System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving physical condition information input by a user; means for receiving sickness level information set by the user; means for receiving drunk place information input by the user; means for calculating an appropriate amount of alcohol based on the received information; and means for issuing an alert based on the calculated amount of alcohol.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] When drinking alcohol, it can be difficult to maintain an appropriate level of alcohol while enjoying a drink, which can lead to overdrinking or other mistakes. In particular, users may not be able to manage their own level of intoxication, which increases the risk of becoming ill or engaging in unexpected behavior. It can also lead to missing the last train or forgetting important topics. Therefore, there is a need for a system that allows users to enjoy drinking safely while maintaining an ideal level of intoxication. [Means for solving the problem]

[0005] The present invention provides a system that receives information on a user's physical condition, drunkenness level, and drinking location, and calculates the appropriate amount of alcohol based on this information. Specifically, the system includes a means for calculating the amount of alcohol consumed based on the received information and issuing an alert based on the calculated amount. The system also includes a means for issuing a last train alert based on the last train time set by the user, a means for receiving alcohol consumption information input by the user while drinking in real time, and a means for providing appropriate assistance information. The system also includes a means for recording drinking conversations using voice recognition and providing the minutes, and a means for receiving information on the user's constitution and calculating the amount of alcohol consumed. This allows users to enjoy drinking safely while maintaining an ideal level of drunkenness.

[0006] "Physical condition information" is information that indicates the user's current health condition and the conditions suitable for drinking alcohol, and includes data such as fatigue level, whether or not the user is ill, and sleep duration.

[0007] "Drunkenness level information" is information indicating the degree of drunkenness the user desires, and is expressed in categories such as "slightly drunk," "very drunk," and "very drunk."

[0008] "Drinking location information" is information about the location where the user plans to drink alcohol, and includes data such as home, a friend's house, a restaurant, or outdoors.

[0009] "Amount of alcohol" is a numerical value that indicates the specific amount of alcohol that a user should consume, and is calculated appropriately.

[0010] An "alert" is a warning or instruction message that is sent to the user based on set conditions, and includes information such as "Be careful not to drink too much" or "The last train is approaching."

[0011] The "Last Train Alert" is a warning message that notifies the user when the last train time that the user has set is approaching.

[0012] "Alcohol intake information" is information about the type and amount of alcohol consumed that is input by the user while drinking.

[0013] "Assistance information" refers to supplementary information provided to help users have an appropriate drinking experience, including, for example, recommended drinking methods and suggestions for suitable snacks.

[0014] "Voice recognition" is a technology that automatically analyzes the content of a user's conversation and records it as text data.

[0015] A "minutes" is a document that records conversations that took place while drinking and is provided in a form that can be referenced later.

[0016] "Constitution information" refers to information relating to the individual physical characteristics of a user, including, for example, alcohol tolerance and allergy information. [Brief explanation of the drawings]

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

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

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

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

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

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

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

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0034] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process 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.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The embodiments for carrying out the present invention will be described in detail below.

[0039] This invention is a system that calculates the appropriate amount of alcohol to drink based on the user's physical condition, drunkenness level, and drinking location information, and issues an alert in real time. This system helps users enjoy drinking while maintaining an ideal level of drunkenness. The system is primarily implemented using the user's smartphone or wearable device (terminal) and a server running on the backend.

[0040] 1. Initial Setup and User Authentication

[0041] Collection of User Information

[0042] When a user installs the application on their device and launches it for the first time, an initial setup screen appears, where the user enters information such as their name, weight, gender, and drinking experience.

[0043] Sending and storing user information

[0044] The device sends the input information to a server, which stores the received information in a database and uses it as the basis for calculating the appropriate alcohol content.

[0045] 2. Input today's situation

[0046] Enter your current physical condition, where you're drinking, and what you plan to eat

[0047] The user inputs their physical condition on the day (e.g., normal, tired, etc.) and the location where they will be drinking (e.g., at home, a friend's house, a restaurant, etc.), as well as the predicted drinks menu (e.g., beer, wine, shochu, etc.).

[0048] Sending and storing status information

[0049] The terminal sends this input information to the server, which then stores the received information in a database.

[0050] 3. Alcohol calculation and alert settings

[0051] Calculating the appropriate amount of alcohol

[0052] The server analyzes the collected user information, physical condition information, and drinking location information based on an algorithm, and calculates the appropriate amount of alcohol to reach the level of intoxication set by the user.

[0053] Alert settings and notifications

[0054] Based on the calculated alcohol content, the server sets an alert and sends it to the device, where the user can receive the alert in real time.

[0055] 4. Real-time assistance while drinking

[0056] Input and record alcohol intake

[0057] Users input the type and amount of alcohol they wish to drink into the device, which then transmits the information to a server, which records it in real time in a database.

[0058] Alcohol intake check and assistance provided

[0059] The server compares the current amount of alcohol consumed with the set amount in real time based on the amount of alcohol consumed entered by the user, and if necessary, sends assistance information such as "recommended snacks" or "warnings about drinking too much" to the user's device.

[0060] 5. Last train alerts and meeting minutes

[0061] Last train time setting and alert notification

[0062] When a user inputs the last train time into the device, the information is sent to the server, which then generates an alert and sends it to the device to notify the user one hour or 30 minutes before the last train.

[0063] Minute creation using voice recognition

[0064] Conversations made while drinking are recorded using the device's voice recognition function, and the data is sent to a server, which generates minutes based on the data and stores them for later reference by the user.

[0065] 6. Follow-up after drinking

[0066] Follow-up notification the next day

[0067] The next morning, the device sends the user a follow-up notification asking, "Did you drink moderately yesterday?" If the user answers "yes" or "no," that feedback is sent to the server.

[0068] Save your feedback and apply it next time

[0069] The server stores the received feedback in a database and reflects it in the next alcohol content calculation.

[0070] This allows users to enjoy drinking safely and healthily while maintaining an ideal level of intoxication.

[0071] The processing flow will be explained below.

[0072] Step 1:

[0073] Enter and submit user information

[0074] When a user launches the app for the first time, they enter information such as their name, weight, gender, and drinking experience.

[0075] The terminal transmits the entered user information to the server.

[0076] Step 2:

[0077] Saving user information

[0078] The server stores the received user information in a database.

[0079] Step 3:

[0080] Input of today's situation

[0081] The user inputs their physical condition on the day, the location where they will be drinking, and the planned drinking menu into the device.

[0082] The terminal transmits this information to the server.

[0083] Step 4:

[0084] Save today's status information

[0085] The server stores the received physical condition information, drinking location information, and drinking menu information in a database.

[0086] Step 5:

[0087] Calculating alcohol content

[0088] The server calculates the ideal amount of alcohol for the day based on the user's weight, physical condition, drinking location, and past data.

[0089] When calculating, an algorithm is applied depending on the set drunkenness level (e.g. tipsy).

[0090] Step 6:

[0091] Alert Settings and Notifications

[0092] The server sets an alert based on the calculation results.

[0093] The device notifies the user of configured alerts.

[0094] Step 7:

[0095] Enter and submit alcohol intake

[0096] The user enters the type and amount of alcohol consumed into the device.

[0097] The terminal transmits the inputted information on the amount of alcohol consumed to the server.

[0098] Step 8:

[0099] Saving and reviewing alcohol intake information

[0100] The server stores the received alcohol intake information in a database.

[0101] The server checks the current amount of alcohol consumed and calculates assistance information if the amount is below the appropriate level.

[0102] Step 9:

[0103] Assistance Information Notification

[0104] The server transmits assistance information during drinking to the terminal.

[0105] The device notifies the user of assistance information.

[0106] When the amount of alcohol consumed approaches the set limit, the user will receive an alert such as "Be careful not to drink too much."

[0107] Step 10:

[0108] Last train alert settings and notifications

[0109] The user sets the last train time on the device and sends that information to the server.

[0110] The server generates a last train alert before the last train and sends it to the terminal.

[0111] The device will notify the user of the last train alert.

[0112] Step 11:

[0113] Generate meeting minutes

[0114] During the drinking party, the device transmits voice data to the server.

[0115] The server uses voice recognition technology to convert the conversation into text data and generate minutes.

[0116] Step 12:

[0117] Next day follow-up

[0118] The next morning, the device will send the user a follow-up notification asking, "Did you drink moderate amounts of alcohol yesterday?"

[0119] The user enters the answer and the device sends the information to the server.

[0120] The server stores the received feedback in a database and reflects it in the next alcohol content calculation.

[0121] By following these steps, users can enjoy safe and enjoyable drinking while taking proper control of their drinking.

[0122] Example 1

[0123] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0124] In modern society, many people enjoy drinking alcohol, but there are concerns about the health risks associated with excessive drinking and inappropriate drinking habits. Furthermore, there are also problems such as forgetting the last train and having difficulty getting home, and issues with efficiency when taking minutes while drinking. In these situations, there is a need for a system that can manage appropriate drinking amounts in real time and provide appropriate assistance to users.

[0125] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0126] In this invention, the server includes a means for receiving physical condition information input by the user, a means for receiving drunkenness level information set by the user, and a means for receiving drinking location information input by the user. This allows the server to calculate the appropriate amount of alcohol based on the collected information, enabling the user to enjoy drinking safely while maintaining an ideal drunkenness level.

[0127] The server also includes a means for receiving alcohol intake information input by the user and checking the current alcohol intake in real time, a means for providing appropriate assistance information, a means for inputting the time of the last train, a means for issuing a last train alert based on the time of the last train, and a means for recording conversations while drinking using voice recognition and generating minutes. This enables the server to comprehensively manage the user's behavior while drinking and also assist with secondary tasks (e.g., managing the time to return home and creating minutes).

[0128] "Physical condition information" is information that indicates the user's current health condition and mood.

[0129] "Drunkenness level information" is information that indicates the level of drunkenness that the user wants to achieve through drinking.

[0130] "Drinking location information" is information about the location where the user plans to drink alcohol.

[0131] "Amount of alcohol" indicates the total amount of alcohol the user plans to drink.

[0132] An "alert" is a notification or warning that prompts a user to take a specific action.

[0133] "Alcohol intake information" is information about the type and amount of alcohol actually consumed by the user.

[0134] "Assistance information" is advice and recommendations to support users in drinking alcohol safely and effectively.

[0135] The "last train time" refers to the last operating time of the public transportation used by the user.

[0136] "Speech recognition" is a technology that analyzes a user's voice and converts it into a format such as text.

[0137] Minutes are documents that record the contents of meetings or conversations and can be referenced later.

[0138] A "database" is a system that stores information systematically and allows it to be quickly searched and retrieved as needed.

[0139] A "server" is a computer system that processes and manages data and communicates with other devices over a network.

[0140] A "terminal" is a device that a user can directly operate to input or receive information.

[0141] The present invention is a system that helps users enjoy drinking alcohol while maintaining an ideal level of intoxication. This system is primarily realized by the user's smartphone or wearable device (terminal) and a server running on the backend.

[0142] The operation of this system will be explained in detail below. First, the user installs the application on their device, and the initial setup screen is displayed when the application is launched for the first time. The user enters physical information such as name, weight, gender, and drinking history, and the device sends this information to the server. The server stores the received information in a database and uses it as basic data.

[0143] Next, the user enters information about the situation on the day, such as their physical condition, the place where they will be drinking, and the menu they plan to have. This information is also sent from the device to the server and stored in a database. The server uses an algorithm based on the collected user information and the situation information for that day to calculate the appropriate amount of alcohol to reach the level of intoxication set by the user.

[0144] Based on the calculated alcohol content, the server generates an alert and sends it to the device. The user can receive the alert in real time while drinking. Furthermore, when the user inputs the type and amount of alcohol consumed into the device each time, the device sends that information to the server, which records the amount consumed in a database in real time and provides assistance information such as "recommended snacks" or "warnings against drinking too much" as needed.

[0145] When a user inputs the last train time, the information is sent from the device to the server, and the server generates an alert one hour or 30 minutes before the last train and sends it to the device to notify the user.

[0146] It is also possible to record conversations while drinking using a voice recognition function. The device sends the voice data to a server, which analyzes it and generates minutes, which are then stored in a database for later reference by the user.

[0147] The next morning, the server sends a follow-up notification to the device asking, "Did you drink a reasonable amount of alcohol yesterday?" If the user answers "yes" or "no," that feedback will be reflected in the next alcohol calculation.

[0148] Here is an example prompt:

[0149] "Please enter your health condition, drinking location, and planned drinking menu for today. For example, please enter your health condition as 'normal', your drinking location as 'izakaya', and your planned menu as 'beer and sake'."

[0150] This allows users to easily input information and enables the system to effectively support the user's drinking experience.

[0151] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0152] Step 1:

[0153] Initial Setup and User Authentication

[0154] The user installs the application on their device and the initial setup screen is displayed when they launch it for the first time.

[0155] Input: The user inputs physical information such as name, weight, gender, and drinking experience.

[0156] The terminal temporarily stores the input information in memory.

[0157] The device transmits the stored information to the server.

[0158] The server stores the received information in a database.

[0159] Output: The server sends a confirmation message to the terminal that the save is complete, and the terminal displays it to the user.

[0160] Step 2:

[0161] Today's situation input

[0162] The user inputs information such as their physical condition on the day, where they will be drinking, and the planned menu into the terminal.

[0163] Input: Physical condition information (e.g., normal), Drinking location information (e.g., izakaya), Drinking menu information (e.g., beer)

[0164] The terminal temporarily stores the input information in memory.

[0165] The device transmits the stored information to the server.

[0166] The server stores the received information in a database.

[0167] Output: The server sends a confirmation message to the terminal that the save is complete, and the terminal displays it to the user.

[0168] Step 3:

[0169] Alcohol calculation and alert settings

[0170] The server uses an algorithm to calculate the appropriate amount of alcohol based on collected user information, physical condition information, and drinking location information.

[0171] Input: User information, physical condition information, drinking location information

[0172] Data processing: Algorithm-based data analysis

[0173] Output: Calculated alcohol content

[0174] The server generates an alert based on the calculated alcohol content and sends it to the device.

[0175] The device notifies the user of alerts in real time.

[0176] Step 4:

[0177] Real-time assistance while drinking

[0178] The user inputs the type and amount of alcohol consumed into the terminal each time.

[0179] Input: type and amount of alcohol (e.g. 500ml beer)

[0180] The terminal temporarily stores the input information in memory.

[0181] The terminal transmits the input information to the server.

[0182] The server records the received alcohol intake information in a database.

[0183] The server compares the current amount of alcohol consumed with the set limit and generates assistance information as needed.

[0184] Output: Assistance information (e.g., recommended snacks, warnings against drinking too much)

[0185] The server sends the assistance information to the terminal.

[0186] The terminal notifies the user of the received information.

[0187] Step 5:

[0188] Last train alert and meeting minutes

[0189] The user enters the last train time into the terminal (e.g., 23:00).

[0190] Input: Last train time information

[0191] The terminal transmits the input information to the server.

[0192] The server stores the received information in a database.

[0193] The server generates an alert and sends it to the terminal one hour or 30 minutes before the last train.

[0194] Output: Last train alert notification

[0195] The terminal notifies the user of the received alert.

[0196] Step 6:

[0197] Follow-up after drinking

[0198] The next morning, the server sends a follow-up notification to the device asking, "Did you drink an appropriate amount of alcohol yesterday?"

[0199] Output: Follow-up notification

[0200] The user answers "yes" or "no."

[0201] Input: User feedback

[0202] The terminal transmits the user's answer to the server.

[0203] The server stores the received feedback in a database.

[0204] The feedback will be reflected in the next alcohol calculation.

[0205] Through these specific processing steps, users can enjoy drinking safely and healthily while maintaining an ideal level of intoxication.

[0206] (Application example 1)

[0207] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0208] In modern society, there is a lack of ways for users to enjoy drinking alcohol while maintaining an appropriate amount of alcohol intake and enjoying content that is optimal for their situation. In particular, there is a need for a means to provide entertainment content that is individually optimized based on the user's physical condition and drinking situation. There is also a need for a system that allows users to enjoy optimal content while managing their drinking amount and physical condition in real time while drinking.

[0209] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0210] In this invention, the server includes means for receiving physical condition information input by the user, means for receiving drunkenness level information set by the user, means for receiving drinking location information input by the user, means for calculating the appropriate amount of alcohol based on the received information, means for issuing an alert based on the calculated amount of alcohol, and content recommendation means for recommending optimal content based on the user's drinking status and physical condition. This allows the user to enjoy entertainment content optimal for their situation at any given time while safely and comfortably enjoying alcohol.

[0211] "Physical condition information" is data indicating the user's physical condition, such as normal, tired, or unwell.

[0212] "Drunkenness level information" is data indicating the ideal level of drunkenness set by the user, such as wanting to get a little drunk, wanting to get tipsy, or not wanting to get drunk.

[0213] "Drinking location information" is data relating to the location where the user drinks alcohol, such as at home, at a friend's house, or at a restaurant.

[0214] The "appropriate amount of alcohol" is the amount of alcohol consumed that a user needs to maintain an ideal level of intoxication, calculated based on the user's physical condition, level of intoxication, and drinking location information.

[0215] An "alert" is a warning or suggestion that the system notifies the user, such as warning them to be careful not to drink too much or informing them when to have their next drink.

[0216] "Content recommendation means" refers to algorithms and technologies for recommending optimal entertainment content based on a user's physical condition, drunkenness level, drinking location, and past viewing history.

[0217] The following is a detailed description of an embodiment of the present invention. The present invention is a system that calculates the appropriate amount of alcohol to drink based on information about the user's physical condition, drunkenness level, and drinking location, and issues an alert in real time. The system also has a function to recommend optimal content based on the user's drinking habits and physical condition. This system is primarily implemented using the user's device (a smartphone or wearable device) and a server operating in the backend.

[0218] 1. Initial Setup and User Authentication

[0219] Collection of User Information

[0220] When the application is first installed and launched, an initial setup screen appears, where the user enters information such as their name, weight, gender, and drinking experience.

[0221] Sending and storing user information

[0222] The device sends the input information to a cloud server, which then stores it in a database, which is used as the basis for calculating the appropriate alcohol content.

[0223] 2. Input today's situation

[0224] Enter your current physical condition, where you're drinking, and what you plan to eat

[0225] Users input their physical condition on the day, the location where they will be drinking, and the planned drinking menu into the device.

[0226] Sending and storing status information

[0227] The device sends this input information to a cloud server, which then stores the received information in a database.

[0228] 3. Alcohol calculation and alert settings

[0229] Calculating the appropriate amount of alcohol

[0230] The server uses an algorithm to analyze the collected user information, physical condition information, and drinking location information, and calculates the appropriate amount of alcohol to reach the level of intoxication set by the user.

[0231] Alert settings and notifications

[0232] Based on the calculated alcohol content, the server sets an alert and sends it to the user's device, where the user can receive the alert in real time.

[0233] 4. Real-time assistance while drinking

[0234] Input and record alcohol intake

[0235] Users input the type and amount of alcohol they wish to drink into the device, which then sends the information to a cloud server, which records it in a database in real time.

[0236] Alcohol intake check and assistance provided

[0237] The server compares the current amount of alcohol consumed with the set amount in real time based on the amount of alcohol consumed entered by the user, and if necessary, sends assistance information such as "recommended snacks" or "warnings about drinking too much" to the device.

[0238] 5. Content Recommendation

[0239] Recommending the right content

[0240] The server recommends optimal content based on the user's drinking habits and physical condition, using Python®-based machine learning models (such as TENSORFLOW® and PyTorch) to reference the user's past viewing history and data on similar users.

[0241] Content Notification

[0242] The server sends a list of recommended content to the user's device, which can then receive the list in real time.

[0243] Hardware and software used

[0244] Hardware: Smartphone (iOS or ANDROID device)

[0245] software:

[0246] Cloud services (AWS (registered trademark) and Google (registered trademark) Cloud)

[0247] Database system (Firestore, MySQL (registered trademark))

[0248] Machine learning frameworks (TensorFlow, PyTorch)

[0249] Specific examples

[0250] Below are some example prompts to input to a generative AI model:

[0251] Username: Yamada Taro

[0252] Weight: 70kg

[0253] Gender: Male

[0254] Drinking experience: Intermediate

[0255] Today's mood: Normal

[0256] Drinking location: Home

[0257] Planned drinks menu: beer, wine

[0258] Generate a list of recommended movies, music playlists, and videos for users who are in normal health and drinking beer and wine at home.

[0259] As described above, the present invention is a system that allows users to enjoy drinking safely and healthily while maintaining an ideal level of intoxication, and to enjoy entertainment content that is optimal for the situation at hand.

[0260] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0261] Step 1:

[0262] Entering and collecting user information

[0263] When a user installs the application on a device, they are prompted to enter information such as their name, weight, gender, and drinking history as initial settings. This data is sent from the device to a cloud server, which then stores it in a database.

[0264] Input: Name, weight, gender, drinking experience, etc.

[0265] Output: User information stored in the database

[0266] How it works: When a user enters information such as their name, weight, gender, and drinking experience into their smartphone and presses the "Save" button, the data is sent to a cloud server, where it is recorded in a database.

[0267] Step 2:

[0268] Today's situation input

[0269] The user inputs information about their physical condition for the day, where they will be drinking, and the planned drinking menu into the device. The device then sends this information to the cloud server, which then stores it in a database.

[0270] Input: Today's health information, drinking location information, planned drinking menu

[0271] Output: Current status information stored in the database

[0272] How it works: When a user enters their current physical condition (e.g., "normal"), where they are drinking (e.g., "home"), and what they plan to drink (e.g., "beer, wine") into their smartphone and presses the "Save" button, the data is sent to the cloud server, which then records the data in a database.

[0273] Step 3:

[0274] Calculating the right amount of alcohol

[0275] The server uses an algorithm to analyze collected user information, physical condition information, and drinking location information to calculate the appropriate amount of alcohol.

[0276] Input: User information, health information, drinking location information

[0277] Output: Calculation result of appropriate amount of alcohol

[0278] Specific operation: The server retrieves user information and today's situation information from the database, and then applies an algorithm within the program (such as a linear regression model with specific coefficients) based on this information to calculate the appropriate amount of alcohol the user can safely drink.

[0279] Step 4:

[0280] Alert settings and notifications

[0281] The server sets an alert based on the appropriate alcohol content and sends it to the device, which the user receives in real time.

[0282] Input: Calculation result of appropriate alcohol amount

[0283] Output: Alert notification to user's terminal

[0284] Specific operation: Based on the calculated appropriate amount of alcohol, the server determines the maximum amount of alcohol the user should drink, and if the limit is exceeded, an alert message such as "Be careful not to drink too much" is sent to the device. The alert is displayed on the user's device in the form of a push notification or other means.

[0285] Step 5:

[0286] Alcohol intake entry and real-time assistance

[0287] The user inputs the type and amount of alcohol consumed into the device, which is then sent to the server, where it is recorded in a database in real time. The server then compares the current amount of alcohol consumed with the set amount, and sends assistance information to the device as needed.

[0288] Input: Type and amount of alcohol consumed

[0289] Output: Assistance information based on current alcohol intake

[0290] How it works: The user enters the type and amount of alcohol they have consumed into their smartphone, and the information is sent to a cloud server. The server records this information in a database in real time, manages the appropriate amount set, and sends assistance notifications to the device as needed (such as "recommended snacks" or "warnings against drinking too much").

[0291] Step 6:

[0292] Content recommendations and notifications

[0293] The server recommends the most suitable content based on the user's drinking habits and physical condition. This recommendation is made using a Python-based machine learning model (such as TensorFlow or PyTorch). A list of recommended content is sent to the user's device.

