according to the user's preferences.

[1298] 4. Panel adjustment

[1299] The terminal receives control commands and physically adjusts the orientation, angle, and area of ​​the solar panels. This optimizes power generation and improves energy efficiency. Adjustments may also be made based on emotional data.

[1300] 5. Status Monitoring

[1301] The server monitors the current state of the panel and records the data. If an anomaly is detected, it generates an alert and notifies the user. The user's emotional state is also continuously monitored.

[1302] Specific example

[1303] For example, consider a scenario where strong winds of 15 m / s are predicted for 12:00 PM on a given day. In this case, a sensor sends wind speed data to a server. The server inputs this data into an AI analysis module, which then outputs an analysis result if strong winds are predicted. The server generates a protective command to position the panels horizontally and sends it to the terminal. The terminal receives this command, and the panel control module activates a motor to move the panels horizontally. Meanwhile, if the emotion engine recognizes that the user's stress level is high, the system takes action to provide the user with a relaxing environment (for example, by changing the panel position or adjusting the timing of notifications). This series of processes prevents damage to the panels due to strong winds, enhances safety, and improves user satisfaction.

[1304] Thus, the AI ​​smart solar power generation system of the present invention maximizes the efficiency and safety of solar power generation through the steps of data collection, data analysis, control command generation, panel adjustment, and condition monitoring, and further optimizes the system's operation while also taking into account the user's emotions.

[1305] The following describes the processing flow.

[1306] Step 1: Data Collection

[1307] A sensor measures the angle of the sun. A sensor measures the amount of light (illuminance). A sensor acquires weather information (sunny, cloudy, rainy, etc.). A sensor measures wind speed. Each sensor sends this data to the server. The emotion engine analyzes the user's facial expressions and voice through the camera and microphone, acquires the user's emotion data, and sends it to the server.

[1308] Step 2: Data aggregation and preprocessing

[1309] The server receives data transmitted from each sensor and emotion engine. The server cleans the received data, processing for missing or outlier values. The server stores the pre-processed data in data storage.

[1310] Step 3: Data Analysis

[1311] The server inputs the stored data into the AI ​​analysis module. The AI ​​analysis module calculates the predicted position of the sun. The AI ​​analysis module calculates the optimal panel orientation, angle, and area. The AI ​​analysis module analyzes the user's emotional data and calculates the optimal placement and operation to satisfy the user.

[1312] Step 4: Control command generation

[1313] The server receives calculation results from the AI ​​analysis module. The server generates control commands to optimize the orientation, angle, and area of ​​the solar panels. The server generates protection commands based on wind and snowfall forecasts. It also considers placement and operation according to user preferences based on sentiment data. The server sends the generated control and protection commands to the terminal.

[1314] Step 5: Panel Position Control

[1315] The terminal receives control commands from the server. The terminal sends commands to the panel control module. The panel control module operates the motors to adjust the orientation, angle, and area of ​​the solar panels. If a protection command is received after a forecast of strong winds or snowfall, the panel control module moves the panels horizontally or vertically. Depending on the user's emotional data, relaxing placements and actions may be performed.

[1316] Step 6: Status Monitoring

[1317] The server monitors the panel's current state. The server records the panel's operational data (change history of orientation, angle, and area). If the server detects an anomaly, it generates an alert and notifies the user. The server also continuously monitors the user's emotional state and provides feedback as needed.

[1318] (Example 2)

[1319] 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".

[1320] Conventional solar power generation systems typically maximize efficiency by considering only sunlight intensity and panel angle. However, this can sometimes come at the expense of user satisfaction and safety. In particular, protective measures for panels during strong winds and snowfall are insufficient, and system operation that takes user feelings into consideration has yet to be realized. There is a need to solve these problems.

[1321] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for measuring the angle of the sun, means for measuring the amount of light, means for acquiring weather information, means for measuring wind speed, means for analyzing the user's emotions, means for receiving data acquired from each of the means and analyzing the data, means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the data analysis, means for physically adjusting the solar panels based on the control commands, means for monitoring the state of the solar panels, and means for detecting abnormalities and notifying the user. This makes it possible to maximize the efficiency and safety of solar power generation and further optimize the operation of the system while also considering the user's emotions.

[1322] "Means for measuring the angle of the sun" refers to devices or techniques for accurately measuring the position and angle of the sun.

