System

Abstract

A system is provided.SOLUTION: A system comprising: an image capturing unit configured to capture an image of a body of a user to check the appearance of the user before the user goes out; an image analyzing unit configured to analyze the image of the user captured by the image capturing unit to detect dirt on clothes, wrinkles, dust, and hair disorder; an advice generating unit configured to generate advice appropriate for the user based on a detection result of the image analyzing unit; and an audio output unit configured to output the advice generated by the advice generating unit as audio.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] In modern society, busy people often find it difficult to find time to check their appearance and belongings before heading out. This can lead to unconsciously overlooking improper grooming or forgotten items. It is also difficult to prepare quickly in response to changes in weather or physical condition, resulting in a high likelihood of unpleasant experiences. The present invention aims to solve these problems and provide a system that allows users to comfortably and quickly prepare for going out. [Means for solving the problem]

[0005] The present invention provides a system for checking a user's appearance before going out. The system includes a photographing device for photographing the user's body and an image analysis device for analyzing the photographed image to detect stains, wrinkles, dust, and messy hair on the user's clothes. The system also includes an advice generation device for generating appropriate advice based on the results of the image analysis device, and an audio output device for outputting the generated advice as audio. The system also includes a weather forecast linkage device for acquiring weather forecast data based on the user's location information and providing advice based on the weather forecast, a temperature measurement device and a physical condition evaluation device for measuring the user's body temperature and evaluating their physical condition, a lost item confirmation device for checking for lost items based on a previously registered user list, and an accessory advice device for analyzing the color information of the user's clothing and generating appropriate accessory color advice. By combining these devices, the user can efficiently prepare for going out.

[0006] "Photographing means" refers to a camera or imaging device for photographing the user's body or clothing.

[0007] "Image analysis means" refers to algorithms or software that analyzes image data obtained by the photographing means and detects stains, wrinkles, dust, and messy hair on clothes.

[0008] The "advice generation means" refers to processing means for generating appropriate advice for the user based on the analysis results obtained from the image analysis means.

[0009] The "audio output means" refers to a speaker or a voice synthesizer for conveying the advice generated by the advice generating means to the user as voice.

[0010] "Weather forecast linkage means" refers to a means for obtaining weather forecast data based on the user's location information and providing advice on going out based on the weather.

[0011] "Temperature measurement means" refers to a sensor or measuring device for measuring a user's temperature.

[0012] The "physical condition evaluation means" refers to a processing means for evaluating the user's physical condition based on the body temperature data obtained by the body temperature measurement means and detecting any abnormalities.

[0013] "Means for checking lost items" refers to a means for checking a user's belongings based on a list of lost items registered in advance by the user.

[0014] The "accessory advice means" refers to a processing means for analyzing color information of the user's clothing and proposing accessory colors that suit the clothing. [Brief explanation of the drawings]

[0015] [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

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] The present invention is a system for enabling a user to efficiently prepare for going out, and it combines a photographing means, an image analysis means, an advice generation means, a voice output means, a weather forecast linkage means, a body temperature measurement means, a physical condition evaluation means, a forgotten item confirmation means, and an accessory advice means. Specific embodiments of this system are described below.

[0037] Overall Overview

[0038] This system allows users to walk around in front of the camera before going out, and automatically checks their appearance and belongings, and provides advice based on the weather and their physical condition. Users simply follow voice instructions and are ready to go out.

[0039] An example of an appearance check

[0040] 1. Terminal

[0041] When the user stands in front of the camera, it automatically activates and takes a picture of the user, with voice prompts to walk around in a circle.

[0042] 2. Server

[0043] It receives the captured image data and uses an image analysis algorithm to detect dirt, wrinkles, dust, and messy hair on the clothes, then generates necessary advice based on the results and generates text data for voice output.

[0044] 3. Terminal

[0045] The generated advice is communicated to the user as audio.

[0046] For example: "There are wrinkles on the back. A steam iron would help."

[0047] Weather forecast advice implementation form

[0048] 1. Server

[0049] The system obtains the latest weather forecast data based on the user's location, and generates advice on whether they need a jacket or an umbrella based on the forecast.

[0050] 2. Terminal

[0051] The message is conveyed to the user as audio.

[0052] Example: "It's raining today, so you should bring an umbrella."

[0053] Temperature Measurement and Alert Implementation

[0054] 1. Terminal

[0055] The user is prompted by voice to take their temperature, and their temperature is measured by touching the temperature sensor.

[0056] 2. Server

[0057] Receives the measured body temperature data and evaluates whether it is within the normal range. If it is abnormal, it generates an alert and generates text data for voice output.

[0058] 3. Terminal

[0059] The content of the alert is announced to the user through audio.

[0060] For example: "Your current temperature is 37.8°C. It's a little high, so I recommend you relax or drink a warm drink."

[0061] Implementation of lost item check

[0062] 1. Terminal

[0063] Based on the loaded lost item list, it outputs a voice prompt to remind the user to check their belongings.

[0064] For example: "Did you bring your keys and wallet?"

[0065] 2. Users

[0066] You will receive a voice confirmation, which the system will analyze to determine if you are fully prepared.

[0067] For example: "Yes, I have it."

[0068] Accessory color advice implementation example

[0069] 1. Server

[0070] It analyzes the user's clothing color information and generates color advice for suitable accessories based on fashion rules.

[0071] 2. Terminal

[0072] The generated advice is communicated to the user as audio.

[0073] For example: "The color of accessories that goes well with today's outfit is silver."

[0074] Customization Settings Implementation Example

[0075] 1. Users

[0076] Customize your voice output settings to adjust the gender, tone, and phrasing of the voice.

[0077] 2. Terminal

[0078] The received customization settings will be saved and reflected from the next time onwards.

[0079] The above configuration allows the user to efficiently prepare before going out, realizing a system that allows for a comfortable outing.

[0080] The processing flow will be explained below.

[0081] Step 1:

[0082] The user stands in front of the camera and activates the system.

[0083] Step 2:

[0084] The device uses facial recognition technology to identify the user and then issues a voice prompt saying, "Take one lap."

[0085] Step 3:

[0086] The user walks around in front of the camera, capturing their entire body.

[0087] Step 4:

[0088] The device sends the captured data from the user's entire rotation to the server.

[0089] Step 5:

[0090] The server processes the received data based on image analysis algorithms to detect dirt, wrinkles, dust, and messy hair on the clothes.

[0091] Step 6:

[0092] Based on the results of image analysis, the server generates appropriate advice for the user as text data and sends it to the terminal for voice output.

[0093] Step 7:

[0094] The device will communicate the advice it receives to the user via voice.

[0095] For example: "There are wrinkles on the back. A steam iron would help."

[0096] Step 8:

[0097] The server retrieves weather forecast data based on the user's location information.

[0098] Step 9:

[0099] The server generates text data based on weather forecast data, giving advice on whether a jacket is needed or whether an umbrella should be carried, and transmits the text data to the terminal for voice output.

[0100] Step 10:

[0101] The device will then communicate the weather forecast advice received to the user via voice.

[0102] Example: "It's raining today, so you should bring an umbrella."

[0103] Step 11:

[0104] The device will output a voice prompt to the user to take their temperature.

[0105] For example: "Please take my temperature."

[0106] Step 12:

[0107] The user touches the temperature sensor to measure their temperature.

[0108] Step 13:

[0109] The device sends the measured body temperature data to the server.

[0110] Step 14:

[0111] The server analyzes the temperature data and determines whether it is within the normal range. If it is abnormal, it generates an alert and generates text data for voice output and sends it to the device.

[0112] Step 15:

[0113] The device will communicate any alerts received to the user via voice.

[0114] For example: "Your current temperature is 37.8°C. It's a little high, so I recommend you relax or drink a warm drink."

[0115] Step 16:

[0116] The device loads the registered lost item list and outputs a voice prompt to ask the user to confirm.

[0117] For example: "Did you bring your keys and wallet?"

[0118] Step 17:

[0119] The user responds with the confirmation result by voice.

[0120] For example: "Yes, I have it."

[0121] Step 18:

[0122] The device converts the received voice into text, confirms that the item has not been left behind, and notifies the user.

[0123] For example: "I made sure you didn't forget anything."

[0124] Step 19:

[0125] The server analyzes the color information of the user's clothing, generates suitable accessory colors as text data, and sends it to the terminal for voice output.

[0126] Step 20:

[0127] The device will then provide the user with audio color advice for the accessory it receives.

[0128] For example: "The color of accessories that goes well with today's outfit is silver."

[0129] Step 21:

[0130] Users can customize voice output settings and adjust the gender, impression, and phrasing of the voice.

[0131] Step 22:

[0132] The device will save your customization settings and apply them the next time.

[0133] Example 1

[0134] 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."