[0294] Input: User's drinking status, physical condition information

[0295] Output: A list of recommended content

[0296] How it works: The server retrieves the user's drinking history and physical condition information from the database, and then uses a machine learning model (such as TensorFlow or PyTorch) to recommend the most suitable content (movies, music, videos, etc.) for the user. The recommendation results are sent to the user's smartphone, and the user can receive a list of content.

[0297] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0298] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The embodiments for carrying out the present invention will be described in detail below.

[0299] This invention combines an emotion engine with a system that calculates the appropriate amount of alcohol to drink based on the user's physical condition, drunkenness level, and drinking location information, and issues alerts in real time. The emotion engine recognizes the user's emotional state from their facial expressions and voice, and uses this information to further optimize the drinking experience. This system is realized using the user's smartphone or wearable device (terminal) and a server running on the backend.

[0300] 1. Initial Setup and User Authentication

[0301] Collection of User Information

[0302] When a user installs the application on their device and launches it for the first time, an initial setup screen appears, where the user enters information such as their name, weight, gender, and drinking experience.

[0303] Sending and storing user information

[0304] The device sends the entered user information to a server, which then stores the received information in a database, which is used as the basis for calculating the appropriate alcohol content.

[0305] 2. Input today's situation

[0306] Enter your current physical condition, where you're drinking, and what you plan to eat

[0307] The user inputs their physical condition on the day (e.g., normal, tired, etc.) and the location where they will be drinking (e.g., at home, a friend's house, a restaurant, etc.), as well as the predicted drinks menu (e.g., beer, wine, shochu, etc.).

[0308] Sending and storing status information

[0309] The terminal sends this input information to the server, which then stores the received information in a database.

[0310] 3. Alcohol calculation and alert settings

[0311] Calculating the appropriate amount of alcohol

[0312] The server analyzes the collected user information, physical condition information, and drinking location information based on an algorithm, and calculates the appropriate amount of alcohol to reach the level of intoxication set by the user.

[0313] Alert settings and notifications

[0314] Based on the calculated alcohol content, the server sets an alert and sends it to the device, where the user can receive the alert in real time.

[0315] 4. Real-time assistance while drinking

[0316] Input and record alcohol intake

[0317] Users input the type and amount of alcohol they wish to drink into the device, which then transmits the information to a server, which records it in real time in a database.

[0318] Alcohol intake check and assistance provided

[0319] The server compares the current amount of alcohol consumed with the set amount in real time based on the amount of alcohol consumed entered by the user, and if necessary, sends assistance information such as "recommended snacks" or "warnings about drinking too much" to the user's device.

[0320] 5. Implementing the Emotion Engine

[0321] Recognition of emotional states

[0322] The device analyzes the user's facial expressions and voice in real time, and the emotion engine recognizes the user's emotional state (e.g., happy, stressed, etc.).

[0323] Transmission and use of emotional information

[0324] The device sends the recognized emotional information to the server, which then uses that emotional information to further adjust the amount of alcohol consumed and the assistance information provided, for example, recommending relaxing snacks if the user is feeling stressed.

[0325] 6. Last Train Alerts and Meeting Minutes

[0326] Last train time setting and alert notification

[0327] When a user inputs the last train time into the device, the information is sent to the server, which then generates an alert and sends it to the device to notify the user one hour or 30 minutes before the last train.

[0328] Minute creation using voice recognition

[0329] Conversations made while drinking are recorded using the device's voice recognition function, and the data is sent to a server, which generates minutes based on the data and stores them for later reference by the user.

[0330] 7. Follow-up after drinking

[0331] Follow-up notification the next day

[0332] The next morning, the device sends the user a follow-up notification asking, "Did you drink moderately yesterday?" If the user answers "yes" or "no," that feedback is sent to the server.

[0333] Save your feedback and apply it next time

[0334] The server stores the received feedback in a database and reflects it in the next alcohol content calculation.

[0335] This allows users to properly manage their drinking while receiving optimal assistance according to their emotional state, allowing them to enjoy drinking in a fun and safe way.

[0336] The processing flow will be explained below.

[0337] Step 1:

[0338] Enter and submit user information

[0339] When a user launches the app for the first time, they enter information such as their name, weight, gender, and drinking experience.

[0340] The terminal transmits the entered user information to the server.

[0341] Step 2:

[0342] Saving user information

[0343] The server stores the received user information in a database.

[0344] Step 3:

[0345] Input of today's situation

[0346] The user inputs their physical condition on the day, the location where they will be drinking, and the planned drinking menu into the device.

[0347] The terminal transmits this information to the server.

[0348] Step 4:

[0349] Save today's status information

[0350] The server stores the received physical condition information, drinking location information, and drinking menu information in a database.

[0351] Step 5:

[0352] Calculating alcohol content

[0353] The server calculates the ideal amount of alcohol for the day based on the user's weight, physical condition, drinking location, and past data.

[0354] When calculating, an algorithm is applied depending on the set drunkenness level (e.g. tipsy).

[0355] Step 6:

[0356] Alert Settings and Notifications

[0357] The server sets an alert based on the calculation results.

[0358] The device notifies the user of configured alerts.

[0359] Step 7:

[0360] Enter and submit alcohol intake

[0361] The user enters the type and amount of alcohol consumed into the device.

[0362] The terminal transmits the inputted information on the amount of alcohol consumed to the server.

[0363] Step 8:

[0364] Saving and reviewing alcohol intake information

[0365] The server stores the received alcohol intake information in a database.

[0366] The server checks the current amount of alcohol consumed and calculates assistance information if the amount is below the appropriate level.

[0367] Step 9:

[0368] Assistance Information Notification

[0369] The server transmits assistance information during drinking to the terminal.

[0370] The device notifies the user of assistance information.

[0371] When the amount of alcohol consumed approaches the set limit, the user will receive an alert such as "Be careful not to drink too much."

[0372] Step 10:

[0373] Recognizing and transmitting emotional states

[0374] The device analyzes the user's facial expressions and voice in real time, and the emotion engine recognizes the user's emotional state (e.g., happy, stressed, etc.).

[0375] The recognized emotion information is sent to the server.

[0376] Step 11:

[0377] Adjustment based on emotional state

[0378] The server further adjusts the amount of alcohol consumed and assistance information based on the emotional information received.

[0379] For example, if a user is feeling stressed, we will recommend snacks that have a relaxing effect.

[0380] Step 12:

[0381] Last train alert settings and notifications

[0382] The user sets the last train time on the device and sends that information to the server.

[0383] The server generates a last train alert before the last train and sends it to the terminal.

[0384] The device will notify the user of the last train alert.

[0385] Step 13:

[0386] Generate meeting minutes

[0387] During the drinking party, the device transmits voice data to the server.

[0388] The server uses voice recognition technology to convert the conversation into text data and generate minutes.

[0389] Step 14:

[0390] Next day follow-up

[0391] The next morning, the device will send the user a follow-up notification asking, "Did you drink moderate amounts of alcohol yesterday?"

[0392] The user enters the answer and the device sends the information to the server.

[0393] The server stores the received feedback in a database and reflects it in the next alcohol content calculation.

[0394] By following these steps, users can enjoy safe drinking while properly managing their drinking and receiving optimal assistance based on their emotional state.

[0395] Example 2

[0396] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0397] Conventional alcohol consumption management systems only managed alcohol intake based on the user's physical condition and level of intoxication, and had the function of issuing an alert, but this did not respond appropriately to the user's emotions or environment, resulting in problems with satisfaction and safety. Furthermore, there was a need for a more accurate way to manage alcohol intake by taking environmental and biological information into account.

[0398] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0399] In this invention, the server includes a means for receiving biometric information input by the user, a means for receiving satisfaction level information set by the user, and a means for receiving environmental information input by the user, thereby enabling calculation of an appropriate alcohol intake amount based on the user's physical condition, emotions, and environment, and providing assistance and alerts in real time.

[0400] "Biometric information" refers to data related to the user's physical condition and health, including, for example, weight, gender, age, past drinking history, and physical condition.

[0401] "Satisfaction information" refers to data that indicates the level of intoxication desired by the user and their expectations regarding drinking, including emotional states such as "fun" or "want to relax."

[0402] "Environmental information" refers to data about the location where the user drinks and the circumstances at the time, including, for example, the location where the drink is taken (home, restaurant, etc.), the atmosphere of the location, and the presence of other people.

[0403] "Intake" refers to the amount of alcohol a user should drink, including an appropriate amount calculated based on the user's physical condition, satisfaction, and environmental information.

[0404] "Emotional state" refers to the user's current psychological and emotional state, and includes information such as "happy," "stressed," and "relaxed."

[0405] "Alerts" refer to warning or suggestion messages sent to users, such as "Be careful not to drink too much" or "Recommended snacks."

[0406] "Support information" refers to information that helps users drink alcohol appropriately, including, for example, advice on adjusting future drinking amounts, recommended meals, and advice on the pace at which to drink.

[0407] This invention combines an emotion engine with a system that calculates the appropriate amount of alcohol intake based on biometric information, satisfaction information, and environmental information input by the user and issues alerts in real time. This system is realized using the user's smartphone or wearable device (terminal) and a server running on the backend.

[0408] Initial Setup and User Authentication

[0409] When a user installs the application on their device and launches it for the first time, an initial setup screen appears. The user enters biometric information such as their name, weight, gender, age, and drinking experience. The device sends this information to a server, which stores it in a database. This information is used as the basis for calculating appropriate alcohol intake.

[0410] Today's situation input

[0411] The user inputs environmental information into the device, such as their physical condition on the day (e.g., normal, tired, feeling a bit under the weather, etc.) and the location where they will be drinking (e.g., at home, a friend's house, a restaurant, etc.). They also input their predicted drinking menu (e.g., two beers and one glass of wine). The device sends this situation information to the server, which then stores the received information in a database.

[0412] Alcohol calculation and alert settings

[0413] The server runs an algorithm based on stored user information, physical condition information, drinking location information, and predicted drinking menu to calculate the appropriate amount of alcohol to reach the user's desired level of satisfaction. The server sets an alert based on the calculated appropriate amount of alcohol, and the device notifies the user in real time. For example, it displays messages such as "Only one more beer" or "Be careful not to drink too much!"

[0414] Real-time assistance while drinking

[0415] The user inputs the type and amount of alcohol consumed into the device. The device then sends the input information to the server, which records it in a database in real time. The server compares the user's current alcohol intake with a preset appropriate drinking amount, and notifies the device of assistance information such as "recommended snacks" or "warnings against drinking too much" as needed.

[0416] Implementing the Emotion Engine

[0417] The device analyzes the user's facial expressions and voice in real time. For example, it uses the smartphone's camera and microphone to analyze the user's facial expressions and tone of voice. The emotion engine recognizes the user's emotional state (e.g., happy, stressed, etc.) and generates information about it. The device sends the recognized emotion information to the server, which then adjusts the amount of alcohol consumed and customizes assistance information based on that emotion information. For example, if the user is feeling stressed, it can recommend snacks that have a relaxing effect.

[0418] Last train alert and meeting minutes creation

[0419] The user enters the time of the last train into the device. For example, if the user enters "The last train is at 10:30 p.m.", the server saves that information in a database. The server generates an alert one hour or 30 minutes before the last train, and the device notifies the user. The device also uses a voice recognition function to record conversations that were taking place while drinking. For example, the smartphone's microphone can be used to convert the conversation into text, and the server can generate and save minutes based on that data.

[0420] Follow-up after drinking

[0421] The next morning, the device sends the user a question: "Were you satisfied with the amount of alcohol you drank yesterday?" The user answers "yes" or "no," and the feedback is sent to the server. The server stores the feedback in a database and reflects it in the next alcohol amount calculation. For example, it may fine-tune the suggested amount of alcohol based on the previous feedback.

[0422] Examples:

[0423] A user named "Taro" enters his weight as 70 kg, his gender as male, his drinking experience, and his preferred types of alcohol as beer and wine. The device sends this information to the server, which then stores it in a database.

[0424] The user inputs, "I'm feeling fine today, I plan to drink at home, and my planned menu is two beers and one glass of wine." The device sends this information to the server, which then stores it in a database.

[0425] The device's camera detects the user's smile, and the emotion engine recognizes it as "fun." The device then sends this information to the server, which then provides "assistance information perfect for a fun drinking party."

[0426] A user sets the last train time to 23:30. The server sends an alert from the device at 22:30 and 23:00.

[0427] Example prompt sentence:

[0428] "User information: Taro, Weight: 70kg, Gender: Male, Drinking experience: Yes. Please calculate the appropriate amount of alcohol."

[0429] "The user has entered their current health state as 'normal', their drinking location as 'home', and their planned menu as '2 beers, 1 glass of wine'. Create appropriate alerts and assistance information."

[0430] "The user entered the last train time as 23:30. Please send an alert 1 hour and 30 minutes before the last train."

[0431] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0432] Processing Steps

[0433] Step 1: Initial Setup and User Authentication

[0434] 1. When a user installs the application on their device and launches it for the first time, an initial setup screen will appear.

[0435] 2. The user enters biometric information such as name, weight, gender, age, and drinking experience.

[0436] Input: User information (name, weight, gender, age, drinking experience)

[0437] Output: User information data

[0438] 3. The device sends this information to the server, and the server stores the received information in a database.

[0439] Data processing / calculation: Saving user information

[0440] Step 2: Input your current situation

[0441] 1. The user inputs environmental information into the device, such as their physical condition on the day (e.g., normal, tired, feeling a bit like a cold, etc.) and the location where they drank alcohol (e.g., at home, a friend's house, a restaurant, etc.).

[0442] Input: Health information, drinking location information

[0443] Output: Today's status information data

[0444] 2. Additionally, enter your predicted drinking menu (e.g., 2 beers, 1 wine).

[0445] Input: Drinking menu information

[0446] Output: Completed status information data

[0447] 3. The device sends this status information to the server, and the server stores the received information in a database.

[0448] Data processing / calculation: Saving status information

[0449] Step 3: Calculate alcohol intake and set alerts

[0450] 1. The server runs an algorithm based on stored user information, physical condition information, drinking location information, and predicted drinking menu.

[0451] Input: User information, physical condition information, drinking location information, drinking menu

[0452] Calculation: Calculating the appropriate amount of alcohol

[0453] Output: Appropriate alcohol content data

[0454] 2. Calculate the appropriate amount of alcohol to reach the user's desired satisfaction level and set an alert.

[0455] Data processing / calculation: Alert information generation

[0456] 3. The server sends the alert information to the device, and the device notifies the user in real time.

[0457] Input: Alert information

[0458] Output: User notification (e.g., "Only one more beer left!", "Don't drink too much!")

[0459] Step 4: Real-time assistance while drinking

[0460] 1. The user enters the type and amount of alcohol consumed into the device.

[0461] Input: Alcohol intake information

[0462] Output: Alcohol intake data

[0463] 2. The device sends the entered alcohol intake information to the server, which records it in a database in real time.

[0464] Data processing / calculation: Saving alcohol intake information

[0465] 3. The server compares the user's current drinking level with the predetermined appropriate drinking level and generates assistance information as needed.

[0466] Input: Alcohol intake data, set appropriate amount

[0467] Calculation: Check alcohol intake

[0468] Output: Assistance information

[0469] 4. The device notifies the user of the generated assistance information. For example, it may present "recommended snacks" or "be careful not to drink too much!"

[0470] Data processing / calculation: Notification of assistance information

[0471] Step 5: Implementing the Emotion Engine

[0472] 1. The device analyzes the user's facial expressions and voice in real time. For example, it uses the smartphone's camera and microphone to analyze the user's facial expressions and tone of voice.

[0473] Input: facial expression data, voice data

[0474] Computation: Recognizing Emotional States

[0475] Output: Emotional information

[0476] 2. The emotion engine recognizes the user's emotional state.

[0477] Data processing / calculation: Generating emotional information

[0478] 3. The device sends the recognized emotional information to the server, which then adjusts the amount of alcohol and customizes the assistance information based on the emotional information.

[0479] Input: Emotion information

[0480] Calculation: Alcohol content adjustment, customization of assistance information

[0481] Output: Adjusted alcohol content data, customized assistance information

[0482] Step 6: Last train alert and meeting minutes

[0483] 1. The user enters the last train time into the terminal.

[0484] Input: Last train time

[0485] Output: Last train time data

[0486] 2. The server saves the last train time information in a database.

[0487] Data processing / calculation: Saving the last train time

[0488] 3. The server generates an alert one hour or 30 minutes before the last train, and the device notifies the user.

[0489] Input: Saved last train time

[0490] Operation: Alert Generation

[0491] Output: User notification (e.g. "1 hour before last train", "30 minutes before last train")

[0492] 4. The device uses voice recognition to record conversations while drinking. For example, it uses a smartphone microphone to convert the conversation into text, and the server generates and stores minutes based on that data.

[0493] Input: Conversation data while drinking

[0494] Computing: Speech recognition and text conversion

[0495] Output: Generate minutes data

[0496] Step 7: Follow up after drinking

[0497] 1. The next morning, the device sends the user the question, "Were you satisfied with the amount of alcohol you drank yesterday?"

[0498] Input: Question submission (automatic)

[0499] Output: User notification

[0500] 2. The user answers with "yes" or "no" and the feedback is sent to the server.

[0501] Input: User feedback

[0502] Output: Feedback data

[0503] 3. The server stores the feedback in a database and uses it in the next alcohol content calculation.

[0504] Data processing / calculation: Saving and reflecting feedback

[0505] Output: Adjusted alcohol content data

[0506] (Application example 2)

[0507] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0508] There is a need for technology to manage appropriate alcohol consumption and reduce the health risks associated with excessive drinking. Another challenge is to provide optimal assistance based on the user's emotional state and further improve the drinking experience. Food delivery services also require management to ensure users do not drink too much and enjoy their food and drink appropriately. In addition, there is a need for comprehensive support, including information on the user's last train and their health the next day.

[0509] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0510] In this invention, the server includes: means for receiving physical condition information input by the user; means for receiving drunkenness level information set by the user; means for receiving drinking location information input by the user; means for calculating an appropriate alcohol intake based on the received information; means for issuing an alert based on the calculated alcohol intake; means for analyzing the user's facial expressions and voice while drinking and recognizing their emotional state; means for providing appropriate assistance information based on the recognized emotional state; and means for implementing the above means using a server operating in the backend and linking with the user's device. This makes it possible to appropriately manage the user's alcohol intake, provide assistance according to their emotions, notify them of last train alerts, and support an optimal drinking experience with food delivery services.

[0511] "User" refers to any person who uses the Services or Applications.

[0512] "Health information" refers to information that indicates the user's health condition and level of fatigue on that day.

[0513] "Drunkenness level information" refers to information that allows a user to set the level of drunkenness they desire.

[0514] "Drinking location information" refers to information about the location where a user drinks alcohol.

[0515] "Alcohol content" refers to the appropriate amount of alcohol a user should drink.

[0516] An "alert" refers to a warning or notification given to the user.

[0517] "Facial expression analysis" refers to technology that recognizes a user's facial expressions and analyzes their state.

[0518] "Voice analysis" refers to technology that recognizes a user's voice and analyzes their emotional state.

[0519] "Emotional state" refers to the emotion the user is feeling (e.g., happy, stressed, etc.).

[0520] "Assistance Information" refers to supplementary information or advice provided to the User.

[0521] "Back-end server" refers to a remote server that processes data in cooperation with user terminals.

[0522] "Terminal" refers to a device used by a user, such as a smartphone or wearable device.

[0523] System Overview

[0524] The system for implementing this invention receives information on the user's physical condition, drunkenness level, and drinking location, calculates the appropriate amount of alcohol based on that information, issues an alert in real time, and recognizes the user's emotional state through facial expression and voice analysis, and provides appropriate assistance based on that information.

[0525] Hardware and software used

[0526] Hardware: Smartphones, wearable devices (e.g., Apple Watch)

[0527] Software: Cloud services (Amazon Web Services, Google Cloud, etc.), databases (MySQL, PostgreSQL), emotion engines (Microsoft® Azure® Emotion API, Google Cloud Vision API)

[0528] Detailed program processing

[0529] The process performed by the server and the device is as follows:

[0530] Collection and storage of user information

[0531] 1. Enter your user information

[0532] Users install the smartphone app and enter their name, weight, gender, and drinking experience on the initial setup screen.

[0533] 2. Transmission and storage of user information

[0534] The terminal sends the entered user information to the server, which stores it in a database.

[0535] Today's situation input

[0536] 1. Enter your physical condition, drinking location, and predicted menu for the day

[0537] Users input their physical condition on the day, the location where they will be drinking, and the anticipated drinking menu.

[0538] 2. Sending and storing status information

[0539] The terminal sends the input information to the server, which stores the information in a database.

[0540] Alcohol calculation and alert settings

[0541] 1. Calculating the amount of alcohol

[0542] The server uses an algorithm to analyze the collected user information and situational information and calculates the appropriate amount of alcohol.

[0543] 2. Setting up alerts and notifications

[0544] Based on the calculated alcohol content, the server sets an alert and notifies the device in real time.

[0545] Real-time assistance while drinking

[0546] 1. Input and record alcohol intake

[0547] The user inputs the type and amount of alcohol consumed into the device while drinking.

[0548] 2. Checking alcohol intake and providing assistance

[0549] Based on the amount of alcohol consumed entered by the user, the server compares the current amount of alcohol consumed with the set appropriate amount, and if necessary, notifies the user with "snack suggestions" or "warnings about drinking too much."

[0550] Implementing the Emotion Engine

[0551] 1. Recognizing emotional states

[0552] The device analyzes the user's facial expressions and voice in real time, and the emotion engine recognizes the user's emotional state.

[0553] 2. Transmission and use of emotional information

[0554] The device transmits the recognized emotion information to the server, which then adjusts the assistance information based on the information.

[0555] Follow-up

[0556] 1. Follow-up notification the next day

[0557] The next morning, the server sends a notification to the user via their device asking, "Did you drink an appropriate amount of alcohol yesterday?"

[0558] 2. Save your feedback and apply it next time

[0559] The server stores the user's feedback in a database and reflects it in the next alcohol content calculation.

[0560] Specific examples

[0561] The user starts drinking beer at home and enters their drinking information into the app.

[0562] The app will alert you that you can drink up to three beers.

[0563] The app detects if you look tired while drinking and notifies you of "recommended snacks."

[0564] The next morning, the app will notify you, "Did you drink an appropriate amount of alcohol yesterday?"

[0565] Prompt Sentence Examples

[0566] I drank three beers yesterday and felt tired afterwards. Do you have any recommended snacks?

[0567] effect

[0568] The system allows users to manage their drinking in real time and receive optimal assistance according to their emotions, allowing them to enjoy themselves while reducing health risks and improving their drinking experience.

[0569] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0570] Step 1: Collecting and storing user information

[0571] Input: The user enters information such as name, weight, gender, and drinking experience into their smartphone.

[0572] Processing: The device acquires this information and sends it to the cloud server, which stores it in a database.

[0573] Output: User information is saved in the database.

[0574] Specific operation: After the user initially sets up the app, they enter information, the device calls an API to send the data, and the server writes it to the database.

[0575] Step 2: Input your current situation

[0576] Input: The user inputs their physical condition for the day, the drinking location, and the predicted drinking menu into their smartphone.

[0577] Processing: The terminal sends the entered information to the server, which stores it in a database.

[0578] Output: Status information is saved in the database.

[0579] Specific operation: The user enters the information for the day, the device sends it to the server, and the server executes an API that stores the information in a database.

[0580] Step 3: Calculate the amount of alcohol

[0581] Input: User information stored on the server and the current situation information.