[1323] "Means for measuring light intensity" refers to devices or technologies for measuring the intensity or illuminance of sunlight.

[1324] "Means for acquiring weather information" refers to devices or technologies for collecting weather conditions (such as sunny, cloudy, or rainy).

[1325] "Means for measuring wind speed" refers to a device or technology for measuring the speed of wind.

[1326] "Means for analyzing user emotions" refers to devices or technologies that analyze a user's facial expressions and voice to determine their emotional and psychological state.

[1327] "Means for receiving data acquired from each of the above means and analyzing the said data" refers to a device or technology for receiving various sensor data and emotional data and analyzing them.

[1328] "Means for generating control commands to optimally adjust the orientation, angle, and area of ​​solar panels" refers to an apparatus or technology for determining the optimal orientation, angle, and area of ​​solar panels based on analysis results, and generating control commands based on those results.

[1329] "Means for physically adjusting solar panels" refers to devices or technologies for actually adjusting the physical arrangement and angle of solar panels based on control commands.

[1330] "Means for monitoring the status of solar panels" refers to devices or technologies for monitoring the current status of solar panels (position, angle, power generation, etc.) in real time.

[1331] "Means for detecting anomalies and notifying users" refers to devices or technologies that inform users of anomalies detected during system monitoring in the form of alerts or notifications.

[1332] This invention relates to an AI-powered smart solar power generation system that enhances the efficiency and safety of solar power generation systems. This system utilizes numerous sensors and real-time AI data analysis to automatically and optimally control the orientation, angle, and area of ​​solar panels. Furthermore, by incorporating an emotion engine that recognizes user emotions, it aims to improve user satisfaction.

[1333] Data collection

[1334] The server uses multiple sensors to measure the angle of the sun, light intensity (illuminance), weather information (sunny, cloudy, rainy, etc.), and wind speed. The data acquired from these sensors is transmitted to the server in real time. It also uses an emotion engine to collect user emotion data. The emotion engine analyzes the user's facial expressions and voice through input devices such as cameras and microphones to recognize the user's emotions.

[1335] Data analysis and control command generation

[1336] The server receives data collected from sensors and the emotion engine and analyzes it using an AI analysis module. Based on the data analysis, it calculates the optimal orientation, angle, and area of ​​solar panels for solar power generation. Furthermore, it takes user emotion data into consideration and performs solar panel placement and other system operations in a way that satisfies the user.

[1337] Specific example

[1338] For example, consider a scenario where strong winds of 15 m / s are predicted for 12:00 PM on a given day. In this case, a sensor sends wind speed data to a server. The server inputs this data into an AI analysis module, which then outputs an analysis result if strong winds are predicted. The server generates a protective command to position the panels horizontally and sends it to the terminal. The terminal receives this command, and the panel control module activates a motor to move the panels horizontally. Meanwhile, if the emotion engine recognizes that the user's stress level is high, the system takes action to provide the user with a relaxing environment (for example, by changing the panel position or adjusting the timing of notifications). This series of processes prevents damage to the panels due to strong winds, enhances safety, and improves user satisfaction.

[1339] Examples of prompt statements

[1340] Enter the following prompt into the generative AI model:

[1341] "Please explain how the AI ​​smart solar power system protects the panels when strong winds of 15 m / s are predicted. Also, please explain how the system responds when the user is under high stress."

[1342] Based on this prompt, the generated response will provide details on how the system collects and analyzes data, how it actually adjusts the panel, and how it responds based on user sentiment data.

[1343] The AI ​​smart solar power generation system of the present invention maximizes the efficiency and safety of solar power generation through the steps of data collection, data analysis, control command generation, panel adjustment, and condition monitoring, and further optimizes the system's operation while also taking into account the user's emotions.

[1344] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1345] Step 1: Data Collection

[1346] The server receives real-time data from numerous sensors regarding the angle of the sun, light intensity (illuminance), weather information (sunny, cloudy, rainy, etc.), and wind speed. Users provide emotional data through their cameras and microphones. An emotion engine analyzes the user's facial expressions and voice to generate emotional data. This data is the input data sent to the server. Specifically, the sensors measure data every minute and send it to the server.

