system

Abstract

We provide the system. [Solution] A data acquisition means for analyzing external environmental data acquired in real time and calculating optimal water environment conditions, Based on the analysis results, a control means for controlling the pool water temperature and associated equipment is provided, A display means for showing the current pool status and suggestions to the user, An anomaly detection means for detecting abnormal weather conditions and issuing warnings, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, 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 chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Due to recent global warming and increasing heatwaves, it has become difficult to provide a safe and comfortable water play environment. In particular, in families with small children and local communities, there is a need for water play facilities that can be used 365 days a year while managing the risks of temperature and ultraviolet rays. In addition, means to eliminate concerns about safety due to rapid weather changes and the accompanying activity restrictions are required.

Means for Solving the Problems

[0005] This invention provides a portable water play system that combines means for analyzing high-precision weather data and real-time environmental data. Based on the acquired data, AI optimizes the water environment conditions and automatically controls the cooling system and mist showers. Furthermore, it displays the latest pool conditions and safety suggestions to users, and ensures safety and comfort by predicting environmental changes. To achieve this, 5G communication technology is used to enable rapid data exchange and device control. Additionally, anomaly detection means issues alerts prompting a quick response to predicted rapid weather changes.

[0006] "Real-time external environmental data" refers to the latest weather information, such as temperature, humidity, UV index, and weather forecasts, which is continuously collected via the internet or dedicated sensors.

[0007] A "data acquisition method" is a component that has the function of taking in external environmental data into the system and recording and storing it in a format suitable for AI analysis.

[0008] "Analysis results" refer to the outcome of an AI algorithm processing external environmental data to generate specific outputs or suggestions, such as the optimal water temperature or the operation of necessary equipment.

[0009] A "control unit" is a unit that automatically adjusts the operation of pool facilities and associated equipment based on analysis results, and performs the function of maintaining an optimal water play environment.

[0010] A "display means" refers to a display or interface that visually shows the system's operating status and AI suggestions to the user, prompting them to take action as needed.

[0011] An "anomaly detection means" is a module that has the function of detecting conditions that deviate from standards based on collected environmental data and promptly issuing warnings.

[0012] A "predictive tool" is part of a system that analyzes past data and current trends, generates future predictions using AI, and has the function of preparing for potential environmental changes.

[0013] "Communication methods" refer to the part that utilizes the latest communication technologies, such as 5G, to enable rapid and highly reliable data exchange both inside and outside the system and to facilitate information transmission between devices. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0015] 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.

[0016] First, the language used in the following description will be explained.

[0017] In the following embodiments, the labeled 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.

[0018] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, the labeled 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, and the like.

[0020] 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).

[0021] 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."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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".

[0035] This invention constitutes a system that provides a comfortable and safe water environment by acquiring and analyzing environmental data in real time. Specific embodiments of this system are described below.

[0036] This system centers around servers, terminals, and users, and utilizes various data via the internet.

[0037] Data collection and analysis

[0038] The server periodically acquires external environmental data through weather APIs and environmental sensors. This data includes current temperature, humidity, UV index, and weather forecasts.

[0039] The collected data is analyzed in real time by an AI algorithm on the server to determine the optimal water temperature for the pool and the operating status of the equipment.

[0040] Control and environmental optimization

[0041] Based on the analysis results, the server determines whether the pool water temperature needs to be adjusted and whether the mist shower or cooling system needs to be activated. This control information is then transmitted to the terminal.

[0042] The terminal performs actual device control based on instructions received from the server. This automatically adjusts the environment within the pool under the configured conditions.

[0043] User interface and alerts

[0044] The terminal provides information to the user. It displays actual water temperature, UV index, and environmental suggestions from AI on its screen, allowing the user to understand the current pool environment at a glance.

[0045] Furthermore, if a sudden change in weather conditions is detected, the server immediately generates an alert, and the terminal notifies the user. This allows the user to take appropriate action at a safe time.

[0046] Specific example

[0047] For example, suppose it's a scorching hot day with an outside temperature of 35 degrees Celsius and a very high UV index. In this case, the server immediately instructs the cooling system to activate and issues a control command to the terminal to maintain the pool water temperature at 28 degrees Celsius. The terminal also activates a mist shower and begins spraying mist to block UV rays. The user can check the display on the terminal and manually adjust the mist intensity as needed.

[0048] Thus, the present invention has embodiments that provide a safe and comfortable water play environment at all times through real-time data management and AI control.

[0049] The following describes the processing flow.

[0050] Step 1:

[0051] The server retrieves external environmental data every five minutes from weather APIs and environmental sensors. This data includes current temperature, humidity, UV index, and short-term weather forecasts.

[0052] Step 2:

[0053] The server inputs the acquired data into its internal AI algorithm for analysis. This analysis aims to understand the trends in the collected data and evaluate what environmental changes can be predicted in the future.

[0054] Step 3:

[0055] Based on the analysis results generated by the AI ​​algorithm, the server creates environmental control commands for the pool. For example, if the outside temperature is high, it will activate the cooling system, and if the UV index is high, it will instruct the mist shower to operate.

[0056] Step 4:

[0057] Upon receiving environmental control commands from the server, the terminal executes the controls as instructed. This includes operations such as turning specific devices on / off and initiating cooling to maintain a constant water temperature.

[0058] Step 5:

[0059] The device displays the current pool status and AI-generated suggestions to the user on its screen. Based on this information, the user can fine-tune the settings as needed.

[0060] Step 6:

[0061] If the environment goes outside of safe ranges or if severe weather changes are predicted, the server will immediately generate an anomaly alert. This will warn of danger in advance and prompt appropriate action.

[0062] Step 7:

[0063] The device notifies the user of the generated alert via voice or screen display. Based on this, the user takes safety actions such as interrupting water activities.

[0064] (Example 1)

[0065] 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."

[0066] In today's rapidly changing climate and with diverse user comfort requirements, there is a need to optimize water environments such as swimming pools in real time to ensure safe and comfortable use. However, existing systems suffer from insufficient accuracy in data collection and analysis, as well as rapid and effective device control, resulting in a lack of responsiveness to environmental changes.

[0067] 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.

[0068] In this invention, the server includes information acquisition means for analyzing weather and environmental information acquired in real time and calculating optimal water environment conditions, control means for controlling water temperature and related equipment based on the analysis results, and information provision means for displaying the current water environment state and environmental adjustment suggestions to the user. This makes it possible to respond to rapid weather changes and always provide a safe and comfortable water environment.

[0069] "Real-time" means that the current situation is reflected immediately, and data acquisition, analysis, and control are performed without delay.

[0070] "Weather information" refers to data related to weather and atmospheric conditions, such as temperature, humidity, UV index, and weather forecasts.

[0071] "Environmental information" refers to physical data measured within a specific environment or facility, including pool water temperature and surrounding humidity.

[0072] "Information acquisition means" refers to a method or apparatus for collecting and analyzing external weather information and physical environmental information.

[0073] "Control means" refers to a method or device for appropriately adjusting the operation of equipment or devices based on analyzed data.

[0074] "Information provision means" refers to a method or device for conveying information and suggestions analyzed by the system to the user.

[0075] An "artificial intelligence algorithm" is a computational method that uses machine learning and data analysis techniques to extract patterns from large amounts of data and make predictions and judgments.

[0076] A "predictive means" is a method or apparatus for estimating future environmental conditions based on past data and taking necessary countermeasures in advance.

[0077] "Efficient communication means" refers to a method or device that utilizes high-speed and reliable communication technology to rapidly transmit data and enable immediate control of equipment.

[0078] A "warning generation means" is a method or device for providing appropriate warnings to users when the system detects an abnormal or dangerous situation.

[0079] This system is designed to provide a comfortable and safe water environment and functions through the interaction of servers, terminals, and users.

[0080] First, the server acquires weather and environmental information in real time from weather APIs and environmental sensors. This allows it to collect data such as temperature, humidity, UV index, and weather forecasts. The server analyzes this data using artificial intelligence algorithms to determine the optimal pool environment. Machine learning models are used for the analysis, and past trends are used to predict future environmental changes.

[0081] Next, instructions are sent from the server to the terminal. The terminal controls the pool equipment based on the instructions received from the server. Specifically, it adjusts the operation of the cooling system and mist showers to maintain optimal water temperature and surrounding environment. Furthermore, the terminal's display shows current water environment data and AI-generated environmental suggestions, allowing the user to understand the pool's condition in real time.

[0082] Users can view information provided through the device's display and manually adjust the environment as needed. For example, on extremely hot days, they can adjust the intensity of the mist shower.

[0083] As a specific example, on extremely hot days, the server detects that the acquired outside temperature is 35 degrees Celsius and the UV index is high, instructs the cooling system to operate, and sends a control command to the terminal to maintain the pool water temperature at 28 degrees Celsius. The terminal also sprays mist, and the user can check the situation on the display and adjust the mist intensity. This ensures a comfortable and safe water environment at all times.

[0084] As an example of a prompt, the following could be input into the generating AI model: "On a scorching hot day with a temperature of 35 degrees Celsius and a high UV index, what controls are necessary to provide a safe and comfortable environment for the swimming pool?"

[0085] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0086] Step 1:

[0087] The server acquires data in real time from weather APIs and environmental sensors. Inputs include weather information (temperature, humidity, UV index, weather forecast) and pool environment sensor information (water temperature, ambient humidity). Output is a single dataset containing this information. Specifically, the server periodically calls the APIs, collects the acquired data, and stores it in the database.

[0088] Step 2:

[0089] The server performs analysis based on the acquired dataset. The input is the dataset obtained in Step 1. The server uses an artificial intelligence algorithm to analyze the data and calculate the optimal water environment conditions. The output is specific control parameters (water temperature setting, whether or not the mist shower is activated). Specifically, it compares the current data with past data to find patterns and determine the optimal control.

[0090] Step 3:

[0091] The server sends control commands to the terminal based on the analysis results. The input is the control parameters obtained in step 2. The output is the specific control command that reaches the terminal (for example, a command to maintain the water temperature at 28 degrees). In terms of actual operation, the server sends this command to the terminal via the communication network and performs immediate control.

[0092] Step 4:

[0093] The terminal controls the pool equipment based on control commands received from the server. The input is the control command from the server. The output is the actual operating status of the equipment (startup of the cooling system, operation of the mist shower). Specifically, the terminal operates the equipment's actuators through an electronic control unit to adjust the set temperature and the amount of mist sprayed.

[0094] Step 5:

[0095] The terminal displays the current pool environment status and AI-generated suggestions on its screen, providing information to the user. Inputs include data provided by the server and real-time sensor information. Outputs are visual information for the user (environmental data and suggestions displayed on the screen). Specifically, the terminal displays this information using a user-friendly GUI, providing an interface that the user can interact with.

[0096] Step 6:

[0097] The user manually adjusts the environment as needed, based on the information displayed on the device's screen. The input is the information displayed on the device (e.g., current water temperature and suggested adjustments). The output is the user's adjustment actions (e.g., changing the intensity of the mist shower). Specifically, the user adjusts the environment settings through the display's touch panel or buttons.

[0098] (Application Example 1)

[0099] 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."

[0100] Maintaining a comfortable environment is a crucial challenge in many facilities. Shopping centers and public facilities, in particular, attract large crowds, leading to rapidly changing environmental conditions. Therefore, real-time analysis of environmental data and maintenance of an optimal environment are essential. However, conventional systems often struggle to respond immediately to environmental changes, failing to provide optimal comfort and safety. To address this challenge, a system capable of efficient, real-time environmental control is necessary.

[0101] 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.

[0102] In this invention, the server includes data acquisition means for analyzing external environmental data acquired in real time and calculating optimal environmental conditions, control means for controlling the temperature and related equipment within the facility based on the analysis results, and analysis means for analyzing pedestrian flow data and providing optimal environmental settings according to the degree of congestion. This makes it possible to maintain optimal comfort within the facility and provide high satisfaction to users even when environmental conditions change rapidly.

[0103] "Real-time external environmental data" refers to data obtained in real time from external environmental conditions such as temperature, humidity, weather, and UV index, for analysis.

[0104] "Calculating optimal environmental conditions" means analyzing acquired environmental data to determine the ideal temperature, humidity, lighting intensity, etc., within the facility.

[0105] "Data acquisition means" refers to devices or software such as sensors or APIs used to collect environmental data.

[0106] A "control system" is a system that operates air conditioning equipment and other related devices to adjust temperature, humidity, etc., based on the analyzed data.

[0107] "Analyzing pedestrian flow data" means analyzing the number and movements of users within a facility to understand the level of congestion.

[0108] "Analysis means for providing optimal environmental settings according to the degree of congestion" refers to a device or software that evaluates the congestion status within a facility based on pedestrian flow data and calculates corresponding environmental conditions.

[0109] The system designed to realize this application aims to provide an optimal facility environment by analyzing real-time environmental data acquired by sensors on a server. The server primarily uses AWS® IoT Core and Google® Cloud IoT to collect environmental data. The collected data is processed in real time by AWS Lambda and Google Cloud Functions.

[0110] The server analyzes temperature, humidity, and pedestrian flow indicators from the acquired data to calculate the optimal environmental settings. Through integration with AWS Greengrass, it automatically adjusts air conditioning and other environmental control devices. 5G communication technology is used for this process to ensure low latency and high reliability.

[0111] Users can check environmental information through smart devices or displays within the facility. The server visualizes the acquired data and provides the information using Amazon S3 and Google Cloud Storage. Notifications are sent using Twilio and Firebase Cloud Messaging in response to sudden changes in weather conditions or congestion levels.

[0112] As a concrete example, in a commercial facility during the height of summer, if a server detects that the outside temperature exceeds 35 degrees Celsius, it automatically adjusts the cooling system to maintain a comfortable indoor temperature. This allows users to continue shopping in a comfortable environment. An example of a prompt for the generating AI model might be, "Please propose the data analysis algorithms necessary to develop a real-time environmental management system for shopping facilities."