[0582] Processing: The server analyzes this information based on an algorithm and calculates the appropriate alcohol content.

[0583] Output: Calculated alcohol content.

[0584] Specific operation: The server retrieves user information and situational information from the database, runs an algorithm to calculate the alcohol content, and temporarily stores the result.

[0585] Step 4: Configure alerts and notifications

[0586] Input: Calculated alcohol amount.

[0587] Processing: The server sets the appropriate alert and notifies the terminal of it.

[0588] Output: The alert is displayed on the terminal.

[0589] Specific operation: The server checks the condition based on alcohol content and calls an API that generates an appropriate alert message and sends it to the device.

[0590] Step 5: Enter and record your drinking

[0591] Input: The user inputs the type and amount of alcohol into their smartphone while drinking.

[0592] Processing: The terminal sends the entered drinking information to the server, which records it in a database.

[0593] Output: Drinking information is recorded in a database.

[0594] Specific operation: The user enters drinking data, the device sends it to the server, and the server writes the information to the database.

[0595] Step 6: Check alcohol intake and provide assistance

[0596] Input: Saved drinking information.

[0597] Processing: The server compares the current amount of alcohol consumed with the set appropriate amount, and generates assistance information as necessary and notifies the device.

[0598] Output: Assistance information displayed on terminal.

[0599] Specific operation: The server retrieves the current amount of alcohol consumed from the database, compares it with the calculated appropriate amount, generates an assistance message, and calls an API to send it to the device.

[0600] Step 7: Recognizing your emotional state

[0601] Input: User's facial and voice data.

[0602] Processing: The device analyzes this data in real time, and the emotion engine recognizes the user's emotional state.

[0603] Output: Perceived emotional state.

[0604] Specific operation: The device uses the camera and microphone to collect the user's facial expressions and voice, then sends the data to the emotion engine API and receives the analysis results.

[0605] Step 8: Sending and using emotional information

[0606] Input: Perceived emotional state.

[0607] Processing: The device transmits its emotional state to the server, which then adjusts the assistance information based on that information.

[0608] Output: Adjusted assistance information.

[0609] Specific operation: The device sends the recognized emotion data to the server, and the server generates an assistance message that takes the emotional state into account and sends it to the device.

[0610] Step 9: Follow-up notification the next day

[0611] Input: User drinking data and analysis results.

[0612] Processing: The next morning, the server sends a notification to the user's device asking, "Did you drink an appropriate amount of alcohol yesterday?"

[0613] Output: A follow-up notification is displayed on the user's device.

[0614] Specific operation: The server uses the scheduling function to generate a notification at the specified time and send it to the user's device.

[0615] Step 10: Save your feedback and apply it next time

[0616] Input: The feedback given by the user.

[0617] Processing: The device sends user feedback to the server, which stores it in a database and reflects it in the next alcohol content calculation.

[0618] Output: The feedback is stored in a database.

[0619] How it works: The user enters feedback within the app, the device sends it to the server, and the server stores it in a database for use in the next calculation.

[0620] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0621] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0622] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0623] [Second embodiment]

[0624] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0625] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0626] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0627] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0628] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0629] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0630] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0631] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0632] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0633] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0634] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0635] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0636] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The embodiments for carrying out the present invention will be described in detail below.

[0637] This invention is a system that calculates the appropriate amount of alcohol to drink based on the user's physical condition, drunkenness level, and drinking location information, and issues an alert in real time. This system helps users enjoy drinking while maintaining an ideal level of drunkenness. The system is primarily implemented using the user's smartphone or wearable device (terminal) and a server running on the backend.

[0638] 1. Initial Setup and User Authentication

[0639] Collection of User Information

[0640] When a user installs the application on their device and launches it for the first time, an initial setup screen appears, where the user enters information such as their name, weight, gender, and drinking experience.

[0641] Sending and storing user information

[0642] The device sends the input information to a server, which stores the received information in a database and uses it as the basis for calculating the appropriate alcohol content.

[0643] 2. Input today's situation

[0644] Enter your current physical condition, where you're drinking, and what you plan to eat

[0645] The user inputs their physical condition on the day (e.g., normal, tired, etc.) and the location where they will be drinking (e.g., at home, a friend's house, a restaurant, etc.), as well as the predicted drinks menu (e.g., beer, wine, shochu, etc.).

[0646] Sending and storing status information

[0647] The terminal sends this input information to the server, which then stores the received information in a database.

[0648] 3. Alcohol calculation and alert settings

[0649] Calculating the appropriate amount of alcohol

[0650] The server analyzes the collected user information, physical condition information, and drinking location information based on an algorithm, and calculates the appropriate amount of alcohol to reach the level of intoxication set by the user.

[0651] Alert settings and notifications

[0652] Based on the calculated alcohol content, the server sets an alert and sends it to the device, where the user can receive the alert in real time.

[0653] 4. Real-time assistance while drinking

[0654] Input and record alcohol intake

[0655] Users input the type and amount of alcohol they wish to drink into the device, which then transmits the information to a server, which records it in real time in a database.

[0656] Alcohol intake check and assistance provided

[0657] The server compares the current amount of alcohol consumed with the set amount in real time based on the amount of alcohol consumed entered by the user, and if necessary, sends assistance information such as "recommended snacks" or "warnings about drinking too much" to the user's device.

[0658] 5. Last train alerts and meeting minutes

[0659] Last train time setting and alert notification

[0660] When a user inputs the last train time into the device, the information is sent to the server, which then generates an alert and sends it to the device to notify the user one hour or 30 minutes before the last train.

[0661] Minute creation using voice recognition

[0662] Conversations made while drinking are recorded using the device's voice recognition function, and the data is sent to a server, which generates minutes based on the data and stores them for later reference by the user.

[0663] 6. Follow-up after drinking

[0664] Follow-up notification the next day

[0665] The next morning, the device sends the user a follow-up notification asking, "Did you drink moderately yesterday?" If the user answers "yes" or "no," that feedback is sent to the server.

[0666] Save your feedback and apply it next time

[0667] The server stores the received feedback in a database and reflects it in the next alcohol content calculation.

[0668] This allows users to enjoy drinking safely and healthily while maintaining an ideal level of intoxication.

[0669] The processing flow will be explained below.

[0670] Step 1:

[0671] Enter and submit user information

[0672] When a user launches the app for the first time, they enter information such as their name, weight, gender, and drinking experience.

[0673] The terminal transmits the entered user information to the server.

[0674] Step 2:

[0675] Saving user information

[0676] The server stores the received user information in a database.

[0677] Step 3:

[0678] Input of today's situation

[0679] The user inputs their physical condition on the day, the location where they will be drinking, and the planned drinking menu into the device.

[0680] The terminal transmits this information to the server.

[0681] Step 4:

[0682] Save today's status information

[0683] The server stores the received physical condition information, drinking location information, and drinking menu information in a database.

[0684] Step 5:

[0685] Calculating alcohol content

[0686] The server calculates the ideal amount of alcohol for the day based on the user's weight, physical condition, drinking location, and past data.

[0687] When calculating, an algorithm is applied depending on the set drunkenness level (e.g. tipsy).

[0688] Step 6:

[0689] Alert Settings and Notifications

[0690] The server sets an alert based on the calculation results.

[0691] The device notifies the user of configured alerts.

[0692] Step 7:

[0693] Enter and submit alcohol intake

[0694] The user enters the type and amount of alcohol consumed into the device.

[0695] The terminal transmits the inputted information on the amount of alcohol consumed to the server.

[0696] Step 8:

[0697] Saving and reviewing alcohol intake information

[0698] The server stores the received alcohol intake information in a database.

[0699] The server checks the current amount of alcohol consumed and calculates assistance information if the amount is below the appropriate level.

[0700] Step 9:

[0701] Assistance Information Notification

[0702] The server transmits assistance information during drinking to the terminal.

[0703] The device notifies the user of assistance information.

[0704] When the amount of alcohol consumed approaches the set limit, the user will receive an alert such as "Be careful not to drink too much."

[0705] Step 10:

[0706] Last train alert settings and notifications

[0707] The user sets the last train time on the device and sends that information to the server.

[0708] The server generates a last train alert before the last train and sends it to the terminal.

[0709] The device will notify the user of the last train alert.

[0710] Step 11:

[0711] Generate meeting minutes

[0712] During the drinking party, the device transmits voice data to the server.

[0713] The server uses voice recognition technology to convert the conversation into text data and generate minutes.

[0714] Step 12:

[0715] Next day follow-up

[0716] The next morning, the device will send the user a follow-up notification asking, "Did you drink moderate amounts of alcohol yesterday?"

[0717] The user enters the answer and the device sends the information to the server.

[0718] The server stores the received feedback in a database and reflects it in the next alcohol content calculation.

[0719] By following these steps, users can enjoy safe and enjoyable drinking while taking proper control of their drinking.

[0720] Example 1

[0721] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0722] In modern society, many people enjoy drinking alcohol, but there are concerns about the health risks associated with excessive drinking and inappropriate drinking habits. Furthermore, there are also problems such as forgetting the last train and having difficulty getting home, and issues with efficiency when taking minutes while drinking. In these situations, there is a need for a system that can manage appropriate drinking amounts in real time and provide appropriate assistance to users.

[0723] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0724] In this invention, the server includes a means for receiving physical condition information input by the user, a means for receiving drunkenness level information set by the user, and a means for receiving drinking location information input by the user. This allows the server to calculate the appropriate amount of alcohol based on the collected information, enabling the user to enjoy drinking safely while maintaining an ideal drunkenness level.

[0725] The server also includes a means for receiving alcohol intake information input by the user and checking the current alcohol intake in real time, a means for providing appropriate assistance information, a means for inputting the time of the last train, a means for issuing a last train alert based on the time of the last train, and a means for recording conversations while drinking using voice recognition and generating minutes. This enables the server to comprehensively manage the user's behavior while drinking and also assist with secondary tasks (e.g., managing the time to return home and creating minutes).

[0726] "Physical condition information" is information that indicates the user's current health condition and mood.

[0727] "Drunkenness level information" is information that indicates the level of drunkenness that the user wants to achieve through drinking.

[0728] "Drinking location information" is information about the location where the user plans to drink alcohol.

[0729] "Amount of alcohol" indicates the total amount of alcohol the user plans to drink.

[0730] An "alert" is a notification or warning that prompts a user to take a specific action.

[0731] "Alcohol intake information" is information about the type and amount of alcohol actually consumed by the user.

[0732] "Assistance information" is advice and recommendations to support users in drinking alcohol safely and effectively.

[0733] The "last train time" refers to the last operating time of the public transportation used by the user.

[0734] "Speech recognition" is a technology that analyzes a user's voice and converts it into a format such as text.

[0735] Minutes are documents that record the contents of meetings or conversations and can be referenced later.

[0736] A "database" is a system that stores information systematically and allows it to be quickly searched and retrieved as needed.

[0737] A "server" is a computer system that processes and manages data and communicates with other devices over a network.

[0738] A "terminal" is a device that a user can directly operate to input or receive information.

[0739] The present invention is a system that helps users enjoy drinking alcohol while maintaining an ideal level of intoxication. This system is primarily realized by the user's smartphone or wearable device (terminal) and a server running on the backend.

[0740] The operation of this system will be explained in detail below. First, the user installs the application on their device, and the initial setup screen is displayed when the application is launched for the first time. The user enters physical information such as name, weight, gender, and drinking history, and the device sends this information to the server. The server stores the received information in a database and uses it as basic data.

[0741] Next, the user enters information about the situation on the day, such as their physical condition, the place where they will be drinking, and the menu they plan to have. This information is also sent from the device to the server and stored in a database. The server uses an algorithm based on the collected user information and the situation information for that day to calculate the appropriate amount of alcohol to reach the level of intoxication set by the user.

[0742] Based on the calculated alcohol content, the server generates an alert and sends it to the device. The user can receive the alert in real time while drinking. Furthermore, when the user inputs the type and amount of alcohol consumed into the device each time, the device sends that information to the server, which records the amount consumed in a database in real time and provides assistance information such as "recommended snacks" or "warnings against drinking too much" as needed.

[0743] When a user inputs the last train time, the information is sent from the device to the server, and the server generates an alert one hour or 30 minutes before the last train and sends it to the device to notify the user.

[0744] It is also possible to record conversations while drinking using a voice recognition function. The device sends the voice data to a server, which analyzes it and generates minutes, which are then stored in a database for later reference by the user.

[0745] The next morning, the server sends a follow-up notification to the device asking, "Did you drink a reasonable amount of alcohol yesterday?" If the user answers "yes" or "no," that feedback will be reflected in the next alcohol calculation.

[0746] Here is an example prompt:

[0747] "Please enter your health condition, drinking location, and planned drinking menu for today. For example, please enter your health condition as 'normal', your drinking location as 'izakaya', and your planned menu as 'beer and sake'."

[0748] This allows users to easily input information and enables the system to effectively support the user's drinking experience.

[0749] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0750] Step 1:

[0751] Initial Setup and User Authentication

[0752] The user installs the application on their device and the initial setup screen is displayed when they launch it for the first time.

[0753] Input: The user inputs physical information such as name, weight, gender, and drinking experience.

[0754] The terminal temporarily stores the input information in memory.

[0755] The device transmits the stored information to the server.

[0756] The server stores the received information in a database.

[0757] Output: The server sends a confirmation message to the terminal that the save is complete, and the terminal displays it to the user.

[0758] Step 2:

[0759] Today's situation input

[0760] The user inputs information such as their physical condition on the day, where they will be drinking, and the planned menu into the terminal.

[0761] Input: Physical condition information (e.g., normal), Drinking location information (e.g., izakaya), Drinking menu information (e.g., beer)

[0762] The terminal temporarily stores the input information in memory.

[0763] The device transmits the stored information to the server.

[0764] The server stores the received information in a database.

[0765] Output: The server sends a confirmation message to the terminal that the save is complete, and the terminal displays it to the user.

[0766] Step 3:

[0767] Alcohol calculation and alert settings

[0768] The server uses an algorithm to calculate the appropriate amount of alcohol based on collected user information, physical condition information, and drinking location information.

[0769] Input: User information, physical condition information, drinking location information

[0770] Data processing: Algorithm-based data analysis

[0771] Output: Calculated alcohol content

[0772] The server generates an alert based on the calculated alcohol content and sends it to the device.

[0773] The device notifies the user of alerts in real time.

[0774] Step 4:

[0775] Real-time assistance while drinking

[0776] The user inputs the type and amount of alcohol consumed into the terminal each time.

[0777] Input: type and amount of alcohol (e.g. 500ml beer)

[0778] The terminal temporarily stores the input information in memory.

[0779] The terminal transmits the input information to the server.

[0780] The server records the received alcohol intake information in a database.

[0781] The server compares the current amount of alcohol consumed with the set limit and generates assistance information as needed.

[0782] Output: Assistance information (e.g., recommended snacks, warnings against drinking too much)

[0783] The server sends the assistance information to the terminal.

[0784] The terminal notifies the user of the received information.

[0785] Step 5:

[0786] Last train alert and meeting minutes

[0787] The user enters the last train time into the terminal (e.g., 23:00).

[0788] Input: Last train time information

[0789] The terminal transmits the input information to the server.

[0790] The server stores the received information in a database.

[0791] The server generates an alert and sends it to the terminal one hour or 30 minutes before the last train.

[0792] Output: Last train alert notification

[0793] The terminal notifies the user of the received alert.

[0794] Step 6:

[0795] Follow-up after drinking

[0796] The next morning, the server sends a follow-up notification to the device asking, "Did you drink an appropriate amount of alcohol yesterday?"

[0797] Output: Follow-up notification

[0798] The user answers "yes" or "no."

[0799] Input: User feedback

[0800] The terminal transmits the user's answer to the server.

[0801] The server stores the received feedback in a database.

[0802] The feedback will be reflected in the next alcohol calculation.

[0803] Through these specific processing steps, users can enjoy drinking safely and healthily while maintaining an ideal level of intoxication.

[0804] (Application example 1)

[0805] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0806] In modern society, there is a lack of ways for users to enjoy drinking alcohol while maintaining an appropriate amount of alcohol intake and enjoying content that is optimal for their situation. In particular, there is a need for a means to provide entertainment content that is individually optimized based on the user's physical condition and drinking situation. There is also a need for a system that allows users to enjoy optimal content while managing their drinking amount and physical condition in real time while drinking.

[0807] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0808] In this invention, the server includes means for receiving physical condition information input by the user, means for receiving drunkenness level information set by the user, means for receiving drinking location information input by the user, means for calculating the appropriate amount of alcohol based on the received information, means for issuing an alert based on the calculated amount of alcohol, and content recommendation means for recommending optimal content based on the user's drinking status and physical condition. This allows the user to enjoy entertainment content optimal for their situation at any given time while safely and comfortably enjoying alcohol.

[0809] "Physical condition information" is data indicating the user's physical condition, such as normal, tired, or unwell.

[0810] "Drunkenness level information" is data indicating the ideal level of drunkenness set by the user, such as wanting to get a little drunk, wanting to get tipsy, or not wanting to get drunk.

[0811] "Drinking location information" is data relating to the location where the user drinks alcohol, such as at home, at a friend's house, or at a restaurant.

[0812] The "appropriate amount of alcohol" is the amount of alcohol consumed that a user needs to maintain an ideal level of intoxication, calculated based on the user's physical condition, level of intoxication, and drinking location information.

[0813] An "alert" is a warning or suggestion that the system notifies the user, such as warning them to be careful not to drink too much or informing them when to have their next drink.

[0814] "Content recommendation means" refers to algorithms and technologies for recommending optimal entertainment content based on a user's physical condition, drunkenness level, drinking location, and past viewing history.

[0815] The following is a detailed description of an embodiment of the present invention. The present invention is a system that calculates the appropriate amount of alcohol to drink based on information about the user's physical condition, drunkenness level, and drinking location, and issues an alert in real time. The system also has a function to recommend optimal content based on the user's drinking habits and physical condition. This system is primarily implemented using the user's device (a smartphone or wearable device) and a server operating in the backend.

[0816] 1. Initial Setup and User Authentication

[0817] Collection of User Information

[0818] When the application is first installed and launched, an initial setup screen appears, where the user enters information such as their name, weight, gender, and drinking experience.

[0819] Sending and storing user information

[0820] The device sends the input information to a cloud server, which then stores it in a database, which is used as the basis for calculating the appropriate alcohol content.

[0821] 2. Input today's situation

[0822] Enter your current physical condition, where you're drinking, and what you plan to eat

[0823] Users input their physical condition on the day, the location where they will be drinking, and the planned drinking menu into the device.

[0824] Sending and storing status information

[0825] The device sends this input information to a cloud server, which then stores the received information in a database.

[0826] 3. Alcohol calculation and alert settings

[0827] Calculating the appropriate amount of alcohol

[0828] The server uses an algorithm to analyze the collected user information, physical condition information, and drinking location information, and calculates the appropriate amount of alcohol to reach the level of intoxication set by the user.

[0829] Alert settings and notifications

[0830] Based on the calculated alcohol content, the server sets an alert and sends it to the user's device, where the user can receive the alert in real time.

[0831] 4. Real-time assistance while drinking

[0832] Input and record alcohol intake

[0833] Users input the type and amount of alcohol they wish to drink into the device, which then sends the information to a cloud server, which records it in a database in real time.

[0834] Alcohol intake check and assistance provided

[0835] The server compares the current amount of alcohol consumed with the set amount in real time based on the amount of alcohol consumed entered by the user, and if necessary, sends assistance information such as "recommended snacks" or "warnings about drinking too much" to the device.

[0836] 5. Content Recommendation

[0837] Recommending the right content

[0838] The server recommends optimal content based on the user's drinking habits and physical condition, using Python-based machine learning models (such as TensorFlow and PyTorch) to reference the user's past viewing history and data on similar users.

[0839] Content Notification

[0840] The server sends a list of recommended content to the user's device, which can then receive the list in real time.

[0841] Hardware and software used

[0842] Hardware: Smartphone (iOS or Android device)

[0843] software:

[0844] Cloud services (AWS and Google Cloud)

[0845] Database systems (Firestore, MySQL)

[0846] Machine learning frameworks (TensorFlow, PyTorch)

[0847] Specific examples

[0848] Below are some example prompts to input to a generative AI model:

[0849] Username: Yamada Taro

[0850] Weight: 70kg

[0851] Gender: Male

[0852] Drinking experience: Intermediate

[0853] Today's mood: Normal

[0854] Drinking location: Home

[0855] Planned drinks menu: beer, wine

[0856] Generate a list of recommended movies, music playlists, and videos for users who are in normal health and drinking beer and wine at home.

[0857] As described above, the present invention is a system that allows users to enjoy drinking safely and healthily while maintaining an ideal level of intoxication, and to enjoy entertainment content that is optimal for the situation at hand.

[0858] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0859] Step 1:

[0860] Entering and collecting user information

[0861] When a user installs the application on a device, they are prompted to enter information such as their name, weight, gender, and drinking history as initial settings. This data is sent from the device to a cloud server, which then stores it in a database.

[0862] Input: Name, weight, gender, drinking experience, etc.

[0863] Output: User information stored in the database

[0864] How it works: When a user enters information such as their name, weight, gender, and drinking experience into their smartphone and presses the "Save" button, the data is sent to a cloud server, where it is recorded in a database.

[0865] Step 2:

[0866] Today's situation input

[0867] The user inputs information about their physical condition for the day, where they will be drinking, and the planned drinking menu into the device. The device then sends this information to the cloud server, which then stores it in a database.

[0868] Input: Today's health information, drinking location information, planned drinking menu

[0869] Output: Current status information stored in the database

[0870] How it works: When a user enters their current physical condition (e.g., "normal"), where they are drinking (e.g., "home"), and what they plan to drink (e.g., "beer, wine") into their smartphone and presses the "Save" button, the data is sent to the cloud server, which then records the data in a database.

[0871] Step 3:

[0872] Calculating the right amount of alcohol

[0873] The server uses an algorithm to analyze collected user information, physical condition information, and drinking location information to calculate the appropriate amount of alcohol.

[0874] Input: User information, health information, drinking location information

[0875] Output: Calculation result of appropriate amount of alcohol

[0876] Specific operation: The server retrieves user information and today's situation information from the database, and then applies an algorithm within the program (such as a linear regression model with specific coefficients) based on this information to calculate the appropriate amount of alcohol the user can safely drink.

[0877] Step 4:

[0878] Alert settings and notifications

[0879] The server sets an alert based on the appropriate alcohol content and sends it to the device, which the user receives in real time.

[0880] Input: Calculation result of appropriate alcohol amount

[0881] Output: Alert notification to user's terminal

[0882] Specific operation: Based on the calculated appropriate amount of alcohol, the server determines the maximum amount of alcohol the user should drink, and if the limit is exceeded, an alert message such as "Be careful not to drink too much" is sent to the device. The alert is displayed on the user's device in the form of a push notification or other means.

[0883] Step 5:

[0884] Alcohol intake entry and real-time assistance

[0885] The user inputs the type and amount of alcohol consumed into the device, which is then sent to the server, where it is recorded in a database in real time. The server then compares the current amount of alcohol consumed with the set amount, and sends assistance information to the device as needed.

[0886] Input: Type and amount of alcohol consumed

[0887] Output: Assistance information based on current alcohol intake

[0888] How it works: The user enters the type and amount of alcohol they have consumed into their smartphone, and the information is sent to a cloud server. The server records this information in a database in real time, manages the appropriate amount set, and sends assistance notifications to the device as needed (such as "recommended snacks" or "warnings against drinking too much").