[1347] Step 2: Data Analysis

[1348] The server receives data collected from sensors and the emotion engine. This data is preprocessed to ensure consistency and fill in any gaps. Next, the server inputs this preprocessed data into the AI ​​analysis module. The AI ​​analysis module analyzes the data to calculate the optimal orientation, angle, and area of ​​the solar panels. Furthermore, it generates control commands that will satisfy the user based on the user's emotion data. Specifically, the AI ​​analysis module inputs the dataset into a model and performs analysis using an optimization algorithm.

[1349] Step 3: Generation of control commands

[1350] The server assembles specific control commands to adjust the orientation, angle, and area of ​​the solar panels based on the analysis results from the AI ​​analysis module. These control commands determine the optimal placement and operation of the solar panels and also include protective commands against wind speed and weather fluctuations. For example, it generates commands such as, "If the wind speed is 15 m / s or higher, position the panels horizontally."

[1351] Step 4: Sending control commands

[1352] The server sends the generated control command to the terminal. The terminal receives this control command and prepares to control the panel according to the settings. Specifically, the server sends command data to the terminal via the network.

[1353] Step 5: Panel adjustment

[1354] The terminal receives control commands sent from the server and physically adjusts the orientation and angle of the solar panels based on them. It drives motors and actuators to move the panels to the optimal position. Specifically, the terminal executes a motor control program to tilt the panels horizontally.

[1355] Step 6: Status Monitoring

[1356] The server monitors the current status of the solar panels in real time and records the data. It also generates an alert and notifies the user if an anomaly is detected. The user can then take the necessary actions after receiving the notification. Specifically, the server periodically checks the panel's position, angle, power generation, etc., and sends email or application notifications if any anomalies are detected.

[1357] (Application Example 2)

[1358] 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".

[1359] Conventional solar power generation systems optimize power generation efficiency based solely on environmental data, without considering comprehensive energy management in logistics facilities or optimizing the emotional well-being of workers. Furthermore, irregular energy consumption in logistics centers often leads to employee stress and problems with the working environment. This presents a challenge: simultaneously improving energy efficiency and working conditions.

[1360] 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.

[1361] In this invention, the server includes means for measuring the angle of the sun, means for measuring light intensity, means for acquiring weather information, means for measuring wind speed, means for measuring the energy consumption of the logistics center, means for analyzing the emotions of employees, means for receiving and analyzing data acquired from each of the means, means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the data analysis, means for physically adjusting the solar panels based on the control commands, means for optimizing the energy consumption pattern of the logistics center, and means for optimizing the working environment of employees based on the results of the emotion analysis. This makes it possible to improve energy efficiency and optimize the working environment of employees in the logistics center.

[1362] "Means for measuring the angle of the sun" refers to devices and sensor sets used to measure the position and angle of the sun in real time.

[1363] "Means for measuring light intensity" refers to devices or sensors used to measure the amount of ambient light.

[1364] "Means for acquiring weather information" refers to means of communication with sensors and databases used to acquire weather conditions (sunny, cloudy, rainy, etc.).

[1365] "Means for measuring wind speed" refers to devices or sensors used to measure wind speed in real time.

[1366] "Means for measuring energy consumption in a logistics center" refers to devices and systems for measuring energy consumption within a logistics facility in real time.

[1367] "Methods for analyzing employee emotions" refer to systems and algorithms that analyze employees' facial expressions and voice data to recognize their emotional state.

[1368] "Means for receiving data acquired from each of the above means and analyzing the data" refers to devices or programs that receive data transmitted from sensors or devices and analyze that data using an AI analysis module.

[1369] "Means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the data analysis" refers to a system or program that generates commands to instruct the optimal settings of the solar panels based on the analysis results.

[1370] "Means for physically adjusting the solar panels based on the control command" refers to machines or devices that receive a control command and physically adjust the orientation and angle of the solar panels.

[1371] "Means for optimizing the energy consumption patterns of a logistics center" refers to systems and programs for efficiently managing and optimizing the energy consumption of a logistics center.

[1372] "Means for optimizing the working environment of employees based on the results of the aforementioned sentiment analysis" refers to systems or programs for improving the working environment by reflecting the results of the employee sentiment analysis.

[1373] This invention is a system for achieving energy management and optimization of the working environment in a logistics center. The detailed configuration and operation for carrying out this invention are described below.