[0135] Previously, preparing to go out required users to individually check their appearance, the weather, their physical condition, and their belongings, which took a lot of time and effort. This often caused stress for users before going out, and was inefficient. There was also a need for a system that could centrally automate these check tasks.

[0136] 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.

[0137] In this invention, the server includes: an imaging means for capturing an image of the user's body; an image analysis means for analyzing the image of the user captured by the imaging means to detect stains, wrinkles, dust, and messy hair on the user's clothes; an advice generation means for generating appropriate advice for the user based on the detection results of the image analysis means; an audio output means for outputting the advice generated by the advice generation means as audio; a weather forecast linkage means for acquiring weather forecast data based on the user's location information and generating advice for the user when going out based on the acquired weather forecast; a temperature measurement means for outputting an audio prompt urging the user to measure their temperature and measuring the user's temperature; a physical condition evaluation means for evaluating the user's physical condition based on the measured temperature data and generating an alert if an abnormality is detected; a forgotten item confirmation means for outputting an audio prompt urging the user to check their belongings; and an accessory advice means for analyzing the color information of the user's clothing and generating color advice for appropriate accessories. This allows the user to efficiently prepare before going out and enjoy a comfortable outing.

[0138] "Photographing means" refers to equipment or devices for photographing the user's body.

[0139] "Image analysis means" refers to a technology or device that analyzes a photographed image of a user and detects stains, wrinkles, dust, and messy hair on the clothes.

[0140] The "advice generation means" is a technology or device for generating appropriate advice for the user based on the detection results obtained by the image analysis means.

[0141] The "audio output means" is a technique or device for outputting the advice generated by the advice generating means as audio.

[0142] The "weather forecast linking means" is a technology or device for acquiring weather forecast data based on the user's location information and generating advice for the user when going out based on the acquired weather forecast.

[0143] "Temperature measurement means" means any technology or device for measuring a user's temperature.

[0144] The "physical condition evaluation means" is a technology or device for evaluating the user's physical condition based on measured body temperature data and generating an alert if any abnormalities are detected.

[0145] A "lost property verification means" is a technology or device that outputs a voice prompt to prompt the user to verify their belongings.

[0146] The "accessory advice means" is a technology or device for analyzing the user's clothing color information and generating color advice for suitable accessories.

[0147] A "user" is a person who uses this system to prepare for going out.

[0148] The present invention is a system for enabling users to efficiently prepare for going out. By combining a photographing means, an image analysis means, a means for generating advice, a means for outputting audio, a means for linking with weather forecasts, a means for measuring body temperature, a means for evaluating physical condition, a means for checking for lost items, and a means for providing advice on accessories, the system allows users to centrally automate their preparations before going out. Specific embodiments of the present invention are described below.

[0149] System Hardware and Software

[0150] Hardware

[0151] Photography method: Uses the camera on a smartphone or tablet to capture a photo of the user's body.

[0152] Body temperature measurement method: A smartwatch or dedicated body temperature sensor is used to measure the user's body temperature.

[0153] software

[0154] Image analysis method: The OpenCV library is used for image analysis, which detects dirt, wrinkles, dust, and messy hair from captured images.

[0155] Advice generation method: The advice is generated using a script written in "Python" or "JavaScript."

[0156] Voice output method: "Google Text-to-Speech" and "Amazon Polly" are used for voice output, which convert text data into voice.

[0157] Weather forecast integration method: The OpenWeatherMap API is used to obtain weather forecast data, which allows users to obtain weather forecasts based on their location.

[0158] Physical condition evaluation method: An analysis system linked to "Raspberry Pi" is used to evaluate body temperature data, which determines whether the body temperature is within the normal range.

[0159] How to check for lost items: To check for lost items, a voice prompt is output through Google Assistant, prompting the user to check for their belongings.

[0160] Accessory advice method: IBM Watson Visual Recognition is used to analyze and advise on clothing colors, suggesting accessory colors that match the user's outfit.

[0161] Example of operation

[0162] 1. Grooming check

[0163] When a user stands in front of the camera, it automatically starts up and takes a picture of the user.

[0164] The device will play a voice prompt saying "Take a turn."

[0165] The server uses OpenCV's image analysis algorithm to detect stains and wrinkles on the clothes.

[0166] The server generates the advice "There are wrinkles on the back. You may want to use a steam iron."

[0167] The device uses Google Text-to-Speech to convert advice into audio and convey it to the user.

[0168] 2. Weather Forecast Advice

[0169] The server uses the OpenWeatherMap API to get the latest weather forecast.

[0170] The server generates the advice "It's raining today, so please take an umbrella."

[0171] The device uses Amazon Polly to convert advice into voice and convey it to the user.

[0172] 3. Temperature measurement and alerts

[0173] The device will play a voice prompt saying, "Please take your temperature."

[0174] The user measures their temperature by touching the temperature sensor on the smartwatch.

[0175] The server receives the body temperature data and analyzes it using a Raspberry Pi.

[0176] The server generates an alert saying, "Your current temperature is 37.8 degrees. It's a little high, so we recommend you relax or drink a warm drink."

[0177] The device converts the alert into audio and relays it to the user.

[0178] 4. Check for lost items

[0179] The device will play a voice prompt asking, "Did you bring your keys and wallet?"

[0180] The user responds by voice, "Yes, I have it."

[0181] The device uses Azure Speech to Text to convert speech into text and analyze it.

[0182] 5. Accessory advice

[0183] The server uses IBM Watson Visual Recognition to analyze clothing colors.

[0184] The server generates advice such as "The color of the accessory that matches your outfit today is silver."

[0185] The device uses Amazon Alexa to convert advice into voice and convey it to the user.

[0186] According to the above-mentioned specific examples, the system of the present invention makes it possible for the user to efficiently prepare for going out and reduces stress.

[0187] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0188] Step 1: The user stands in front of the camera

[0189] Input: The user stands in front of the camera.

[0190] Action: The device detects the user's presence using a sensor.

[0191] Output: The camera starts automatically.

[0192] What it does: Your smartphone or tablet's camera app will automatically launch and you'll hear a voice prompt saying, "Take a full turn."

[0193] Step 2: The device takes a photo of the user

[0194] Input: The user moves around in a circle.

[0195] Processing: The device takes continuous shots and records the footage.

[0196] Output: Video data is generated.

[0197] Specific operation: The smartphone takes continuous shots and sends the video data to the server.

[0198] Step 3: The server performs image analysis

[0199] Input: Video data sent from the device.

[0200] Processing: The server uses the OpenCV library to analyze the images and detect stains, wrinkles, dust, and messy hair on the clothes.

[0201] Output: The detection results are generated.

[0202] Specific operation: The server analyzes the video data frame by frame and identifies problem areas.

[0203] Step 4: Server generates advice

[0204] Input: Detection results from image analysis.

[0205] Processing: The server generates advice for the user based on the analysis results.

[0206] Output: Text data of advice is generated.

[0207] Specific behavior: If dirt is detected, generate advice such as "There is dirt on the back. It may be a good idea to use a brush."

[0208] Step 5: Your device will speak the advice

[0209] Input: Text data of advice sent from the server.

[0210] Processing: Your device uses Google Text-to-Speech to convert the text data into audio.

[0211] Output: A spoken advice is generated.

[0212] Specific behavior: The smartphone conveys the generated voice advice to the user.

[0213] Step 6: Server retrieves weather forecast data

[0214] Input: User's location.

[0215] Process: The server retrieves weather forecast data using the OpenWeatherMap API.

[0216] Output: Weather forecast data is generated.

[0217] Specific operation: The server retrieves the latest weather forecast based on the location information.

[0218] Step 7: Server generates weather-based advice

[0219] Input: Weather forecast data.

[0220] Processing: The server generates advice for going out based on the weather forecast data.

[0221] Output: Weather-based advice text data is generated.

[0222] Specific behavior: If rain is forecast, generate advice such as "It's going to rain today, so please bring an umbrella."

[0223] Step 8: Your device will speak weather advice

[0224] Input: Weather advice text data sent from the server.

[0225] Processing: The device uses Amazon Polly to convert the text data into speech.

[0226] Output: A spoken advice is generated.

[0227] Specific behavior: The smartphone conveys the generated voice advice to the user.

[0228] Step 9: The device prompts you to take your temperature

[0229] Input: The act of the user hearing a voice prompt.

[0230] Action: The device outputs a voice prompt saying "Please take your temperature."

[0231] Output: The user begins taking their temperature.

[0232] What it does: The smartwatch will play a voice prompt to remind the user to take their temperature.

[0233] Step 10: User takes temperature

[0234] Input: Touching the temperature sensor.

[0235] Processing: The temperature sensor measures the user's temperature and generates the data.

[0236] Output: Temperature data is generated.

[0237] What happens: The user touches the sensor on the smartwatch to measure their body temperature.