[0889] Step 6:

[0890] Content recommendations and notifications

[0891] The server recommends the most suitable content based on the user's drinking habits and physical condition. This recommendation is made using a Python-based machine learning model (such as TensorFlow or PyTorch). A list of recommended content is sent to the user's device.

[0892] Input: User's drinking status, physical condition information

[0893] Output: A list of recommended content

[0894] How it works: The server retrieves the user's drinking history and physical condition information from the database, and then uses a machine learning model (such as TensorFlow or PyTorch) to recommend the most suitable content (movies, music, videos, etc.) for the user. The recommendation results are sent to the user's smartphone, and the user can receive a list of content.

[0895] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0896] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The embodiments for carrying out the present invention will be described in detail below.

[0897] This invention combines an emotion engine with a system that calculates the appropriate amount of alcohol to drink based on the user's physical condition, drunkenness level, and drinking location information, and issues alerts in real time. The emotion engine recognizes the user's emotional state from their facial expressions and voice, and uses this information to further optimize the drinking experience. This system is realized using the user's smartphone or wearable device (terminal) and a server running on the backend.

[0898] 1. Initial Setup and User Authentication

[0899] Collection of User Information

[0900] When a user installs the application on their device and launches it for the first time, an initial setup screen appears, where the user enters information such as their name, weight, gender, and drinking experience.

[0901] Sending and storing user information

[0902] The device sends the entered user information to a server, which then stores the received information in a database, which is used as the basis for calculating the appropriate alcohol content.

[0903] 2. Input today's situation

[0904] Enter your current physical condition, where you're drinking, and what you plan to eat

[0905] The user inputs their physical condition on the day (e.g., normal, tired, etc.) and the location where they will be drinking (e.g., at home, a friend's house, a restaurant, etc.), as well as the predicted drinks menu (e.g., beer, wine, shochu, etc.).

[0906] Sending and storing status information

[0907] The terminal sends this input information to the server, which then stores the received information in a database.

[0908] 3. Alcohol calculation and alert settings

[0909] Calculating the appropriate amount of alcohol

[0910] The server analyzes the collected user information, physical condition information, and drinking location information based on an algorithm, and calculates the appropriate amount of alcohol to reach the level of intoxication set by the user.

[0911] Alert settings and notifications

[0912] Based on the calculated alcohol content, the server sets an alert and sends it to the device, where the user can receive the alert in real time.

[0913] 4. Real-time assistance while drinking

[0914] Input and record alcohol intake

[0915] Users input the type and amount of alcohol they wish to drink into the device, which then transmits the information to a server, which records it in real time in a database.

[0916] Alcohol intake check and assistance provided

[0917] The server compares the current amount of alcohol consumed with the set amount in real time based on the amount of alcohol consumed entered by the user, and if necessary, sends assistance information such as "recommended snacks" or "warnings about drinking too much" to the user's device.

[0918] 5. Implementing the Emotion Engine

[0919] Recognition of emotional states

[0920] The device analyzes the user's facial expressions and voice in real time, and the emotion engine recognizes the user's emotional state (e.g., happy, stressed, etc.).

[0921] Transmission and use of emotional information

[0922] The device sends the recognized emotional information to the server, which then uses that emotional information to further adjust the amount of alcohol consumed and the assistance information provided, for example, recommending relaxing snacks if the user is feeling stressed.

[0923] 6. Last Train Alerts and Meeting Minutes

[0924] Last train time setting and alert notification

[0925] When a user inputs the last train time into the device, the information is sent to the server, which then generates an alert and sends it to the device to notify the user one hour or 30 minutes before the last train.

[0926] Minute creation using voice recognition

[0927] Conversations made while drinking are recorded using the device's voice recognition function, and the data is sent to a server, which generates minutes based on the data and stores them for later reference by the user.

[0928] 7. Follow-up after drinking

[0929] Follow-up notification the next day

[0930] The next morning, the device sends the user a follow-up notification asking, "Did you drink moderately yesterday?" If the user answers "yes" or "no," that feedback is sent to the server.

[0931] Save your feedback and apply it next time

[0932] The server stores the received feedback in a database and reflects it in the next alcohol content calculation.

[0933] This allows users to properly manage their drinking while receiving optimal assistance according to their emotional state, allowing them to enjoy drinking in a fun and safe way.

[0934] The processing flow will be explained below.

[0935] Step 1:

[0936] Enter and submit user information

[0937] When a user launches the app for the first time, they enter information such as their name, weight, gender, and drinking experience.

[0938] The terminal transmits the entered user information to the server.

[0939] Step 2:

[0940] Saving user information

[0941] The server stores the received user information in a database.

[0942] Step 3:

[0943] Input of today's situation

[0944] The user inputs their physical condition on the day, the location where they will be drinking, and the planned drinking menu into the device.

[0945] The terminal transmits this information to the server.

[0946] Step 4:

[0947] Save today's status information

[0948] The server stores the received physical condition information, drinking location information, and drinking menu information in a database.

[0949] Step 5:

[0950] Calculating alcohol content

[0951] The server calculates the ideal amount of alcohol for the day based on the user's weight, physical condition, drinking location, and past data.

[0952] When calculating, an algorithm is applied depending on the set drunkenness level (e.g. tipsy).

[0953] Step 6:

[0954] Alert Settings and Notifications

[0955] The server sets an alert based on the calculation results.

[0956] The device notifies the user of configured alerts.

[0957] Step 7:

[0958] Enter and submit alcohol intake

[0959] The user enters the type and amount of alcohol consumed into the device.

[0960] The terminal transmits the inputted information on the amount of alcohol consumed to the server.

[0961] Step 8:

[0962] Saving and reviewing alcohol intake information

[0963] The server stores the received alcohol intake information in a database.

[0964] The server checks the current amount of alcohol consumed and calculates assistance information if the amount is below the appropriate level.

[0965] Step 9:

[0966] Assistance Information Notification

[0967] The server transmits assistance information during drinking to the terminal.

[0968] The device notifies the user of assistance information.

[0969] When the amount of alcohol consumed approaches the set limit, the user will receive an alert such as "Be careful not to drink too much."

[0970] Step 10:

[0971] Recognizing and transmitting emotional states

[0972] The device analyzes the user's facial expressions and voice in real time, and the emotion engine recognizes the user's emotional state (e.g., happy, stressed, etc.).

[0973] The recognized emotion information is sent to the server.

[0974] Step 11:

[0975] Adjustment based on emotional state

[0976] The server further adjusts the amount of alcohol consumed and assistance information based on the emotional information received.

[0977] For example, if a user is feeling stressed, we will recommend snacks that have a relaxing effect.

[0978] Step 12:

[0979] Last train alert settings and notifications

[0980] The user sets the last train time on the device and sends that information to the server.

[0981] The server generates a last train alert before the last train and sends it to the terminal.

[0982] The device will notify the user of the last train alert.

[0983] Step 13:

[0984] Generate meeting minutes

[0985] During the drinking party, the device transmits voice data to the server.

[0986] The server uses voice recognition technology to convert the conversation into text data and generate minutes.

[0987] Step 14:

[0988] Next day follow-up

[0989] The next morning, the device will send the user a follow-up notification asking, "Did you drink moderate amounts of alcohol yesterday?"

[0990] The user enters the answer and the device sends the information to the server.

[0991] The server stores the received feedback in a database and reflects it in the next alcohol content calculation.

[0992] By following these steps, users can enjoy safe drinking while properly managing their drinking and receiving optimal assistance based on their emotional state.

[0993] Example 2

[0994] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0995] Conventional alcohol consumption management systems only managed alcohol intake based on the user's physical condition and level of intoxication, and had the function of issuing an alert, but this did not respond appropriately to the user's emotions or environment, resulting in problems with satisfaction and safety. Furthermore, there was a need for a more accurate way to manage alcohol intake by taking environmental and biological information into account.

[0996] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0997] In this invention, the server includes a means for receiving biometric information input by the user, a means for receiving satisfaction level information set by the user, and a means for receiving environmental information input by the user, thereby enabling calculation of an appropriate alcohol intake amount based on the user's physical condition, emotions, and environment, and providing assistance and alerts in real time.

[0998] "Biometric information" refers to data related to the user's physical condition and health, including, for example, weight, gender, age, past drinking history, and physical condition.

[0999] "Satisfaction information" refers to data that indicates the level of intoxication desired by the user and their expectations regarding drinking, including emotional states such as "fun" or "want to relax."

[1000] "Environmental information" refers to data about the location where the user drinks and the circumstances at the time, including, for example, the location where the drink is taken (home, restaurant, etc.), the atmosphere of the location, and the presence of other people.

[1001] "Intake" refers to the amount of alcohol a user should drink, including an appropriate amount calculated based on the user's physical condition, satisfaction, and environmental information.

[1002] "Emotional state" refers to the user's current psychological and emotional state, and includes information such as "happy," "stressed," and "relaxed."

[1003] "Alerts" refer to warning or suggestion messages sent to users, such as "Be careful not to drink too much" or "Recommended snacks."

[1004] "Support information" refers to information that helps users drink alcohol appropriately, including, for example, advice on adjusting future drinking amounts, recommended meals, and advice on the pace at which to drink.

[1005] This invention combines an emotion engine with a system that calculates the appropriate amount of alcohol intake based on biometric information, satisfaction information, and environmental information input by the user and issues alerts in real time. This system is realized using the user's smartphone or wearable device (terminal) and a server running on the backend.

[1006] Initial Setup and User Authentication

[1007] When a user installs the application on their device and launches it for the first time, an initial setup screen appears. The user enters biometric information such as their name, weight, gender, age, and drinking experience. The device sends this information to a server, which stores it in a database. This information is used as the basis for calculating appropriate alcohol intake.

[1008] Today's situation input

[1009] The user inputs environmental information into the device, such as their physical condition on the day (e.g., normal, tired, feeling a bit under the weather, etc.) and the location where they will be drinking (e.g., at home, a friend's house, a restaurant, etc.). They also input their predicted drinking menu (e.g., two beers and one glass of wine). The device sends this situation information to the server, which then stores the received information in a database.

[1010] Alcohol calculation and alert settings

[1011] The server runs an algorithm based on stored user information, physical condition information, drinking location information, and predicted drinking menu to calculate the appropriate amount of alcohol to reach the user's desired level of satisfaction. The server sets an alert based on the calculated appropriate amount of alcohol, and the device notifies the user in real time. For example, it displays messages such as "Only one more beer" or "Be careful not to drink too much!"

[1012] Real-time assistance while drinking

[1013] The user inputs the type and amount of alcohol consumed into the device. The device then sends the input information to the server, which records it in a database in real time. The server compares the user's current alcohol intake with a preset appropriate drinking amount, and notifies the device of assistance information such as "recommended snacks" or "warnings against drinking too much" as needed.

[1014] Implementing the Emotion Engine

[1015] The device analyzes the user's facial expressions and voice in real time. For example, it uses the smartphone's camera and microphone to analyze the user's facial expressions and tone of voice. The emotion engine recognizes the user's emotional state (e.g., happy, stressed, etc.) and generates information about it. The device sends the recognized emotion information to the server, which then adjusts the amount of alcohol consumed and customizes assistance information based on that emotion information. For example, if the user is feeling stressed, it can recommend snacks that have a relaxing effect.

[1016] Last train alert and meeting minutes creation

[1017] The user enters the time of the last train into the device. For example, if the user enters "The last train is at 10:30 p.m.", the server saves that information in a database. The server generates an alert one hour or 30 minutes before the last train, and the device notifies the user. The device also uses a voice recognition function to record conversations that were taking place while drinking. For example, the smartphone's microphone can be used to convert the conversation into text, and the server can generate and save minutes based on that data.

[1018] Follow-up after drinking

[1019] The next morning, the device sends the user a question: "Were you satisfied with the amount of alcohol you drank yesterday?" The user answers "yes" or "no," and the feedback is sent to the server. The server stores the feedback in a database and reflects it in the next alcohol amount calculation. For example, it may fine-tune the suggested amount of alcohol based on the previous feedback.

[1020] Examples:

[1021] A user named "Taro" enters his weight as 70 kg, his gender as male, his drinking experience, and his preferred types of alcohol as beer and wine. The device sends this information to the server, which then stores it in a database.

[1022] The user inputs, "I'm feeling fine today, I plan to drink at home, and my planned menu is two beers and one glass of wine." The device sends this information to the server, which then stores it in a database.

[1023] The device's camera detects the user's smile, and the emotion engine recognizes it as "fun." The device then sends this information to the server, which then provides "assistance information perfect for a fun drinking party."

[1024] A user sets the last train time to 23:30. The server sends an alert from the device at 22:30 and 23:00.

[1025] Example prompt sentence:

[1026] "User information: Taro, Weight: 70kg, Gender: Male, Drinking experience: Yes. Please calculate the appropriate amount of alcohol."

[1027] "The user has entered their current health state as 'normal', their drinking location as 'home', and their planned menu as '2 beers, 1 glass of wine'. Create appropriate alerts and assistance information."

[1028] "The user entered the last train time as 23:30. Please send an alert 1 hour and 30 minutes before the last train."

[1029] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1030] Processing Steps

[1031] Step 1: Initial Setup and User Authentication

[1032] 1. When a user installs the application on their device and launches it for the first time, an initial setup screen will appear.

[1033] 2. The user enters biometric information such as name, weight, gender, age, and drinking experience.

[1034] Input: User information (name, weight, gender, age, drinking experience)

[1035] Output: User information data

[1036] 3. The device sends this information to the server, and the server stores the received information in a database.

[1037] Data processing / calculation: Saving user information

[1038] Step 2: Input your current situation

[1039] 1. The user inputs environmental information into the device, such as their physical condition on the day (e.g., normal, tired, feeling a bit like a cold, etc.) and the location where they drank alcohol (e.g., at home, a friend's house, a restaurant, etc.).

[1040] Input: Health information, drinking location information

[1041] Output: Today's status information data

[1042] 2. Additionally, enter your predicted drinking menu (e.g., 2 beers, 1 wine).

[1043] Input: Drinking menu information

[1044] Output: Completed status information data

[1045] 3. The device sends this status information to the server, and the server stores the received information in a database.

[1046] Data processing / calculation: Saving status information

[1047] Step 3: Calculate alcohol intake and set alerts

[1048] 1. The server runs an algorithm based on stored user information, physical condition information, drinking location information, and predicted drinking menu.

[1049] Input: User information, physical condition information, drinking location information, drinking menu

[1050] Calculation: Calculating the appropriate amount of alcohol

[1051] Output: Appropriate alcohol content data

[1052] 2. Calculate the appropriate amount of alcohol to reach the user's desired satisfaction level and set an alert.

[1053] Data processing / calculation: Alert information generation

[1054] 3. The server sends the alert information to the device, and the device notifies the user in real time.

[1055] Input: Alert information

[1056] Output: User notification (e.g., "Only one more beer left!", "Don't drink too much!")

[1057] Step 4: Real-time assistance while drinking

[1058] 1. The user enters the type and amount of alcohol consumed into the device.

[1059] Input: Alcohol intake information

[1060] Output: Alcohol intake data

[1061] 2. The device sends the entered alcohol intake information to the server, which records it in a database in real time.

[1062] Data processing / calculation: Saving alcohol intake information

[1063] 3. The server compares the user's current drinking level with the predetermined appropriate drinking level and generates assistance information as needed.

[1064] Input: Alcohol intake data, set appropriate amount

[1065] Calculation: Check alcohol intake

[1066] Output: Assistance information

[1067] 4. The device notifies the user of the generated assistance information. For example, it may present "recommended snacks" or "be careful not to drink too much!"

[1068] Data processing / calculation: Notification of assistance information

[1069] Step 5: Implementing the Emotion Engine

[1070] 1. The device analyzes the user's facial expressions and voice in real time. For example, it uses the smartphone's camera and microphone to analyze the user's facial expressions and tone of voice.

[1071] Input: facial expression data, voice data

[1072] Computation: Recognizing Emotional States

[1073] Output: Emotional information

[1074] 2. The emotion engine recognizes the user's emotional state.

[1075] Data processing / calculation: Generating emotional information

[1076] 3. The device sends the recognized emotional information to the server, which then adjusts the amount of alcohol and customizes the assistance information based on the emotional information.

[1077] Input: Emotion information

[1078] Calculation: Alcohol content adjustment, customization of assistance information

[1079] Output: Adjusted alcohol content data, customized assistance information

[1080] Step 6: Last train alert and meeting minutes

[1081] 1. The user enters the last train time into the terminal.

[1082] Input: Last train time

[1083] Output: Last train time data

[1084] 2. The server saves the last train time information in a database.

[1085] Data processing / calculation: Saving the last train time

[1086] 3. The server generates an alert one hour or 30 minutes before the last train, and the device notifies the user.

[1087] Input: Saved last train time

[1088] Operation: Alert Generation

[1089] Output: User notification (e.g. "1 hour before last train", "30 minutes before last train")

[1090] 4. The device uses voice recognition to record conversations while drinking. For example, it uses a smartphone microphone to convert the conversation into text, and the server generates and stores minutes based on that data.

[1091] Input: Conversation data while drinking

[1092] Computing: Speech recognition and text conversion

[1093] Output: Generate minutes data

[1094] Step 7: Follow up after drinking

[1095] 1. The next morning, the device sends the user the question, "Were you satisfied with the amount of alcohol you drank yesterday?"

[1096] Input: Question submission (automatic)

[1097] Output: User notification

[1098] 2. The user answers with "yes" or "no" and the feedback is sent to the server.

[1099] Input: User feedback

[1100] Output: Feedback data

[1101] 3. The server stores the feedback in a database and uses it in the next alcohol content calculation.

[1102] Data processing / calculation: Saving and reflecting feedback

[1103] Output: Adjusted alcohol content data

[1104] (Application example 2)

[1105] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1106] There is a need for technology to manage appropriate alcohol consumption and reduce the health risks associated with excessive drinking. Another challenge is to provide optimal assistance based on the user's emotional state and further improve the drinking experience. Food delivery services also require management to ensure users do not drink too much and enjoy their food and drink appropriately. In addition, there is a need for comprehensive support, including information on the user's last train and their health the next day.

[1107] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1108] In this invention, the server includes: means for receiving physical condition information input by the user; means for receiving drunkenness level information set by the user; means for receiving drinking location information input by the user; means for calculating an appropriate alcohol intake based on the received information; means for issuing an alert based on the calculated alcohol intake; means for analyzing the user's facial expressions and voice while drinking and recognizing their emotional state; means for providing appropriate assistance information based on the recognized emotional state; and means for implementing the above means using a server operating in the backend and linking with the user's device. This makes it possible to appropriately manage the user's alcohol intake, provide assistance according to their emotions, notify them of last train alerts, and support an optimal drinking experience with food delivery services.

[1109] "User" refers to any person who uses the Services or Applications.

[1110] "Health information" refers to information that indicates the user's health condition and level of fatigue on that day.

[1111] "Drunkenness level information" refers to information that allows a user to set the level of drunkenness they desire.

[1112] "Drinking location information" refers to information about the location where a user drinks alcohol.

[1113] "Alcohol content" refers to the appropriate amount of alcohol a user should drink.

[1114] An "alert" refers to a warning or notification given to the user.

[1115] "Facial expression analysis" refers to technology that recognizes a user's facial expressions and analyzes their state.

[1116] "Voice analysis" refers to technology that recognizes a user's voice and analyzes their emotional state.

[1117] "Emotional state" refers to the emotion the user is feeling (e.g., happy, stressed, etc.).

[1118] "Assistance Information" refers to supplementary information or advice provided to the User.

[1119] "Back-end server" refers to a remote server that processes data in cooperation with user terminals.

[1120] "Terminal" refers to a device used by a user, such as a smartphone or wearable device.

[1121] System Overview

[1122] The system for implementing this invention receives information on the user's physical condition, drunkenness level, and drinking location, calculates the appropriate amount of alcohol based on that information, issues an alert in real time, and recognizes the user's emotional state through facial expression and voice analysis, and provides appropriate assistance based on that information.

[1123] Hardware and software used

[1124] Hardware: Smartphones, wearable devices (e.g., Apple Watch)

[1125] Software: Cloud services (Amazon Web Services, Google Cloud, etc.), databases (MySQL, PostgreSQL), emotion engines (Microsoft Azure Emotion API, Google Cloud Vision API)

[1126] Detailed program processing

[1127] The process performed by the server and the device is as follows:

[1128] Collection and storage of user information

[1129] 1. Enter your user information

[1130] Users install the smartphone app and enter their name, weight, gender, and drinking experience on the initial setup screen.

[1131] 2. Transmission and storage of user information

[1132] The terminal sends the entered user information to the server, which stores it in a database.

[1133] Today's situation input

[1134] 1. Enter your physical condition, drinking location, and predicted menu for the day

[1135] Users input their physical condition on the day, the location where they will be drinking, and the anticipated drinking menu.

[1136] 2. Sending and storing status information

[1137] The terminal sends the input information to the server, which stores the information in a database.

[1138] Alcohol calculation and alert settings

[1139] 1. Calculating the amount of alcohol

[1140] The server uses an algorithm to analyze the collected user information and situational information and calculates the appropriate amount of alcohol.

[1141] 2. Setting up alerts and notifications

[1142] Based on the calculated alcohol content, the server sets an alert and notifies the device in real time.

[1143] Real-time assistance while drinking

[1144] 1. Input and record alcohol intake

[1145] The user inputs the type and amount of alcohol consumed into the device while drinking.

[1146] 2. Checking alcohol intake and providing assistance

[1147] Based on the amount of alcohol consumed entered by the user, the server compares the current amount of alcohol consumed with the set appropriate amount, and if necessary, notifies the user with "snack suggestions" or "warnings about drinking too much."

[1148] Implementing the Emotion Engine

[1149] 1. Recognizing emotional states

[1150] The device analyzes the user's facial expressions and voice in real time, and the emotion engine recognizes the user's emotional state.

[1151] 2. Transmission and use of emotional information

[1152] The device transmits the recognized emotion information to the server, which then adjusts the assistance information based on the information.

[1153] Follow-up

[1154] 1. Follow-up notification the next day

[1155] The next morning, the server sends a notification to the user via their device asking, "Did you drink an appropriate amount of alcohol yesterday?"

[1156] 2. Save your feedback and apply it next time

[1157] The server stores the user's feedback in a database and reflects it in the next alcohol content calculation.

[1158] Specific examples

[1159] The user starts drinking beer at home and enters their drinking information into the app.

[1160] The app will alert you that you can drink up to three beers.

[1161] The app detects if you look tired while drinking and notifies you of "recommended snacks."

[1162] The next morning, the app will notify you, "Did you drink an appropriate amount of alcohol yesterday?"

[1163] Prompt Sentence Examples

[1164] I drank three beers yesterday and felt tired afterwards. Do you have any recommended snacks?

[1165] effect

[1166] The system allows users to manage their drinking in real time and receive optimal assistance according to their emotions, allowing them to enjoy themselves while reducing health risks and improving their drinking experience.

[1167] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1168] Step 1: Collecting and storing user information

[1169] Input: The user enters information such as name, weight, gender, and drinking experience into their smartphone.

[1170] Processing: The device acquires this information and sends it to the cloud server, which stores it in a database.

[1171] Output: User information is saved in the database.

[1172] Specific operation: After the user initially sets up the app, they enter information, the device calls an API to send the data, and the server writes it to the database.

[1173] Step 2: Input your current situation

[1174] Input: The user inputs their physical condition for the day, the drinking location, and the predicted drinking menu into their smartphone.

[1175] Processing: The terminal sends the entered information to the server, which stores it in a database.