[0113] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0114] Step 1:

[0115] The server uses AWS IoT Core or Google Cloud IoT to receive data acquired from environmental sensors in real time. The inputs are temperature, humidity, and pedestrian flow data, which the server receives. The received data is then initially processed by AWS Lambda or Google Cloud Functions and converted into an analyzable format.

[0116] Step 2:

[0117] The server uses AI algorithms running on AWS Lambda or Google Cloud Functions to analyze incoming environmental data. The input is data from environmental sensors. This AI algorithm calculates optimal environmental conditions and outputs indicators for temperature, humidity, and congestion management within the facility.

[0118] Step 3:

[0119] The server sends commands to the facility's air conditioning system and other control devices via AWS Greengrass. The input is the analysis result of the AI ​​algorithm, and the output is specific operation commands to the control devices. Environmental control devices such as air conditioning and lighting equipment are automatically and optimally adjusted.

[0120] Step 4:

[0121] The terminal receives information from the server and displays current environmental information on displays and smart devices within the facility. Input is environmental information and warning alerts sent from the server, and output is information displayed to the user. The display shows temperature, humidity, and suggestions for optimal environmental settings.

[0122] Step 5:

[0123] The server uses Twilio and Firebase Cloud Messaging to send notifications to users when it detects extreme weather or rapid environmental changes. The input is information about rapid changes in environmental data, and the output is an alert notification sent to the user. This allows users to take necessary actions quickly.

[0124] 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.

[0125] This invention is a system that provides a comfortable and safe water environment by acquiring and analyzing environmental data in real time and integrating it with emotion recognition technology. Specific embodiments of this system are described below.

[0126] This system is built around servers, terminals, and users, and not only optimizes the water environment using external environmental data, but also provides an experience that responds to the user's emotions.

[0127] Data collection and analysis

[0128] The server periodically acquires external environmental data via weather APIs and environmental sensors. It also utilizes an emotion engine to monitor the user's facial expressions and movements through the device's camera and sensors, and collects emotional data.

[0129] The AI ​​algorithm simultaneously analyzes this data to calculate the conditions for optimizing the pool environment and the interactions that respond to the user's emotions.

[0130] Environmental control and emotional response

[0131] Based on the analysis results, the server generates basic environmental commands such as pool water temperature and mist showers. It also generates commands to adjust effects such as lighting and music based on the user's emotions.

[0132] The terminal receives these commands and operates physical devices and performance equipment to provide a water environment and experience that the user finds comfortable.

[0133] User interface and alerts

[0134] The device displays the current status of the pool, as well as suggestions from the AI ​​and emotion engines. This allows users to intuitively receive suggestions tailored to the environment and their own emotions.

[0135] If a sudden change in environmental or emotional data is detected, the server generates an alert, and the terminal quickly notifies the user.

[0136] Specific example

[0137] For example, if the outside temperature is 30 degrees Celsius and the user is smiling and relaxed, the system will activate the cooling system to maintain the water temperature at a comfortable 28 degrees Celsius. It will also individually adjust soothing music and comfortable lighting to create an environment that helps maintain the user's relaxed state. If the system detects that the user is stressed, it can further adjust the environment and change to a calming, relaxing atmosphere to alleviate tension.

[0138] Thus, the present invention has embodiments that provide a customized water play experience tailored to individual users by combining real-time data management with AI and emotion recognition technology.

[0139] The following describes the processing flow.

[0140] Step 1:

[0141] The server collects external environmental data every five minutes from weather APIs and environmental sensors. This data includes temperature, humidity, UV index, and weather forecasts. It also receives user facial expression data transmitted from the device.

[0142] Step 2:

[0143] The device uses its built-in camera and sensors to monitor the user's facial expressions and movements, and transmits the data to an emotion engine in real time. This emotion data is used to estimate the user's level of happiness, tension, stress, and other factors.

[0144] Step 3:

[0145] The server inputs environmental and emotional data into an AI algorithm for analysis. The analysis results in the calculation of optimal water environment and performance settings based on necessary emotions. Historical data is also referenced to improve prediction accuracy.

[0146] Step 4:

[0147] Based on the analysis results, the server generates commands to adjust the pool water temperature and activate the mist shower. At the same time, it also determines music and lighting settings that correspond to the user's emotions and sends control commands, including these settings, to the terminal.

[0148] Step 5:

[0149] The terminal receives commands and controls the actual equipment. This includes adjusting water temperature, turning mist on / off, changing lighting color and brightness, and selecting and playing music. This provides the user with an optimal user experience.

[0150] Step 6:

[0151] The device displays the current pool environment, AI suggestions, and advice based on the user's emotions in its user interface. Based on this information, the user can further manually adjust the environment settings to their liking.

[0152] Step 7:

[0153] If anomalies or sudden changes occur in environmental or emotional data, the server immediately generates an alert. The terminal notifies the user of this alert via voice or screen display, prompting them to take necessary corrective action.

[0154] (Example 2)

[0155] 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".

[0156] In aquatic environments such as swimming pools, there is a need to accurately grasp the external environment and the emotional state of users in real time and instantly provide comfortable and safe conditions. However, conventional systems have difficulty effectively utilizing this data and providing appropriate interactions tailored to users. In particular, the detection of abnormal weather conditions, which require immediate response, and the insufficient response to individual emotional needs are major challenges.

[0157] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0158] In this invention, the server includes information acquisition means for analyzing environmental information acquired using external input to derive optimal water environment conditions, analysis means for analyzing the user's actions and facial expressions using emotion analysis technology based on the collected data, and control means for controlling water temperature and environmental settings and providing interactive effects that respond to emotions based on the analysis results. This makes it possible to provide a comfortable and safe water environment optimized for the user in real time.

[0159] "External input" refers to data obtained from external sources, and is a concept that includes weather data and information obtained from environmental monitoring systems.

[0160] "Environmental information" refers to data that reflects the external natural environment and the conditions within the facility, and includes information such as temperature, humidity, and light intensity.

[0161] "Information acquisition means" refers to a device or system that has the function of collecting data from the external environment.

[0162] "Emotional analysis technology" refers to algorithms and system technologies that analyze a user's facial expressions and actions to determine their emotional state.

[0163] "Analysis means" refers to an apparatus or method for performing an analysis based on collected data and deriving a specific result.

[0164] "Control means" refers to mechanisms or systems used to adjust environmental settings and the operation of devices based on the results of analysis.

[0165] "Interactive effects" refer to a system that provides lighting and music effects that automatically change settings in response to the user's emotions and actions.

[0166] This invention is a system that analyzes real-time environmental information and the emotional state of users, and based on this analysis, provides a comfortable and safe water environment. The system is composed of a server, terminals, and users as its core components.

[0167] The server is responsible for analyzing environmental information acquired from external sources. It obtains data from weather APIs and various sensors, and utilizes Python®-based machine learning algorithms to analyze it. This allows it to analyze current environmental conditions and generate information to provide an optimized water environment. Furthermore, the server uses cameras and sensors installed on the terminal to collect data on the user's facial expressions and movements, and analyzes this data using emotion analysis technology.

[0168] The terminal receives commands from the server and controls the actual equipment and effects. Specifically, it operates the water temperature control system, controls the mist shower, and sets the lighting and sound. The terminal also provides the user with visual information about the current situation and AI-generated suggestions through its display. This allows the user to intuitively understand changes in the environment in real time and enjoy an experience that responds to their emotions.

[0169] For users, this system guarantees a comfortable water play experience. For example, if the outside temperature is very high and the system determines that the user is relaxed, it will adjust the pool water temperature to a comfortable level and play relaxing music. Conversely, if the system detects that the user is stressed, it will further adjust the system to provide a more calming environment.

[0170] An example of a prompt sentence to be input to the generating AI model is, "Please tell me how to adjust the water environment to be suitable when the user is relaxed at a high temperature." In this way, the present invention aims to maximize the user experience by utilizing real-time data analysis.

[0171] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0172] Step 1:

[0173] The server acquires external environmental information. It receives data on temperature, humidity, and precipitation from weather APIs and surrounding sensors as input. This data is collected and compiled into a JSON-formatted dataset for processing. The output is real-time data of the external environment. Specifically, the server periodically sends API requests to obtain the latest weather information.

[0174] Step 2:

[0175] The server collects user emotion data from the terminal. As input, the terminal captures the user's face and gestures using its camera and motion sensors. Based on this, an emotion analysis model analyzes the image data and estimates the user's emotional state from their facial expressions and movements. The output is the analysis result indicating the user's emotional state. Specifically, the terminal's camera periodically sends images to the server, and the server activates the emotion analysis engine to process them.

[0176] Step 3:

[0177] The server uses an AI algorithm to analyze acquired environmental data and user emotion data. It receives weather data and emotion data as input and processes them into an analysis model. Data processing maps the relationship between environment and emotion to calculate optimal conditions for the water environment. The output consists of optimization conditions and performance instructions. Specifically, the server initiates a machine learning analysis process to calculate appropriate water temperature settings and performance plans.

[0178] Step 4:

[0179] The server generates control commands based on the analysis results and sends them to the terminal. The input consists of optimization conditions generated by an AI algorithm. Data calculations determine specific water temperature settings, mist shower on / off settings, lighting color, and music selection. The output is a specific control command. In terms of operation, the server sends commands to the terminal via the cloud, and the terminal activates the control system.

[0180] Step 5:

[0181] The terminal executes commands received from the server and adjusts the physical environment. The input is control commands from the server. Specific actions include operating a water temperature control device to set the water temperature, adjusting the mist shower output, and appropriately setting lighting and sound equipment. The output is the altered environmental conditions and effects.

[0182] Step 6:

[0183] Users view the current situation and suggestions through the device's display. The input consists of visually provided current information and analytical suggestions from the device. This allows users to receive appropriate interactions tailored to their environment and emotions. Specifically, the display shows things like temperature, emotion analysis results, and suggested actions.

[0184] Step 7:

[0185] The server generates an alarm when it detects an anomaly and notifies the user via the terminal. Inputs include rapid changes in environmental data and anomalies in emotional data. A detection algorithm analyzes the situation and creates an alarm as needed. The output is the alarm notification. Specifically, the server identifies the anomaly event, and the terminal presents the alert message to the user.

[0186] (Application Example 2)

[0187] 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".

[0188] Providing visitors with a personalized and comfortable experience in current commercial and entertainment facilities is challenging. In particular, there is no established method for reflecting visitors' emotional states in real time and adjusting the environment accordingly. Furthermore, there is a need for a system that integrates various external conditions and visitors' emotions to intuitively improve the experience.

[0189] 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.

[0190] In this invention, the server includes data acquisition means for analyzing external environmental information acquired in real time and calculating optimal base conditions; control means for controlling liquid temperature and associated equipment based on the analysis results; display means for displaying the current facility status and suggestions to the user; anomaly detection means for detecting abnormal external conditions and issuing warnings; emotion recognition means for understanding the user's emotional state and adjusting the environmental presentation; and environmental presentation control means for adjusting lighting and sound to provide an individualized experience. This makes it possible to provide each visitor with an optimal experience tailored to their emotions and environment in real time.

[0191] "External environmental information" refers to data on natural conditions obtained from outside the facility, such as weather data, ambient temperature, humidity, and illuminance.

[0192] "Basic conditions" refer to the fundamental and optimal physical conditions for providing a comfortable experience within a facility, calculated using external environmental information.

[0193] "Data acquisition means" refers to a combination of hardware and software for collecting external environmental information and user sentiment data in real time.

[0194] A "control means" is a mechanism for optimally operating ancillary equipment such as temperature control and sound systems within a facility, based on the analysis results.

[0195] "Display means" refers to devices or interfaces that visually show users the current status of a facility or the proposed experience.

[0196] An "anomaly detection system" is a system that identifies external conditions that differ from normal conditions and issues a warning as necessary.

[0197] "Emotion recognition means" refers to technology that analyzes a user's facial expressions and movements and evaluates their emotional state in real time.

[0198] "Environmental design control means" refers to a method for providing an optimal environment by adjusting design elements such as lighting and sound according to the user's emotions and the conditions within the facility.

[0199] The system for implementing this invention consists of multiple modules and has the capability to perform real-time analysis of environmental and emotional data. The server acquires data from weather APIs and environmental sensors to obtain external environmental information, and collects emotional data through the terminal's camera and sensors to understand the user's emotional state. This data is analyzed by an AI algorithm to provide information necessary to adjust the basic conditions within the facility.

[0200] The server generates control commands to operate lighting and sound equipment within the facility using the analysis results. For this purpose, data processing is performed using the Python language, and TENSORFLOW® handles emotion analysis. External information processing is also performed using AWS cloud services. Terminals receive these control commands and intuitively control devices within the facility.

[0201] For example, when a user visits the welcome zone in a shopping mall, if they are in a relaxed state, the system will provide calming lighting and music. Conversely, if they are in a cheerful state, it can provide bright lighting and lively music.

[0202] By using generative AI models, real-time adjustments can be made to enhance the user experience. An example of a prompt might be: "Please tell me how to analyze a visitor's face, identify their fatigue and well-being levels, and then adjust the environment (music, lighting) within the commercial facility in real time to match those levels."

[0203] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0204] Step 1:

[0205] The server acquires external environmental information from weather APIs and environmental sensors. Inputs are weather data and sensor values ​​from the APIs, and outputs are integrated external environmental information. This process involves receiving data and performing data format conversion for integration.

[0206] Step 2:

[0207] The device captures the user's facial expression data in real time through its camera and sensors. The input is camera footage, and the output is facial expression features obtained through image processing. A facial recognition module is used to extract emotional features.

[0208] Step 3:

[0209] The server uses TensorFlow to analyze acquired emotion features and identify the user's emotional state. The input is facial expression features, and the output is the user's emotional state. It prompts a generative AI model to perform data calculations to predict the emotional state.

[0210] Step 4:

[0211] The server calculates the optimal environmental conditions within the facility based on acquired external environmental information and the user's emotional state. The inputs are external environmental information and emotional state, and the output is control commands. An AI algorithm is used to generate adjustment parameters for lighting and music.