[0238] Step 11: Server evaluates temperature data

[0239] Input: Temperature measurement data.

[0240] Processing: The server analyzes the received temperature data and evaluates whether it is within the normal range.

[0241] Output: Text data of health alert is generated.

[0242] What it does: The server analyzes data from the temperature sensor connected to the Raspberry Pi and generates alerts as needed.

[0243] Step 12: Your device will output a health alert

[0244] Input: Text data of health alert sent from the server.

[0245] Action: The device uses iOS VoiceOver to convert the alert into audio.

[0246] Output: An audio alert is generated.

[0247] What it does: The smartphone plays the generated audio alert to the user.

[0248] Step 13: The device will output a lost item confirmation prompt

[0249] Input: System loaded lost item checklist.

[0250] Action: Your device uses Google Assistant to speak a prompt to check your belongings.

[0251] Output: A voice prompt is generated.

[0252] What happens: Your smartphone will play a voice prompt saying, "Did you bring your keys and wallet?"

[0253] Step 14: User responds with confirmation by voice

[0254] Input: User's voice input.

[0255] Processing: The device converts the user's voice into text using Azure Speech to Text, which is then analyzed by the system.

[0256] Output: Text data of the belongings check result is generated.

[0257] Specific operation: The user replies "Yes, I have it," and the device converts the speech into text and analyzes it.

[0258] Step 15: Check that your device is ready

[0259] Input: Text data of the inventory check results.

[0260] Processing: The device checks the lost item checklist against the user's voice response to determine if they are ready.

[0261] Output: A text message is generated to notify you that the device is ready.

[0262] What it does: The device checks the checklist and the user's responses, then notifies them that all items are in order.

[0263] Step 16: Server analyzes clothing color

[0264] Input: User's clothing image data.

[0265] Processing: The server analyzes the clothing color using IBM Watson Visual Recognition.

[0266] Output: Color analysis results are generated.

[0267] Specific operation: The server analyzes the user's clothing image and obtains color information.

[0268] Step 17: Server generates color advice for accessories

[0269] Input: Color analysis results.

[0270] Processing: The server generates color advice for suitable accessories based on the analysis results.

[0271] Output: Text data of accessory advice is generated.

[0272] Specific behavior: Generates advice such as "The color of accessories that goes well with today's outfit is silver."

[0273] Step 18: Your device will speak accessory advice

[0274] Input: Text data of accessory advice sent from the server.

[0275] Processing: The device uses Amazon Alexa to convert the advice into voice.

[0276] Output: A spoken advice is generated.

[0277] Specific operation: The smart speaker outputs advice aloud and conveys it to the user.

[0278] Through the above steps, the system of the present invention enables the user to efficiently prepare for going out and ensure a comfortable outing.

[0279] (Application example 1)

[0280] 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."

[0281] In the past, factory workers' work preparation required individual checking of equipment, temperature checks, and checking for forgotten items, which was inefficient and required a great deal of time and effort. Furthermore, there was a lack of appropriate advice regarding weather changes, which led to a decline in worker safety and efficiency. To solve these issues, a system was needed that centralized the worker preparation process and made it possible to do so quickly and efficiently.

[0282] 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.

[0283] In this invention, the server includes a photographing means for photographing the user's body, an image analysis means for analyzing the image of the user photographed by the photographing means to detect stains, wrinkles, dust, and messy hair on the clothes, and an advice generation means for generating appropriate advice for the user based on the detection results of the image analysis means. This makes it possible to streamline work preparation for factory workers and to centrally manage equipment checks, temperature measurements, and forgotten item checks.

[0284] "Photographing means" is a mechanism for photographing the user's body and equipment, and is a device for obtaining the user's appearance as digital data.

[0285] The "image analysis means" is a mechanism that processes and analyzes the image data acquired by the photographing means and detects specific features (for example, dirt, wrinkles, dust, or messy hair).

[0286] The "advice generator" is a mechanism or algorithm for generating appropriate advice for a user based on the image analysis means and other data inputs.

[0287] The "audio output means" is a device or software for conveying the advice generated by the advice generating means to the user in audio form.

[0288] "Temperature measurement means" means a sensor or device for measuring a user's temperature and providing the data necessary to assess the user's health condition.

[0289] The "physical condition assessment means" is an algorithm or mechanism that assesses the user's health condition based on the body temperature data obtained by the body temperature measurement means and generates appropriate advice or warnings.

[0290] The "weather forecast linking means" is an information processing system that acquires current weather forecast data and generates appropriate advice for the user when going out or working.

[0291] The "lost item confirmation means" is a system that checks whether all important belongings are present based on the user's belongings list and notifies the user of the results.

[0292] The present invention is a system for improving the efficiency of work preparation by factory workers. Each means and its processing will be described in detail below.

[0293] Photography and image analysis methods

[0294] A camera that captures images of the user's body and equipment is connected to the server. The camera automatically activates when the worker stands in front of the camera, capturing images of the worker in all 360-degree directions. This captured image data is immediately sent to the image analysis means, which uses an open-source image processing library (e.g., OpenCV) to detect dirt, wrinkles, dust, and messy hair on the equipment.

[0295] Advice generation means and voice output means

[0296] Based on the results obtained by the image analysis means, the advice generation means of the server generates appropriate advice for the worker. The generated advice is communicated to the worker in real time by the voice output means. A library that converts text to voice (e.g., pyttsx3) is used for the voice output.

[0297] For example, the advice "Dirt has been detected on your equipment. Please clean it" is output as voice.

[0298] Temperature measurement and health assessment methods

[0299] The system is equipped with a sensor for measuring the worker's body temperature. The body temperature measurement means measures the worker's body temperature when the worker touches the sensor and sends the data to a server. The physical condition evaluation means evaluates the worker's physical condition based on this body temperature data and generates an alert if there is an abnormality. The worker is also notified of this alert by voice.

[0300] For example, advice such as "Your body temperature is high. Don't push yourself and take care of your health" is output as audio.

[0301] Weather forecast linkage method

[0302] The server retrieves current weather forecast data via an Internet connection and generates advice based on the worker's working environment. For this purpose, a weather forecast API is used. If the weather is bad (e.g., rainy), the server will give the worker appropriate warnings.

[0303] For example, advice such as "Rain is expected today, so please wear appropriate waterproof gear" may be output via voice.

[0304] How to check for lost items

[0305] A list of important items that the worker should have is loaded onto the server, and the lost item confirmation means prompts the worker by voice to check the items he or she has brought with him or her based on this list.

[0306] For example, a question such as "Did you bring your helmet and gloves?" is output by voice, and the worker confirms this.

[0307] Examples of prompt statements

[0308] By inputting the following prompt sentence into the generative AI model, appropriate advice can be generated.

[0309] "Get data from a weather forecast API and generate weather-based advice. Data includes conditions like sunny, rainy, snowy, cloudy, etc. Generate appropriate voice prompts for each."

[0310] Based on this prompt, the system can provide appropriate advice to workers in real time, helping them prepare for work efficiently and safely.

[0311] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0312] Step 1:

[0313] When a user stands in front of the camera, the server automatically activates the camera. The camera captures a 360-degree image of the user's entire body. The image data obtained as input is then sent to the next step.

[0314] Step 2:

[0315] The server sends the captured image data to the image analysis means, which uses an image processing library such as OpenCV to detect features such as dirt, wrinkles, dust, and messy hair from the input image data. The analysis results are sent to the advice generation means.

[0316] Step 3:

[0317] The server generates appropriate advice through the advice generating means based on the image analysis results. For example, if dirt is detected, the server generates advice such as "Dirt has been detected on the equipment. Please clean it." The generated advice is sent to the voice output means.

[0318] Step 4:

[0319] The server notifies the generated advice to the user by voice using the voice output means, thereby providing the user with information about their own equipment and physical condition.

[0320] Step 5:

[0321] When the user touches the body temperature sensor, the terminal's body temperature measurement means measures the user's body temperature and sends the data to the server. The body temperature data obtained as input is then sent to the physical condition evaluation means.

[0322] Step 6:

[0323] The server processes the body temperature measurement data using a physical condition evaluation means to evaluate the user's physical condition. If a temperature above the normal range is detected, an alert is generated stating, "Your body temperature is high. Please do not overexert yourself and take care of your health." This alert is sent to a voice output means.

[0324] Step 7:

[0325] The server uses a weather forecast API to obtain current weather data. Based on the data obtained from the API, it generates advice appropriate to the weather. For example, it generates advice such as "Rain is expected today, so please wear appropriate waterproof gear." The generated advice is sent to the audio output means.

[0326] Step 8:

[0327] The server uses the lost item confirmation means to prompt the user to check their belongings based on the list of important belongings, generating questions such as "Did you bring your helmet and gloves?" and notifying the user through the voice output means.