[1176] Output: Status information is saved in the database.

[1177] Specific operation: The user enters the information for the day, the device sends it to the server, and the server executes an API that stores the information in a database.

[1178] Step 3: Calculate the amount of alcohol

[1179] Input: User information stored on the server and the current situation information.

[1180] Processing: The server analyzes this information based on an algorithm and calculates the appropriate alcohol content.

[1181] Output: Calculated alcohol content.

[1182] Specific operation: The server retrieves user information and situational information from the database, runs an algorithm to calculate the alcohol content, and temporarily stores the result.

[1183] Step 4: Configure alerts and notifications

[1184] Input: Calculated alcohol amount.

[1185] Processing: The server sets the appropriate alert and notifies the terminal of it.

[1186] Output: The alert is displayed on the terminal.

[1187] Specific operation: The server checks the condition based on alcohol content and calls an API that generates an appropriate alert message and sends it to the device.

[1188] Step 5: Enter and record your drinking

[1189] Input: The user inputs the type and amount of alcohol into their smartphone while drinking.

[1190] Processing: The terminal sends the entered drinking information to the server, which records it in a database.

[1191] Output: Drinking information is recorded in a database.

[1192] Specific operation: The user enters drinking data, the device sends it to the server, and the server writes the information to the database.

[1193] Step 6: Check alcohol intake and provide assistance

[1194] Input: Saved drinking information.

[1195] Processing: The server compares the current amount of alcohol consumed with the set appropriate amount, and generates assistance information as necessary and notifies the device.

[1196] Output: Assistance information displayed on terminal.

[1197] Specific operation: The server retrieves the current amount of alcohol consumed from the database, compares it with the calculated appropriate amount, generates an assistance message, and calls an API to send it to the device.

[1198] Step 7: Recognizing your emotional state

[1199] Input: User's facial and voice data.

[1200] Processing: The device analyzes this data in real time, and the emotion engine recognizes the user's emotional state.

[1201] Output: Perceived emotional state.

[1202] Specific operation: The device uses the camera and microphone to collect the user's facial expressions and voice, then sends the data to the emotion engine API and receives the analysis results.

[1203] Step 8: Sending and using emotional information

[1204] Input: Perceived emotional state.

[1205] Processing: The device transmits its emotional state to the server, which then adjusts the assistance information based on that information.

[1206] Output: Adjusted assistance information.

[1207] Specific operation: The device sends the recognized emotion data to the server, and the server generates an assistance message that takes the emotional state into account and sends it to the device.

[1208] Step 9: Follow-up notification the next day

[1209] Input: User drinking data and analysis results.

[1210] Processing: The next morning, the server sends a notification to the user's device asking, "Did you drink an appropriate amount of alcohol yesterday?"

[1211] Output: A follow-up notification is displayed on the user's device.

[1212] Specific operation: The server uses the scheduling function to generate a notification at the specified time and send it to the user's device.

[1213] Step 10: Save your feedback and apply it next time

[1214] Input: The feedback given by the user.

[1215] Processing: The device sends user feedback to the server, which stores it in a database and reflects it in the next alcohol content calculation.

[1216] Output: The feedback is stored in a database.

[1217] How it works: The user enters feedback within the app, the device sends it to the server, and the server stores it in a database for use in the next calculation.

[1218] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1219] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1220] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1221] [Third embodiment]

[1222] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1223] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1224] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1225] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1226] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1227] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1228] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1229] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1230] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1231] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1232] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1233] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[1234] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The embodiments for carrying out the present invention will be described in detail below.

[1235] This invention is a system that calculates the appropriate amount of alcohol to drink based on the user's physical condition, drunkenness level, and drinking location information, and issues an alert in real time. This system helps users enjoy drinking while maintaining an ideal level of drunkenness. The system is primarily implemented using the user's smartphone or wearable device (terminal) and a server running on the backend.

[1236] 1. Initial Setup and User Authentication

[1237] Collection of User Information

[1238] When a user installs the application on their device and launches it for the first time, an initial setup screen appears, where the user enters information such as their name, weight, gender, and drinking experience.

[1239] Sending and storing user information

[1240] The device sends the input information to a server, which stores the received information in a database and uses it as the basis for calculating the appropriate alcohol content.

[1241] 2. Input today's situation

[1242] Enter your current physical condition, where you're drinking, and what you plan to eat

[1243] The user inputs their physical condition on the day (e.g., normal, tired, etc.) and the location where they will be drinking (e.g., at home, a friend's house, a restaurant, etc.), as well as the predicted drinks menu (e.g., beer, wine, shochu, etc.).

[1244] Sending and storing status information

[1245] The terminal sends this input information to the server, which then stores the received information in a database.

[1246] 3. Alcohol calculation and alert settings

[1247] Calculating the appropriate amount of alcohol

[1248] The server analyzes the collected user information, physical condition information, and drinking location information based on an algorithm, and calculates the appropriate amount of alcohol to reach the level of intoxication set by the user.

[1249] Alert settings and notifications

[1250] Based on the calculated alcohol content, the server sets an alert and sends it to the device, where the user can receive the alert in real time.

[1251] 4. Real-time assistance while drinking

[1252] Input and record alcohol intake

[1253] Users input the type and amount of alcohol they wish to drink into the device, which then transmits the information to a server, which records it in real time in a database.

[1254] Alcohol intake check and assistance provided

[1255] The server compares the current amount of alcohol consumed with the set amount in real time based on the amount of alcohol consumed entered by the user, and if necessary, sends assistance information such as "recommended snacks" or "warnings about drinking too much" to the user's device.

[1256] 5. Last train alerts and meeting minutes

[1257] Last train time setting and alert notification

[1258] When a user inputs the last train time into the device, the information is sent to the server, which then generates an alert and sends it to the device to notify the user one hour or 30 minutes before the last train.

[1259] Minute creation using voice recognition

[1260] Conversations made while drinking are recorded using the device's voice recognition function, and the data is sent to a server, which generates minutes based on the data and stores them for later reference by the user.

[1261] 6. Follow-up after drinking

[1262] Follow-up notification the next day

[1263] The next morning, the device sends the user a follow-up notification asking, "Did you drink moderately yesterday?" If the user answers "yes" or "no," that feedback is sent to the server.

[1264] Save your feedback and apply it next time

[1265] The server stores the received feedback in a database and reflects it in the next alcohol content calculation.

[1266] This allows users to enjoy drinking safely and healthily while maintaining an ideal level of intoxication.

[1267] The processing flow will be explained below.

[1268] Step 1:

[1269] Enter and submit user information

[1270] When a user launches the app for the first time, they enter information such as their name, weight, gender, and drinking experience.

[1271] The terminal transmits the entered user information to the server.

[1272] Step 2:

[1273] Saving user information

[1274] The server stores the received user information in a database.

[1275] Step 3:

[1276] Input of today's situation

[1277] The user inputs their physical condition on the day, the location where they will be drinking, and the planned drinking menu into the device.

[1278] The terminal transmits this information to the server.

[1279] Step 4:

[1280] Save today's status information

[1281] The server stores the received physical condition information, drinking location information, and drinking menu information in a database.

[1282] Step 5:

[1283] Calculating alcohol content

[1284] The server calculates the ideal amount of alcohol for the day based on the user's weight, physical condition, drinking location, and past data.

[1285] When calculating, an algorithm is applied depending on the set drunkenness level (e.g. tipsy).

[1286] Step 6:

[1287] Alert Settings and Notifications

[1288] The server sets an alert based on the calculation results.

[1289] The device notifies the user of configured alerts.

[1290] Step 7:

[1291] Enter and submit alcohol intake

[1292] The user enters the type and amount of alcohol consumed into the device.

[1293] The terminal transmits the inputted information on the amount of alcohol consumed to the server.

[1294] Step 8:

[1295] Saving and reviewing alcohol intake information

[1296] The server stores the received alcohol intake information in a database.

[1297] The server checks the current amount of alcohol consumed and calculates assistance information if the amount is below the appropriate level.

[1298] Step 9:

[1299] Assistance Information Notification

[1300] The server transmits assistance information during drinking to the terminal.

[1301] The device notifies the user of assistance information.

[1302] When the amount of alcohol consumed approaches the set limit, the user will receive an alert such as "Be careful not to drink too much."

[1303] Step 10:

[1304] Last train alert settings and notifications

[1305] The user sets the last train time on the device and sends that information to the server.

[1306] The server generates a last train alert before the last train and sends it to the terminal.

[1307] The device will notify the user of the last train alert.

[1308] Step 11:

[1309] Generate meeting minutes

[1310] During the drinking party, the device transmits voice data to the server.

[1311] The server uses voice recognition technology to convert the conversation into text data and generate minutes.

[1312] Step 12:

[1313] Next day follow-up

[1314] The next morning, the device will send the user a follow-up notification asking, "Did you drink moderate amounts of alcohol yesterday?"

[1315] The user enters the answer and the device sends the information to the server.

[1316] The server stores the received feedback in a database and reflects it in the next alcohol content calculation.

[1317] By following these steps, users can enjoy safe and enjoyable drinking while taking proper control of their drinking.

[1318] Example 1

[1319] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1320] In modern society, many people enjoy drinking alcohol, but there are concerns about the health risks associated with excessive drinking and inappropriate drinking habits. Furthermore, there are also problems such as forgetting the last train and having difficulty getting home, and issues with efficiency when taking minutes while drinking. In these situations, there is a need for a system that can manage appropriate drinking amounts in real time and provide appropriate assistance to users.

[1321] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1322] In this invention, the server includes a means for receiving physical condition information input by the user, a means for receiving drunkenness level information set by the user, and a means for receiving drinking location information input by the user. This allows the server to calculate the appropriate amount of alcohol based on the collected information, enabling the user to enjoy drinking safely while maintaining an ideal drunkenness level.

[1323] The server also includes a means for receiving alcohol intake information input by the user and checking the current alcohol intake in real time, a means for providing appropriate assistance information, a means for inputting the time of the last train, a means for issuing a last train alert based on the time of the last train, and a means for recording conversations while drinking using voice recognition and generating minutes. This enables the server to comprehensively manage the user's behavior while drinking and also assist with secondary tasks (e.g., managing the time to return home and creating minutes).

[1324] "Physical condition information" is information that indicates the user's current health condition and mood.

[1325] "Drunkenness level information" is information that indicates the level of drunkenness that the user wants to achieve through drinking.

[1326] "Drinking location information" is information about the location where the user plans to drink alcohol.

[1327] "Amount of alcohol" indicates the total amount of alcohol the user plans to drink.

[1328] An "alert" is a notification or warning that prompts a user to take a specific action.

[1329] "Alcohol intake information" is information about the type and amount of alcohol actually consumed by the user.

[1330] "Assistance information" is advice and recommendations to support users in drinking alcohol safely and effectively.

[1331] The "last train time" refers to the last operating time of the public transportation used by the user.

[1332] "Speech recognition" is a technology that analyzes a user's voice and converts it into a format such as text.

[1333] Minutes are documents that record the contents of meetings or conversations and can be referenced later.

[1334] A "database" is a system that stores information systematically and allows it to be quickly searched and retrieved as needed.

[1335] A "server" is a computer system that processes and manages data and communicates with other devices over a network.

[1336] A "terminal" is a device that a user can directly operate to input or receive information.

[1337] The present invention is a system that helps users enjoy drinking alcohol while maintaining an ideal level of intoxication. This system is primarily realized by the user's smartphone or wearable device (terminal) and a server running on the backend.

[1338] The operation of this system will be explained in detail below. First, the user installs the application on their device, and the initial setup screen is displayed when the application is launched for the first time. The user enters physical information such as name, weight, gender, and drinking history, and the device sends this information to the server. The server stores the received information in a database and uses it as basic data.

[1339] Next, the user enters information about the situation on the day, such as their physical condition, the place where they will be drinking, and the menu they plan to have. This information is also sent from the device to the server and stored in a database. The server uses an algorithm based on the collected user information and the situation information for that day to calculate the appropriate amount of alcohol to reach the level of intoxication set by the user.

[1340] Based on the calculated alcohol content, the server generates an alert and sends it to the device. The user can receive the alert in real time while drinking. Furthermore, when the user inputs the type and amount of alcohol consumed into the device each time, the device sends that information to the server, which records the amount consumed in a database in real time and provides assistance information such as "recommended snacks" or "warnings against drinking too much" as needed.

[1341] When a user inputs the last train time, the information is sent from the device to the server, and the server generates an alert one hour or 30 minutes before the last train and sends it to the device to notify the user.

[1342] It is also possible to record conversations while drinking using a voice recognition function. The device sends the voice data to a server, which analyzes it and generates minutes, which are then stored in a database for later reference by the user.

[1343] The next morning, the server sends a follow-up notification to the device asking, "Did you drink a reasonable amount of alcohol yesterday?" If the user answers "yes" or "no," that feedback will be reflected in the next alcohol calculation.

[1344] Here is an example prompt:

[1345] "Please enter your health condition, drinking location, and planned drinking menu for today. For example, please enter your health condition as 'normal', your drinking location as 'izakaya', and your planned menu as 'beer and sake'."

[1346] This allows users to easily input information and enables the system to effectively support the user's drinking experience.

[1347] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1348] Step 1:

[1349] Initial Setup and User Authentication

[1350] The user installs the application on their device and the initial setup screen is displayed when they launch it for the first time.

[1351] Input: The user inputs physical information such as name, weight, gender, and drinking experience.

[1352] The terminal temporarily stores the input information in memory.

[1353] The device transmits the stored information to the server.

[1354] The server stores the received information in a database.

[1355] Output: The server sends a confirmation message to the terminal that the save is complete, and the terminal displays it to the user.

[1356] Step 2:

[1357] Today's situation input

[1358] The user inputs information such as their physical condition on the day, where they will be drinking, and the planned menu into the terminal.

[1359] Input: Physical condition information (e.g., normal), Drinking location information (e.g., izakaya), Drinking menu information (e.g., beer)

[1360] The terminal temporarily stores the input information in memory.

[1361] The device transmits the stored information to the server.

[1362] The server stores the received information in a database.

[1363] Output: The server sends a confirmation message to the terminal that the save is complete, and the terminal displays it to the user.

[1364] Step 3:

[1365] Alcohol calculation and alert settings

[1366] The server uses an algorithm to calculate the appropriate amount of alcohol based on collected user information, physical condition information, and drinking location information.

[1367] Input: User information, physical condition information, drinking location information

[1368] Data processing: Algorithm-based data analysis

[1369] Output: Calculated alcohol content

[1370] The server generates an alert based on the calculated alcohol content and sends it to the device.

[1371] The device notifies the user of alerts in real time.

[1372] Step 4:

[1373] Real-time assistance while drinking

[1374] The user inputs the type and amount of alcohol consumed into the terminal each time.

[1375] Input: type and amount of alcohol (e.g. 500ml beer)

[1376] The terminal temporarily stores the input information in memory.

[1377] The terminal transmits the input information to the server.

[1378] The server records the received alcohol intake information in a database.

[1379] The server compares the current amount of alcohol consumed with the set limit and generates assistance information as needed.

[1380] Output: Assistance information (e.g., recommended snacks, warnings against drinking too much)

[1381] The server sends the assistance information to the terminal.

[1382] The terminal notifies the user of the received information.

[1383] Step 5:

[1384] Last train alert and meeting minutes

[1385] The user enters the last train time into the terminal (e.g., 23:00).

[1386] Input: Last train time information

[1387] The terminal transmits the input information to the server.

[1388] The server stores the received information in a database.

[1389] The server generates an alert and sends it to the terminal one hour or 30 minutes before the last train.

[1390] Output: Last train alert notification

[1391] The terminal notifies the user of the received alert.

[1392] Step 6:

[1393] Follow-up after drinking

[1394] The next morning, the server sends a follow-up notification to the device asking, "Did you drink an appropriate amount of alcohol yesterday?"

[1395] Output: Follow-up notification

[1396] The user answers "yes" or "no."

[1397] Input: User feedback

[1398] The terminal transmits the user's answer to the server.

[1399] The server stores the received feedback in a database.

[1400] The feedback will be reflected in the next alcohol calculation.

[1401] Through these specific processing steps, users can enjoy drinking safely and healthily while maintaining an ideal level of intoxication.

[1402] (Application example 1)

[1403] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1404] In modern society, there is a lack of ways for users to enjoy drinking alcohol while maintaining an appropriate amount of alcohol intake and enjoying content that is optimal for their situation. In particular, there is a need for a means to provide entertainment content that is individually optimized based on the user's physical condition and drinking situation. There is also a need for a system that allows users to enjoy optimal content while managing their drinking amount and physical condition in real time while drinking.

[1405] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1406] In this invention, the server includes means for receiving physical condition information input by the user, means for receiving drunkenness level information set by the user, means for receiving drinking location information input by the user, means for calculating the appropriate amount of alcohol based on the received information, means for issuing an alert based on the calculated amount of alcohol, and content recommendation means for recommending optimal content based on the user's drinking status and physical condition. This allows the user to enjoy entertainment content optimal for their situation at any given time while safely and comfortably enjoying alcohol.

[1407] "Physical condition information" is data indicating the user's physical condition, such as normal, tired, or unwell.

[1408] "Drunkenness level information" is data indicating the ideal level of drunkenness set by the user, such as wanting to get a little drunk, wanting to get tipsy, or not wanting to get drunk.

[1409] "Drinking location information" is data relating to the location where the user drinks alcohol, such as at home, at a friend's house, or at a restaurant.

[1410] The "appropriate amount of alcohol" is the amount of alcohol consumed that a user needs to maintain an ideal level of intoxication, calculated based on the user's physical condition, level of intoxication, and drinking location information.

[1411] An "alert" is a warning or suggestion that the system notifies the user, such as warning them to be careful not to drink too much or informing them when to have their next drink.

[1412] "Content recommendation means" refers to algorithms and technologies for recommending optimal entertainment content based on a user's physical condition, drunkenness level, drinking location, and past viewing history.

[1413] The following is a detailed description of an embodiment of the present invention. The present invention is a system that calculates the appropriate amount of alcohol to drink based on information about the user's physical condition, drunkenness level, and drinking location, and issues an alert in real time. The system also has a function to recommend optimal content based on the user's drinking habits and physical condition. This system is primarily implemented using the user's device (a smartphone or wearable device) and a server operating in the backend.

[1414] 1. Initial Setup and User Authentication

[1415] Collection of User Information

[1416] When the application is first installed and launched, an initial setup screen appears, where the user enters information such as their name, weight, gender, and drinking experience.

[1417] Sending and storing user information

[1418] The device sends the input information to a cloud server, which then stores it in a database, which is used as the basis for calculating the appropriate alcohol content.

[1419] 2. Input today's situation

[1420] Enter your current physical condition, where you're drinking, and what you plan to eat

[1421] Users input their physical condition on the day, the location where they will be drinking, and the planned drinking menu into the device.

[1422] Sending and storing status information

[1423] The device sends this input information to a cloud server, which then stores the received information in a database.

[1424] 3. Alcohol calculation and alert settings

[1425] Calculating the appropriate amount of alcohol

[1426] The server uses an algorithm to analyze the collected user information, physical condition information, and drinking location information, and calculates the appropriate amount of alcohol to reach the level of intoxication set by the user.

[1427] Alert settings and notifications

[1428] Based on the calculated alcohol content, the server sets an alert and sends it to the user's device, where the user can receive the alert in real time.

[1429] 4. Real-time assistance while drinking

[1430] Input and record alcohol intake

[1431] Users input the type and amount of alcohol they wish to drink into the device, which then sends the information to a cloud server, which records it in a database in real time.

[1432] Alcohol intake check and assistance provided

[1433] The server compares the current amount of alcohol consumed with the set amount in real time based on the amount of alcohol consumed entered by the user, and if necessary, sends assistance information such as "recommended snacks" or "warnings about drinking too much" to the device.

[1434] 5. Content Recommendation

[1435] Recommending the right content

[1436] The server recommends optimal content based on the user's drinking habits and physical condition, using Python-based machine learning models (such as TensorFlow and PyTorch) to reference the user's past viewing history and data on similar users.

[1437] Content Notification

[1438] The server sends a list of recommended content to the user's device, which can then receive the list in real time.

[1439] Hardware and software used

[1440] Hardware: Smartphone (iOS or Android device)

[1441] software:

[1442] Cloud services (AWS and Google Cloud)

[1443] Database systems (Firestore, MySQL)

[1444] Machine learning frameworks (TensorFlow, PyTorch)

[1445] Specific examples

[1446] Below are some example prompts to input to a generative AI model:

[1447] Username: Yamada Taro

[1448] Weight: 70kg

[1449] Gender: Male

[1450] Drinking experience: Intermediate

[1451] Today's mood: Normal

[1452] Drinking location: Home

[1453] Planned drinks menu: beer, wine

[1454] Generate a list of recommended movies, music playlists, and videos for users who are in normal health and drinking beer and wine at home.

[1455] As described above, the present invention is a system that allows users to enjoy drinking safely and healthily while maintaining an ideal level of intoxication, and to enjoy entertainment content that is optimal for the situation at hand.

[1456] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1457] Step 1:

[1458] Entering and collecting user information

[1459] When a user installs the application on a device, they are prompted to enter information such as their name, weight, gender, and drinking history as initial settings. This data is sent from the device to a cloud server, which then stores it in a database.

[1460] Input: Name, weight, gender, drinking experience, etc.

[1461] Output: User information stored in the database

[1462] How it works: When a user enters information such as their name, weight, gender, and drinking experience into their smartphone and presses the "Save" button, the data is sent to a cloud server, where it is recorded in a database.

[1463] Step 2:

[1464] Today's situation input

[1465] The user inputs information about their physical condition for the day, where they will be drinking, and the planned drinking menu into the device. The device then sends this information to the cloud server, which then stores it in a database.

[1466] Input: Today's health information, drinking location information, planned drinking menu

[1467] Output: Current status information stored in the database

[1468] How it works: When a user enters their current physical condition (e.g., "normal"), where they are drinking (e.g., "home"), and what they plan to drink (e.g., "beer, wine") into their smartphone and presses the "Save" button, the data is sent to the cloud server, which then records the data in a database.

[1469] Step 3:

[1470] Calculating the right amount of alcohol

[1471] The server uses an algorithm to analyze collected user information, physical condition information, and drinking location information to calculate the appropriate amount of alcohol.

[1472] Input: User information, health information, drinking location information

[1473] Output: Calculation result of appropriate amount of alcohol

[1474] Specific operation: The server retrieves user information and today's situation information from the database, and then applies an algorithm within the program (such as a linear regression model with specific coefficients) based on this information to calculate the appropriate amount of alcohol the user can safely drink.

[1475] Step 4:

[1476] Alert settings and notifications

[1477] The server sets an alert based on the appropriate alcohol content and sends it to the device, which the user receives in real time.

[1478] Input: Calculation result of appropriate alcohol amount

[1479] Output: Alert notification to user's terminal

[1480] Specific operation: Based on the calculated appropriate amount of alcohol, the server determines the maximum amount of alcohol the user should drink, and if the limit is exceeded, an alert message such as "Be careful not to drink too much" is sent to the device. The alert is displayed on the user's device in the form of a push notification or other means.

[1481] Step 5:

[1482] Alcohol intake entry and real-time assistance

[1483] The user inputs the type and amount of alcohol consumed into the device, which is then sent to the server, where it is recorded in a database in real time. The server then compares the current amount of alcohol consumed with the set amount, and sends assistance information to the device as needed.