[0212] Step 5:

[0213] The server sends control commands to the terminal, initiating control of the physical device. The input is the control command, and the output is the control status of the field equipment. The terminal adjusts the lighting and sound systems based on the received commands.

[0214] Step 6:

[0215] Users experience altered facility environments. The input is the modified environmental conditions, and the output is the user's reaction to that experience. Ultimately, it serves as a means of monitoring how environmental changes affect the user's emotional state.

[0216] 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.

[0217] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0218] 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.

[0219] [Second Embodiment]

[0220] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0221] 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.

[0222] 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).

[0223] 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.

[0224] 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.

[0225] 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).

[0226] 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.

[0227] 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.

[0228] 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.

[0229] 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.

[0230] 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.

[0231] 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".

[0232] This invention constitutes a system that provides a comfortable and safe water environment by acquiring and analyzing environmental data in real time. Specific embodiments of this system are described below.

[0233] This system centers around servers, terminals, and users, and utilizes various data via the internet.

[0234] Data collection and analysis

[0235] The server periodically acquires external environmental data through weather APIs and environmental sensors. This data includes current temperature, humidity, UV index, and weather forecasts.

[0236] The collected data is analyzed in real time by an AI algorithm on the server to determine the optimal water temperature for the pool and the operating status of the equipment.

[0237] Control and environmental optimization

[0238] Based on the analysis results, the server determines whether the pool water temperature needs to be adjusted and whether the mist shower or cooling system needs to be activated. This control information is then transmitted to the terminal.

[0239] The terminal performs actual device control based on instructions received from the server. This automatically adjusts the environment within the pool under the configured conditions.

[0240] User interface and alerts

[0241] The terminal provides information to the user. It displays actual water temperature, UV index, and environmental suggestions from AI on its screen, allowing the user to understand the current pool environment at a glance.

[0242] Furthermore, if a sudden change in weather conditions is detected, the server immediately generates an alert, and the terminal notifies the user. This allows the user to take appropriate action at a safe time.

[0243] Specific example

[0244] For example, suppose it's a scorching hot day with an outside temperature of 35 degrees Celsius and a very high UV index. In this case, the server immediately instructs the cooling system to activate and issues a control command to the terminal to maintain the pool water temperature at 28 degrees Celsius. The terminal also activates a mist shower and begins spraying mist to block UV rays. The user can check the display on the terminal and manually adjust the mist intensity as needed.

[0245] Thus, the present invention has embodiments that provide a safe and comfortable water play environment at all times through real-time data management and AI control.

[0246] The following describes the processing flow.

[0247] Step 1:

[0248] The server retrieves external environmental data every five minutes from weather APIs and environmental sensors. This data includes current temperature, humidity, UV index, and short-term weather forecasts.

[0249] Step 2:

[0250] The server inputs the acquired data into its internal AI algorithm for analysis. This analysis aims to understand the trends in the collected data and evaluate what environmental changes can be predicted in the future.

[0251] Step 3:

[0252] Based on the analysis results generated by the AI ​​algorithm, the server creates environmental control commands for the pool. For example, if the outside temperature is high, it will activate the cooling system, and if the UV index is high, it will instruct the mist shower to operate.

[0253] Step 4:

[0254] Upon receiving environmental control commands from the server, the terminal executes the controls as instructed. This includes operations such as turning specific devices on / off and initiating cooling to maintain a constant water temperature.

[0255] Step 5:

[0256] The device displays the current pool status and AI-generated suggestions to the user on its screen. Based on this information, the user can fine-tune the settings as needed.

[0257] Step 6:

[0258] If the environment goes outside of safe ranges or if severe weather changes are predicted, the server will immediately generate an anomaly alert. This will warn of danger in advance and prompt appropriate action.

[0259] Step 7:

[0260] The device notifies the user of the generated alert via voice or screen display. Based on this, the user takes safety actions such as interrupting water activities.

[0261] (Example 1)

[0262] 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."

[0263] In today's rapidly changing climate and with diverse user comfort requirements, there is a need to optimize water environments such as swimming pools in real time to ensure safe and comfortable use. However, existing systems suffer from insufficient accuracy in data collection and analysis, as well as rapid and effective device control, resulting in a lack of responsiveness to environmental changes.

[0264] 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.

[0265] In this invention, the server includes information acquisition means for analyzing weather and environmental information acquired in real time and calculating optimal water environment conditions, control means for controlling water temperature and related equipment based on the analysis results, and information provision means for displaying the current water environment state and environmental adjustment suggestions to the user. This makes it possible to respond to rapid weather changes and always provide a safe and comfortable water environment.

[0266] "Real-time" means that the current situation is reflected immediately, and data acquisition, analysis, and control are performed without delay.

[0267] "Weather information" refers to data related to weather and atmospheric conditions, such as temperature, humidity, UV index, and weather forecasts.

[0268] "Environmental information" refers to physical data measured within a specific environment or facility, including pool water temperature and surrounding humidity.

[0269] "Information acquisition means" refers to a method or apparatus for collecting and analyzing external weather information and physical environmental information.

[0270] "Control means" refers to a method or device for appropriately adjusting the operation of equipment or devices based on analyzed data.

[0271] "Information provision means" refers to a method or device for conveying information and suggestions analyzed by the system to the user.

[0272] An "artificial intelligence algorithm" is a computational method that uses machine learning and data analysis techniques to extract patterns from large amounts of data and make predictions and judgments.

[0273] A "predictive means" is a method or apparatus for estimating future environmental conditions based on past data and taking necessary countermeasures in advance.

[0274] "Efficient communication means" refers to a method or device that utilizes high-speed and reliable communication technology to rapidly transmit data and enable immediate control of equipment.

[0275] A "warning generation means" is a method or device for providing appropriate warnings to users when the system detects an abnormal or dangerous situation.

[0276] This system is designed to provide a comfortable and safe water environment and functions through the interaction of servers, terminals, and users.

[0277] First, the server acquires weather and environmental information in real time from weather APIs and environmental sensors. This allows it to collect data such as temperature, humidity, UV index, and weather forecasts. The server analyzes this data using artificial intelligence algorithms to determine the optimal pool environment. Machine learning models are used for the analysis, and past trends are used to predict future environmental changes.

[0278] Next, instructions are sent from the server to the terminal. The terminal controls the pool equipment based on the instructions received from the server. Specifically, it adjusts the operation of the cooling system and mist showers to maintain optimal water temperature and surrounding environment. Furthermore, the terminal's display shows current water environment data and AI-generated environmental suggestions, allowing the user to understand the pool's condition in real time.

[0279] Users can view information provided through the device's display and manually adjust the environment as needed. For example, on extremely hot days, they can adjust the intensity of the mist shower.

[0280] As a specific example, on extremely hot days, the server detects that the acquired outside temperature is 35 degrees Celsius and the UV index is high, instructs the cooling system to operate, and sends a control command to the terminal to maintain the pool water temperature at 28 degrees Celsius. The terminal also sprays mist, and the user can check the situation on the display and adjust the mist intensity. This ensures a comfortable and safe water environment at all times.

[0281] As an example of a prompt, the following could be input into the generating AI model: "On a scorching hot day with a temperature of 35 degrees Celsius and a high UV index, what controls are necessary to provide a safe and comfortable environment for the swimming pool?"

[0282] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0283] Step 1:

[0284] The server retrieves data in real time from the weather API and environmental sensors. The inputs are weather information (temperature, humidity, UV index, weather forecast) and pool environment sensor information (water temperature, ambient humidity). The output is these pieces of information organized into a single dataset. As a specific operation, the server periodically calls the API, collects the retrieved data, and stores it in the database.

[0285] Step 2:

[0286] The server performs analysis based on the retrieved dataset. The input is the dataset obtained in Step 1. The server uses artificial intelligence algorithms to analyze the data and calculate the optimal water environment conditions. The output is specific control parameters (water temperature setting, operation of the mist shower). Specifically, it compares with past data, finds patterns, and determines the optimal control.

[0287] Step 3:

[0288] The server sends a control command to the terminal based on the analysis result. The input is the control parameters obtained in Step 2. The output is a specific control command that reaches the terminal (for example, a command to maintain the water temperature at 28 degrees). As a specific operation, the server sends this command to the terminal via the communication network for immediate control.

[0289] Step 4:

[0290] The terminal controls the pool facilities based on the control command received from the server. The input is the control command from the server. The output is the actual operating status of the facilities (activation of the cooling system, operation of the mist shower). Specifically, the terminal operates the actuators of the facilities through an electronic control device to adjust the set temperature and the amount of mist sprayed.

[0291] Step 5:

[0292] The terminal displays the current pool environment status and AI-generated suggestions on its screen, providing information to the user. Inputs include data provided by the server and real-time sensor information. Outputs are visual information for the user (environmental data and suggestions displayed on the screen). Specifically, the terminal displays this information using a user-friendly GUI, providing an interface that the user can interact with.

[0293] Step 6:

[0294] The user manually adjusts the environment as needed, based on the information displayed on the device's screen. The input is the information displayed on the device (e.g., current water temperature and suggested adjustments). The output is the user's adjustment actions (e.g., changing the intensity of the mist shower). Specifically, the user adjusts the environment settings through the display's touch panel or buttons.

[0295] (Application Example 1)

[0296] 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."

[0297] Maintaining a comfortable environment is a crucial challenge in many facilities. Shopping centers and public facilities, in particular, attract large crowds, leading to rapidly changing environmental conditions. Therefore, real-time analysis of environmental data and maintenance of an optimal environment are essential. However, conventional systems often struggle to respond immediately to environmental changes, failing to provide optimal comfort and safety. To address this challenge, a system capable of efficient, real-time environmental control is necessary.

[0298] 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.

[0299] In this invention, the server includes data acquisition means for analyzing external environmental data acquired in real time and calculating optimal environmental conditions, control means for controlling the temperature and related equipment within the facility based on the analysis results, and analysis means for analyzing pedestrian flow data and providing optimal environmental settings according to the degree of congestion. This makes it possible to maintain optimal comfort within the facility and provide high satisfaction to users even when environmental conditions change rapidly.

[0300] "Real-time external environmental data" refers to data obtained in real time from external environmental conditions such as temperature, humidity, weather, and UV index, for analysis.

[0301] "Calculating optimal environmental conditions" means analyzing acquired environmental data to determine the ideal temperature, humidity, lighting intensity, etc., within the facility.

[0302] "Data acquisition means" refers to devices or software such as sensors or APIs used to collect environmental data.

[0303] A "control system" is a system that operates air conditioning equipment and other related devices to adjust temperature, humidity, etc., based on the analyzed data.

[0304] "Analyzing pedestrian flow data" means analyzing the number and movements of users within a facility to understand the level of congestion.

[0305] "Analysis means for providing optimal environmental settings according to the degree of congestion" refers to a device or software that evaluates the congestion status within a facility based on pedestrian flow data and calculates corresponding environmental conditions.

[0306] The system for realizing this application example aims to analyze real-time environmental data acquired by sensors on a server and provide an optimal in-facility environment. The server mainly uses AWS IoT Core or Google Cloud IoT to collect environmental data. The collected data is processed in real time by AWS Lambda or Google Cloud Functions.

[0307] The server analyzes temperature, humidity, and people flow indicators from the acquired data and calculates optimal environmental settings. Through cooperation with AWS Greengrass, air conditioners and other environmental control devices are automatically adjusted. At this time, 5G communication technology is used to perform low-latency and highly reliable communication.

[0308] Users can check environmental information through smart devices or displays in the facility. The server visualizes the acquired data and provides information using Amazon S3 or Google Cloud Storage. Notifications are sent using Twilio or Firebase Cloud Messaging according to sudden changes in weather conditions or congestion.

[0309] As a specific example, when the server senses that the outside temperature exceeds 35 degrees Celsius in a commercial facility in the middle of summer, the cooling system is automatically adjusted to keep the indoor temperature of the facility at a comfortable level. As a result, users can continue shopping in a comfortable environment. An example of a prompt sentence for the generative AI model could be "Please propose the data analysis algorithms required to develop a real-time environmental management system in a shopping facility."

[0310] The flow of specific processing in Application Example 1 will be described using FIG. 12.

[0311] Step 1:

[0312] The server uses AWS IoT Core or Google Cloud IoT to receive data acquired from environmental sensors in real time. The inputs are temperature, humidity, and pedestrian flow data, which the server receives. The received data is then initially processed by AWS Lambda or Google Cloud Functions and converted into an analyzable format.

[0313] Step 2:

[0314] The server uses AI algorithms running on AWS Lambda or Google Cloud Functions to analyze incoming environmental data. The input is data from environmental sensors. This AI algorithm calculates optimal environmental conditions and outputs indicators for temperature, humidity, and congestion management within the facility.

[0315] Step 3:

[0316] The server sends commands to the facility's air conditioning system and other control devices via AWS Greengrass. The input is the analysis result of the AI ​​algorithm, and the output is specific operation commands to the control devices. Environmental control devices such as air conditioning and lighting equipment are automatically and optimally adjusted.

[0317] Step 4:

[0318] The terminal receives information from the server and displays current environmental information on displays and smart devices within the facility. Input is environmental information and warning alerts sent from the server, and output is information displayed to the user. The display shows temperature, humidity, and suggestions for optimal environmental settings.

[0319] Step 5:

[0320] The server uses Twilio and Firebase Cloud Messaging to send notifications to users when it detects extreme weather or rapid environmental changes. The input is information about rapid changes in environmental data, and the output is an alert notification sent to the user. This allows users to take necessary actions quickly.

[0321] 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.

[0322] This invention is a system that provides a comfortable and safe water environment by acquiring and analyzing environmental data in real time and integrating it with emotion recognition technology. Specific embodiments of this system are described below.

[0323] This system is built around servers, terminals, and users, and not only optimizes the water environment using external environmental data, but also provides an experience that responds to the user's emotions.

[0324] Data collection and analysis

[0325] The server periodically acquires external environmental data via weather APIs and environmental sensors. It also utilizes an emotion engine to monitor the user's facial expressions and movements through the device's camera and sensors, and collects emotional data.