[0328] Step 9:

[0329] Users can respond to voice prompts to check their belongings and take necessary actions, and the system will analyze their responses and provide appropriate feedback.

[0330] 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.

[0331] The present invention is a system for enabling a user to efficiently prepare for going out, and combines a photographing means, an image analysis means, an advice generation means, a voice output means, a weather forecast linkage means, a body temperature measurement means, a physical condition evaluation means, a forgotten item confirmation means, an accessory advice means, and an emotion recognition means. Specific embodiments of this system are described below.

[0332] Overall Overview

[0333] This system allows the user to walk around in front of the camera before going out, and automatically checks their appearance and belongings, and provides advice based on the weather and their physical condition. It also recognizes the user's emotions and provides adaptive advice. The user simply follows voice instructions and is ready to go out.

[0334] An example of an appearance check

[0335] 1. The user stands in front of the camera and activates the system. The device uses facial recognition technology to identify the user and issues a voice prompt saying, "Turn around once." The user turns around in front of the camera, capturing a full-body image. The device then sends the captured image data to the server.

[0336] 2. The server processes the received data using an image analysis algorithm to detect dirt, wrinkles, dust, and messy hair on the clothes. Based on the detection results, it generates appropriate advice as text data and sends it to the device for voice output.

[0337] 3. The device will then verbally communicate the generated advice to the user.

[0338] For example: "There are wrinkles on the back. A steam iron would help."

[0339] Weather forecast advice implementation form

[0340] 1. The server obtains weather forecast data based on the user's location information, and generates advice based on the forecast, such as whether or not to bring a jacket or an umbrella. The generated advice is sent to the device as text data.

[0341] 2. The device will provide voice weather forecast advice to the user.

[0342] Example: "It's raining today, so you should bring an umbrella."

[0343] Temperature Measurement and Alert Implementation

[0344] 1. The device outputs a voice prompt to the user to measure their temperature.

[0345] For example: "Please take my temperature."

[0346] 2. The user touches the temperature sensor to measure their temperature, and the device sends the measured temperature data to the server.

[0347] 3. The server analyzes the temperature data and evaluates whether it is within the normal range. If it is abnormal, it generates an alert and sends text data to the device for voice output.

[0348] 4. The device will audibly communicate the alert to the user.

[0349] For example: "Your current temperature is 37.8°C. It's a little high, so I recommend you relax or drink a warm drink."

[0350] Implementation of lost item check

[0351] 1. The device outputs a voice prompt to prompt the user to check their belongings based on the lost items list.

[0352] For example: "Did you bring your keys and wallet?"

[0353] 2. The user responds with the confirmation result by voice.

[0354] For example: "Yes, I have it."

[0355] 3. The device converts the received voice into text, confirms that the item has not been left behind, and notifies the user.

[0356] For example: "I made sure you didn't forget anything."

[0357] Accessory color advice implementation example

[0358] 1. The server analyzes the color information of the user's clothing and generates text data on suitable accessory colors. The generated advice is sent to the device.

[0359] 2. The device will provide the user with audio advice on the color of the accessory.

[0360] For example: "The color of accessories that goes well with today's outfit is silver."

[0361] Emotion Recognition Embodiment

[0362] 1. The device captures the user's voice and facial expressions and analyzes the user's emotions using emotion recognition algorithms. Emotions such as stress, satisfaction, dissatisfaction, and tension are recognized.

[0363] 2. The server adjusts the content and tone of the advice based on the user's emotion recognized by the emotion recognition means. For example, if the user is feeling stressed, the server provides advice to relax and slows down the tone and speed of the voice.

[0364] 3. The device will then provide tailored advice to the user via voice.

[0365] For example: "Why don't you relax a bit?"

[0366] Customization Settings Implementation Example

[0367] 1. The user customizes the voice output settings in the system settings screen, including the gender, impression, and phrasing of the voice.

[0368] 2. The device will save your customization settings and apply them to future audio outputs.

[0369] With the above configuration, users can efficiently prepare before going out, allowing them to go out comfortably, and a system can be realized that also provides psychological support by using emotion recognition.

[0370] The processing flow will be explained below.

[0371] Step 1:

[0372] The user stands in front of the camera and activates the system.

[0373] Step 2:

[0374] The device uses facial recognition technology to identify the user and then issues a voice prompt saying, "Take one lap."

[0375] Step 3:

[0376] The user walks around in front of the camera, capturing their entire body.

[0377] Step 4:

[0378] The device sends the user's photo data to the server.

[0379] Step 5:

[0380] The server uses image analysis algorithms to detect dirt, wrinkles, dust, and messy hair on the clothes.

[0381] Step 6:

[0382] Based on the results of the image analysis, the server generates appropriate advice as text data and sends it to the terminal for voice output.

[0383] Step 7:

[0384] The device will then give the generated advice to the user via voice, for example, "There are wrinkles on your back. You may want to use a steam iron."

[0385] Step 8:

[0386] The server retrieves weather forecast data based on the user's location information.

[0387] Step 9:

[0388] The server generates weather-appropriate advice based on weather forecast data and transmits it to the terminal as text data.

[0389] Step 10:

[0390] The device will then give you weather forecast advice by voice, for example, "It's going to rain today, so you should bring an umbrella."

[0391] Step 11:

[0392] The device will output a voice prompt to the user to take their temperature. For example, "Please take your temperature."

[0393] Step 12:

[0394] The user touches the temperature sensor to measure their temperature.

[0395] Step 13:

[0396] The device sends the measured body temperature data to the server.

[0397] Step 14:

[0398] The server analyzes the temperature data and evaluates whether it is within the normal range. If there is an abnormality, an alert is generated and text data is sent to the device for voice output.

[0399] Step 15:

[0400] The device will then verbally announce the alert to the user, for example, "Your current body temperature is 37.8°C. It's a little high, so we recommend you relax or drink a warm drink."

[0401] Step 16:

[0402] The device will then output a voice prompt based on the list of lost items to remind the user to check their belongings, for example, "Did you bring your keys and wallet?"

[0403] Step 17:

[0404] The user responds with a voice confirmation, for example, "Yes, I have it."

[0405] Step 18:

[0406] The device converts the received voice into text, confirms that the item has not been left behind, and notifies the user.

[0407] Step 19:

[0408] The server analyzes the color information of the user's clothing, generates suitable accessory colors as text data, and sends it to the terminal.

[0409] Step 20:

[0410] The device will give the user audio advice on the color of the accessories, for example, "The color of the accessories that matches your outfit today is silver."

[0411] Step 21:

[0412] The device captures the user's voice and facial expressions, and analyzes the user's emotions using emotion recognition algorithms to recognize emotions such as stress, satisfaction, dissatisfaction, and tension.

[0413] Step 22:

[0414] The server adjusts the content and tone of the advice based on the user's emotion recognized by the emotion recognition means. For example, if the user is feeling stressed, the server provides advice to relax and slows down the tone and speed of the voice.

[0415] Step 23:

[0416] The device will then give tailored advice to the user, such as "Why don't you try to relax a bit?"

[0417] Step 24:

[0418] Users can customize voice output settings in the system settings screen, including voice gender, impression, and phrasing.

[0419] Step 25:

[0420] The device will save your customization settings and apply them to future audio outputs.

[0421] Example 2

[0422] 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."

[0423] For users to prepare for going out efficiently and reliably, they need to check many factors. These include checking their appearance, preparing appropriate gear for the weather, managing their physical condition, checking for forgotten items, and providing advice that adapts to the user's emotions. Performing these tasks manually takes time and effort, hindering efficient preparation for going out. The objective of this invention is to comprehensively solve these problems with a single system.

[0424] 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.

[0425] In this invention, the server includes: an imaging means for imaging the user's body; an image analysis means for analyzing the image of the user captured by the imaging means and detecting stains, wrinkles, dust, and messy hair on the clothes; an advice generation means for generating appropriate advice for the user based on the detection results of the image analysis means; an audio output means for outputting the advice generated by the advice generation means as audio; an emotion recognition means for acquiring the user's voice and facial expression and recognizing their emotion; and an advice generation means for adjusting the content and tone of the advice based on the user's emotion recognized by the emotion recognition means. This enables the user to prepare to go out efficiently and comprehensively using a single system.

[0426] The "system" is an integrated device that combines multiple means to help users efficiently prepare for going out.

[0427] "Photographing means" refers to a device for photographing the user's body, and includes cameras and image capture devices.

[0428] The "image analysis means" is an algorithm or system for analyzing image data acquired by the imaging means and extracting specific information.

[0429] The "advice generation means" is a device or program for generating appropriate advice for the user based on the results of the image analysis means, the weather forecast linkage means, and the emotion recognition means.