[1374] Data collection

[1375] 1. Measuring the angle of the sun:

[1376] • Hardware used: Solar angle sensor

[1377] • Measures the position and angle of the sun in real time and transmits the data to the server.

[1378] 2. Measurement of light intensity:

[1379] • Hardware used: Light sensor

[1380] • Measures the amount of ambient light and sends the data to the server.

[1381] 3. Obtaining weather information:

[1382] • Hardware used: Weather sensor, Internet connection

[1383] • Acquire weather conditions in real time and send the data to the server.

[1384] 4. Measuring wind speed:

[1385] • Hardware used: Wind speed sensor

[1386] • Measure wind speed and send the data to the server.

[1387] 5. Measurement of energy consumption:

[1388] Hardware used: energy meter, RFID tag, GPS

[1389] • Collect energy consumption data within the logistics center and send it to the server.

[1390] 6. Emotion analysis:

[1391] • Hardware used: Camera, microphone

[1392] • Software used: Sentiment analysis engine (e.g., OpenCV)

[1393] • Analyzes employees' facial expressions and voices and sends emotional data to the server.

[1394] Data analysis and control command generation

[1395] 1. Data reception:

[1396] The server receives data from each sensor and emotion analysis engine.

[1397] 2. AI Analysis Module:

[1398] • Software used: TensorFlow, PyTorch

[1399] The server inputs the received data into the AI ​​analysis module to calculate the optimal orientation, angle, and area of ​​the solar panels.

[1400] • Calculate patterns to optimize energy consumption at the logistics center.

[1401] 3. Control command generation:

[1402] The server generates control commands based on the AI ​​analysis results.

[1403] • Transmits commands for physical adjustment of solar panels and optimization of energy consumption patterns.

[1404] • It also generates instructions to optimize the employee work environment based on emotional data.

[1405] Panel adjustment and energy management

[1406] 1. Panel adjustment:

[1407] Hardware used: Solar panel angle adjustment mechanism, motor

[1408] Based on control commands, the orientation and angle of the solar panels are physically adjusted.

[1409] 2. Energy Management:

[1410] • Software used: Energy Management System

[1411] • Optimize the energy consumption patterns of logistics centers in real time.

[1412] 3. Optimizing the working environment:

[1413] Hardware used: Lighting, air conditioning system

[1414] • Optimize the working environment for employees based on control commands.

[1415] Status Monitoring

[1416] 1. Monitoring:

[1417] The server constantly monitors the current status of each device.

[1418] 2. Anomaly detection:

[1419] • If an anomaly is detected, an alert will be generated and the user will be notified.

[1420] Specific example

[1421] 1. How to respond during strong winds:

[1422] • Hardware used: Wind speed sensor, solar panel angle adjustment mechanism

[1423] When the wind speed sensor measures 15 m / s, the server inputs the wind speed data into the AI ​​analysis module and generates commands to cope with strong winds. A command is issued to position the solar panels horizontally, and the motor moves the panels.

[1424] Example of a prompt:

[1425] 1. Environmental data collection:

[1426] "Collect light intensity data in real time from the sensor device during sunny conditions and transmit it to the data server."

[1427] 2. Emotion analysis:

[1428] "We analyze employees' facial images in real time to assess their stress levels."

[1429] 3. Control command generation:

[1430] "Protect the solar panels to a safe horizontal position, given the current wind speed of 15 m / s."

[1431] 4. Anomaly monitoring:

[1432] "Continuously monitor the panel status and issue an immediate alert if any abnormal values ​​are detected."

[1433] In this way, the system will perform panel adjustments, optimize energy consumption, and improve the working environment by collecting data from various sensors and analyzing it with AI.

[1434] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1435] Step 1:

[1436] Collect energy data

[1437] Inputs: Sun angle sensor, light sensor, weather sensor, wind speed sensor, energy meter, camera and microphone

[1438] The server collects data from the above sensors and devices in real time.

[1439] Output: Data from each sensor (sun angle, light intensity, weather information, wind speed, energy consumption, emotion data)

[1440] Specific operation: The server periodically receives data transmitted from sensors and saves it to local storage. In addition, the emotion engine analyzes employees' facial expressions and voices and saves their emotional state as data.

[1441] Step 2:

[1442] Preprocessing of data

[1443] Input: Raw data collected in Step 1

[1444] The server cleanses the raw data it collects, removing outliers and noise.