[0326] The AI ​​algorithm simultaneously analyzes this data to calculate the conditions for optimizing the pool environment and the interactions that respond to the user's emotions.

[0327] Environmental control and emotional response

[0328] Based on the analysis results, the server generates basic environmental commands such as pool water temperature and mist showers. It also generates commands to adjust effects such as lighting and music based on the user's emotions.

[0329] The terminal receives these commands and operates physical devices and performance equipment to provide a water environment and experience that the user finds comfortable.

[0330] User interface and alerts

[0331] The device displays the current status of the pool, as well as suggestions from the AI ​​and emotion engines. This allows users to intuitively receive suggestions tailored to the environment and their own emotions.

[0332] If a sudden change in environmental or emotional data is detected, the server generates an alert, and the terminal quickly notifies the user.

[0333] Specific example

[0334] For example, if the outside temperature is 30 degrees Celsius and the user is smiling and relaxed, the system will activate the cooling system to maintain the water temperature at a comfortable 28 degrees Celsius. It will also individually adjust soothing music and comfortable lighting to create an environment that helps maintain the user's relaxed state. If the system detects that the user is stressed, it can further adjust the environment and change to a calming, relaxing atmosphere to alleviate tension.

[0335] Thus, the present invention has embodiments that provide a customized water play experience tailored to individual users by combining real-time data management with AI and emotion recognition technology.

[0336] The following describes the processing flow.

[0337] Step 1:

[0338] The server collects external environmental data every five minutes from weather APIs and environmental sensors. This data includes temperature, humidity, UV index, and weather forecasts. It also receives user facial expression data transmitted from the device.

[0339] Step 2:

[0340] The device uses its built-in camera and sensors to monitor the user's facial expressions and movements, and transmits the data to an emotion engine in real time. This emotion data is used to estimate the user's level of happiness, tension, stress, and other factors.

[0341] Step 3:

[0342] The server inputs environmental and emotional data into an AI algorithm for analysis. The analysis results in the calculation of optimal water environment and performance settings based on necessary emotions. Historical data is also referenced to improve prediction accuracy.

[0343] Step 4:

[0344] Based on the analysis results, the server generates commands to adjust the pool water temperature and activate the mist shower. At the same time, it also determines music and lighting settings that correspond to the user's emotions and sends control commands, including these settings, to the terminal.

[0345] Step 5:

[0346] The terminal receives commands and controls the actual equipment. This includes adjusting water temperature, turning mist on / off, changing lighting color and brightness, and selecting and playing music. This provides the user with an optimal user experience.

[0347] Step 6:

[0348] The device displays the current pool environment, AI suggestions, and advice based on the user's emotions in its user interface. Based on this information, the user can further manually adjust the environment settings to their liking.

[0349] Step 7:

[0350] If anomalies or sudden changes occur in environmental or emotional data, the server immediately generates an alert. The terminal notifies the user of this alert via voice or screen display, prompting them to take necessary corrective action.

[0351] (Example 2)

[0352] 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".

[0353] In aquatic environments such as swimming pools, there is a need to accurately grasp the external environment and the emotional state of users in real time and instantly provide comfortable and safe conditions. However, conventional systems have difficulty effectively utilizing this data and providing appropriate interactions tailored to users. In particular, the detection of abnormal weather conditions, which require immediate response, and the insufficient response to individual emotional needs are major challenges.

[0354] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0355] In this invention, the server includes information acquisition means for analyzing environmental information acquired using external input to derive optimal water environment conditions, analysis means for analyzing the user's actions and facial expressions using emotion analysis technology based on the collected data, and control means for controlling water temperature and environmental settings and providing interactive effects that respond to emotions based on the analysis results. This makes it possible to provide a comfortable and safe water environment optimized for the user in real time.

[0356] "External input" refers to data obtained from external sources, and is a concept that includes weather data and information obtained from environmental monitoring systems.

[0357] "Environmental information" refers to data that reflects the external natural environment and the conditions within the facility, and includes information such as temperature, humidity, and light intensity.

[0358] "Information acquisition means" refers to a device or system that has the function of collecting data from the external environment.

[0359] "Emotional analysis technology" refers to algorithms and system technologies that analyze a user's facial expressions and actions to determine their emotional state.

[0360] "Analysis means" refers to an apparatus or method for performing an analysis based on collected data and deriving a specific result.

[0361] "Control means" refers to mechanisms or systems used to adjust environmental settings and the operation of devices based on the results of analysis.

[0362] "Interactive effects" refer to a system that provides lighting and music effects that automatically change settings in response to the user's emotions and actions.

[0363] This invention is a system that analyzes real-time environmental information and the emotional state of users, and based on this analysis, provides a comfortable and safe water environment. The system is composed of a server, terminals, and users as its core components.

[0364] The server is responsible for analyzing environmental information acquired from external sources. It obtains data from weather APIs and various sensors, and utilizes Python-based machine learning algorithms to analyze it. This allows it to analyze current environmental conditions and generate information to provide an optimized water environment. Furthermore, the server uses cameras and sensors installed on the terminal to collect data on the user's facial expressions and movements, and analyzes this data using emotion analysis technology.

[0365] The terminal receives commands from the server and controls the actual equipment and effects. Specifically, it operates the water temperature control system, controls the mist shower, and sets the lighting and sound. The terminal also provides the user with visual information about the current situation and AI-generated suggestions through its display. This allows the user to intuitively understand changes in the environment in real time and enjoy an experience that responds to their emotions.

[0366] For users, this system guarantees a comfortable water play experience. For example, if the outside temperature is very high and the system determines that the user is relaxed, it will adjust the pool water temperature to a comfortable level and play relaxing music. Conversely, if the system detects that the user is stressed, it will further adjust the system to provide a more calming environment.

[0367] An example of a prompt sentence to be input to the generating AI model is, "Please tell me how to adjust the water environment to be suitable when the user is relaxed at a high temperature." In this way, the present invention aims to maximize the user experience by utilizing real-time data analysis.

[0368] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0369] Step 1:

[0370] The server acquires external environmental information. It receives data on temperature, humidity, and precipitation from weather APIs and surrounding sensors as input. This data is collected and compiled into a JSON-formatted dataset for processing. The output is real-time data of the external environment. Specifically, the server periodically sends API requests to obtain the latest weather information.

[0371] Step 2:

[0372] The server collects user emotion data from the terminal. As input, the terminal captures the user's face and gestures using its camera and motion sensors. Based on this, an emotion analysis model analyzes the image data and estimates the user's emotional state from their facial expressions and movements. The output is the analysis result indicating the user's emotional state. Specifically, the terminal's camera periodically sends images to the server, and the server activates the emotion analysis engine to process them.

[0373] Step 3:

[0374] The server uses an AI algorithm to analyze acquired environmental data and user emotion data. It receives weather data and emotion data as input and processes them into an analysis model. Data processing maps the relationship between environment and emotion to calculate optimal conditions for the water environment. The output consists of optimization conditions and performance instructions. Specifically, the server initiates a machine learning analysis process to calculate appropriate water temperature settings and performance plans.

[0375] Step 4:

[0376] The server generates control commands based on the analysis results and sends them to the terminal. The input consists of optimization conditions generated by an AI algorithm. Data calculations determine specific water temperature settings, mist shower on / off settings, lighting color, and music selection. The output is a specific control command. In terms of operation, the server sends commands to the terminal via the cloud, and the terminal activates the control system.

[0377] Step 5:

[0378] The terminal executes commands received from the server and adjusts the physical environment. The input is control commands from the server. Specific actions include operating a water temperature control device to set the water temperature, adjusting the mist shower output, and appropriately setting lighting and sound equipment. The output is the altered environmental conditions and effects.

[0379] Step 6:

[0380] Users view the current situation and suggestions through the device's display. The input consists of visually provided current information and analytical suggestions from the device. This allows users to receive appropriate interactions tailored to their environment and emotions. Specifically, the display shows things like temperature, emotion analysis results, and suggested actions.

[0381] Step 7:

[0382] The server generates an alarm when it detects an anomaly and notifies the user via the terminal. Inputs include rapid changes in environmental data and anomalies in emotional data. A detection algorithm analyzes the situation and creates an alarm as needed. The output is the alarm notification. Specifically, the server identifies the anomaly event, and the terminal presents the alert message to the user.

[0383] (Application Example 2)

[0384] 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."

[0385] Providing visitors with a personalized and comfortable experience in current commercial and entertainment facilities is challenging. In particular, there is no established method for reflecting visitors' emotional states in real time and adjusting the environment accordingly. Furthermore, there is a need for a system that integrates various external conditions and visitors' emotions to intuitively improve the experience.

[0386] 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.

[0387] In this invention, the server includes data acquisition means for analyzing external environmental information acquired in real time and calculating optimal base conditions; control means for controlling liquid temperature and associated equipment based on the analysis results; display means for displaying the current facility status and suggestions to the user; anomaly detection means for detecting abnormal external conditions and issuing warnings; emotion recognition means for understanding the user's emotional state and adjusting the environmental presentation; and environmental presentation control means for adjusting lighting and sound to provide an individualized experience. This makes it possible to provide each visitor with an optimal experience tailored to their emotions and environment in real time.

[0388] "External environmental information" refers to data on natural conditions obtained from outside the facility, such as weather data, ambient temperature, humidity, and illuminance.

[0389] "Basic conditions" refer to the fundamental and optimal physical conditions for providing a comfortable experience within a facility, calculated using external environmental information.

[0390] "Data acquisition means" refers to a combination of hardware and software for collecting external environmental information and user sentiment data in real time.

[0391] A "control means" is a mechanism for optimally operating ancillary equipment such as temperature control and sound systems within a facility, based on the analysis results.

[0392] "Display means" refers to devices or interfaces that visually show users the current status of a facility or the proposed experience.

[0393] An "anomaly detection system" is a system that identifies external conditions that differ from normal conditions and issues a warning as necessary.

[0394] "Emotion recognition means" refers to technology that analyzes a user's facial expressions and movements and evaluates their emotional state in real time.

[0395] "Environmental design control means" refers to a method for providing an optimal environment by adjusting design elements such as lighting and sound according to the user's emotions and the conditions within the facility.

[0396] The system for implementing this invention consists of multiple modules and has the capability to perform real-time analysis of environmental and emotional data. The server acquires data from weather APIs and environmental sensors to obtain external environmental information, and collects emotional data through the terminal's camera and sensors to understand the user's emotional state. This data is analyzed by an AI algorithm to provide information necessary to adjust the basic conditions within the facility.

[0397] The server uses the analysis results to generate control commands for operating lighting and sound equipment within the facility. For this purpose, it uses the Python language for data processing, with TensorFlow handling sentiment analysis. It also utilizes AWS cloud services to process external information. Terminals receive these control commands and intuitively control devices within the facility.

[0398] For example, when a user visits the welcome zone in a shopping mall, if they are in a relaxed state, the system will provide calming lighting and music. Conversely, if they are in a cheerful state, it can provide bright lighting and lively music.

[0399] By using generative AI models, real-time adjustments can be made to enhance the user experience. An example of a prompt might be: "Please tell me how to analyze a visitor's face, identify their fatigue and well-being levels, and then adjust the environment (music, lighting) within the commercial facility in real time to match those levels."

[0400] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0401] Step 1:

[0402] The server acquires external environmental information from weather APIs and environmental sensors. Inputs are weather data and sensor values ​​from the APIs, and outputs are integrated external environmental information. This process involves receiving data and performing data format conversion for integration.

[0403] Step 2:

[0404] The device captures the user's facial expression data in real time through its camera and sensors. The input is camera footage, and the output is facial expression features obtained through image processing. A facial recognition module is used to extract emotional features.

[0405] Step 3:

[0406] The server uses TensorFlow to analyze acquired emotion features and identify the user's emotional state. The input is facial expression features, and the output is the user's emotional state. It prompts a generative AI model to perform data calculations to predict the emotional state.

[0407] Step 4:

[0408] The server calculates the optimal environmental conditions within the facility based on acquired external environmental information and the user's emotional state. The inputs are external environmental information and emotional state, and the output is control commands. An AI algorithm is used to generate adjustment parameters for lighting and music.

[0409] Step 5:

[0410] The server sends control commands to the terminal, initiating control of the physical device. The input is the control command, and the output is the control status of the field equipment. The terminal adjusts the lighting and sound systems based on the received commands.

[0411] Step 6:

[0412] Users experience altered facility environments. The input is the modified environmental conditions, and the output is the user's reaction to that experience. Ultimately, it serves as a means of monitoring how environmental changes affect the user's emotional state.

[0413] 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.

[0414] 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.

[0415] 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.

[0416] [Third Embodiment]

[0417] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0418] 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.

[0419] 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).

[0420] 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.

[0421] 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.

[0422] 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).

[0423] 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.

[0424] 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.

[0425] 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.

[0426] 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.

[0427] 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.

[0428] 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".

[0429] This invention constitutes a system that provides a comfortable and safe water environment by acquiring and analyzing environmental data in real time. Specific embodiments of this system are described below.

[0430] This system centers around servers, terminals, and users, and utilizes various data via the internet.

[0431] Data collection and analysis

[0432] The server periodically acquires external environmental data through weather APIs and environmental sensors. This data includes current temperature, humidity, UV index, and weather forecasts.

[0433] The collected data is analyzed in real time by an AI algorithm on the server to determine the optimal water temperature for the pool and the operating status of the equipment.

[0434] Control and environmental optimization

[0435] Based on the analysis results, the server determines whether the pool water temperature needs to be adjusted and whether the mist shower or cooling system needs to be activated. This control information is then transmitted to the terminal.

[0436] The terminal performs actual device control based on instructions received from the server. This automatically adjusts the environment within the pool under the configured conditions.

[0437] User interface and alerts

[0438] The terminal provides information to the user. It displays actual water temperature, UV index, and environmental suggestions from AI on its screen, allowing the user to understand the current pool environment at a glance.

[0439] Furthermore, if a sudden change in weather conditions is detected, the server immediately generates an alert, and the terminal notifies the user. This allows the user to take appropriate action at a safe time.