[0430] The "audio output means" is a device for conveying the generated advice to the user by voice, and includes a speaker and a voice synthesis system.

[0431] An "emotion recognition means" is an algorithm or system that acquires the user's voice and facial expressions and determines the user's emotions based on them.

[0432] The "weather forecast linking means" is a device or program for acquiring weather forecast data based on the user's location information and generating advice based on that data.

[0433] "Temperature measurement means" refers to a device for measuring the user's temperature, and includes a thermometer and a sensor.

[0434] The "physical condition evaluation means" is a system for analyzing the measured body temperature data and evaluating the user's physical condition.

[0435] The "lost item confirmation means" is a device or program that allows the user to confirm whether or not they have the necessary items.

[0436] The present invention is a system for enabling a user to efficiently prepare for going out, and is realized by combining multiple pieces of hardware and software. Specific embodiments will be described below.

[0437] This system is mainly composed of a terminal and a server. The terminal is connected to input and output devices such as a camera, microphone, speaker, and thermometer. The server also functions as a processing device for executing various analysis and generation algorithms.

[0438] Hardware and software used

[0439] 1. Terminal

[0440] Camera: To capture the user's entire body. For example, a typical webcam or smartphone camera can be used.

[0441] Microphone: To capture the user's voice input, using the built-in microphone on your smartphone or laptop.

[0442] Speakers: For system sound output, using headphones or the device's built-in speakers.

[0443] Thermometer: Use a Bluetooth-connected thermometer.

[0444] 2. Server

[0445] Image analysis algorithm: The captured image data is analyzed using TensorFlow and PyTorch.

[0446] Emotion recognition algorithm: Recognizes user emotions using Microsoft Azure Emotion API, etc.

[0447] Weather forecast data: Obtain weather information using the OpenWeatherMap API.

[0448] Specific processing of the program

[0449] When a user starts the system, the device uses a camera to capture a full-body image of the user. A voice prompt is played saying, "Please turn around in front of the camera." As the user turns around, image data of the entire body is acquired. This data is sent to the server in real time.

[0450] An image analysis model using TensorFlow and PyTorch runs on the server and analyzes the captured image data. This detects dirt, wrinkles, dust, and messy hair on the clothes. Based on the analysis results, appropriate advice is generated and sent to the device as text data. For example, "There are wrinkles on the back. It would be a good idea to use a steam iron."

[0451] As a means of weather forecast integration, the server calls the OpenWeatherMap API based on the user's location information to obtain weather forecast data. Advice for going out based on the weather is generated and sent to the device. Example: "It's going to rain today, so you should bring an umbrella."

[0452] To measure body temperature, the device will issue a voice prompt saying, "Please measure your temperature." When the user measures their temperature using a Bluetooth-connected thermometer, the data is sent to the server, which evaluates their physical condition. For example, "Your current body temperature is 37.8 degrees. It's a little high, so we recommend you relax or drink a warm drink."

[0453] To recognize emotions, the device captures the user's voice and facial expressions and uses the Microsoft Azure Emotion API to recognize their emotions. The server then adjusts the tone and content of the advice based on this emotional information to generate the most appropriate advice. Example: "Why don't you try relaxing a bit?"

[0454] Prompt Sentence Examples

[0455] "I want to use this system to get ready to go out. Can you explain how the system works?"

[0456] "What are the steps to generate weather advice?"

[0457] Please explain with examples how to recognize users' emotions and give advice based on them.

[0458] With the above configuration, users can efficiently prepare before going out, ensuring a comfortable outing. In addition, by using emotion recognition, a system can be realized that also provides psychological support.

[0459] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0460] Step 1: Boot the system

[0461] The user starts the system. The terminal initializes devices such as the camera, microphone, speaker, and thermometer. The input is the user's startup operation, and the output is a notification that each device is ready. Specifically, the terminal checks the connection status of each device and verifies that it is operating normally.

[0462] Step 2: Photographing the user's entire body

[0463] The device uses a voice prompt to instruct the user to "turn around in front of the camera." The camera captures the user's position and movements as input and generates full-body image data as output. The user turns around in front of the camera, and the camera captures multiple images in succession. These images are temporarily stored on the device and immediately sent to the server.

[0464] Step 3: Analyze image data and generate advice

[0465] The image data received by the server is processed using an image analysis algorithm using TensorFlow or PyTorch. Image data of the entire body is sent to the server as input, and the output generates detection results for stains, wrinkles, dust, and messy hair on clothes. Specifically, the analysis algorithm extracts features from the image and performs recognition and classification using a trained model. Based on the results, appropriate advice is generated and sent to the device as text data.

[0466] Step 4: Obtaining weather forecast data and generating advice

[0467] The server retrieves weather forecast data from the OpenWeatherMap API based on the user's location information. Location information is provided as input, and weather forecast data and advice based on it are generated as output. Specifically, the server sends an API request based on the location information and receives weather forecast data. It then analyzes the data and generates appropriate advice (e.g., "Bring an umbrella") and sends it to the device.

[0468] Step 5: Temperature check and health assessment

[0469] The device issues a voice prompt saying "Please measure your temperature." The user measures their temperature using a Bluetooth-connected thermometer. The measurement result is sent to the device as input, and temperature data and a health assessment are generated as output. Specifically, the device receives the thermometer measurement data via Bluetooth and sends it to the server. The server analyzes the temperature data, evaluates whether it is within the normal range, and sends the result to the device.

[0470] Step 6: Emotion recognition and advice adjustment

[0471] The device captures the user's voice and facial expressions and analyzes them using an emotion recognition algorithm. Voice and image data are provided as input, and advice tailored to the user's emotions is generated as output. Specifically, the device collects voice and facial expression data and sends it to a server. The server analyzes it using an emotion recognition algorithm (for example, Microsoft Azure Emotion API) and adjusts the tone and content of the advice based on the results. As a result, advice tailored to the user is generated and sent to the device.

[0472] Step 7: Final output of the advice

[0473] The device will then verbally communicate to the user all the advice it has generated so far. Various analysis results and advice data are provided as input, and voice guidance is provided to the user as output. Specifically, it uses a speech synthesis engine (e.g., Google Text-to-Speech API) to convert text data into speech, which is then transmitted to the user through the speaker.

[0474] Through the above processing steps, the user can easily prepare to go out efficiently and effectively.

[0475] (Application example 2)

[0476] 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."

[0477] Conventional outing preparation systems require time and effort for users to check their appearance and belongings, and are unable to provide a wide range of support in a unified manner, such as advice based on weather and physical condition, or emotional support. This can lead to problems such as users feeling anxious before going out and needing time to get ready. The present invention aims to solve these problems and provide a system that allows users to prepare for going out more efficiently and comfortably.

[0478] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: an imaging means for capturing an image of the user's body; an image analysis means for analyzing the image of the user captured by the imaging means and detecting stains, wrinkles, dust, and messy hair on the user's clothes; an advice generation means for generating appropriate advice for the user based on the detection results of the image analysis means; an audio output means for outputting the advice generated by the advice generation means as audio; an accessory advice means for advising the user on appropriate accessory colors based on color information of the user's clothing analyzed by the image analysis means; and an emotion recognition means for acquiring the user's voice and facial expression, analyzing the user's emotions using emotion recognition means, and adjusting the content and tone of the advice based on the recognized emotions. This improves the efficiency of the user's preparations for going out and enables appropriate advice to be provided according to individual needs and emotions.

[0479] "Photographing means" refers to a device for photographing the user's body.

[0480] The "image analysis means" is a device or software that analyzes the image of the user captured by the image capture means and detects stains, wrinkles, dust, and messy hair on the clothes.

[0481] The "advice generating means" is a device or software for generating appropriate advice for the user based on the detection results of the image analyzing means.

[0482] The "audio output means" is a device or software for audibly outputting the advice generated by the advice generating means.

[0483] The "accessory advice means" is a device or software that advises on suitable accessory colors based on the color information of the user's clothing analyzed by the image analysis means.

[0484] "Emotion recognition means" refers to a device or software that acquires the user's voice and facial expressions and analyzes and recognizes their emotions.

[0485] The "weather forecast linking means" is a device or software that acquires weather forecast data based on the user's location information and generates advice for going out based on the weather forecast.

[0486] "Temperature measuring means" refers to a device for measuring the user's temperature.

[0487] The "physical condition evaluation means" is a device or software for evaluating the physical condition of the user based on the body temperature data measured by the body temperature measurement means.

[0488] The present invention is a system for helping users get ready to go out more efficiently, combining a photography unit, an image analysis unit, an advice generation unit, a voice output unit, an accessory advice unit, and an emotion recognition unit. This system can be applied to smart fitting rooms in apparel shops, in particular, to improve customer experience.

[0489] The main components of the system are:

[0490] 1. Photography Method:

[0491] When a user enters a fitting room, a camera installed in the fitting room automatically captures the user's entire body.