[1484] Input: Type and amount of alcohol consumed

[1485] Output: Assistance information based on current alcohol intake

[1486] How it works: The user enters the type and amount of alcohol they have consumed into their smartphone, and the information is sent to a cloud server. The server records this information in a database in real time, manages the appropriate amount set, and sends assistance notifications to the device as needed (such as "recommended snacks" or "warnings against drinking too much").

[1487] Step 6:

[1488] Content recommendations and notifications

[1489] The server recommends the most suitable content based on the user's drinking habits and physical condition. This recommendation is made using a Python-based machine learning model (such as TensorFlow or PyTorch). A list of recommended content is sent to the user's device.

[1490] Input: User's drinking status, physical condition information

[1491] Output: A list of recommended content

[1492] How it works: The server retrieves the user's drinking history and physical condition information from the database, and then uses a machine learning model (such as TensorFlow or PyTorch) to recommend the most suitable content (movies, music, videos, etc.) for the user. The recommendation results are sent to the user's smartphone, and the user can receive a list of content.

[1493] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1494] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The embodiments for carrying out the present invention will be described in detail below.

[1495] This invention combines an emotion engine with a system that calculates the appropriate amount of alcohol to drink based on the user's physical condition, drunkenness level, and drinking location information, and issues alerts in real time. The emotion engine recognizes the user's emotional state from their facial expressions and voice, and uses this information to further optimize the drinking experience. This system is realized using the user's smartphone or wearable device (terminal) and a server running on the backend.

[1496] 1. Initial Setup and User Authentication

[1497] Collection of User Information

[1498] When a user installs the application on their device and launches it for the first time, an initial setup screen appears, where the user enters information such as their name, weight, gender, and drinking experience.

[1499] Sending and storing user information

[1500] The device sends the entered user information to a server, which then stores the received information in a database, which is used as the basis for calculating the appropriate alcohol content.

[1501] 2. Input today's situation

[1502] Enter your current physical condition, where you're drinking, and what you plan to eat

[1503] The user inputs their physical condition on the day (e.g., normal, tired, etc.) and the location where they will be drinking (e.g., at home, a friend's house, a restaurant, etc.), as well as the predicted drinks menu (e.g., beer, wine, shochu, etc.).

[1504] Sending and storing status information

[1505] The terminal sends this input information to the server, which then stores the received information in a database.

[1506] 3. Alcohol calculation and alert settings

[1507] Calculating the appropriate amount of alcohol

[1508] The server analyzes the collected user information, physical condition information, and drinking location information based on an algorithm, and calculates the appropriate amount of alcohol to reach the level of intoxication set by the user.

[1509] Alert settings and notifications

[1510] Based on the calculated alcohol content, the server sets an alert and sends it to the device, where the user can receive the alert in real time.

[1511] 4. Real-time assistance while drinking

[1512] Input and record alcohol intake

[1513] Users input the type and amount of alcohol they wish to drink into the device, which then transmits the information to a server, which records it in real time in a database.

[1514] Alcohol intake check and assistance provided

[1515] The server compares the current amount of alcohol consumed with the set amount in real time based on the amount of alcohol consumed entered by the user, and if necessary, sends assistance information such as "recommended snacks" or "warnings about drinking too much" to the user's device.

[1516] 5. Implementing the Emotion Engine

[1517] Recognition of emotional states

[1518] The device analyzes the user's facial expressions and voice in real time, and the emotion engine recognizes the user's emotional state (e.g., happy, stressed, etc.).

[1519] Transmission and use of emotional information

[1520] The device sends the recognized emotional information to the server, which then uses that emotional information to further adjust the amount of alcohol consumed and the assistance information provided, for example, recommending relaxing snacks if the user is feeling stressed.

[1521] 6. Last Train Alerts and Meeting Minutes

[1522] Last train time setting and alert notification

[1523] When a user inputs the last train time into the device, the information is sent to the server, which then generates an alert and sends it to the device to notify the user one hour or 30 minutes before the last train.

[1524] Minute creation using voice recognition

[1525] Conversations made while drinking are recorded using the device's voice recognition function, and the data is sent to a server, which generates minutes based on the data and stores them for later reference by the user.

[1526] 7. Follow-up after drinking

[1527] Follow-up notification the next day

[1528] The next morning, the device sends the user a follow-up notification asking, "Did you drink moderately yesterday?" If the user answers "yes" or "no," that feedback is sent to the server.

[1529] Save your feedback and apply it next time

[1530] The server stores the received feedback in a database and reflects it in the next alcohol content calculation.

[1531] This allows users to properly manage their drinking while receiving optimal assistance according to their emotional state, allowing them to enjoy drinking in a fun and safe way.

[1532] The processing flow will be explained below.

[1533] Step 1:

[1534] Enter and submit user information

[1535] When a user launches the app for the first time, they enter information such as their name, weight, gender, and drinking experience.

[1536] The terminal transmits the entered user information to the server.

[1537] Step 2:

[1538] Saving user information

[1539] The server stores the received user information in a database.

[1540] Step 3:

[1541] Input of today's situation

[1542] The user inputs their physical condition on the day, the location where they will be drinking, and the planned drinking menu into the device.

[1543] The terminal transmits this information to the server.

[1544] Step 4:

[1545] Save today's status information

[1546] The server stores the received physical condition information, drinking location information, and drinking menu information in a database.

[1547] Step 5:

[1548] Calculating alcohol content

[1549] The server calculates the ideal amount of alcohol for the day based on the user's weight, physical condition, drinking location, and past data.

[1550] When calculating, an algorithm is applied depending on the set drunkenness level (e.g. tipsy).

[1551] Step 6:

[1552] Alert Settings and Notifications

[1553] The server sets an alert based on the calculation results.

[1554] The device notifies the user of configured alerts.

[1555] Step 7:

[1556] Enter and submit alcohol intake

[1557] The user enters the type and amount of alcohol consumed into the device.

[1558] The terminal transmits the inputted information on the amount of alcohol consumed to the server.

[1559] Step 8:

[1560] Saving and reviewing alcohol intake information

[1561] The server stores the received alcohol intake information in a database.

[1562] The server checks the current amount of alcohol consumed and calculates assistance information if the amount is below the appropriate level.

[1563] Step 9:

[1564] Assistance Information Notification

[1565] The server transmits assistance information during drinking to the terminal.

[1566] The device notifies the user of assistance information.

[1567] When the amount of alcohol consumed approaches the set limit, the user will receive an alert such as "Be careful not to drink too much."

[1568] Step 10:

[1569] Recognizing and transmitting emotional states

[1570] The device analyzes the user's facial expressions and voice in real time, and the emotion engine recognizes the user's emotional state (e.g., happy, stressed, etc.).

[1571] The recognized emotion information is sent to the server.

[1572] Step 11:

[1573] Adjustment based on emotional state

[1574] The server further adjusts the amount of alcohol consumed and assistance information based on the emotional information received.

[1575] For example, if a user is feeling stressed, we will recommend snacks that have a relaxing effect.

[1576] Step 12:

[1577] Last train alert settings and notifications

[1578] The user sets the last train time on the device and sends that information to the server.

[1579] The server generates a last train alert before the last train and sends it to the terminal.

[1580] The device will notify the user of the last train alert.

[1581] Step 13:

[1582] Generate meeting minutes

[1583] During the drinking party, the device transmits voice data to the server.

[1584] The server uses voice recognition technology to convert the conversation into text data and generate minutes.

[1585] Step 14:

[1586] Next day follow-up

[1587] The next morning, the device will send the user a follow-up notification asking, "Did you drink moderate amounts of alcohol yesterday?"

[1588] The user enters the answer and the device sends the information to the server.

[1589] The server stores the received feedback in a database and reflects it in the next alcohol content calculation.

[1590] By following these steps, users can enjoy safe drinking while properly managing their drinking and receiving optimal assistance based on their emotional state.

[1591] Example 2

[1592] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1593] Conventional alcohol consumption management systems only managed alcohol intake based on the user's physical condition and level of intoxication, and had the function of issuing an alert, but this did not respond appropriately to the user's emotions or environment, resulting in problems with satisfaction and safety. Furthermore, there was a need for a more accurate way to manage alcohol intake by taking environmental and biological information into account.

[1594] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1595] In this invention, the server includes a means for receiving biometric information input by the user, a means for receiving satisfaction level information set by the user, and a means for receiving environmental information input by the user, thereby enabling calculation of an appropriate alcohol intake amount based on the user's physical condition, emotions, and environment, and providing assistance and alerts in real time.

[1596] "Biometric information" refers to data related to the user's physical condition and health, including, for example, weight, gender, age, past drinking history, and physical condition.

[1597] "Satisfaction information" refers to data that indicates the level of intoxication desired by the user and their expectations regarding drinking, including emotional states such as "fun" or "want to relax."

[1598] "Environmental information" refers to data about the location where the user drinks and the circumstances at the time, including, for example, the location where the drink is taken (home, restaurant, etc.), the atmosphere of the location, and the presence of other people.

[1599] "Intake" refers to the amount of alcohol a user should drink, including an appropriate amount calculated based on the user's physical condition, satisfaction, and environmental information.

[1600] "Emotional state" refers to the user's current psychological and emotional state, and includes information such as "happy," "stressed," and "relaxed."

[1601] "Alerts" refer to warning or suggestion messages sent to users, such as "Be careful not to drink too much" or "Recommended snacks."

[1602] "Support information" refers to information that helps users drink alcohol appropriately, including, for example, advice on adjusting future drinking amounts, recommended meals, and advice on the pace at which to drink.

[1603] This invention combines an emotion engine with a system that calculates the appropriate amount of alcohol intake based on biometric information, satisfaction information, and environmental information input by the user and issues alerts in real time. This system is realized using the user's smartphone or wearable device (terminal) and a server running on the backend.

[1604] Initial Setup and User Authentication

[1605] When a user installs the application on their device and launches it for the first time, an initial setup screen appears. The user enters biometric information such as their name, weight, gender, age, and drinking experience. The device sends this information to a server, which stores it in a database. This information is used as the basis for calculating appropriate alcohol intake.

[1606] Today's situation input

[1607] The user inputs environmental information into the device, such as their physical condition on the day (e.g., normal, tired, feeling a bit under the weather, etc.) and the location where they will be drinking (e.g., at home, a friend's house, a restaurant, etc.). They also input their predicted drinking menu (e.g., two beers and one glass of wine). The device sends this situation information to the server, which then stores the received information in a database.

[1608] Alcohol calculation and alert settings

[1609] The server runs an algorithm based on stored user information, physical condition information, drinking location information, and predicted drinking menu to calculate the appropriate amount of alcohol to reach the user's desired level of satisfaction. The server sets an alert based on the calculated appropriate amount of alcohol, and the device notifies the user in real time. For example, it displays messages such as "Only one more beer" or "Be careful not to drink too much!"

[1610] Real-time assistance while drinking

[1611] The user inputs the type and amount of alcohol consumed into the device. The device then sends the input information to the server, which records it in a database in real time. The server compares the user's current alcohol intake with a preset appropriate drinking amount, and notifies the device of assistance information such as "recommended snacks" or "warnings against drinking too much" as needed.

[1612] Implementing the Emotion Engine

[1613] The device analyzes the user's facial expressions and voice in real time. For example, it uses the smartphone's camera and microphone to analyze the user's facial expressions and tone of voice. The emotion engine recognizes the user's emotional state (e.g., happy, stressed, etc.) and generates information about it. The device sends the recognized emotion information to the server, which then adjusts the amount of alcohol consumed and customizes assistance information based on that emotion information. For example, if the user is feeling stressed, it can recommend snacks that have a relaxing effect.

[1614] Last train alert and meeting minutes creation

[1615] The user enters the time of the last train into the device. For example, if the user enters "The last train is at 10:30 p.m.", the server saves that information in a database. The server generates an alert one hour or 30 minutes before the last train, and the device notifies the user. The device also uses a voice recognition function to record conversations that were taking place while drinking. For example, the smartphone's microphone can be used to convert the conversation into text, and the server can generate and save minutes based on that data.

[1616] Follow-up after drinking

[1617] The next morning, the device sends the user a question: "Were you satisfied with the amount of alcohol you drank yesterday?" The user answers "yes" or "no," and the feedback is sent to the server. The server stores the feedback in a database and reflects it in the next alcohol amount calculation. For example, it may fine-tune the suggested amount of alcohol based on the previous feedback.

[1618] Examples:

[1619] A user named "Taro" enters his weight as 70 kg, his gender as male, his drinking experience, and his preferred types of alcohol as beer and wine. The device sends this information to the server, which then stores it in a database.

[1620] The user inputs, "I'm feeling fine today, I plan to drink at home, and my planned menu is two beers and one glass of wine." The device sends this information to the server, which then stores it in a database.

[1621] The device's camera detects the user's smile, and the emotion engine recognizes it as "fun." The device then sends this information to the server, which then provides "assistance information perfect for a fun drinking party."

[1622] A user sets the last train time to 23:30. The server sends an alert from the device at 22:30 and 23:00.

[1623] Example prompt sentence:

[1624] "User information: Taro, Weight: 70kg, Gender: Male, Drinking experience: Yes. Please calculate the appropriate amount of alcohol."

[1625] "The user has entered their current health state as 'normal', their drinking location as 'home', and their planned menu as '2 beers, 1 glass of wine'. Create appropriate alerts and assistance information."

[1626] "The user entered the last train time as 23:30. Please send an alert 1 hour and 30 minutes before the last train."

[1627] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1628] Processing Steps

[1629] Step 1: Initial Setup and User Authentication

[1630] 1. When a user installs the application on their device and launches it for the first time, an initial setup screen will appear.

[1631] 2. The user enters biometric information such as name, weight, gender, age, and drinking experience.

[1632] Input: User information (name, weight, gender, age, drinking experience)

[1633] Output: User information data

[1634] 3. The device sends this information to the server, and the server stores the received information in a database.

[1635] Data processing / calculation: Saving user information

[1636] Step 2: Input your current situation

[1637] 1. The user inputs environmental information into the device, such as their physical condition on the day (e.g., normal, tired, feeling a bit like a cold, etc.) and the location where they drank alcohol (e.g., at home, a friend's house, a restaurant, etc.).

[1638] Input: Health information, drinking location information

[1639] Output: Today's status information data

[1640] 2. Additionally, enter your predicted drinking menu (e.g., 2 beers, 1 wine).

[1641] Input: Drinking menu information

[1642] Output: Completed status information data

[1643] 3. The device sends this status information to the server, and the server stores the received information in a database.

[1644] Data processing / calculation: Saving status information

[1645] Step 3: Calculate alcohol intake and set alerts

[1646] 1. The server runs an algorithm based on stored user information, physical condition information, drinking location information, and predicted drinking menu.

[1647] Input: User information, physical condition information, drinking location information, drinking menu

[1648] Calculation: Calculating the appropriate amount of alcohol

[1649] Output: Appropriate alcohol content data

[1650] 2. Calculate the appropriate amount of alcohol to reach the user's desired satisfaction level and set an alert.

[1651] Data processing / calculation: Alert information generation

[1652] 3. The server sends the alert information to the device, and the device notifies the user in real time.

[1653] Input: Alert information

[1654] Output: User notification (e.g., "Only one more beer left!", "Don't drink too much!")

[1655] Step 4: Real-time assistance while drinking

[1656] 1. The user enters the type and amount of alcohol consumed into the device.

[1657] Input: Alcohol intake information

[1658] Output: Alcohol intake data

[1659] 2. The device sends the entered alcohol intake information to the server, which records it in a database in real time.

[1660] Data processing / calculation: Saving alcohol intake information

[1661] 3. The server compares the user's current drinking level with the predetermined appropriate drinking level and generates assistance information as needed.

[1662] Input: Alcohol intake data, set appropriate amount

[1663] Calculation: Check alcohol intake

[1664] Output: Assistance information

[1665] 4. The device notifies the user of the generated assistance information. For example, it may present "recommended snacks" or "be careful not to drink too much!"

[1666] Data processing / calculation: Notification of assistance information

[1667] Step 5: Implementing the Emotion Engine

[1668] 1. The device analyzes the user's facial expressions and voice in real time. For example, it uses the smartphone's camera and microphone to analyze the user's facial expressions and tone of voice.

[1669] Input: facial expression data, voice data

[1670] Computation: Recognizing Emotional States

[1671] Output: Emotional information

[1672] 2. The emotion engine recognizes the user's emotional state.

[1673] Data processing / calculation: Generating emotional information

[1674] 3. The device sends the recognized emotional information to the server, which then adjusts the amount of alcohol and customizes the assistance information based on the emotional information.

[1675] Input: Emotion information

[1676] Calculation: Alcohol content adjustment, customization of assistance information

[1677] Output: Adjusted alcohol content data, customized assistance information

[1678] Step 6: Last train alert and meeting minutes

[1679] 1. The user enters the last train time into the terminal.

[1680] Input: Last train time

[1681] Output: Last train time data

[1682] 2. The server saves the last train time information in a database.

[1683] Data processing / calculation: Saving the last train time

[1684] 3. The server generates an alert one hour or 30 minutes before the last train, and the device notifies the user.

[1685] Input: Saved last train time

[1686] Operation: Alert Generation

[1687] Output: User notification (e.g. "1 hour before last train", "30 minutes before last train")

[1688] 4. The device uses voice recognition to record conversations while drinking. For example, it uses a smartphone microphone to convert the conversation into text, and the server generates and stores minutes based on that data.

[1689] Input: Conversation data while drinking

[1690] Computing: Speech recognition and text conversion

[1691] Output: Generate minutes data

[1692] Step 7: Follow up after drinking

[1693] 1. The next morning, the device sends the user the question, "Were you satisfied with the amount of alcohol you drank yesterday?"

[1694] Input: Question submission (automatic)

[1695] Output: User notification

[1696] 2. The user answers with "yes" or "no" and the feedback is sent to the server.

[1697] Input: User feedback

[1698] Output: Feedback data

[1699] 3. The server stores the feedback in a database and uses it in the next alcohol content calculation.

[1700] Data processing / calculation: Saving and reflecting feedback

[1701] Output: Adjusted alcohol content data

[1702] (Application example 2)

[1703] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1704] There is a need for technology to manage appropriate alcohol consumption and reduce the health risks associated with excessive drinking. Another challenge is to provide optimal assistance based on the user's emotional state and further improve the drinking experience. Food delivery services also require management to ensure users do not drink too much and enjoy their food and drink appropriately. In addition, there is a need for comprehensive support, including information on the user's last train and their health the next day.

[1705] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1706] In this invention, the server includes: means for receiving physical condition information input by the user; means for receiving drunkenness level information set by the user; means for receiving drinking location information input by the user; means for calculating an appropriate alcohol intake based on the received information; means for issuing an alert based on the calculated alcohol intake; means for analyzing the user's facial expressions and voice while drinking and recognizing their emotional state; means for providing appropriate assistance information based on the recognized emotional state; and means for implementing the above means using a server operating in the backend and linking with the user's device. This makes it possible to appropriately manage the user's alcohol intake, provide assistance according to their emotions, notify them of last train alerts, and support an optimal drinking experience with food delivery services.

[1707] "User" refers to any person who uses the Services or Applications.

[1708] "Health information" refers to information that indicates the user's health condition and level of fatigue on that day.

[1709] "Drunkenness level information" refers to information that allows a user to set the level of drunkenness they desire.

[1710] "Drinking location information" refers to information about the location where a user drinks alcohol.

[1711] "Alcohol content" refers to the appropriate amount of alcohol a user should drink.

[1712] An "alert" refers to a warning or notification given to the user.

[1713] "Facial expression analysis" refers to technology that recognizes a user's facial expressions and analyzes their state.

[1714] "Voice analysis" refers to technology that recognizes a user's voice and analyzes their emotional state.

[1715] "Emotional state" refers to the emotion the user is feeling (e.g., happy, stressed, etc.).

[1716] "Assistance Information" refers to supplementary information or advice provided to the User.

[1717] "Back-end server" refers to a remote server that processes data in cooperation with user terminals.

[1718] "Terminal" refers to a device used by a user, such as a smartphone or wearable device.

[1719] System Overview

[1720] The system for implementing this invention receives information on the user's physical condition, drunkenness level, and drinking location, calculates the appropriate amount of alcohol based on that information, issues an alert in real time, and recognizes the user's emotional state through facial expression and voice analysis, and provides appropriate assistance based on that information.

[1721] Hardware and software used

[1722] Hardware: Smartphones, wearable devices (e.g., Apple Watch)

[1723] Software: Cloud services (Amazon Web Services, Google Cloud, etc.), databases (MySQL, PostgreSQL), emotion engines (Microsoft Azure Emotion API, Google Cloud Vision API)

[1724] Detailed program processing

[1725] The process performed by the server and the device is as follows:

[1726] Collection and storage of user information

[1727] 1. Enter your user information

[1728] Users install the smartphone app and enter their name, weight, gender, and drinking experience on the initial setup screen.

[1729] 2. Transmission and storage of user information

[1730] The terminal sends the entered user information to the server, which stores it in a database.

[1731] Today's situation input

[1732] 1. Enter your physical condition, drinking location, and predicted menu for the day

[1733] Users input their physical condition on the day, the location where they will be drinking, and the anticipated drinking menu.

[1734] 2. Sending and storing status information

[1735] The terminal sends the input information to the server, which stores the information in a database.

[1736] Alcohol calculation and alert settings

[1737] 1. Calculating the amount of alcohol

[1738] The server uses an algorithm to analyze the collected user information and situational information and calculates the appropriate amount of alcohol.

[1739] 2. Setting up alerts and notifications

[1740] Based on the calculated alcohol content, the server sets an alert and notifies the device in real time.

[1741] Real-time assistance while drinking

[1742] 1. Input and record alcohol intake

[1743] The user inputs the type and amount of alcohol consumed into the device while drinking.

[1744] 2. Checking alcohol intake and providing assistance

[1745] Based on the amount of alcohol consumed entered by the user, the server compares the current amount of alcohol consumed with the set appropriate amount, and if necessary, notifies the user with "snack suggestions" or "warnings about drinking too much."

[1746] Implementing the Emotion Engine

[1747] 1. Recognizing emotional states

[1748] The device analyzes the user's facial expressions and voice in real time, and the emotion engine recognizes the user's emotional state.

[1749] 2. Transmission and use of emotional information

[1750] The device transmits the recognized emotion information to the server, which then adjusts the assistance information based on the information.

[1751] Follow-up

[1752] 1. Follow-up notification the next day

[1753] The next morning, the server sends a notification to the user via their device asking, "Did you drink an appropriate amount of alcohol yesterday?"

[1754] 2. Save your feedback and apply it next time

[1755] The server stores the user's feedback in a database and reflects it in the next alcohol content calculation.

[1756] Specific examples

[1757] The user starts drinking beer at home and enters their drinking information into the app.

[1758] The app will alert you that you can drink up to three beers.

[1759] The app detects if you look tired while drinking and notifies you of "recommended snacks."

[1760] The next morning, the app will notify you, "Did you drink an appropriate amount of alcohol yesterday?"

[1761] Prompt Sentence Examples

[1762] I drank three beers yesterday and felt tired afterwards. Do you have any recommended snacks?

[1763] effect

[1764] The system allows users to manage their drinking in real time and receive optimal assistance according to their emotions, allowing them to enjoy themselves while reducing health risks and improving their drinking experience.

[1765] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1766] Step 1: Collecting and storing user information

[1767] Input: The user enters information such as name, weight, gender, and drinking experience into their smartphone.

[1768] Processing: The device acquires this information and sends it to the cloud server, which stores it in a database.

[1769] Output: User information is saved in the database.

[1770] Specific operation: After the user initially sets up the app, they enter information, the device calls an API to send the data, and the server writes it to the database.