[0440] Specific example

[0441] For example, suppose it's a scorching hot day with an outside temperature of 35 degrees Celsius and a very high UV index. In this case, the server immediately instructs the cooling system to activate and issues a control command to the terminal to maintain the pool water temperature at 28 degrees Celsius. The terminal also activates a mist shower and begins spraying mist to block UV rays. The user can check the display on the terminal and manually adjust the mist intensity as needed.

[0442] Thus, the present invention has embodiments that provide a safe and comfortable water play environment at all times through real-time data management and AI control.

[0443] The following describes the processing flow.

[0444] Step 1:

[0445] The server retrieves external environmental data every five minutes from weather APIs and environmental sensors. This data includes current temperature, humidity, UV index, and short-term weather forecasts.

[0446] Step 2:

[0447] The server inputs the acquired data into its internal AI algorithm for analysis. This analysis aims to understand the trends in the collected data and evaluate what environmental changes can be predicted in the future.

[0448] Step 3:

[0449] Based on the analysis results generated by the AI ​​algorithm, the server creates environmental control commands for the pool. For example, if the outside temperature is high, it will activate the cooling system, and if the UV index is high, it will instruct the mist shower to operate.

[0450] Step 4:

[0451] Upon receiving environmental control commands from the server, the terminal executes the controls as instructed. This includes operations such as turning specific devices on / off and initiating cooling to maintain a constant water temperature.

[0452] Step 5:

[0453] The device displays the current pool status and AI-generated suggestions to the user on its screen. Based on this information, the user can fine-tune the settings as needed.

[0454] Step 6:

[0455] If the environment goes outside of safe ranges or if severe weather changes are predicted, the server will immediately generate an anomaly alert. This will warn of danger in advance and prompt appropriate action.

[0456] Step 7:

[0457] The device notifies the user of the generated alert via voice or screen display. Based on this, the user takes safety actions such as interrupting water activities.

[0458] (Example 1)

[0459] 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."

[0460] In today's rapidly changing climate and with diverse user comfort requirements, there is a need to optimize water environments such as swimming pools in real time to ensure safe and comfortable use. However, existing systems suffer from insufficient accuracy in data collection and analysis, as well as rapid and effective device control, resulting in a lack of responsiveness to environmental changes.

[0461] 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.

[0462] In this invention, the server includes information acquisition means for analyzing weather and environmental information acquired in real time and calculating optimal water environment conditions, control means for controlling water temperature and related equipment based on the analysis results, and information provision means for displaying the current water environment state and environmental adjustment suggestions to the user. This makes it possible to respond to rapid weather changes and always provide a safe and comfortable water environment.

[0463] "Real-time" means that the current situation is reflected immediately, and data acquisition, analysis, and control are performed without delay.

[0464] "Weather information" refers to data related to weather and atmospheric conditions, such as temperature, humidity, UV index, and weather forecasts.

[0465] "Environmental information" refers to physical data measured within a specific environment or facility, including pool water temperature and surrounding humidity.

[0466] "Information acquisition means" refers to a method or apparatus for collecting and analyzing external weather information and physical environmental information.

[0467] "Control means" refers to a method or device for appropriately adjusting the operation of equipment or devices based on analyzed data.

[0468] "Information provision means" refers to a method or device for conveying information and suggestions analyzed by the system to the user.

[0469] An "artificial intelligence algorithm" is a computational method that uses machine learning and data analysis techniques to extract patterns from large amounts of data and make predictions and judgments.

[0470] A "predictive means" is a method or apparatus for estimating future environmental conditions based on past data and taking necessary countermeasures in advance.

[0471] "Efficient communication means" refers to a method or device that utilizes high-speed and reliable communication technology to rapidly transmit data and enable immediate control of equipment.

[0472] A "warning generation means" is a method or device for providing appropriate warnings to users when the system detects an abnormal or dangerous situation.

[0473] This system is designed to provide a comfortable and safe water environment and functions through the interaction of servers, terminals, and users.

[0474] First, the server acquires weather and environmental information in real time from weather APIs and environmental sensors. This allows it to collect data such as temperature, humidity, UV index, and weather forecasts. The server analyzes this data using artificial intelligence algorithms to determine the optimal pool environment. Machine learning models are used for the analysis, and past trends are used to predict future environmental changes.

[0475] Next, instructions are sent from the server to the terminal. The terminal controls the pool equipment based on the instructions received from the server. Specifically, it adjusts the operation of the cooling system and mist showers to maintain optimal water temperature and surrounding environment. Furthermore, the terminal's display shows current water environment data and AI-generated environmental suggestions, allowing the user to understand the pool's condition in real time.

[0476] Users can view information provided through the device's display and manually adjust the environment as needed. For example, on extremely hot days, they can adjust the intensity of the mist shower.

[0477] As a specific example, on extremely hot days, the server detects that the acquired outside temperature is 35 degrees Celsius and the UV index is high, instructs the cooling system to operate, and sends a control command to the terminal to maintain the pool water temperature at 28 degrees Celsius. The terminal also sprays mist, and the user can check the situation on the display and adjust the mist intensity. This ensures a comfortable and safe water environment at all times.

[0478] As an example of a prompt, the following could be input into the generating AI model: "On a scorching hot day with a temperature of 35 degrees Celsius and a high UV index, what controls are necessary to provide a safe and comfortable environment for the swimming pool?"

[0479] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0480] Step 1:

[0481] The server acquires data in real time from weather APIs and environmental sensors. Inputs include weather information (temperature, humidity, UV index, weather forecast) and pool environment sensor information (water temperature, ambient humidity). Output is a single dataset containing this information. Specifically, the server periodically calls the APIs, collects the acquired data, and stores it in the database.

[0482] Step 2:

[0483] The server performs analysis based on the acquired dataset. The input is the dataset obtained in Step 1. The server uses an artificial intelligence algorithm to analyze the data and calculate the optimal water environment conditions. The output is specific control parameters (water temperature setting, whether or not the mist shower is activated). Specifically, it compares the current data with past data to find patterns and determine the optimal control.

[0484] Step 3:

[0485] The server sends control commands to the terminal based on the analysis results. The input is the control parameters obtained in step 2. The output is the specific control command that reaches the terminal (for example, a command to maintain the water temperature at 28 degrees). In terms of actual operation, the server sends this command to the terminal via the communication network and performs immediate control.

[0486] Step 4:

[0487] The terminal controls the pool equipment based on control commands received from the server. The input is the control command from the server. The output is the actual operating status of the equipment (startup of the cooling system, operation of the mist shower). Specifically, the terminal operates the equipment's actuators through an electronic control unit to adjust the set temperature and the amount of mist sprayed.

[0488] Step 5:

[0489] The terminal displays the current pool environment status and AI-generated suggestions on its screen, providing information to the user. Inputs include data provided by the server and real-time sensor information. Outputs are visual information for the user (environmental data and suggestions displayed on the screen). Specifically, the terminal displays this information using a user-friendly GUI, providing an interface that the user can interact with.

[0490] Step 6:

[0491] The user manually adjusts the environment as needed, based on the information displayed on the device's screen. The input is the information displayed on the device (e.g., current water temperature and suggested adjustments). The output is the user's adjustment actions (e.g., changing the intensity of the mist shower). Specifically, the user adjusts the environment settings through the display's touch panel or buttons.

[0492] (Application Example 1)

[0493] 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."

[0494] Maintaining a comfortable environment is a crucial challenge in many facilities. Shopping centers and public facilities, in particular, attract large crowds, leading to rapidly changing environmental conditions. Therefore, real-time analysis of environmental data and maintenance of an optimal environment are essential. However, conventional systems often struggle to respond immediately to environmental changes, failing to provide optimal comfort and safety. To address this challenge, a system capable of efficient, real-time environmental control is necessary.

[0495] 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.

[0496] In this invention, the server includes data acquisition means for analyzing external environmental data acquired in real time and calculating optimal environmental conditions, control means for controlling the temperature and related equipment within the facility based on the analysis results, and analysis means for analyzing pedestrian flow data and providing optimal environmental settings according to the degree of congestion. This makes it possible to maintain optimal comfort within the facility and provide high satisfaction to users even when environmental conditions change rapidly.

[0497] "Real-time external environmental data" refers to data obtained in real time from external environmental conditions such as temperature, humidity, weather, and UV index, for analysis.

[0498] "Calculating optimal environmental conditions" means analyzing acquired environmental data to determine the ideal temperature, humidity, lighting intensity, etc., within the facility.

[0499] "Data acquisition means" refers to devices or software such as sensors or APIs used to collect environmental data.

[0500] A "control system" is a system that operates air conditioning equipment and other related devices to adjust temperature, humidity, etc., based on the analyzed data.

[0501] "Analyzing pedestrian flow data" means analyzing the number and movements of users within a facility to understand the level of congestion.

[0502] "Analysis means for providing optimal environmental settings according to the degree of congestion" refers to a device or software that evaluates the congestion status within a facility based on pedestrian flow data and calculates corresponding environmental conditions.

[0503] The system designed to realize this application aims to provide an optimal facility environment by analyzing real-time environmental data acquired by sensors on a server. The server primarily uses AWS IoT Core and Google Cloud IoT to collect environmental data. The collected data is processed in real time by AWS Lambda and Google Cloud Functions.

[0504] The server analyzes temperature, humidity, and pedestrian flow indicators from the acquired data to calculate the optimal environmental settings. Through integration with AWS Greengrass, it automatically adjusts air conditioning and other environmental control devices. 5G communication technology is used for this process to ensure low latency and high reliability.

[0505] Users can check environmental information through smart devices or displays within the facility. The server visualizes the acquired data and provides the information using Amazon S3 and Google Cloud Storage. Notifications are sent using Twilio and Firebase Cloud Messaging in response to sudden changes in weather conditions or congestion levels.

[0506] As a concrete example, in a commercial facility during the height of summer, if a server detects that the outside temperature exceeds 35 degrees Celsius, it automatically adjusts the cooling system to maintain a comfortable indoor temperature. This allows users to continue shopping in a comfortable environment. An example of a prompt for the generating AI model might be, "Please propose the data analysis algorithms necessary to develop a real-time environmental management system for shopping facilities."

[0507] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0508] Step 1:

[0509] The server uses AWS IoT Core or Google Cloud IoT to receive data acquired from environmental sensors in real time. The inputs are temperature, humidity, and pedestrian flow data, which the server receives. The received data is then initially processed by AWS Lambda or Google Cloud Functions and converted into an analyzable format.

[0510] Step 2:

[0511] The server uses AI algorithms running on AWS Lambda or Google Cloud Functions to analyze incoming environmental data. The input is data from environmental sensors. This AI algorithm calculates optimal environmental conditions and outputs indicators for temperature, humidity, and congestion management within the facility.

[0512] Step 3:

[0513] The server sends commands to the facility's air conditioning system and other control devices via AWS Greengrass. The input is the analysis result of the AI ​​algorithm, and the output is specific operation commands to the control devices. Environmental control devices such as air conditioning and lighting equipment are automatically and optimally adjusted.

[0514] Step 4:

[0515] The terminal receives information from the server and displays current environmental information on displays and smart devices within the facility. Input is environmental information and warning alerts sent from the server, and output is information displayed to the user. The display shows temperature, humidity, and suggestions for optimal environmental settings.

[0516] Step 5:

[0517] The server uses Twilio and Firebase Cloud Messaging to send notifications to users when it detects extreme weather or rapid environmental changes. The input is information about rapid changes in environmental data, and the output is an alert notification sent to the user. This allows users to take necessary actions quickly.

[0518] 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.

[0519] This invention is a system that provides a comfortable and safe water environment by acquiring and analyzing environmental data in real time and integrating it with emotion recognition technology. Specific embodiments of this system are described below.

[0520] This system is built around servers, terminals, and users, and not only optimizes the water environment using external environmental data, but also provides an experience that responds to the user's emotions.

[0521] Data collection and analysis

[0522] The server periodically acquires external environmental data via weather APIs and environmental sensors. It also utilizes an emotion engine to monitor the user's facial expressions and movements through the device's camera and sensors, and collects emotional data.

[0523] The AI ​​algorithm simultaneously analyzes this data to calculate the conditions for optimizing the pool environment and the interactions that respond to the user's emotions.

[0524] Environmental control and emotional response

[0525] Based on the analysis results, the server generates basic environmental commands such as pool water temperature and mist showers. It also generates commands to adjust effects such as lighting and music based on the user's emotions.

[0526] The terminal receives these commands and operates physical devices and performance equipment to provide a water environment and experience that the user finds comfortable.

[0527] User interface and alerts

[0528] The device displays the current status of the pool, as well as suggestions from the AI ​​and emotion engines. This allows users to intuitively receive suggestions tailored to the environment and their own emotions.

[0529] If a sudden change in environmental or emotional data is detected, the server generates an alert, and the terminal quickly notifies the user.

[0530] Specific example

[0531] For example, if the outside temperature is 30 degrees Celsius and the user is smiling and relaxed, the system will activate the cooling system to maintain the water temperature at a comfortable 28 degrees Celsius. It will also individually adjust soothing music and comfortable lighting to create an environment that helps maintain the user's relaxed state. If the system detects that the user is stressed, it can further adjust the environment and change to a calming, relaxing atmosphere to alleviate tension.

[0532] Thus, the present invention has embodiments that provide a customized water play experience tailored to individual users by combining real-time data management with AI and emotion recognition technology.

[0533] The following describes the processing flow.

[0534] Step 1:

[0535] The server collects external environmental data every five minutes from weather APIs and environmental sensors. This data includes temperature, humidity, UV index, and weather forecasts. It also receives user facial expression data transmitted from the device.

[0536] Step 2:

[0537] The device uses its built-in camera and sensors to monitor the user's facial expressions and movements, and transmits the data to an emotion engine in real time. This emotion data is used to estimate the user's level of happiness, tension, stress, and other factors.