[0492] The captured image is sent to a server.

[0493] 2. Image analysis methods:

[0494] The server analyzes the received images using an image analysis algorithm (e.g., a model using TensorFlow).

[0495] It detects wrinkles and stains on clothes and messy hair and generates the necessary advice.

[0496] 3. Advice Generation Methods:

[0497] Based on the results obtained by the image analysis means, appropriate advice is automatically generated for the user.

[0498] For example: "There are wrinkles on the back. A steam iron would help."

[0499] 4. Audio output means:

[0500] The generated advice is communicated to the user via audio through a speaker in the fitting room.

[0501] Use a speech synthesis library such as Python's pyttsx3.

[0502] 5. Accessory advice:

[0503] Based on the color information of the user's clothing obtained through image analysis, the system advises on the appropriate color of accessories.

[0504] For example: "A silver necklace would go well with this outfit."

[0505] 6. Emotion recognition means:

[0506] It captures the user's facial expressions and voice and analyzes their emotions using an emotion recognition model.

[0507] If the user is anxious, they are given advice to help them relax.

[0508] For example: "Please relax and feel free to try things on."

[0509] 7. Weather forecast integration methods:

[0510] The server obtains weather forecast data based on the user's location information (using WeatherAPI, etc.).

[0511] Generate advice for going out based on weather forecasts.

[0512] For example: "It's raining outside, so I recommend a waterproof coat."

[0513] The specific hardware is a fitting room device equipped with a camera, speaker, and microphone. The software uses Python, OpenCV, TensorFlow, pyttsx3, etc. The fitting room camera captures the user's image, which is then sent to a server for analysis. Advice generated based on the analysis results is communicated to the user using audio output.

[0514] This system allows users to receive detailed advice when preparing to go out, enabling a stress-free shopping experience. It also has an emotion recognition function that can provide psychological support to users, improving customer satisfaction.

[0515] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0516] Step 1:

[0517] When a user enters a fitting room, the device uses a camera to take a full-body image of the user, which is then sent to the server as input for further processing.

[0518] Step 2:

[0519] The server analyzes the received full-body image using image analysis tools. Specifically, it uses image analysis models such as TensorFlow to detect dirt, wrinkles, dust, and messy hair on the clothes. The data obtained from this analysis becomes the input for the next process.

[0520] Step 3:

[0521] Based on the analysis results, the server uses the advice generation means to generate appropriate advice for the user. This advice generation includes the user's clothing status and detailed comments. The generated advice becomes the input for the next step.

[0522] Step 4:

[0523] The device communicates the generated advice to the user through a voice output means. Specifically, the advice is output as voice using a voice synthesis library such as Python's pyttsx3. The user receives this voice advice.

[0524] Step 5:

[0525] The server acquires color information of the user's clothing using the image analysis means, and advises the user on the appropriate accessory color using the accessory advice means. This advice is also conveyed to the user by the voice output means, and is output as advice to the user.

[0526] Step 6:

[0527] The user's facial expressions and voice are acquired by the device and analyzed by the emotion recognition means. Based on the analysis results, the server analyzes the user's emotions and generates advice on how to relax as needed. The advice generated by this emotion recognition is conveyed to the user by the voice output means.

[0528] Step 7:

[0529] The server uses the weather forecast linking means to acquire weather forecast data from the user's location information. Based on the acquired weather data, advice for going out is generated. This advice based on the weather forecast is also conveyed to the user by the voice output means.

[0530] 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.

[0531] 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.

[0532] 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.

[0533] [Second embodiment]

[0534] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0535] 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.

[0536] 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).

[0537] 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.

[0538] 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.

[0539] 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).

[0540] 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.

[0541] 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.

[0542] 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.

[0543] 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.

[0544] In the smart glasses 214, the 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.

[0545] 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."

[0546] The present invention is a system for enabling a user to efficiently prepare for going out, and it combines a photographing means, an image analysis means, an advice generation means, a voice output means, a weather forecast linkage means, a body temperature measurement means, a physical condition evaluation means, a forgotten item confirmation means, and an accessory advice means. Specific embodiments of this system are described below.

[0547] Overall Overview

[0548] This system allows users to walk around in front of the camera before going out, and automatically checks their appearance and belongings, and provides advice based on the weather and their physical condition. Users simply follow voice instructions and are ready to go out.

[0549] An example of an appearance check

[0550] 1. Terminal

[0551] When the user stands in front of the camera, it automatically activates and takes a picture of the user, with voice prompts to walk around in a circle.

[0552] 2. Server

[0553] It receives the captured image data and uses an image analysis algorithm to detect dirt, wrinkles, dust, and messy hair on the clothes, then generates necessary advice based on the results and generates text data for voice output.

[0554] 3. Terminal

[0555] The generated advice is communicated to the user as audio.

[0556] For example: "There are wrinkles on the back. A steam iron would help."

[0557] Weather forecast advice implementation form

[0558] 1. Server

[0559] The system obtains the latest weather forecast data based on the user's location, and generates advice on whether they need a jacket or an umbrella based on the forecast.

[0560] 2. Terminal

[0561] The message is conveyed to the user as audio.

[0562] Example: "It's raining today, so you should bring an umbrella."

[0563] Temperature Measurement and Alert Implementation

[0564] 1. Terminal

[0565] The user is prompted by voice to take their temperature, and their temperature is measured by touching the temperature sensor.

[0566] 2. Server

[0567] Receives the measured body temperature data and evaluates whether it is within the normal range. If it is abnormal, it generates an alert and generates text data for voice output.

[0568] 3. Terminal

[0569] The content of the alert is announced to the user through audio.

[0570] For example: "Your current temperature is 37.8°C. It's a little high, so I recommend you relax or drink a warm drink."

[0571] Implementation of lost item check

[0572] 1. Terminal

[0573] Based on the loaded lost item list, it outputs a voice prompt to remind the user to check their belongings.

[0574] For example: "Did you bring your keys and wallet?"

[0575] 2. Users

[0576] You will receive a voice confirmation, which the system will analyze to determine if you are fully prepared.

[0577] For example: "Yes, I have it."

[0578] Accessory color advice implementation example

[0579] 1. Server

[0580] It analyzes the user's clothing color information and generates color advice for suitable accessories based on fashion rules.

[0581] 2. Terminal

[0582] The generated advice is communicated to the user as audio.

[0583] For example: "The color of accessories that goes well with today's outfit is silver."

[0584] Customization Settings Implementation Example

[0585] 1. Users

[0586] Customize your voice output settings to adjust the gender, tone, and phrasing of the voice.

[0587] 2. Terminal

[0588] The received customization settings will be saved and reflected from the next time onwards.

[0589] The above configuration allows the user to efficiently prepare before going out, realizing a system that allows for a comfortable outing.

[0590] The processing flow will be explained below.

[0591] Step 1:

[0592] The user stands in front of the camera and activates the system.

[0593] Step 2:

[0594] The device uses facial recognition technology to identify the user and then issues a voice prompt saying, "Take one lap."

[0595] Step 3:

[0596] The user walks around in front of the camera, capturing their entire body.

[0597] Step 4:

[0598] The device sends the captured data from the user's entire rotation to the server.

[0599] Step 5:

[0600] The server processes the received data based on image analysis algorithms to detect dirt, wrinkles, dust, and messy hair on the clothes.

[0601] Step 6:

[0602] Based on the results of image analysis, the server generates appropriate advice for the user as text data and sends it to the terminal for voice output.

[0603] Step 7:

[0604] The device will communicate the advice it receives to the user via voice.

[0605] For example: "There are wrinkles on the back. A steam iron would help."

[0606] Step 8:

[0607] The server retrieves weather forecast data based on the user's location information.

[0608] Step 9:

[0609] The server generates text data based on weather forecast data, giving advice on whether a jacket is needed or whether an umbrella should be carried, and transmits the text data to the terminal for voice output.

[0610] Step 10:

[0611] The device will then communicate the weather forecast advice received to the user via voice.

[0612] Example: "It's raining today, so you should bring an umbrella."

[0613] Step 11:

[0614] The device will output a voice prompt to the user to take their temperature.

[0615] For example: "Please take my temperature."

[0616] Step 12:

[0617] The user touches the temperature sensor to measure their temperature.

[0618] Step 13:

[0619] The device sends the measured body temperature data to the server.

[0620] Step 14:

[0621] The server analyzes the temperature data and determines whether it is within the normal range. If it is abnormal, it generates an alert and generates text data for voice output and sends it to the device.

[0622] Step 15:

[0623] The device will communicate any alerts received to the user via voice.

[0624] For example: "Your current temperature is 37.8°C. It's a little high, so I recommend you relax or drink a warm drink."