[1771] Step 2: Input your current situation

[1772] Input: The user inputs their physical condition for the day, the drinking location, and the predicted drinking menu into their smartphone.

[1773] Processing: The terminal sends the entered information to the server, which stores it in a database.

[1774] Output: Status information is saved in the database.

[1775] Specific operation: The user enters the information for the day, the device sends it to the server, and the server executes an API that stores the information in a database.

[1776] Step 3: Calculate the amount of alcohol

[1777] Input: User information stored on the server and the current situation information.

[1778] Processing: The server analyzes this information based on an algorithm and calculates the appropriate alcohol content.

[1779] Output: Calculated alcohol content.

[1780] Specific operation: The server retrieves user information and situational information from the database, runs an algorithm to calculate the alcohol content, and temporarily stores the result.

[1781] Step 4: Configure alerts and notifications

[1782] Input: Calculated alcohol amount.

[1783] Processing: The server sets the appropriate alert and notifies the terminal of it.

[1784] Output: The alert is displayed on the terminal.

[1785] Specific operation: The server checks the condition based on alcohol content and calls an API that generates an appropriate alert message and sends it to the device.

[1786] Step 5: Enter and record your drinking

[1787] Input: The user inputs the type and amount of alcohol into their smartphone while drinking.

[1788] Processing: The terminal sends the entered drinking information to the server, which records it in a database.

[1789] Output: Drinking information is recorded in a database.

[1790] Specific operation: The user enters drinking data, the device sends it to the server, and the server writes the information to the database.

[1791] Step 6: Check alcohol intake and provide assistance

[1792] Input: Saved drinking information.

[1793] Processing: The server compares the current amount of alcohol consumed with the set appropriate amount, and generates assistance information as necessary and notifies the device.

[1794] Output: Assistance information displayed on terminal.

[1795] Specific operation: The server retrieves the current amount of alcohol consumed from the database, compares it with the calculated appropriate amount, generates an assistance message, and calls an API to send it to the device.

[1796] Step 7: Recognizing your emotional state

[1797] Input: User's facial and voice data.

[1798] Processing: The device analyzes this data in real time, and the emotion engine recognizes the user's emotional state.

[1799] Output: Perceived emotional state.

[1800] Specific operation: The device uses the camera and microphone to collect the user's facial expressions and voice, then sends the data to the emotion engine API and receives the analysis results.

[1801] Step 8: Sending and using emotional information

[1802] Input: Perceived emotional state.

[1803] Processing: The device transmits its emotional state to the server, which then adjusts the assistance information based on that information.

[1804] Output: Adjusted assistance information.

[1805] Specific operation: The device sends the recognized emotion data to the server, and the server generates an assistance message that takes the emotional state into account and sends it to the device.

[1806] Step 9: Follow-up notification the next day

[1807] Input: User drinking data and analysis results.

[1808] Processing: The next morning, the server sends a notification to the user's device asking, "Did you drink an appropriate amount of alcohol yesterday?"

[1809] Output: A follow-up notification is displayed on the user's device.

[1810] Specific operation: The server uses the scheduling function to generate a notification at the specified time and send it to the user's device.

[1811] Step 10: Save your feedback and apply it next time

[1812] Input: The feedback given by the user.

[1813] Processing: The device sends user feedback to the server, which stores it in a database and reflects it in the next alcohol content calculation.

[1814] Output: The feedback is stored in a database.

[1815] How it works: The user enters feedback within the app, the device sends it to the server, and the server stores it in a database for use in the next calculation.

[1816] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1817] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1818] 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 the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1819] [Fourth embodiment]

[1820] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1821] 7, a 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.

[1822] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1823] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1824] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1825] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1826] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1827] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1828] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1829] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1830] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1831] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1832] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1833] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The embodiments for carrying out the present invention will be described in detail below.

[1834] This invention is a system that calculates the appropriate amount of alcohol to drink based on the user's physical condition, drunkenness level, and drinking location information, and issues an alert in real time. This system helps users enjoy drinking while maintaining an ideal level of drunkenness. The system is primarily implemented using the user's smartphone or wearable device (terminal) and a server running on the backend.

[1835] 1. Initial Setup and User Authentication

[1836] Collection of User Information

[1837] When a user installs the application on their device and launches it for the first time, an initial setup screen appears, where the user enters information such as their name, weight, gender, and drinking experience.

[1838] Sending and storing user information

[1839] The device sends the input information to a server, which stores the received information in a database and uses it as the basis for calculating the appropriate alcohol content.

[1840] 2. Input today's situation

[1841] Enter your current physical condition, where you're drinking, and what you plan to eat

[1842] The user inputs their physical condition on the day (e.g., normal, tired, etc.) and the location where they will be drinking (e.g., at home, a friend's house, a restaurant, etc.), as well as the predicted drinks menu (e.g., beer, wine, shochu, etc.).

[1843] Sending and storing status information

[1844] The terminal sends this input information to the server, which then stores the received information in a database.

[1845] 3. Alcohol calculation and alert settings

[1846] Calculating the appropriate amount of alcohol

[1847] The server analyzes the collected user information, physical condition information, and drinking location information based on an algorithm, and calculates the appropriate amount of alcohol to reach the level of intoxication set by the user.

[1848] Alert settings and notifications

[1849] Based on the calculated alcohol content, the server sets an alert and sends it to the device, where the user can receive the alert in real time.

[1850] 4. Real-time assistance while drinking

[1851] Input and record alcohol intake

[1852] Users input the type and amount of alcohol they wish to drink into the device, which then transmits the information to a server, which records it in real time in a database.

[1853] Alcohol intake check and assistance provided

[1854] The server compares the current amount of alcohol consumed with the set amount in real time based on the amount of alcohol consumed entered by the user, and if necessary, sends assistance information such as "recommended snacks" or "warnings about drinking too much" to the user's device.

[1855] 5. Last train alerts and meeting minutes

[1856] Last train time setting and alert notification

[1857] When a user inputs the last train time into the device, the information is sent to the server, which then generates an alert and sends it to the device to notify the user one hour or 30 minutes before the last train.

[1858] Minute creation using voice recognition

[1859] Conversations made while drinking are recorded using the device's voice recognition function, and the data is sent to a server, which generates minutes based on the data and stores them for later reference by the user.

[1860] 6. Follow-up after drinking

[1861] Follow-up notification the next day

[1862] The next morning, the device sends the user a follow-up notification asking, "Did you drink moderately yesterday?" If the user answers "yes" or "no," that feedback is sent to the server.

[1863] Save your feedback and apply it next time

[1864] The server stores the received feedback in a database and reflects it in the next alcohol content calculation.

[1865] This allows users to enjoy drinking safely and healthily while maintaining an ideal level of intoxication.

[1866] The processing flow will be explained below.

[1867] Step 1:

[1868] Enter and submit user information

[1869] When a user launches the app for the first time, they enter information such as their name, weight, gender, and drinking experience.

[1870] The terminal transmits the entered user information to the server.

[1871] Step 2:

[1872] Saving user information

[1873] The server stores the received user information in a database.

[1874] Step 3:

[1875] Input of today's situation

[1876] The user inputs their physical condition on the day, the location where they will be drinking, and the planned drinking menu into the device.

[1877] The terminal transmits this information to the server.

[1878] Step 4:

[1879] Save today's status information

[1880] The server stores the received physical condition information, drinking location information, and drinking menu information in a database.

[1881] Step 5:

[1882] Calculating alcohol content

[1883] The server calculates the ideal amount of alcohol for the day based on the user's weight, physical condition, drinking location, and past data.

[1884] When calculating, an algorithm is applied depending on the set drunkenness level (e.g. tipsy).

[1885] Step 6:

[1886] Alert Settings and Notifications

[1887] The server sets an alert based on the calculation results.

[1888] The device notifies the user of configured alerts.

[1889] Step 7:

[1890] Enter and submit alcohol intake

[1891] The user enters the type and amount of alcohol consumed into the device.

[1892] The terminal transmits the inputted information on the amount of alcohol consumed to the server.

[1893] Step 8:

[1894] Saving and reviewing alcohol intake information

[1895] The server stores the received alcohol intake information in a database.

[1896] The server checks the current amount of alcohol consumed and calculates assistance information if the amount is below the appropriate level.

[1897] Step 9:

[1898] Assistance Information Notification

[1899] The server transmits assistance information during drinking to the terminal.

[1900] The device notifies the user of assistance information.

[1901] When the amount of alcohol consumed approaches the set limit, the user will receive an alert such as "Be careful not to drink too much."

[1902] Step 10:

[1903] Last train alert settings and notifications

[1904] The user sets the last train time on the device and sends that information to the server.

[1905] The server generates a last train alert before the last train and sends it to the terminal.

[1906] The device will notify the user of the last train alert.

[1907] Step 11:

[1908] Generate meeting minutes

[1909] During the drinking party, the device transmits voice data to the server.

[1910] The server uses voice recognition technology to convert the conversation into text data and generate minutes.

[1911] Step 12:

[1912] Next day follow-up

[1913] The next morning, the device will send the user a follow-up notification asking, "Did you drink moderate amounts of alcohol yesterday?"

[1914] The user enters the answer and the device sends the information to the server.

[1915] The server stores the received feedback in a database and reflects it in the next alcohol content calculation.

[1916] By following these steps, users can enjoy safe and enjoyable drinking while taking proper control of their drinking.

[1917] Example 1

[1918] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1919] In modern society, many people enjoy drinking alcohol, but there are concerns about the health risks associated with excessive drinking and inappropriate drinking habits. Furthermore, there are also problems such as forgetting the last train and having difficulty getting home, and issues with efficiency when taking minutes while drinking. In these situations, there is a need for a system that can manage appropriate drinking amounts in real time and provide appropriate assistance to users.

[1920] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1921] In this invention, the server includes a means for receiving physical condition information input by the user, a means for receiving drunkenness level information set by the user, and a means for receiving drinking location information input by the user. This allows the server to calculate the appropriate amount of alcohol based on the collected information, enabling the user to enjoy drinking safely while maintaining an ideal drunkenness level.

[1922] The server also includes a means for receiving alcohol intake information input by the user and checking the current alcohol intake in real time, a means for providing appropriate assistance information, a means for inputting the time of the last train, a means for issuing a last train alert based on the time of the last train, and a means for recording conversations while drinking using voice recognition and generating minutes. This enables the server to comprehensively manage the user's behavior while drinking and also assist with secondary tasks (e.g., managing the time to return home and creating minutes).

[1923] "Physical condition information" is information that indicates the user's current health condition and mood.

[1924] "Drunkenness level information" is information that indicates the level of drunkenness that the user wants to achieve through drinking.

[1925] "Drinking location information" is information about the location where the user plans to drink alcohol.

[1926] "Amount of alcohol" indicates the total amount of alcohol the user plans to drink.

[1927] An "alert" is a notification or warning that prompts a user to take a specific action.

[1928] "Alcohol intake information" is information about the type and amount of alcohol actually consumed by the user.

[1929] "Assistance information" is advice and recommendations to support users in drinking alcohol safely and effectively.

[1930] The "last train time" refers to the last operating time of the public transportation used by the user.

[1931] "Speech recognition" is a technology that analyzes a user's voice and converts it into a format such as text.

[1932] Minutes are documents that record the contents of meetings or conversations and can be referenced later.

[1933] A "database" is a system that stores information systematically and allows it to be quickly searched and retrieved as needed.

[1934] A "server" is a computer system that processes and manages data and communicates with other devices over a network.

[1935] A "terminal" is a device that a user can directly operate to input or receive information.

[1936] The present invention is a system that helps users enjoy drinking alcohol while maintaining an ideal level of intoxication. This system is primarily realized by the user's smartphone or wearable device (terminal) and a server running on the backend.

[1937] The operation of this system will be explained in detail below. First, the user installs the application on their device, and the initial setup screen is displayed when the application is launched for the first time. The user enters physical information such as name, weight, gender, and drinking history, and the device sends this information to the server. The server stores the received information in a database and uses it as basic data.

[1938] Next, the user enters information about the situation on the day, such as their physical condition, the place where they will be drinking, and the menu they plan to have. This information is also sent from the device to the server and stored in a database. The server uses an algorithm based on the collected user information and the situation information for that day to calculate the appropriate amount of alcohol to reach the level of intoxication set by the user.

[1939] Based on the calculated alcohol content, the server generates an alert and sends it to the device. The user can receive the alert in real time while drinking. Furthermore, when the user inputs the type and amount of alcohol consumed into the device each time, the device sends that information to the server, which records the amount consumed in a database in real time and provides assistance information such as "recommended snacks" or "warnings against drinking too much" as needed.

[1940] When a user inputs the last train time, the information is sent from the device to the server, and the server generates an alert one hour or 30 minutes before the last train and sends it to the device to notify the user.

[1941] It is also possible to record conversations while drinking using a voice recognition function. The device sends the voice data to a server, which analyzes it and generates minutes, which are then stored in a database for later reference by the user.

[1942] The next morning, the server sends a follow-up notification to the device asking, "Did you drink a reasonable amount of alcohol yesterday?" If the user answers "yes" or "no," that feedback will be reflected in the next alcohol calculation.

[1943] Here is an example prompt:

[1944] "Please enter your health condition, drinking location, and planned drinking menu for today. For example, please enter your health condition as 'normal', your drinking location as 'izakaya', and your planned menu as 'beer and sake'."

[1945] This allows users to easily input information and enables the system to effectively support the user's drinking experience.

[1946] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1947] Step 1:

[1948] Initial Setup and User Authentication

[1949] The user installs the application on their device and the initial setup screen is displayed when they launch it for the first time.

[1950] Input: The user inputs physical information such as name, weight, gender, and drinking experience.

[1951] The terminal temporarily stores the input information in memory.

[1952] The device transmits the stored information to the server.

[1953] The server stores the received information in a database.

[1954] Output: The server sends a confirmation message to the terminal that the save is complete, and the terminal displays it to the user.

[1955] Step 2:

[1956] Today's situation input

[1957] The user inputs information such as their physical condition on the day, where they will be drinking, and the planned menu into the terminal.

[1958] Input: Physical condition information (e.g., normal), Drinking location information (e.g., izakaya), Drinking menu information (e.g., beer)

[1959] The terminal temporarily stores the input information in memory.

[1960] The device transmits the stored information to the server.

[1961] The server stores the received information in a database.

[1962] Output: The server sends a confirmation message to the terminal that the save is complete, and the terminal displays it to the user.

[1963] Step 3:

[1964] Alcohol calculation and alert settings

[1965] The server uses an algorithm to calculate the appropriate amount of alcohol based on collected user information, physical condition information, and drinking location information.

[1966] Input: User information, physical condition information, drinking location information

[1967] Data processing: Algorithm-based data analysis

[1968] Output: Calculated alcohol content

[1969] The server generates an alert based on the calculated alcohol content and sends it to the device.

[1970] The device notifies the user of alerts in real time.

[1971] Step 4:

[1972] Real-time assistance while drinking

[1973] The user inputs the type and amount of alcohol consumed into the terminal each time.

[1974] Input: type and amount of alcohol (e.g. 500ml beer)

[1975] The terminal temporarily stores the input information in memory.

[1976] The terminal transmits the input information to the server.

[1977] The server records the received alcohol intake information in a database.

[1978] The server compares the current amount of alcohol consumed with the set limit and generates assistance information as needed.

[1979] Output: Assistance information (e.g., recommended snacks, warnings against drinking too much)

[1980] The server sends the assistance information to the terminal.

[1981] The terminal notifies the user of the received information.

[1982] Step 5:

[1983] Last train alert and meeting minutes

[1984] The user enters the last train time into the terminal (e.g., 23:00).

[1985] Input: Last train time information

[1986] The terminal transmits the input information to the server.

[1987] The server stores the received information in a database.

[1988] The server generates an alert and sends it to the terminal one hour or 30 minutes before the last train.

[1989] Output: Last train alert notification

[1990] The terminal notifies the user of the received alert.

[1991] Step 6:

[1992] Follow-up after drinking

[1993] The next morning, the server sends a follow-up notification to the device asking, "Did you drink an appropriate amount of alcohol yesterday?"

[1994] Output: Follow-up notification

[1995] The user answers "yes" or "no."

[1996] Input: User feedback

[1997] The terminal transmits the user's answer to the server.

[1998] The server stores the received feedback in a database.

[1999] The feedback will be reflected in the next alcohol calculation.

[2000] Through these specific processing steps, users can enjoy drinking safely and healthily while maintaining an ideal level of intoxication.

[2001] (Application example 1)

[2002] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2003] In modern society, there is a lack of ways for users to enjoy drinking alcohol while maintaining an appropriate amount of alcohol intake and enjoying content that is optimal for their situation. In particular, there is a need for a means to provide entertainment content that is individually optimized based on the user's physical condition and drinking situation. There is also a need for a system that allows users to enjoy optimal content while managing their drinking amount and physical condition in real time while drinking.

[2004] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[2005] In this invention, the server includes means for receiving physical condition information input by the user, means for receiving drunkenness level information set by the user, means for receiving drinking location information input by the user, means for calculating the appropriate amount of alcohol based on the received information, means for issuing an alert based on the calculated amount of alcohol, and content recommendation means for recommending optimal content based on the user's drinking status and physical condition. This allows the user to enjoy entertainment content optimal for their situation at any given time while safely and comfortably enjoying alcohol.

[2006] "Physical condition information" is data indicating the user's physical condition, such as normal, tired, or unwell.

[2007] "Drunkenness level information" is data indicating the ideal level of drunkenness set by the user, such as wanting to get a little drunk, wanting to get tipsy, or not wanting to get drunk.

[2008] "Drinking location information" is data relating to the location where the user drinks alcohol, such as at home, at a friend's house, or at a restaurant.

[2009] The "appropriate amount of alcohol" is the amount of alcohol consumed that a user needs to maintain an ideal level of intoxication, calculated based on the user's physical condition, level of intoxication, and drinking location information.

[2010] An "alert" is a warning or suggestion that the system notifies the user, such as warning them to be careful not to drink too much or informing them when to have their next drink.

[2011] "Content recommendation means" refers to algorithms and technologies for recommending optimal entertainment content based on a user's physical condition, drunkenness level, drinking location, and past viewing history.

[2012] The following is a detailed description of an embodiment of the present invention. The present invention is a system that calculates the appropriate amount of alcohol to drink based on information about the user's physical condition, drunkenness level, and drinking location, and issues an alert in real time. The system also has a function to recommend optimal content based on the user's drinking habits and physical condition. This system is primarily implemented using the user's device (a smartphone or wearable device) and a server operating in the backend.

[2013] 1. Initial Setup and User Authentication

[2014] Collection of User Information

[2015] When the application is first installed and launched, an initial setup screen appears, where the user enters information such as their name, weight, gender, and drinking experience.

[2016] Sending and storing user information

[2017] The device sends the input information to a cloud server, which then stores it in a database, which is used as the basis for calculating the appropriate alcohol content.

[2018] 2. Input today's situation

[2019] Enter your current physical condition, where you're drinking, and what you plan to eat

[2020] Users input their physical condition on the day, the location where they will be drinking, and the planned drinking menu into the device.

[2021] Sending and storing status information

[2022] The device sends this input information to a cloud server, which then stores the received information in a database.

[2023] 3. Alcohol calculation and alert settings

[2024] Calculating the appropriate amount of alcohol

[2025] The server uses an algorithm to analyze the collected user information, physical condition information, and drinking location information, and calculates the appropriate amount of alcohol to reach the level of intoxication set by the user.

[2026] Alert settings and notifications

[2027] Based on the calculated alcohol content, the server sets an alert and sends it to the user's device, where the user can receive the alert in real time.

[2028] 4. Real-time assistance while drinking

[2029] Input and record alcohol intake

[2030] Users input the type and amount of alcohol they wish to drink into the device, which then sends the information to a cloud server, which records it in a database in real time.

[2031] Alcohol intake check and assistance provided

[2032] The server compares the current amount of alcohol consumed with the set amount in real time based on the amount of alcohol consumed entered by the user, and if necessary, sends assistance information such as "recommended snacks" or "warnings about drinking too much" to the device.

[2033] 5. Content Recommendation

[2034] Recommending the right content

[2035] The server recommends optimal content based on the user's drinking habits and physical condition, using Python-based machine learning models (such as TensorFlow and PyTorch) to reference the user's past viewing history and data on similar users.

[2036] Content Notification

[2037] The server sends a list of recommended content to the user's device, which can then receive the list in real time.

[2038] Hardware and software used

[2039] Hardware: Smartphone (iOS or Android device)

[2040] software:

[2041] Cloud services (AWS and Google Cloud)

[2042] Database systems (Firestore, MySQL)

[2043] Machine learning frameworks (TensorFlow, PyTorch)

[2044] Specific examples

[2045] Below are some example prompts to input to a generative AI model:

[2046] Username: Yamada Taro

[2047] Weight: 70kg

[2048] Gender: Male

[2049] Drinking experience: Intermediate

[2050] Today's mood: Normal

[2051] Drinking location: Home

[2052] Planned drinks menu: beer, wine

[2053] Generate a list of recommended movies, music playlists, and videos for users who are in normal health and drinking beer and wine at home.

[2054] As described above, the present invention is a system that allows users to enjoy drinking safely and healthily while maintaining an ideal level of intoxication, and to enjoy entertainment content that is optimal for the situation at hand.

[2055] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2056] Step 1:

[2057] Entering and collecting user information

[2058] When a user installs the application on a device, they are prompted to enter information such as their name, weight, gender, and drinking history as initial settings. This data is sent from the device to a cloud server, which then stores it in a database.

[2059] Input: Name, weight, gender, drinking experience, etc.

[2060] Output: User information stored in the database

[2061] How it works: When a user enters information such as their name, weight, gender, and drinking experience into their smartphone and presses the "Save" button, the data is sent to a cloud server, where it is recorded in a database.

[2062] Step 2:

[2063] Today's situation input

[2064] The user inputs information about their physical condition for the day, where they will be drinking, and the planned drinking menu into the device. The device then sends this information to the cloud server, which then stores it in a database.

[2065] Input: Today's health information, drinking location information, planned drinking menu

[2066] Output: Current status information stored in the database

[2067] How it works: When a user enters their current physical condition (e.g., "normal"), where they are drinking (e.g., "home"), and what they plan to drink (e.g., "beer, wine") into their smartphone and presses the "Save" button, the data is sent to the cloud server, which then records the data in a database.

[2068] Step 3:

[2069] Calculating the right amount of alcohol

[2070] The server uses an algorithm to analyze collected user information, physical condition information, and drinking location information to calculate the appropriate amount of alcohol.

[2071] Input: User information, health information, drinking location information

[2072] Output: Calculation result of appropriate amount of alcohol

[2073] Specific operation: The server retrieves user information and today's situation information from the database, and then applies an algorithm within the program (such as a linear regression model with specific coefficients) based on this information to calculate the appropriate amount of alcohol the user can safely drink.

[2074] Step 4:

[2075] Alert settings and notifications

[2076] The server sets an alert based on the appropriate alcohol content and sends it to the device, which the user receives in real time.

[2077] Input: Calculation result of appropriate alcohol amount

[2078] Output: Alert notification to user's terminal

[2079] Specific operation: Based on the calculated appropriate amount of alcohol, the server determines the maximum amount of alcohol the user should drink, and if the limit is exceeded, an alert message such as "Be careful not to drink too much" is sent to the device. The alert is displayed on the user's device in the form of a push notification or other means.