[0538] Step 3:

[0539] The server inputs environmental and emotional data into an AI algorithm for analysis. The analysis results in the calculation of optimal water environment and performance settings based on necessary emotions. Historical data is also referenced to improve prediction accuracy.

[0540] Step 4:

[0541] Based on the analysis results, the server generates commands to adjust the pool water temperature and activate the mist shower. At the same time, it also determines music and lighting settings that correspond to the user's emotions and sends control commands, including these settings, to the terminal.

[0542] Step 5:

[0543] The terminal receives commands and controls the actual equipment. This includes adjusting water temperature, turning mist on / off, changing lighting color and brightness, and selecting and playing music. This provides the user with an optimal user experience.

[0544] Step 6:

[0545] The device displays the current pool environment, AI suggestions, and advice based on the user's emotions in its user interface. Based on this information, the user can further manually adjust the environment settings to their liking.

[0546] Step 7:

[0547] If anomalies or sudden changes occur in environmental or emotional data, the server immediately generates an alert. The terminal notifies the user of this alert via voice or screen display, prompting them to take necessary corrective action.

[0548] (Example 2)

[0549] 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."

[0550] In aquatic environments such as swimming pools, there is a need to accurately grasp the external environment and the emotional state of users in real time and instantly provide comfortable and safe conditions. However, conventional systems have difficulty effectively utilizing this data and providing appropriate interactions tailored to users. In particular, the detection of abnormal weather conditions, which require immediate response, and the insufficient response to individual emotional needs are major challenges.

[0551] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0552] In this invention, the server includes information acquisition means for analyzing environmental information acquired using external input to derive optimal water environment conditions, analysis means for analyzing the user's actions and facial expressions using emotion analysis technology based on the collected data, and control means for controlling water temperature and environmental settings and providing interactive effects that respond to emotions based on the analysis results. This makes it possible to provide a comfortable and safe water environment optimized for the user in real time.

[0553] "External input" refers to data obtained from external sources, and is a concept that includes weather data and information obtained from environmental monitoring systems.

[0554] "Environmental information" refers to data that reflects the external natural environment and the conditions within the facility, and includes information such as temperature, humidity, and light intensity.

[0555] "Information acquisition means" refers to a device or system that has the function of collecting data from the external environment.

[0556] "Emotional analysis technology" refers to algorithms and system technologies that analyze a user's facial expressions and actions to determine their emotional state.

[0557] "Analysis means" refers to an apparatus or method for performing an analysis based on collected data and deriving a specific result.

[0558] "Control means" refers to mechanisms or systems used to adjust environmental settings and the operation of devices based on the results of analysis.

[0559] "Interactive effects" refer to a system that provides lighting and music effects that automatically change settings in response to the user's emotions and actions.

[0560] This invention is a system that analyzes real-time environmental information and the emotional state of users, and based on this analysis, provides a comfortable and safe water environment. The system is composed of a server, terminals, and users as its core components.

[0561] The server is responsible for analyzing environmental information acquired from external sources. It obtains data from weather APIs and various sensors, and utilizes Python-based machine learning algorithms to analyze it. This allows it to analyze current environmental conditions and generate information to provide an optimized water environment. Furthermore, the server uses cameras and sensors installed on the terminal to collect data on the user's facial expressions and movements, and analyzes this data using emotion analysis technology.

[0562] The terminal receives commands from the server and controls the actual equipment and effects. Specifically, it operates the water temperature control system, controls the mist shower, and sets the lighting and sound. The terminal also provides the user with visual information about the current situation and AI-generated suggestions through its display. This allows the user to intuitively understand changes in the environment in real time and enjoy an experience that responds to their emotions.

[0563] For users, this system guarantees a comfortable water play experience. For example, if the outside temperature is very high and the system determines that the user is relaxed, it will adjust the pool water temperature to a comfortable level and play relaxing music. Conversely, if the system detects that the user is stressed, it will further adjust the system to provide a more calming environment.

[0564] An example of a prompt sentence to be input to the generating AI model is, "Please tell me how to adjust the water environment to be suitable when the user is relaxed at a high temperature." In this way, the present invention aims to maximize the user experience by utilizing real-time data analysis.

[0565] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0566] Step 1:

[0567] The server acquires external environmental information. It receives data on temperature, humidity, and precipitation from weather APIs and surrounding sensors as input. This data is collected and compiled into a JSON-formatted dataset for processing. The output is real-time data of the external environment. Specifically, the server periodically sends API requests to obtain the latest weather information.

[0568] Step 2:

[0569] The server collects user emotion data from the terminal. As input, the terminal captures the user's face and gestures using its camera and motion sensors. Based on this, an emotion analysis model analyzes the image data and estimates the user's emotional state from their facial expressions and movements. The output is the analysis result indicating the user's emotional state. Specifically, the terminal's camera periodically sends images to the server, and the server activates the emotion analysis engine to process them.

[0570] Step 3:

[0571] The server uses an AI algorithm to analyze acquired environmental data and user emotion data. It receives weather data and emotion data as input and processes them into an analysis model. Data processing maps the relationship between environment and emotion to calculate optimal conditions for the water environment. The output consists of optimization conditions and performance instructions. Specifically, the server initiates a machine learning analysis process to calculate appropriate water temperature settings and performance plans.

[0572] Step 4:

[0573] The server generates control commands based on the analysis results and sends them to the terminal. The input consists of optimization conditions generated by an AI algorithm. Data calculations determine specific water temperature settings, mist shower on / off settings, lighting color, and music selection. The output is a specific control command. In terms of operation, the server sends commands to the terminal via the cloud, and the terminal activates the control system.

[0574] Step 5:

[0575] The terminal executes commands received from the server and adjusts the physical environment. The input is control commands from the server. Specific actions include operating a water temperature control device to set the water temperature, adjusting the mist shower output, and appropriately setting lighting and sound equipment. The output is the altered environmental conditions and effects.

[0576] Step 6:

[0577] Users view the current situation and suggestions through the device's display. The input consists of visually provided current information and analytical suggestions from the device. This allows users to receive appropriate interactions tailored to their environment and emotions. Specifically, the display shows things like temperature, emotion analysis results, and suggested actions.

[0578] Step 7:

[0579] The server generates an alarm when it detects an anomaly and notifies the user via the terminal. Inputs include rapid changes in environmental data and anomalies in emotional data. A detection algorithm analyzes the situation and creates an alarm as needed. The output is the alarm notification. Specifically, the server identifies the anomaly event, and the terminal presents the alert message to the user.

[0580] (Application Example 2)

[0581] 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."

[0582] Providing visitors with a personalized and comfortable experience in current commercial and entertainment facilities is challenging. In particular, there is no established method for reflecting visitors' emotional states in real time and adjusting the environment accordingly. Furthermore, there is a need for a system that integrates various external conditions and visitors' emotions to intuitively improve the experience.

[0583] 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.

[0584] In this invention, the server includes data acquisition means for analyzing external environmental information acquired in real time and calculating optimal base conditions; control means for controlling liquid temperature and associated equipment based on the analysis results; display means for displaying the current facility status and suggestions to the user; anomaly detection means for detecting abnormal external conditions and issuing warnings; emotion recognition means for understanding the user's emotional state and adjusting the environmental presentation; and environmental presentation control means for adjusting lighting and sound to provide an individualized experience. This makes it possible to provide each visitor with an optimal experience tailored to their emotions and environment in real time.

[0585] "External environmental information" refers to data on natural conditions obtained from outside the facility, such as weather data, ambient temperature, humidity, and illuminance.

[0586] "Basic conditions" refer to the fundamental and optimal physical conditions for providing a comfortable experience within a facility, calculated using external environmental information.

[0587] "Data acquisition means" refers to a combination of hardware and software for collecting external environmental information and user sentiment data in real time.

[0588] A "control means" is a mechanism for optimally operating ancillary equipment such as temperature control and sound systems within a facility, based on the analysis results.

[0589] "Display means" refers to devices or interfaces that visually show users the current status of a facility or the proposed experience.

[0590] An "anomaly detection system" is a system that identifies external conditions that differ from normal conditions and issues a warning as necessary.

[0591] "Emotion recognition means" refers to technology that analyzes a user's facial expressions and movements and evaluates their emotional state in real time.

[0592] "Environmental design control means" refers to a method for providing an optimal environment by adjusting design elements such as lighting and sound according to the user's emotions and the conditions within the facility.

[0593] The system for implementing this invention consists of multiple modules and has the capability to perform real-time analysis of environmental and emotional data. The server acquires data from weather APIs and environmental sensors to obtain external environmental information, and collects emotional data through the terminal's camera and sensors to understand the user's emotional state. This data is analyzed by an AI algorithm to provide information necessary to adjust the basic conditions within the facility.

[0594] The server uses the analysis results to generate control commands for operating lighting and sound equipment within the facility. For this purpose, it uses the Python language for data processing, with TensorFlow handling sentiment analysis. It also utilizes AWS cloud services to process external information. Terminals receive these control commands and intuitively control devices within the facility.

[0595] For example, when a user visits the welcome zone in a shopping mall, if they are in a relaxed state, the system will provide calming lighting and music. Conversely, if they are in a cheerful state, it can provide bright lighting and lively music.

[0596] By using generative AI models, real-time adjustments can be made to enhance the user experience. An example of a prompt might be: "Please tell me how to analyze a visitor's face, identify their fatigue and well-being levels, and then adjust the environment (music, lighting) within the commercial facility in real time to match those levels."

[0597] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0598] Step 1:

[0599] The server acquires external environmental information from weather APIs and environmental sensors. Inputs are weather data and sensor values ​​from the APIs, and outputs are integrated external environmental information. This process involves receiving data and performing data format conversion for integration.

[0600] Step 2:

[0601] The device captures the user's facial expression data in real time through its camera and sensors. The input is camera footage, and the output is facial expression features obtained through image processing. A facial recognition module is used to extract emotional features.

[0602] Step 3:

[0603] The server uses TensorFlow to analyze acquired emotion features and identify the user's emotional state. The input is facial expression features, and the output is the user's emotional state. It prompts a generative AI model to perform data calculations to predict the emotional state.

[0604] Step 4:

[0605] The server calculates the optimal environmental conditions within the facility based on acquired external environmental information and the user's emotional state. The inputs are external environmental information and emotional state, and the output is control commands. An AI algorithm is used to generate adjustment parameters for lighting and music.

[0606] Step 5:

[0607] The server sends control commands to the terminal, initiating control of the physical device. The input is the control command, and the output is the control status of the field equipment. The terminal adjusts the lighting and sound systems based on the received commands.

[0608] Step 6:

[0609] Users experience altered facility environments. The input is the modified environmental conditions, and the output is the user's reaction to that experience. Ultimately, it serves as a means of monitoring how environmental changes affect the user's emotional state.

[0610] 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.

[0611] 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.

[0612] 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.

[0613] [Fourth Embodiment]

[0614] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0615] 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.

[0616] 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).

[0617] 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.

[0618] 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.

[0619] 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).

[0620] 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.

[0621] 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.

[0622] 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.

[0623] 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.

[0624] 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.

[0625] 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.

[0626] 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".

[0627] This invention constitutes a system that provides a comfortable and safe water environment by acquiring and analyzing environmental data in real time. Specific embodiments of this system are described below.

[0628] This system centers around servers, terminals, and users, and utilizes various data via the internet.

[0629] Data collection and analysis

[0630] The server periodically acquires external environmental data through weather APIs and environmental sensors. This data includes current temperature, humidity, UV index, and weather forecasts.

[0631] The collected data is analyzed in real time by an AI algorithm on the server to determine the optimal water temperature for the pool and the operating status of the equipment.

[0632] Control and environmental optimization

[0633] Based on the analysis results, the server determines whether the pool water temperature needs to be adjusted and whether the mist shower or cooling system needs to be activated. This control information is then transmitted to the terminal.

[0634] The terminal performs actual device control based on instructions received from the server. This automatically adjusts the environment within the pool under the configured conditions.

[0635] User interface and alerts

[0636] The terminal provides information to the user. It displays actual water temperature, UV index, and environmental suggestions from AI on its screen, allowing the user to understand the current pool environment at a glance.

[0637] Furthermore, if a sudden change in weather conditions is detected, the server immediately generates an alert, and the terminal notifies the user. This allows the user to take appropriate action at a safe time.

[0638] Specific example

[0639] For example, suppose it's a scorching hot day with an outside temperature of 35 degrees Celsius and a very high UV index. In this case, the server immediately instructs the cooling system to activate and issues a control command to the terminal to maintain the pool water temperature at 28 degrees Celsius. The terminal also activates a mist shower and begins spraying mist to block UV rays. The user can check the display on the terminal and manually adjust the mist intensity as needed.

[0640] Thus, the present invention has embodiments that provide a safe and comfortable water play environment at all times through real-time data management and AI control.

[0641] The following describes the processing flow.

[0642] Step 1:

[0643] The server retrieves external environmental data every five minutes from weather APIs and environmental sensors. This data includes current temperature, humidity, UV index, and short-term weather forecasts.

[0644] Step 2:

[0645] The server inputs the acquired data into its internal AI algorithm for analysis. This analysis aims to understand the trends in the collected data and evaluate what environmental changes can be predicted in the future.

[0646] Step 3:

[0647] Based on the analysis results generated by the AI ​​algorithm, the server creates environmental control commands for the pool. For example, if the outside temperature is high, it will activate the cooling system, and if the UV index is high, it will instruct the mist shower to operate.

[0648] Step 4:

[0649] Upon receiving environmental control commands from the server, the terminal executes the controls as instructed. This includes operations such as turning specific devices on / off and initiating cooling to maintain a constant water temperature.

[0650] Step 5:

[0651] The device displays the current pool status and AI-generated suggestions to the user on its screen. Based on this information, the user can fine-tune the settings as needed.

[0652] Step 6:

[0653] If the environment goes outside of safe ranges or if severe weather changes are predicted, the server will immediately generate an anomaly alert. This will warn of danger in advance and prompt appropriate action.

[0654] Step 7:

[0655] The device notifies the user of the generated alert via voice or screen display. Based on this, the user takes safety actions such as interrupting water activities.