[0625] Step 16:

[0626] The device loads the registered lost item list and outputs a voice prompt to ask the user to confirm.

[0627] For example: "Did you bring your keys and wallet?"

[0628] Step 17:

[0629] The user responds with the confirmation result by voice.

[0630] For example: "Yes, I have it."

[0631] Step 18:

[0632] The device converts the received voice into text, confirms that the item has not been left behind, and notifies the user.

[0633] For example: "I made sure you didn't forget anything."

[0634] Step 19:

[0635] The server analyzes the color information of the user's clothing, generates suitable accessory colors as text data, and sends it to the terminal for voice output.

[0636] Step 20:

[0637] The device will then provide the user with audio color advice for the accessory it receives.

[0638] For example: "The color of accessories that goes well with today's outfit is silver."

[0639] Step 21:

[0640] Users can customize voice output settings and adjust the gender, impression, and phrasing of the voice.

[0641] Step 22:

[0642] The device will save your customization settings and apply them the next time.

[0643] Example 1

[0644] 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."

[0645] Previously, preparing to go out required users to individually check their appearance, the weather, their physical condition, and their belongings, which took a lot of time and effort. This often caused stress for users before going out, and was inefficient. There was also a need for a system that could centrally automate these check tasks.

[0646] 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.

[0647] In this invention, the server includes: an imaging means for capturing an image of the user's body; an image analysis means for analyzing the image of the user captured by the imaging means to detect stains, wrinkles, dust, and messy hair on the user's clothes; an advice generation means for generating appropriate advice for the user based on the detection results of the image analysis means; an audio output means for outputting the advice generated by the advice generation means as audio; a weather forecast linkage means for acquiring weather forecast data based on the user's location information and generating advice for the user when going out based on the acquired weather forecast; a temperature measurement means for outputting an audio prompt urging the user to measure their temperature and measuring the user's temperature; a physical condition evaluation means for evaluating the user's physical condition based on the measured temperature data and generating an alert if an abnormality is detected; a forgotten item confirmation means for outputting an audio prompt urging the user to check their belongings; and an accessory advice means for analyzing the color information of the user's clothing and generating color advice for appropriate accessories. This allows the user to efficiently prepare before going out and enjoy a comfortable outing.

[0648] "Photographing means" refers to equipment or devices for photographing the user's body.

[0649] "Image analysis means" refers to a technology or device that analyzes a photographed image of a user and detects stains, wrinkles, dust, and messy hair on the clothes.

[0650] The "advice generation means" is a technology or device for generating appropriate advice for the user based on the detection results obtained by the image analysis means.

[0651] The "audio output means" is a technique or device for outputting the advice generated by the advice generating means as audio.

[0652] The "weather forecast linking means" is a technology or device for acquiring weather forecast data based on the user's location information and generating advice for the user when going out based on the acquired weather forecast.

[0653] "Temperature measurement means" means any technology or device for measuring a user's temperature.

[0654] The "physical condition evaluation means" is a technology or device for evaluating the user's physical condition based on measured body temperature data and generating an alert if any abnormalities are detected.

[0655] A "lost property verification means" is a technology or device that outputs a voice prompt to prompt the user to verify their belongings.

[0656] The "accessory advice means" is a technology or device for analyzing the user's clothing color information and generating color advice for suitable accessories.

[0657] A "user" is a person who uses this system to prepare for going out.

[0658] The present invention is a system for enabling users to efficiently prepare for going out. By combining a photographing means, an image analysis means, a means for generating advice, a means for outputting audio, a means for linking with weather forecasts, a means for measuring body temperature, a means for evaluating physical condition, a means for checking for lost items, and a means for providing advice on accessories, the system allows users to centrally automate their preparations before going out. Specific embodiments of the present invention are described below.

[0659] System Hardware and Software

[0660] Hardware

[0661] Photography method: Uses the camera on a smartphone or tablet to capture a photo of the user's body.

[0662] Body temperature measurement method: A smartwatch or dedicated body temperature sensor is used to measure the user's body temperature.

[0663] software

[0664] Image analysis method: The OpenCV library is used for image analysis, which detects dirt, wrinkles, dust, and messy hair from captured images.

[0665] Advice generation method: The advice is generated using a script written in "Python" or "JavaScript."

[0666] Voice output method: "Google Text-to-Speech" and "Amazon Polly" are used for voice output, which convert text data into voice.

[0667] Weather forecast integration method: The OpenWeatherMap API is used to obtain weather forecast data, which allows users to obtain weather forecasts based on their location.

[0668] Physical condition evaluation method: An analysis system linked to "Raspberry Pi" is used to evaluate body temperature data, which determines whether the body temperature is within the normal range.

[0669] How to check for lost items: To check for lost items, a voice prompt is output through Google Assistant, prompting the user to check for their belongings.

[0670] Accessory advice method: IBM Watson Visual Recognition is used to analyze and advise on clothing colors, suggesting accessory colors that match the user's outfit.

[0671] Example of operation

[0672] 1. Grooming check

[0673] When a user stands in front of the camera, it automatically starts up and takes a picture of the user.

[0674] The device will play a voice prompt saying "Take a turn."

[0675] The server uses OpenCV's image analysis algorithm to detect stains and wrinkles on the clothes.

[0676] The server generates the advice "There are wrinkles on the back. You may want to use a steam iron."

[0677] The device uses Google Text-to-Speech to convert advice into audio and convey it to the user.

[0678] 2. Weather Forecast Advice

[0679] The server uses the OpenWeatherMap API to get the latest weather forecast.

[0680] The server generates the advice "It's raining today, so please take an umbrella."

[0681] The device uses Amazon Polly to convert advice into voice and convey it to the user.

[0682] 3. Temperature measurement and alerts

[0683] The device will play a voice prompt saying, "Please take your temperature."

[0684] The user measures their temperature by touching the temperature sensor on the smartwatch.

[0685] The server receives the body temperature data and analyzes it using a Raspberry Pi.

[0686] The server generates an alert saying, "Your current temperature is 37.8 degrees. It's a little high, so we recommend you relax or drink a warm drink."

[0687] The device converts the alert into audio and relays it to the user.

[0688] 4. Check for lost items

[0689] The device will play a voice prompt asking, "Did you bring your keys and wallet?"

[0690] The user responds by voice, "Yes, I have it."

[0691] The device uses Azure Speech to Text to convert speech into text and analyze it.

[0692] 5. Accessory advice

[0693] The server uses IBM Watson Visual Recognition to analyze clothing colors.

[0694] The server generates advice such as "The color of the accessory that matches your outfit today is silver."

[0695] The device uses Amazon Alexa to convert advice into voice and convey it to the user.

[0696] According to the above-mentioned specific examples, the system of the present invention makes it possible for the user to efficiently prepare for going out and reduces stress.

[0697] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0698] Step 1: The user stands in front of the camera

[0699] Input: The user stands in front of the camera.

[0700] Action: The device detects the user's presence using a sensor.

[0701] Output: The camera starts automatically.

[0702] What it does: Your smartphone or tablet's camera app will automatically launch and you'll hear a voice prompt saying, "Take a full turn."

[0703] Step 2: The device takes a photo of the user

[0704] Input: The user moves around in a circle.

[0705] Processing: The device takes continuous shots and records the footage.

[0706] Output: Video data is generated.

[0707] Specific operation: The smartphone takes continuous shots and sends the video data to the server.

[0708] Step 3: The server performs image analysis

[0709] Input: Video data sent from the device.

[0710] Processing: The server uses the OpenCV library to analyze the images and detect stains, wrinkles, dust, and messy hair on the clothes.

[0711] Output: The detection results are generated.

[0712] Specific operation: The server analyzes the video data frame by frame and identifies problem areas.

[0713] Step 4: Server generates advice

[0714] Input: Detection results from image analysis.

[0715] Processing: The server generates advice for the user based on the analysis results.

[0716] Output: Text data of advice is generated.

[0717] Specific behavior: If dirt is detected, generate advice such as "There is dirt on the back. It may be a good idea to use a brush."

[0718] Step 5: Your device will speak the advice

[0719] Input: Text data of advice sent from the server.

[0720] Processing: Your device uses Google Text-to-Speech to convert the text data into audio.

[0721] Output: A spoken advice is generated.

[0722] Specific behavior: The smartphone conveys the generated voice advice to the user.

[0723] Step 6: Server retrieves weather forecast data

[0724] Input: User's location.

[0725] Process: The server retrieves weather forecast data using the OpenWeatherMap API.

[0726] Output: Weather forecast data is generated.

[0727] Specific operation: The server retrieves the latest weather forecast based on the location information.

[0728] Step 7: Server generates weather-based advice

[0729] Input: Weather forecast data.

[0730] Processing: The server generates advice for going out based on the weather forecast data.

[0731] Output: Weather-based advice text data is generated.