[1445] Output: Cleansed data

[1446] Specific operation: The server uses a database management system to format and normalize data, generating a clean dataset. For example, it filters out abnormal values ​​from temperature sensors (such as sudden fluctuations).

[1447] Step 3:

[1448] Data Analysis

[1449] Input: Clean data obtained in Step 2

[1450] The server uses AI analysis modules such as TensorFlow and PyTorch to analyze data and calculate the optimal settings for the orientation, angle, and area of ​​solar panels. It also analyzes energy consumption patterns and employee sentiment data to generate instructions for setting up the optimal work environment.

[1451] Output: Analysis results (optimal solar panel settings, energy consumption patterns, work environment settings)

[1452] Specific operation: Data is input into the AI ​​model, and the optimal numerical settings are calculated as a result of the analysis. For example, based on the angle of the sun at 3 PM, the panel angle is calculated to be 30 degrees. At the same time, if an employee is working for a long time, a command prompting them to take a break is generated.

[1453] Step 4:

[1454] Generation of control commands

[1455] Input: Analysis results obtained in Step 3

[1456] The server sends control commands to each sensor and device based on the analysis results.

[1457] Output: Control commands (adjustment of solar panel angle, change of energy consumption pattern, adjustment of working environment)

[1458] Specific operation: The server sends a control signal to the solar panel control unit, for example, "Adjust the panel to 30 degrees." At the same time, it sends a command to the lighting system to "Switch to an energy-saving mode."

[1459] Step 5:

[1460] Control implementation

[1461] Input: Control command from step 4

[1462] The terminal receives control commands and physically adjusts the orientation and angle of the solar panels. It also changes the settings of lighting and air conditioning systems.

[1463] Output: Actual adjustment results (orientation and angle of solar panels, changes in working environment)

[1464] Specific operation: The solar panel control unit drives a motor to adjust the panels to the specified angle. It also optimizes energy consumption and automatically switches between lighting and air conditioning.

[1465] Step 6:

[1466] Status Monitoring

[1467] Input: Real-time data from each source

[1468] The server constantly monitors the current status of each system and immediately generates an alert if an anomaly occurs.

[1469] Output: Anomaly detection alert, system log

[1470] Specific operation: The server monitors sensor data at regular intervals and detects abnormal values ​​(e.g., excessive temperature changes). If an abnormality is found, it sends an email or SMS notification to the administrator. It also logs all data.

[1471] 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.

[1472] 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.

[1473] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1474] 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.

[1475] 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.

[1476] 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.

[1477] 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.

[1478] 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.

[1479] 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."

[1480] 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.

[1481] 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.

[1482] 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.

[1483] 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.

[1484] 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.

[1485] 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.

[1486] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1487] 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.

[1488] 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.

[1489] 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.

[1490] 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.

[1491] 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.

[1492] The following is further disclosed regarding the embodiments described above.

[1493] (Claim 1)

[1494] A means of measuring the angle of the sun,

[1495] A means for measuring light intensity,

[1496] Means of obtaining weather information,

[1497] A means of measuring wind speed,

[1498] A means for receiving data acquired from each of the above means and analyzing the said data,

[1499] A means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the aforementioned data analysis,

[1500] Means for physically adjusting the solar panels based on the aforementioned control command,

[1501] A system that includes this.

[1502] (Claim 2)

[1503] The system according to claim 1, wherein the data analysis means calculates the optimal orientation, angle, and area of ​​the solar panel using an AI analysis module.

[1504] (Claim 3)

[1505] The system according to claim 1, wherein the control command generation means generates protective commands to move the panel horizontally in the event of strong winds and vertically in the event of snowfall.

[1506]

[1507] "Example 1"

[1508] (Claim 1)

[1509] A means of measuring the angle of the sun,

[1510] A means for measuring light intensity,

[1511] Means of obtaining weather information,

[1512] A means of measuring wind speed,

[1513] A means for receiving data acquired from each of the aforementioned means and storing it in a database,

[1514] Means including an AI analysis module for analyzing the aforementioned data,

[1515] A means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the aforementioned data analysis,

[1516] The means for physically adjusting the solar panel via a servo motor in response to the aforementioned control command,

[1517] A means of monitoring the current status of solar panels and notifying the user if an abnormality is detected,

[1518] A system that includes this.