[0656] (Example 1)

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

[0658] In today's rapidly changing climate and with diverse user comfort requirements, there is a need to optimize water environments such as swimming pools in real time to ensure safe and comfortable use. However, existing systems suffer from insufficient accuracy in data collection and analysis, as well as rapid and effective device control, resulting in a lack of responsiveness to environmental changes.

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

[0660] In this invention, the server includes information acquisition means for analyzing weather and environmental information acquired in real time and calculating optimal water environment conditions, control means for controlling water temperature and related equipment based on the analysis results, and information provision means for displaying the current water environment state and environmental adjustment suggestions to the user. This makes it possible to respond to rapid weather changes and always provide a safe and comfortable water environment.

[0661] "Real-time" means that the current situation is reflected immediately, and data acquisition, analysis, and control are performed without delay.

[0662] "Weather information" refers to data related to weather and atmospheric conditions, such as temperature, humidity, UV index, and weather forecasts.

[0663] "Environmental information" refers to physical data measured within a specific environment or facility, including pool water temperature and surrounding humidity.

[0664] "Information acquisition means" refers to a method or apparatus for collecting and analyzing external weather information and physical environmental information.

[0665] "Control means" refers to a method or device for appropriately adjusting the operation of equipment or devices based on analyzed data.

[0666] "Information provision means" refers to a method or device for conveying information and suggestions analyzed by the system to the user.

[0667] An "artificial intelligence algorithm" is a computational method that uses machine learning and data analysis techniques to extract patterns from large amounts of data and make predictions and judgments.

[0668] A "predictive means" is a method or apparatus for estimating future environmental conditions based on past data and taking necessary countermeasures in advance.

[0669] "Efficient communication means" refers to a method or device that utilizes high-speed and reliable communication technology to rapidly transmit data and enable immediate control of equipment.

[0670] A "warning generation means" is a method or device for providing appropriate warnings to users when the system detects an abnormal or dangerous situation.

[0671] This system is designed to provide a comfortable and safe water environment and functions through the interaction of servers, terminals, and users.

[0672] First, the server acquires weather and environmental information in real time from weather APIs and environmental sensors. This allows it to collect data such as temperature, humidity, UV index, and weather forecasts. The server analyzes this data using artificial intelligence algorithms to determine the optimal pool environment. Machine learning models are used for the analysis, and past trends are used to predict future environmental changes.

[0673] Next, instructions are sent from the server to the terminal. The terminal controls the pool equipment based on the instructions received from the server. Specifically, it adjusts the operation of the cooling system and mist showers to maintain optimal water temperature and surrounding environment. Furthermore, the terminal's display shows current water environment data and AI-generated environmental suggestions, allowing the user to understand the pool's condition in real time.

[0674] Users can view information provided through the device's display and manually adjust the environment as needed. For example, on extremely hot days, they can adjust the intensity of the mist shower.

[0675] As a specific example, on extremely hot days, the server detects that the acquired outside temperature is 35 degrees Celsius and the UV index is high, instructs the cooling system to operate, and sends a control command to the terminal to maintain the pool water temperature at 28 degrees Celsius. The terminal also sprays mist, and the user can check the situation on the display and adjust the mist intensity. This ensures a comfortable and safe water environment at all times.

[0676] As an example of a prompt, the following could be input into the generating AI model: "On a scorching hot day with a temperature of 35 degrees Celsius and a high UV index, what controls are necessary to provide a safe and comfortable environment for the swimming pool?"

[0677] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0678] Step 1:

[0679] The server acquires data in real time from weather APIs and environmental sensors. Inputs include weather information (temperature, humidity, UV index, weather forecast) and pool environment sensor information (water temperature, ambient humidity). Output is a single dataset containing this information. Specifically, the server periodically calls the APIs, collects the acquired data, and stores it in the database.

[0680] Step 2:

[0681] The server performs analysis based on the acquired dataset. The input is the dataset obtained in Step 1. The server uses an artificial intelligence algorithm to analyze the data and calculate the optimal water environment conditions. The output is specific control parameters (water temperature setting, whether or not the mist shower is activated). Specifically, it compares the current data with past data to find patterns and determine the optimal control.

[0682] Step 3:

[0683] The server sends control commands to the terminal based on the analysis results. The input is the control parameters obtained in step 2. The output is the specific control command that reaches the terminal (for example, a command to maintain the water temperature at 28 degrees). In terms of actual operation, the server sends this command to the terminal via the communication network and performs immediate control.

[0684] Step 4:

[0685] The terminal controls the pool equipment based on control commands received from the server. The input is the control command from the server. The output is the actual operating status of the equipment (startup of the cooling system, operation of the mist shower). Specifically, the terminal operates the equipment's actuators through an electronic control unit to adjust the set temperature and the amount of mist sprayed.

[0686] Step 5:

[0687] The terminal displays the current pool environment status and AI-generated suggestions on its screen, providing information to the user. Inputs include data provided by the server and real-time sensor information. Outputs are visual information for the user (environmental data and suggestions displayed on the screen). Specifically, the terminal displays this information using a user-friendly GUI, providing an interface that the user can interact with.

[0688] Step 6:

[0689] The user manually adjusts the environment as needed, based on the information displayed on the device's screen. The input is the information displayed on the device (e.g., current water temperature and suggested adjustments). The output is the user's adjustment actions (e.g., changing the intensity of the mist shower). Specifically, the user adjusts the environment settings through the display's touch panel or buttons.

[0690] (Application Example 1)

[0691] 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".

[0692] Maintaining a comfortable environment is a crucial challenge in many facilities. Shopping centers and public facilities, in particular, attract large crowds, leading to rapidly changing environmental conditions. Therefore, real-time analysis of environmental data and maintenance of an optimal environment are essential. However, conventional systems often struggle to respond immediately to environmental changes, failing to provide optimal comfort and safety. To address this challenge, a system capable of efficient, real-time environmental control is necessary.

[0693] 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.

[0694] In this invention, the server includes data acquisition means for analyzing external environmental data acquired in real time and calculating optimal environmental conditions, control means for controlling the temperature and related equipment within the facility based on the analysis results, and analysis means for analyzing pedestrian flow data and providing optimal environmental settings according to the degree of congestion. This makes it possible to maintain optimal comfort within the facility and provide high satisfaction to users even when environmental conditions change rapidly.

[0695] "Real-time external environmental data" refers to data obtained in real time from external environmental conditions such as temperature, humidity, weather, and UV index, for analysis.

[0696] "Calculating optimal environmental conditions" means analyzing acquired environmental data to determine the ideal temperature, humidity, lighting intensity, etc., within the facility.

[0697] "Data acquisition means" refers to devices or software such as sensors or APIs used to collect environmental data.

[0698] A "control system" is a system that operates air conditioning equipment and other related devices to adjust temperature, humidity, etc., based on the analyzed data.

[0699] "Analyzing pedestrian flow data" means analyzing the number and movements of users within a facility to understand the level of congestion.

[0700] "Analysis means for providing optimal environmental settings according to the degree of congestion" refers to a device or software that evaluates the congestion status within a facility based on pedestrian flow data and calculates corresponding environmental conditions.

[0701] The system designed to realize this application aims to provide an optimal facility environment by analyzing real-time environmental data acquired by sensors on a server. The server primarily uses AWS IoT Core and Google Cloud IoT to collect environmental data. The collected data is processed in real time by AWS Lambda and Google Cloud Functions.

[0702] The server analyzes temperature, humidity, and pedestrian flow indicators from the acquired data to calculate the optimal environmental settings. Through integration with AWS Greengrass, it automatically adjusts air conditioning and other environmental control devices. 5G communication technology is used for this process to ensure low latency and high reliability.

[0703] Users can check environmental information through smart devices or displays within the facility. The server visualizes the acquired data and provides the information using Amazon S3 and Google Cloud Storage. Notifications are sent using Twilio and Firebase Cloud Messaging in response to sudden changes in weather conditions or congestion levels.

[0704] As a concrete example, in a commercial facility during the height of summer, if a server detects that the outside temperature exceeds 35 degrees Celsius, it automatically adjusts the cooling system to maintain a comfortable indoor temperature. This allows users to continue shopping in a comfortable environment. An example of a prompt for the generating AI model might be, "Please propose the data analysis algorithms necessary to develop a real-time environmental management system for shopping facilities."

[0705] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0706] Step 1:

[0707] The server uses AWS IoT Core or Google Cloud IoT to receive data acquired from environmental sensors in real time. The inputs are temperature, humidity, and pedestrian flow data, which the server receives. The received data is then initially processed by AWS Lambda or Google Cloud Functions and converted into an analyzable format.

[0708] Step 2:

[0709] The server uses AI algorithms running on AWS Lambda or Google Cloud Functions to analyze incoming environmental data. The input is data from environmental sensors. This AI algorithm calculates optimal environmental conditions and outputs indicators for temperature, humidity, and congestion management within the facility.

[0710] Step 3:

[0711] The server sends commands to the facility's air conditioning system and other control devices via AWS Greengrass. The input is the analysis result of the AI ​​algorithm, and the output is specific operation commands to the control devices. Environmental control devices such as air conditioning and lighting equipment are automatically and optimally adjusted.

[0712] Step 4:

[0713] The terminal receives information from the server and displays current environmental information on displays and smart devices within the facility. Input is environmental information and warning alerts sent from the server, and output is information displayed to the user. The display shows temperature, humidity, and suggestions for optimal environmental settings.

[0714] Step 5:

[0715] The server uses Twilio and Firebase Cloud Messaging to send notifications to users when it detects extreme weather or rapid environmental changes. The input is information about rapid changes in environmental data, and the output is an alert notification sent to the user. This allows users to take necessary actions quickly.

[0716] 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.

[0717] This invention is a system that provides a comfortable and safe water environment by acquiring and analyzing environmental data in real time and integrating it with emotion recognition technology. Specific embodiments of this system are described below.

[0718] This system is built around servers, terminals, and users, and not only optimizes the water environment using external environmental data, but also provides an experience that responds to the user's emotions.

[0719] Data collection and analysis

[0720] The server periodically acquires external environmental data via weather APIs and environmental sensors. It also utilizes an emotion engine to monitor the user's facial expressions and movements through the device's camera and sensors, and collects emotional data.

[0721] The AI ​​algorithm simultaneously analyzes this data to calculate the conditions for optimizing the pool environment and the interactions that respond to the user's emotions.

[0722] Environmental control and emotional response

[0723] Based on the analysis results, the server generates basic environmental commands such as pool water temperature and mist showers. It also generates commands to adjust effects such as lighting and music based on the user's emotions.

[0724] The terminal receives these commands and operates physical devices and performance equipment to provide a water environment and experience that the user finds comfortable.

[0725] User interface and alerts

[0726] The device displays the current status of the pool, as well as suggestions from the AI ​​and emotion engines. This allows users to intuitively receive suggestions tailored to the environment and their own emotions.

[0727] If a sudden change in environmental or emotional data is detected, the server generates an alert, and the terminal quickly notifies the user.

[0728] Specific example

[0729] For example, if the outside temperature is 30 degrees Celsius and the user is smiling and relaxed, the system will activate the cooling system to maintain the water temperature at a comfortable 28 degrees Celsius. It will also individually adjust soothing music and comfortable lighting to create an environment that helps maintain the user's relaxed state. If the system detects that the user is stressed, it can further adjust the environment and change to a calming, relaxing atmosphere to alleviate tension.

[0730] Thus, the present invention has embodiments that provide a customized water play experience tailored to individual users by combining real-time data management with AI and emotion recognition technology.

[0731] The following describes the processing flow.

[0732] Step 1:

[0733] The server collects external environmental data every five minutes from weather APIs and environmental sensors. This data includes temperature, humidity, UV index, and weather forecasts. It also receives user facial expression data transmitted from the device.

[0734] Step 2:

[0735] The device uses its built-in camera and sensors to monitor the user's facial expressions and movements, and transmits the data to an emotion engine in real time. This emotion data is used to estimate the user's level of happiness, tension, stress, and other factors.

[0736] Step 3:

[0737] The server inputs environmental and emotional data into an AI algorithm for analysis. The analysis results in the calculation of optimal water environment and performance settings based on necessary emotions. Historical data is also referenced to improve prediction accuracy.

[0738] Step 4:

[0739] Based on the analysis results, the server generates commands to adjust the pool water temperature and activate the mist shower. At the same time, it also determines music and lighting settings that correspond to the user's emotions and sends control commands, including these settings, to the terminal.

[0740] Step 5:

[0741] The terminal receives commands and controls the actual equipment. This includes adjusting water temperature, turning mist on / off, changing lighting color and brightness, and selecting and playing music. This provides the user with an optimal user experience.

[0742] Step 6:

[0743] The device displays the current pool environment, AI suggestions, and advice based on the user's emotions in its user interface. Based on this information, the user can further manually adjust the environment settings to their liking.

[0744] Step 7:

[0745] If anomalies or sudden changes occur in environmental or emotional data, the server immediately generates an alert. The terminal notifies the user of this alert via voice or screen display, prompting them to take necessary corrective action.

[0746] (Example 2)

[0747] 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".

[0748] In aquatic environments such as swimming pools, there is a need to accurately grasp the external environment and the emotional state of users in real time and instantly provide comfortable and safe conditions. However, conventional systems have difficulty effectively utilizing this data and providing appropriate interactions tailored to users. In particular, the detection of abnormal weather conditions, which require immediate response, and the insufficient response to individual emotional needs are major challenges.

[0749] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0750] In this invention, the server includes information acquisition means for analyzing environmental information acquired using external input to derive optimal water environment conditions, analysis means for analyzing the user's actions and facial expressions using emotion analysis technology based on the collected data, and control means for controlling water temperature and environmental settings and providing interactive effects that respond to emotions based on the analysis results. This makes it possible to provide a comfortable and safe water environment optimized for the user in real time.

[0751] "External input" refers to data obtained from external sources, and is a concept that includes weather data and information obtained from environmental monitoring systems.