[2080] Step 5:

[2081] Alcohol intake entry and real-time assistance

[2082] The user inputs the type and amount of alcohol consumed into the device, which is then sent to the server, where it is recorded in a database in real time. The server then compares the current amount of alcohol consumed with the set amount, and sends assistance information to the device as needed.

[2083] Input: Type and amount of alcohol consumed

[2084] Output: Assistance information based on current alcohol intake

[2085] How it works: The user enters the type and amount of alcohol they have consumed into their smartphone, and the information is sent to a cloud server. The server records this information in a database in real time, manages the appropriate amount set, and sends assistance notifications to the device as needed (such as "recommended snacks" or "warnings against drinking too much").

[2086] Step 6:

[2087] Content recommendations and notifications

[2088] The server recommends the most suitable content based on the user's drinking habits and physical condition. This recommendation is made using a Python-based machine learning model (such as TensorFlow or PyTorch). A list of recommended content is sent to the user's device.

[2089] Input: User's drinking status, physical condition information

[2090] Output: A list of recommended content

[2091] How it works: The server retrieves the user's drinking history and physical condition information from the database, and then uses a machine learning model (such as TensorFlow or PyTorch) to recommend the most suitable content (movies, music, videos, etc.) for the user. The recommendation results are sent to the user's smartphone, and the user can receive a list of content.

[2092] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[2093] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The embodiments for carrying out the present invention will be described in detail below.

[2094] This invention combines an emotion engine with a system that calculates the appropriate amount of alcohol to drink based on the user's physical condition, drunkenness level, and drinking location information, and issues alerts in real time. The emotion engine recognizes the user's emotional state from their facial expressions and voice, and uses this information to further optimize the drinking experience. This system is realized using the user's smartphone or wearable device (terminal) and a server running on the backend.

[2095] 1. Initial Setup and User Authentication

[2096] Collection of User Information

[2097] When a user installs the application on their device and launches it for the first time, an initial setup screen appears, where the user enters information such as their name, weight, gender, and drinking experience.

[2098] Sending and storing user information

[2099] The device sends the entered user information to a server, which then stores the received information in a database, which is used as the basis for calculating the appropriate alcohol content.

[2100] 2. Input today's situation

[2101] Enter your current physical condition, where you're drinking, and what you plan to eat

[2102] The user inputs their physical condition on the day (e.g., normal, tired, etc.) and the location where they will be drinking (e.g., at home, a friend's house, a restaurant, etc.), as well as the predicted drinks menu (e.g., beer, wine, shochu, etc.).

[2103] Sending and storing status information

[2104] The terminal sends this input information to the server, which then stores the received information in a database.

[2105] 3. Alcohol calculation and alert settings

[2106] Calculating the appropriate amount of alcohol

[2107] The server analyzes the collected user information, physical condition information, and drinking location information based on an algorithm, and calculates the appropriate amount of alcohol to reach the level of intoxication set by the user.

[2108] Alert settings and notifications

[2109] Based on the calculated alcohol content, the server sets an alert and sends it to the device, where the user can receive the alert in real time.

[2110] 4. Real-time assistance while drinking

[2111] Input and record alcohol intake

[2112] Users input the type and amount of alcohol they wish to drink into the device, which then transmits the information to a server, which records it in real time in a database.

[2113] Alcohol intake check and assistance provided

[2114] The server compares the current amount of alcohol consumed with the set amount in real time based on the amount of alcohol consumed entered by the user, and if necessary, sends assistance information such as "recommended snacks" or "warnings about drinking too much" to the user's device.

[2115] 5. Implementing the Emotion Engine

[2116] Recognition of emotional states

[2117] The device analyzes the user's facial expressions and voice in real time, and the emotion engine recognizes the user's emotional state (e.g., happy, stressed, etc.).

[2118] Transmission and use of emotional information

[2119] The device sends the recognized emotional information to the server, which then uses that emotional information to further adjust the amount of alcohol consumed and the assistance information provided, for example, recommending relaxing snacks if the user is feeling stressed.

[2120] 6. Last Train Alerts and Meeting Minutes

[2121] Last train time setting and alert notification

[2122] When a user inputs the last train time into the device, the information is sent to the server, which then generates an alert and sends it to the device to notify the user one hour or 30 minutes before the last train.

[2123] Minute creation using voice recognition

[2124] Conversations made while drinking are recorded using the device's voice recognition function, and the data is sent to a server, which generates minutes based on the data and stores them for later reference by the user.

[2125] 7. Follow-up after drinking

[2126] Follow-up notification the next day

[2127] The next morning, the device sends the user a follow-up notification asking, "Did you drink moderately yesterday?" If the user answers "yes" or "no," that feedback is sent to the server.

[2128] Save your feedback and apply it next time

[2129] The server stores the received feedback in a database and reflects it in the next alcohol content calculation.

[2130] This allows users to properly manage their drinking while receiving optimal assistance according to their emotional state, allowing them to enjoy drinking in a fun and safe way.

[2131] The processing flow will be explained below.

[2132] Step 1:

[2133] Enter and submit user information

[2134] When a user launches the app for the first time, they enter information such as their name, weight, gender, and drinking experience.

[2135] The terminal transmits the entered user information to the server.

[2136] Step 2:

[2137] Saving user information

[2138] The server stores the received user information in a database.

[2139] Step 3:

[2140] Input of today's situation

[2141] The user inputs their physical condition on the day, the location where they will be drinking, and the planned drinking menu into the device.

[2142] The terminal transmits this information to the server.

[2143] Step 4:

[2144] Save today's status information

[2145] The server stores the received physical condition information, drinking location information, and drinking menu information in a database.

[2146] Step 5:

[2147] Calculating alcohol content

[2148] The server calculates the ideal amount of alcohol for the day based on the user's weight, physical condition, drinking location, and past data.

[2149] When calculating, an algorithm is applied depending on the set drunkenness level (e.g. tipsy).

[2150] Step 6:

[2151] Alert Settings and Notifications

[2152] The server sets an alert based on the calculation results.

[2153] The device notifies the user of configured alerts.

[2154] Step 7:

[2155] Enter and submit alcohol intake

[2156] The user enters the type and amount of alcohol consumed into the device.

[2157] The terminal transmits the inputted information on the amount of alcohol consumed to the server.

[2158] Step 8:

[2159] Saving and reviewing alcohol intake information

[2160] The server stores the received alcohol intake information in a database.

[2161] The server checks the current amount of alcohol consumed and calculates assistance information if the amount is below the appropriate level.

[2162] Step 9:

[2163] Assistance Information Notification

[2164] The server transmits assistance information during drinking to the terminal.

[2165] The device notifies the user of assistance information.

[2166] When the amount of alcohol consumed approaches the set limit, the user will receive an alert such as "Be careful not to drink too much."

[2167] Step 10:

[2168] Recognizing and transmitting emotional states

[2169] The device analyzes the user's facial expressions and voice in real time, and the emotion engine recognizes the user's emotional state (e.g., happy, stressed, etc.).

[2170] The recognized emotion information is sent to the server.

[2171] Step 11:

[2172] Adjustment based on emotional state

[2173] The server further adjusts the amount of alcohol consumed and assistance information based on the emotional information received.

[2174] For example, if a user is feeling stressed, we will recommend snacks that have a relaxing effect.

[2175] Step 12:

[2176] Last train alert settings and notifications

[2177] The user sets the last train time on the device and sends that information to the server.

[2178] The server generates a last train alert before the last train and sends it to the terminal.

[2179] The device will notify the user of the last train alert.

[2180] Step 13:

[2181] Generate meeting minutes

[2182] During the drinking party, the device transmits voice data to the server.

[2183] The server uses voice recognition technology to convert the conversation into text data and generate minutes.

[2184] Step 14:

[2185] Next day follow-up

[2186] The next morning, the device will send the user a follow-up notification asking, "Did you drink moderate amounts of alcohol yesterday?"

[2187] The user enters the answer and the device sends the information to the server.

[2188] The server stores the received feedback in a database and reflects it in the next alcohol content calculation.

[2189] By following these steps, users can enjoy safe drinking while properly managing their drinking and receiving optimal assistance based on their emotional state.

[2190] Example 2

[2191] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2192] Conventional alcohol consumption management systems only managed alcohol intake based on the user's physical condition and level of intoxication, and had the function of issuing an alert, but this did not respond appropriately to the user's emotions or environment, resulting in problems with satisfaction and safety. Furthermore, there was a need for a more accurate way to manage alcohol intake by taking environmental and biological information into account.

[2193] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2194] In this invention, the server includes a means for receiving biometric information input by the user, a means for receiving satisfaction level information set by the user, and a means for receiving environmental information input by the user, thereby enabling calculation of an appropriate alcohol intake amount based on the user's physical condition, emotions, and environment, and providing assistance and alerts in real time.

[2195] "Biometric information" refers to data related to the user's physical condition and health, including, for example, weight, gender, age, past drinking history, and physical condition.

[2196] "Satisfaction information" refers to data that indicates the level of intoxication desired by the user and their expectations regarding drinking, including emotional states such as "fun" or "want to relax."

[2197] "Environmental information" refers to data about the location where the user drinks and the circumstances at the time, including, for example, the location where the drink is taken (home, restaurant, etc.), the atmosphere of the location, and the presence of other people.

[2198] "Intake" refers to the amount of alcohol a user should drink, including an appropriate amount calculated based on the user's physical condition, satisfaction, and environmental information.

[2199] "Emotional state" refers to the user's current psychological and emotional state, and includes information such as "happy," "stressed," and "relaxed."

[2200] "Alerts" refer to warning or suggestion messages sent to users, such as "Be careful not to drink too much" or "Recommended snacks."

[2201] "Support information" refers to information that helps users drink alcohol appropriately, including, for example, advice on adjusting future drinking amounts, recommended meals, and advice on the pace at which to drink.

[2202] This invention combines an emotion engine with a system that calculates the appropriate amount of alcohol intake based on biometric information, satisfaction information, and environmental information input by the user and issues alerts in real time. This system is realized using the user's smartphone or wearable device (terminal) and a server running on the backend.

[2203] Initial Setup and User Authentication

[2204] When a user installs the application on their device and launches it for the first time, an initial setup screen appears. The user enters biometric information such as their name, weight, gender, age, and drinking experience. The device sends this information to a server, which stores it in a database. This information is used as the basis for calculating appropriate alcohol intake.

[2205] Today's situation input

[2206] The user inputs environmental information into the device, such as their physical condition on the day (e.g., normal, tired, feeling a bit under the weather, etc.) and the location where they will be drinking (e.g., at home, a friend's house, a restaurant, etc.). They also input their predicted drinking menu (e.g., two beers and one glass of wine). The device sends this situation information to the server, which then stores the received information in a database.

[2207] Alcohol calculation and alert settings

[2208] The server runs an algorithm based on stored user information, physical condition information, drinking location information, and predicted drinking menu to calculate the appropriate amount of alcohol to reach the user's desired level of satisfaction. The server sets an alert based on the calculated appropriate amount of alcohol, and the device notifies the user in real time. For example, it displays messages such as "Only one more beer" or "Be careful not to drink too much!"

[2209] Real-time assistance while drinking

[2210] The user inputs the type and amount of alcohol consumed into the device. The device then sends the input information to the server, which records it in a database in real time. The server compares the user's current alcohol intake with a preset appropriate drinking amount, and notifies the device of assistance information such as "recommended snacks" or "warnings against drinking too much" as needed.

[2211] Implementing the Emotion Engine

[2212] The device analyzes the user's facial expressions and voice in real time. For example, it uses the smartphone's camera and microphone to analyze the user's facial expressions and tone of voice. The emotion engine recognizes the user's emotional state (e.g., happy, stressed, etc.) and generates information about it. The device sends the recognized emotion information to the server, which then adjusts the amount of alcohol consumed and customizes assistance information based on that emotion information. For example, if the user is feeling stressed, it can recommend snacks that have a relaxing effect.

[2213] Last train alert and meeting minutes creation

[2214] The user enters the time of the last train into the device. For example, if the user enters "The last train is at 10:30 p.m.", the server saves that information in a database. The server generates an alert one hour or 30 minutes before the last train, and the device notifies the user. The device also uses a voice recognition function to record conversations that were taking place while drinking. For example, the smartphone's microphone can be used to convert the conversation into text, and the server can generate and save minutes based on that data.

[2215] Follow-up after drinking

[2216] The next morning, the device sends the user a question: "Were you satisfied with the amount of alcohol you drank yesterday?" The user answers "yes" or "no," and the feedback is sent to the server. The server stores the feedback in a database and reflects it in the next alcohol amount calculation. For example, it may fine-tune the suggested amount of alcohol based on the previous feedback.

[2217] Examples:

[2218] A user named "Taro" enters his weight as 70 kg, his gender as male, his drinking experience, and his preferred types of alcohol as beer and wine. The device sends this information to the server, which then stores it in a database.

[2219] The user inputs, "I'm feeling fine today, I plan to drink at home, and my planned menu is two beers and one glass of wine." The device sends this information to the server, which then stores it in a database.

[2220] The device's camera detects the user's smile, and the emotion engine recognizes it as "fun." The device then sends this information to the server, which then provides "assistance information perfect for a fun drinking party."

[2221] A user sets the last train time to 23:30. The server sends an alert from the device at 22:30 and 23:00.

[2222] Example prompt sentence:

[2223] "User information: Taro, Weight: 70kg, Gender: Male, Drinking experience: Yes. Please calculate the appropriate amount of alcohol."

[2224] "The user has entered their current health state as 'normal', their drinking location as 'home', and their planned menu as '2 beers, 1 glass of wine'. Create appropriate alerts and assistance information."

[2225] "The user entered the last train time as 23:30. Please send an alert 1 hour and 30 minutes before the last train."

[2226] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2227] Processing Steps

[2228] Step 1: Initial Setup and User Authentication

[2229] 1. When a user installs the application on their device and launches it for the first time, an initial setup screen will appear.

[2230] 2. The user enters biometric information such as name, weight, gender, age, and drinking experience.

[2231] Input: User information (name, weight, gender, age, drinking experience)

[2232] Output: User information data

[2233] 3. The device sends this information to the server, and the server stores the received information in a database.

[2234] Data processing / calculation: Saving user information

[2235] Step 2: Input your current situation

[2236] 1. The user inputs environmental information into the device, such as their physical condition on the day (e.g., normal, tired, feeling a bit like a cold, etc.) and the location where they drank alcohol (e.g., at home, a friend's house, a restaurant, etc.).

[2237] Input: Health information, drinking location information

[2238] Output: Today's status information data

[2239] 2. Additionally, enter your predicted drinking menu (e.g., 2 beers, 1 wine).

[2240] Input: Drinking menu information

[2241] Output: Completed status information data

[2242] 3. The device sends this status information to the server, and the server stores the received information in a database.

[2243] Data processing / calculation: Saving status information

[2244] Step 3: Calculate alcohol intake and set alerts

[2245] 1. The server runs an algorithm based on stored user information, physical condition information, drinking location information, and predicted drinking menu.

[2246] Input: User information, physical condition information, drinking location information, drinking menu

[2247] Calculation: Calculating the appropriate amount of alcohol

[2248] Output: Appropriate alcohol content data

[2249] 2. Calculate the appropriate amount of alcohol to reach the user's desired satisfaction level and set an alert.

[2250] Data processing / calculation: Alert information generation

[2251] 3. The server sends the alert information to the device, and the device notifies the user in real time.

[2252] Input: Alert information

[2253] Output: User notification (e.g., "Only one more beer left!", "Don't drink too much!")

[2254] Step 4: Real-time assistance while drinking

[2255] 1. The user enters the type and amount of alcohol consumed into the device.

[2256] Input: Alcohol intake information

[2257] Output: Alcohol intake data

[2258] 2. The device sends the entered alcohol intake information to the server, which records it in a database in real time.

[2259] Data processing / calculation: Saving alcohol intake information

[2260] 3. The server compares the user's current drinking level with the predetermined appropriate drinking level and generates assistance information as needed.

[2261] Input: Alcohol intake data, set appropriate amount

[2262] Calculation: Check alcohol intake

[2263] Output: Assistance information

[2264] 4. The device notifies the user of the generated assistance information. For example, it may present "recommended snacks" or "be careful not to drink too much!"

[2265] Data processing / calculation: Notification of assistance information

[2266] Step 5: Implementing the Emotion Engine

[2267] 1. The device analyzes the user's facial expressions and voice in real time. For example, it uses the smartphone's camera and microphone to analyze the user's facial expressions and tone of voice.

[2268] Input: facial expression data, voice data

[2269] Computation: Recognizing Emotional States

[2270] Output: Emotional information

[2271] 2. The emotion engine recognizes the user's emotional state.

[2272] Data processing / calculation: Generating emotional information

[2273] 3. The device sends the recognized emotional information to the server, which then adjusts the amount of alcohol and customizes the assistance information based on the emotional information.

[2274] Input: Emotion information

[2275] Calculation: Alcohol content adjustment, customization of assistance information

[2276] Output: Adjusted alcohol content data, customized assistance information

[2277] Step 6: Last train alert and meeting minutes

[2278] 1. The user enters the last train time into the terminal.

[2279] Input: Last train time

[2280] Output: Last train time data

[2281] 2. The server saves the last train time information in a database.

[2282] Data processing / calculation: Saving the last train time

[2283] 3. The server generates an alert one hour or 30 minutes before the last train, and the device notifies the user.

[2284] Input: Saved last train time

[2285] Operation: Alert Generation

[2286] Output: User notification (e.g. "1 hour before last train", "30 minutes before last train")

[2287] 4. The device uses voice recognition to record conversations while drinking. For example, it uses a smartphone microphone to convert the conversation into text, and the server generates and stores minutes based on that data.

[2288] Input: Conversation data while drinking

[2289] Computing: Speech recognition and text conversion

[2290] Output: Generate minutes data

[2291] Step 7: Follow up after drinking

[2292] 1. The next morning, the device sends the user the question, "Were you satisfied with the amount of alcohol you drank yesterday?"

[2293] Input: Question submission (automatic)

[2294] Output: User notification

[2295] 2. The user answers with "yes" or "no" and the feedback is sent to the server.

[2296] Input: User feedback

[2297] Output: Feedback data

[2298] 3. The server stores the feedback in a database and uses it in the next alcohol content calculation.

[2299] Data processing / calculation: Saving and reflecting feedback

[2300] Output: Adjusted alcohol content data

[2301] (Application example 2)

[2302] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2303] There is a need for technology to manage appropriate alcohol consumption and reduce the health risks associated with excessive drinking. Another challenge is to provide optimal assistance based on the user's emotional state and further improve the drinking experience. Food delivery services also require management to ensure users do not drink too much and enjoy their food and drink appropriately. In addition, there is a need for comprehensive support, including information on the user's last train and their health the next day.

[2304] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2305] In this invention, the server includes: means for receiving physical condition information input by the user; means for receiving drunkenness level information set by the user; means for receiving drinking location information input by the user; means for calculating an appropriate alcohol intake based on the received information; means for issuing an alert based on the calculated alcohol intake; means for analyzing the user's facial expressions and voice while drinking and recognizing their emotional state; means for providing appropriate assistance information based on the recognized emotional state; and means for implementing the above means using a server operating in the backend and linking with the user's device. This makes it possible to appropriately manage the user's alcohol intake, provide assistance according to their emotions, notify them of last train alerts, and support an optimal drinking experience with food delivery services.

[2306] "User" refers to any person who uses the Services or Applications.

[2307] "Health information" refers to information that indicates the user's health condition and level of fatigue on that day.

[2308] "Drunkenness level information" refers to information that allows a user to set the level of drunkenness they desire.

[2309] "Drinking location information" refers to information about the location where a user drinks alcohol.

[2310] "Alcohol content" refers to the appropriate amount of alcohol a user should drink.

[2311] An "alert" refers to a warning or notification given to the user.

[2312] "Facial expression analysis" refers to technology that recognizes a user's facial expressions and analyzes their state.

[2313] "Voice analysis" refers to technology that recognizes a user's voice and analyzes their emotional state.

[2314] "Emotional state" refers to the emotion the user is feeling (e.g., happy, stressed, etc.).

[2315] "Assistance Information" refers to supplementary information or advice provided to the User.

[2316] "Back-end server" refers to a remote server that processes data in cooperation with user terminals.

[2317] "Terminal" refers to a device used by a user, such as a smartphone or wearable device.

[2318] System Overview

[2319] The system for implementing this invention receives information on the user's physical condition, drunkenness level, and drinking location, calculates the appropriate amount of alcohol based on that information, issues an alert in real time, and recognizes the user's emotional state through facial expression and voice analysis, and provides appropriate assistance based on that information.

[2320] Hardware and software used

[2321] Hardware: Smartphones, wearable devices (e.g., Apple Watch)

[2322] Software: Cloud services (Amazon Web Services, Google Cloud, etc.), databases (MySQL, PostgreSQL), emotion engines (Microsoft Azure Emotion API, Google Cloud Vision API)

[2323] Detailed program processing

[2324] The process performed by the server and the device is as follows:

[2325] Collection and storage of user information

[2326] 1. Enter your user information

[2327] Users install the smartphone app and enter their name, weight, gender, and drinking experience on the initial setup screen.

[2328] 2. Transmission and storage of user information

[2329] The terminal sends the entered user information to the server, which stores it in a database.

[2330] Today's situation input

[2331] 1. Enter your physical condition, drinking location, and predicted menu for the day

[2332] Users input their physical condition on the day, the location where they will be drinking, and the anticipated drinking menu.

[2333] 2. Sending and storing status information

[2334] The terminal sends the input information to the server, which stores the information in a database.

[2335] Alcohol calculation and alert settings

[2336] 1. Calculating the amount of alcohol

[2337] The server uses an algorithm to analyze the collected user information and situational information and calculates the appropriate amount of alcohol.

[2338] 2. Setting up alerts and notifications

[2339] Based on the calculated alcohol content, the server sets an alert and notifies the device in real time.

[2340] Real-time assistance while drinking

[2341] 1. Input and record alcohol intake

[2342] The user inputs the type and amount of alcohol consumed into the device while drinking.

[2343] 2. Checking alcohol intake and providing assistance

[2344] Based on the amount of alcohol consumed entered by the user, the server compares the current amount of alcohol consumed with the set appropriate amount, and if necessary, notifies the user with "snack suggestions" or "warnings about drinking too much."

[2345] Implementing the Emotion Engine

[2346] 1. Recognizing emotional states

[2347] The device analyzes the user's facial expressions and voice in real time, and the emotion engine recognizes the user's emotional state.

[2348] 2. Transmission and use of emotional information

[2349] The device transmits the recognized emotion information to the server, which then adjusts the assistance information based on the information.

[2350] Follow-up

[2351] 1. Follow-up notification the next day

[2352] The next morning, the server sends a notification to the user via their device asking, "Did you drink an appropriate amount of alcohol yesterday?"

[2353] 2. Save your feedback and apply it next time

[2354] The server stores the user's feedback in a database and reflects it in the next alcohol content calc...

Claims

1. A means for receiving physical condition information input by a user; A means for receiving sickness level information set by a user; means for receiving drinking location information input by a user; means for calculating an appropriate amount of alcohol based on each piece of information received; a means for issuing an alert based on the calculated alcohol content; A system including:

2. 2. The system according to claim 1, wherein the means for issuing an alert issues a last train alert based on a last train time set by a user.

3. 2. The system of claim 1, further comprising means for receiving alcohol amount information input by a user while drinking alcohol and providing appropriate assistance information.

4. The system according to claim 1, further comprising means for recording the contents of the talk by voice recognition and providing the recorded contents as minutes.

5. The system according to claim 1, wherein the system receives information about the user's constitution and calculates the amount of alcohol based on the information.

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