[1519] (Claim 2)

[1520] The system according to claim 1, wherein the data analysis means calculates the optimal orientation, angle, and area of ​​the solar panel using a deep learning model.

[1521] (Claim 3)

[1522] The system according to claim 1, wherein the control command generation means generates a protective command to move the panel horizontally when the wind speed exceeds a certain value, and to move the panel vertically when snowfall is observed.

[1523] "Application Example 1"

[1524] (Claim 1)

[1525] A means of measuring the angle of the sun,

[1526] A means for measuring light intensity,

[1527] Means of obtaining weather information,

[1528] A means of measuring wind speed,

[1529] A means for receiving data acquired from each of the above means and analyzing the said data,

[1530] A means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the aforementioned data analysis,

[1531] Means for physically adjusting the solar panels based on the aforementioned control command,

[1532] A means of displaying results in real time on a smart device,

[1533] A means for the user to manually control the panel using voice commands or touch gestures,

[1534] A system that includes this.

[1535] (Claim 2)

[1536] The system according to claim 1, wherein the data analysis means calculates the optimal orientation, angle, and area of ​​the solar panel using an AI analysis module.

[1537] (Claim 3)

[1538] The system according to claim 1, wherein the control command generation means generates protective commands to move the panel horizontally in the event of strong winds and vertically in the event of snowfall.

[1539] "Example 2 of combining an emotion engine"

[1540] (Claim 1)

[1541] A means of measuring the angle of the sun,

[1542] A means for measuring light intensity,

[1543] Means of obtaining weather information,

[1544] A means of measuring wind speed,

[1545] A means of analyzing user emotions,

[1546] A means for receiving data acquired from each of the above means and analyzing the said data,

[1547] A means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the aforementioned data analysis,

[1548] Means for physically adjusting the solar panels based on the aforementioned control command,

[1549] means for monitoring the status of the solar panels,

[1550] A means of detecting anomalies and notifying the user,

[1551] A system that includes this.

[1552] (Claim 2)

[1553] The system according to claim 1, wherein the data analysis means uses an AI analysis module to calculate the optimal orientation, angle, and area of ​​the solar panel, and further generates control commands considering the user's emotional data.

[1554] (Claim 3)

[1555] The system according to claim 1, wherein the control command generation means generates protective commands to move the panel horizontally in strong winds and vertically in snowfall, and further provides a relaxing environment based on the user's emotions.

[1556] "Application example 2 when combining with an emotional engine"

[1557] (Claim 1)

[1558] A means of measuring the angle of the sun,

[1559] A means for measuring light intensity,

[1560] Means of obtaining weather information,

[1561] A means of measuring wind speed,

[1562] A means of measuring the energy consumption of a logistics center,

[1563] A means of analyzing employee emotions,

[1564] A means for receiving data acquired from each of the above means and analyzing the said data,

[1565] A means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the aforementioned data analysis,

[1566] Means for physically adjusting the solar panels based on the aforementioned control command,

[1567] A means to optimize the energy consumption patterns of a logistics center,

[1568] A means for optimizing the working environment of employees based on the results of the aforementioned emotion analysis,

[1569] A system that includes this.

[1570] (Claim 2)

[1571] The system according to claim 1, wherein the data analysis means calculates the optimal orientation, angle, and area of ​​the solar panel using an AI analysis module.

[1572] (Claim 3)

[1573] The system according to claim 1, wherein the control command generation means generates protective commands to move the panel horizontally in the event of strong winds and vertically in the event of snowfall. [Explanation of symbols]

[1574] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of measuring the angle of the sun, A means for measuring light intensity, Means of obtaining weather information, A means of measuring wind speed, A means for receiving data acquired from each of the above means and analyzing the said data, A means for generating control commands to optimally adjust the orientation, angle, and area of ​​the solar panels based on the results of the aforementioned data analysis, Means for physically adjusting the solar panels based on the aforementioned control command, A system that includes this.

2. The system according to claim 1, wherein the data analysis means calculates the optimal orientation, angle, and area of ​​the solar panel using an AI analysis module.

3. The system according to claim 1, wherein the control command generation means generates protective commands to move the panel horizontally in the event of strong winds and vertically in the event of snowfall.

Images