[0752] "Environmental information" refers to data that reflects the external natural environment and the conditions within the facility, and includes information such as temperature, humidity, and light intensity.

[0753] "Information acquisition means" refers to a device or system that has the function of collecting data from the external environment.

[0754] "Emotional analysis technology" refers to algorithms and system technologies that analyze a user's facial expressions and actions to determine their emotional state.

[0755] "Analysis means" refers to an apparatus or method for performing an analysis based on collected data and deriving a specific result.

[0756] "Control means" refers to mechanisms or systems used to adjust environmental settings and the operation of devices based on the results of analysis.

[0757] "Interactive effects" refer to a system that provides lighting and music effects that automatically change settings in response to the user's emotions and actions.

[0758] This invention is a system that analyzes real-time environmental information and the emotional state of users, and based on this analysis, provides a comfortable and safe water environment. The system is composed of a server, terminals, and users as its core components.

[0759] The server is responsible for analyzing environmental information acquired from external sources. It obtains data from weather APIs and various sensors, and utilizes Python-based machine learning algorithms to analyze it. This allows it to analyze current environmental conditions and generate information to provide an optimized water environment. Furthermore, the server uses cameras and sensors installed on the terminal to collect data on the user's facial expressions and movements, and analyzes this data using emotion analysis technology.

[0760] The terminal receives commands from the server and controls the actual equipment and effects. Specifically, it operates the water temperature control system, controls the mist shower, and sets the lighting and sound. The terminal also provides the user with visual information about the current situation and AI-generated suggestions through its display. This allows the user to intuitively understand changes in the environment in real time and enjoy an experience that responds to their emotions.

[0761] For users, this system guarantees a comfortable water play experience. For example, if the outside temperature is very high and the system determines that the user is relaxed, it will adjust the pool water temperature to a comfortable level and play relaxing music. Conversely, if the system detects that the user is stressed, it will further adjust the system to provide a more calming environment.

[0762] An example of a prompt sentence to be input to the generating AI model is, "Please tell me how to adjust the water environment to be suitable when the user is relaxed at a high temperature." In this way, the present invention aims to maximize the user experience by utilizing real-time data analysis.

[0763] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0764] Step 1:

[0765] The server acquires external environmental information. It receives data on temperature, humidity, and precipitation from weather APIs and surrounding sensors as input. This data is collected and compiled into a JSON-formatted dataset for processing. The output is real-time data of the external environment. Specifically, the server periodically sends API requests to obtain the latest weather information.

[0766] Step 2:

[0767] The server collects user emotion data from the terminal. As input, the terminal captures the user's face and gestures using its camera and motion sensors. Based on this, an emotion analysis model analyzes the image data and estimates the user's emotional state from their facial expressions and movements. The output is the analysis result indicating the user's emotional state. Specifically, the terminal's camera periodically sends images to the server, and the server activates the emotion analysis engine to process them.

[0768] Step 3:

[0769] The server uses an AI algorithm to analyze acquired environmental data and user emotion data. It receives weather data and emotion data as input and processes them into an analysis model. Data processing maps the relationship between environment and emotion to calculate optimal conditions for the water environment. The output consists of optimization conditions and performance instructions. Specifically, the server initiates a machine learning analysis process to calculate appropriate water temperature settings and performance plans.

[0770] Step 4:

[0771] The server generates control commands based on the analysis results and sends them to the terminal. The input consists of optimization conditions generated by an AI algorithm. Data calculations determine specific water temperature settings, mist shower on / off settings, lighting color, and music selection. The output is a specific control command. In terms of operation, the server sends commands to the terminal via the cloud, and the terminal activates the control system.

[0772] Step 5:

[0773] The terminal executes commands received from the server and adjusts the physical environment. The input is control commands from the server. Specific actions include operating a water temperature control device to set the water temperature, adjusting the mist shower output, and appropriately setting lighting and sound equipment. The output is the altered environmental conditions and effects.

[0774] Step 6:

[0775] Users view the current situation and suggestions through the device's display. The input consists of visually provided current information and analytical suggestions from the device. This allows users to receive appropriate interactions tailored to their environment and emotions. Specifically, the display shows things like temperature, emotion analysis results, and suggested actions.

[0776] Step 7:

[0777] The server generates an alarm when it detects an anomaly and notifies the user via the terminal. Inputs include rapid changes in environmental data and anomalies in emotional data. A detection algorithm analyzes the situation and creates an alarm as needed. The output is the alarm notification. Specifically, the server identifies the anomaly event, and the terminal presents the alert message to the user.

[0778] (Application Example 2)

[0779] 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".

[0780] Providing visitors with a personalized and comfortable experience in current commercial and entertainment facilities is challenging. In particular, there is no established method for reflecting visitors' emotional states in real time and adjusting the environment accordingly. Furthermore, there is a need for a system that integrates various external conditions and visitors' emotions to intuitively improve the experience.

[0781] 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.

[0782] In this invention, the server includes data acquisition means for analyzing external environmental information acquired in real time and calculating optimal base conditions; control means for controlling liquid temperature and associated equipment based on the analysis results; display means for displaying the current facility status and suggestions to the user; anomaly detection means for detecting abnormal external conditions and issuing warnings; emotion recognition means for understanding the user's emotional state and adjusting the environmental presentation; and environmental presentation control means for adjusting lighting and sound to provide an individualized experience. This makes it possible to provide each visitor with an optimal experience tailored to their emotions and environment in real time.

[0783] "External environmental information" refers to data on natural conditions obtained from outside the facility, such as weather data, ambient temperature, humidity, and illuminance.

[0784] "Basic conditions" refer to the fundamental and optimal physical conditions for providing a comfortable experience within a facility, calculated using external environmental information.

[0785] "Data acquisition means" refers to a combination of hardware and software for collecting external environmental information and user sentiment data in real time.

[0786] A "control means" is a mechanism for optimally operating ancillary equipment such as temperature control and sound systems within a facility, based on the analysis results.

[0787] "Display means" refers to devices or interfaces that visually show users the current status of a facility or the proposed experience.

[0788] An "anomaly detection system" is a system that identifies external conditions that differ from normal conditions and issues a warning as necessary.

[0789] "Emotion recognition means" refers to technology that analyzes a user's facial expressions and movements and evaluates their emotional state in real time.

[0790] "Environmental design control means" refers to a method for providing an optimal environment by adjusting design elements such as lighting and sound according to the user's emotions and the conditions within the facility.

[0791] The system for implementing this invention consists of multiple modules and has the capability to perform real-time analysis of environmental and emotional data. The server acquires data from weather APIs and environmental sensors to obtain external environmental information, and collects emotional data through the terminal's camera and sensors to understand the user's emotional state. This data is analyzed by an AI algorithm to provide information necessary to adjust the basic conditions within the facility.

[0792] The server uses the analysis results to generate control commands for operating lighting and sound equipment within the facility. For this purpose, it uses the Python language for data processing, with TensorFlow handling sentiment analysis. It also utilizes AWS cloud services to process external information. Terminals receive these control commands and intuitively control devices within the facility.

[0793] For example, when a user visits the welcome zone in a shopping mall, if they are in a relaxed state, the system will provide calming lighting and music. Conversely, if they are in a cheerful state, it can provide bright lighting and lively music.

[0794] By using generative AI models, real-time adjustments can be made to enhance the user experience. An example of a prompt might be: "Please tell me how to analyze a visitor's face, identify their fatigue and well-being levels, and then adjust the environment (music, lighting) within the commercial facility in real time to match those levels."

[0795] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0796] Step 1:

[0797] The server acquires external environmental information from weather APIs and environmental sensors. Inputs are weather data and sensor values ​​from the APIs, and outputs are integrated external environmental information. This process involves receiving data and performing data format conversion for integration.

[0798] Step 2:

[0799] The device captures the user's facial expression data in real time through its camera and sensors. The input is camera footage, and the output is facial expression features obtained through image processing. A facial recognition module is used to extract emotional features.

[0800] Step 3:

[0801] The server uses TensorFlow to analyze acquired emotion features and identify the user's emotional state. The input is facial expression features, and the output is the user's emotional state. It prompts a generative AI model to perform data calculations to predict the emotional state.

[0802] Step 4:

[0803] The server calculates the optimal environmental conditions within the facility based on acquired external environmental information and the user's emotional state. The inputs are external environmental information and emotional state, and the output is control commands. An AI algorithm is used to generate adjustment parameters for lighting and music.

[0804] Step 5:

[0805] The server sends control commands to the terminal, initiating control of the physical device. The input is the control command, and the output is the control status of the field equipment. The terminal adjusts the lighting and sound systems based on the received commands.

[0806] Step 6:

[0807] Users experience altered facility environments. The input is the modified environmental conditions, and the output is the user's reaction to that experience. Ultimately, it serves as a means of monitoring how environmental changes affect the user's emotional state.

[0808] 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.

[0809] 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.

[0810] 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.

[0811] 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.

[0812] 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.

[0813] 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.

[0814] 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.

[0815] 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.

[0816] 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."

[0817] 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.

[0818] 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.

[0819] 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.

[0820] 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.

[0821] 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.

[0822] 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.

[0823] 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.

[0824] 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.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] The following is further disclosed regarding the embodiments described above.

[0830] (Claim 1)

[0831] A data acquisition method for analyzing external environmental data acquired in real time and calculating optimal water environment conditions,

[0832] Based on the analysis results, a control means for controlling the pool water temperature and associated equipment is provided,

[0833] A display means for showing the current pool status and suggestions to the user,

[0834] An anomaly detection means for detecting abnormal weather conditions and issuing warnings,

[0835] A system that includes this.

[0836] (Claim 2)

[0837] The system according to claim 1, comprising a prediction means for integrating highly accurate weather information and environmental data and predicting future environmental changes by referring to past trends.

[0838] (Claim 3)

[0839] The system according to claim 1, comprising communication means for achieving low-latency and highly reliable data communication using 5G communication technology and for rapid device control.

[0840] "Example 1"

[0841] (Claim 1)

[0842] A means for acquiring information to analyze weather and environmental information obtained in real time and calculate optimal water environment conditions,

[0843] Based on the analysis results, a control means for controlling the water temperature and related devices,

[0844] A means of providing information to users to display the current state of the water environment and suggestions for environmental adjustment,

[0845] A warning generation means for detecting and issuing warnings about sudden changes in weather conditions,

[0846] A prediction method for predicting the optimal environment settings from past data using artificial intelligence algorithms,

[0847] A system that includes this.

[0848] (Claim 2)

[0849] The system according to claim 1, comprising efficient communication means for rapidly transmitting data and immediately managing devices.

[0850] (Claim 3)

[0851] The system according to claim 1, which has a function for the user to manually adjust the environment and means for enabling visualization of the environment using an information display device.

[0852] "Application Example 1"

[0853] (Claim 1)

[0854] A data acquisition method for analyzing external environmental data acquired in real time and calculating optimal environmental conditions,

[0855] Based on the aforementioned analysis results, a control means for controlling the temperature and related equipment within the facility is provided.

[0856] A display means for showing users the current facility status and suggestions,

[0857] An anomaly detection means for detecting abnormal environmental conditions and issuing warnings,

[0858] An analytical means for analyzing pedestrian flow data and providing optimal environmental settings according to the degree of congestion,

[0859] A system that includes this.

[0860] (Claim 2)

[0861] The system according to claim 1, comprising a prediction means for integrating highly accurate weather information and environmental data and predicting future environmental changes by referring to past trends.

[0862] (Claim 3)

[0863] The system according to claim 1, comprising communication means for achieving low-latency and highly reliable communication and for rapid device control, and means for providing environmental information to users in real time.

[0864] "Example 2 of combining an emotion engine"

[0865] (Claim 1)

[0866] An information acquisition means for analyzing environmental information obtained using external input and deriving optimal water environment conditions,

[0867] Based on the collected data, an analytical method is developed to analyze the user's actions and facial expressions using emotion analysis technology.

[0868] Based on the analysis results, a control means is provided to control water temperature and environmental settings, and to provide interactive effects that respond to emotions.

[0869] A display means for presenting users with the current state of the water environment and suggestions based on the analysis results,

[0870] A warning system for detecting rapid environmental changes and providing warnings,

[0871] A system that includes this.

[0872] (Claim 2)

[0873] The system according to claim 1, comprising a prediction means for predicting future environmental changes based on past data using machine learning technology.

[0874] (Claim 3)

[0875] The system according to claim 1, comprising communication means for minimizing delays, ensuring reliable communication, and enabling rapid control using advanced data communication technology.

[0876] "Application example 2 when combining with an emotional engine"

[0877] (Claim 1)

[0878] A data acquisition method for analyzing external environmental information acquired in real time and calculating optimal foundational conditions,

[0879] Based on the analysis results, a control means for controlling the liquid temperature and associated equipment is provided.

[0880] A display means for showing users the current facility status and suggestions,

[0881] An anomaly detection means for detecting abnormal external conditions and issuing warnings,

[0882] A means of recognizing emotions to understand the emotional state of users and adjust the environmental design accordingly,

[0883] Environmental control means for adjusting lighting and sound to provide individualized experiences,

[0884] A system that includes this.

[0885] (Claim 2)

[0886] The system according to claim 1, comprising a predictive means for predicting future changes by integrating highly accurate environmental information and past trends.

[0887] (Claim 3)

[0888] The system according to claim 1, comprising communication means for rapid and highly reliable communication, enabling real-time data analysis and control. [Explanation of Symbols]

[0889] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A data acquisition method for analyzing external environmental data acquired in real time and calculating optimal water environment conditions, Based on the analysis results, a control means for controlling the pool water temperature and associated equipment is provided, A display means for showing the current pool status and suggestions to the user, An anomaly detection means for detecting abnormal weather conditions and issuing warnings, A system that includes this.

2. The system according to claim 1, comprising a prediction means for integrating highly accurate weather information and environmental data and predicting future environmental changes by referring to past trends.

3. The system according to claim 1, comprising communication means for achieving low-latency and highly reliable data communication using 5G communication technology and for rapid device control.

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