[0732] Specific behavior: If rain is forecast, generate advice such as "It's going to rain today, so please bring an umbrella."

[0733] Step 8: Your device will speak weather advice

[0734] Input: Weather advice text data sent from the server.

[0735] Processing: The device uses Amazon Polly to convert the text data into speech.

[0736] Output: A spoken advice is generated.

[0737] Specific behavior: The smartphone conveys the generated voice advice to the user.

[0738] Step 9: The device prompts you to take your temperature

[0739] Input: The act of the user hearing a voice prompt.

[0740] Action: The device outputs a voice prompt saying "Please take your temperature."

[0741] Output: The user begins taking their temperature.

[0742] What it does: The smartwatch will play a voice prompt to remind the user to take their temperature.

[0743] Step 10: User takes temperature

[0744] Input: Touching the temperature sensor.

[0745] Processing: The temperature sensor measures the user's temperature and generates the data.

[0746] Output: Temperature data is generated.

[0747] What happens: The user touches the sensor on the smartwatch to measure their body temperature.

[0748] Step 11: Server evaluates temperature data

[0749] Input: Temperature measurement data.

[0750] Processing: The server analyzes the received temperature data and evaluates whether it is within the normal range.

[0751] Output: Text data of health alert is generated.

[0752] What it does: The server analyzes data from the temperature sensor connected to the Raspberry Pi and generates alerts as needed.

[0753] Step 12: Your device will output a health alert

[0754] Input: Text data of health alert sent from the server.

[0755] Action: The device uses iOS VoiceOver to convert the alert into audio.

[0756] Output: An audio alert is generated.

[0757] What it does: The smartphone plays the generated audio alert to the user.

[0758] Step 13: The device will output a lost item confirmation prompt

[0759] Input: System loaded lost item checklist.

[0760] Action: Your device uses Google Assistant to speak a prompt to check your belongings.

[0761] Output: A voice prompt is generated.

[0762] What happens: Your smartphone will play a voice prompt saying, "Did you bring your keys and wallet?"

[0763] Step 14: User responds with confirmation by voice

[0764] Input: User's voice input.

[0765] Processing: The device converts the user's voice into text using Azure Speech to Text, which is then analyzed by the system.

[0766] Output: Text data of the belongings check result is generated.

[0767] Specific operation: The user replies "Yes, I have it," and the device converts the speech into text and analyzes it.

[0768] Step 15: Check that your device is ready

[0769] Input: Text data of the inventory check results.

[0770] Processing: The device checks the lost item checklist against the user's voice response to determine if they are ready.

[0771] Output: A text message is generated to notify you that the device is ready.

[0772] What it does: The device checks the checklist and the user's responses, then notifies them that all items are in order.

[0773] Step 16: Server analyzes clothing color

[0774] Input: User's clothing image data.

[0775] Processing: The server analyzes the clothing color using IBM Watson Visual Recognition.

[0776] Output: Color analysis results are generated.

[0777] Specific operation: The server analyzes the user's clothing image and obtains color information.

[0778] Step 17: Server generates color advice for accessories

[0779] Input: Color analysis results.

[0780] Processing: The server generates color advice for suitable accessories based on the analysis results.

[0781] Output: Text data of accessory advice is generated.

[0782] Specific behavior: Generates advice such as "The color of accessories that goes well with today's outfit is silver."

[0783] Step 18: Your device will speak accessory advice

[0784] Input: Text data of accessory advice sent from the server.

[0785] Processing: The device uses Amazon Alexa to convert the advice into voice.

[0786] Output: A spoken advice is generated.

[0787] Specific operation: The smart speaker outputs advice aloud and conveys it to the user.

[0788] Through the above steps, the system of the present invention enables the user to efficiently prepare for going out and ensure a comfortable outing.

[0789] (Application example 1)

[0790] 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."

[0791] In the past, factory workers' work preparation required individual checking of equipment, temperature checks, and checking for forgotten items, which was inefficient and required a great deal of time and effort. Furthermore, there was a lack of appropriate advice regarding weather changes, which led to a decline in worker safety and efficiency. To solve these issues, a system was needed that centralized the worker preparation process and made it possible to do so quickly and efficiently.

[0792] 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.

[0793] In this invention, the server includes a photographing means for photographing the user's body, an image analysis means for analyzing the image of the user photographed by the photographing means to detect stains, wrinkles, dust, and messy hair on the clothes, and an advice generation means for generating appropriate advice for the user based on the detection results of the image analysis means. This makes it possible to streamline work preparation for factory workers and to centrally manage equipment checks, temperature measurements, and forgotten item checks.

[0794] "Photographing means" is a mechanism for photographing the user's body and equipment, and is a device for obtaining the user's appearance as digital data.

[0795] The "image analysis means" is a mechanism that processes and analyzes the image data acquired by the photographing means and detects specific features (for example, dirt, wrinkles, dust, or messy hair).

[0796] The "advice generator" is a mechanism or algorithm for generating appropriate advice for a user based on the image analysis means and other data inputs.

[0797] The "audio output means" is a device or software for conveying the advice generated by the advice generating means to the user in audio form.

[0798] "Temperature measurement means" means a sensor or device for measuring a user's temperature and providing the data necessary to assess the user's health condition.

[0799] The "physical condition assessment means" is an algorithm or mechanism that assesses the user's health condition based on the body temperature data obtained by the body temperature measurement means and generates appropriate advice or warnings.

[0800] The "weather forecast linking means" is an information processing system that acquires current weather forecast data and generates appropriate advice for the user when going out or working.

[0801] The "lost item confirmation means" is a system that checks whether all important belongings are present based on the user's belongings list and notifies the user of the results.

[0802] The present invention is a system for improving the efficiency of work preparation by factory workers. Each means and its processing will be described in detail below.

[0803] Photography and image analysis methods

[0804] A camera that captures images of the user's body and equipment is connected to the server. The camera automatically activates when the worker stands in front of the camera, capturing images of the worker in all 360-degree directions. This captured image data is immediately sent to the image analysis means, which uses an open-source image processing library (e.g., OpenCV) to detect dirt, wrinkles, dust, and messy hair on the equipment.

[0805] Advice generation means and voice output means

[0806] Based on the results obtained by the image analysis means, the advice generation means of the server generates appropriate advice for the worker. The generated advice is communicated to the worker in real time by the voice output means. A library that converts text to voice (e.g., pyttsx3) is used for the voice output.

[0807] For example, the advice "Dirt has been detected on your equipment. Please clean it" is output as voice.

[0808] Temperature measurement and health assessment methods

[0809] The system is equipped with a sensor for measuring the worker's body temperature. The body temperature measurement means measures the worker's body temperature when the worker touches the sensor and sends the data to a server. The physical condition evaluation means evaluates the worker's physical condition based on this body temperature data and generates an alert if there is an abnormality. The worker is also notified of this alert by voice.

[0810] For example, advice such as "Your body temperature is high. Don't push yourself and take care of your health" is output as audio.

[0811] Weather forecast linkage method

[0812] The server retrieves current weather forecast data via an Internet connection and generates advice based on the worker's working environment. For this purpose, a weather forecast API is used. If the weather is bad (e.g., rainy), the server will give the worker appropriate warnings.

[0813] For example, advice such as "Rain is expected today, so please wear appropriate waterproof gear" may be output via voice.

[0814] How to check for lost items

[0815] A list of important items that the worker should have is loaded onto the server, and the lost item confirmation means prompts the worker by voice to check the items he or she has brought with him or her based on this list.

[0816] For example, a question such as "Did you bring your helmet and gloves?" is output by voice, and the worker confirms this.

[0817] Examples of prompt statements

[0818] By inputting the following prompt sentence into the generative AI model, appropriate advice can be generated.

[0819] "Get data from a weather forecast API and generate weather-based advice. Data includes conditions like sunny, rainy, snowy, cloudy, etc. Generate appropriate voice prompts for each."

[0820] Based on this prompt, the system can provide appropriate advice to workers in real time, helping them prepare for work efficiently and safely.

[0821] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0822] Step 1:

[0823] When a user stands in front of the camera, the server automatically activates the camera. The camera captures a 360-degree image of the user's entire body. The image data obtained as input is then sent to the next step.

[0824] Step 2:

[0825] The server sends the captured image data to the image analysis means, which uses an image processing library such as OpenCV to detect features such as dirt, wrinkles, dust, and messy hair from the input image data. The analysis results are sent to the advice generation means.

[0826] Step 3:

[0827] The server generates appropriate advice through the advice generating means based on the image analysis results. For example, if dirt is detected, the server generates advice such as "Dirt has been detected on the equipment. Please clean it." The generated advice is sent to the voice output means.

[0828] Step 4:

[0829] The server notifies the generated advice to the user by voice using the voice output means, thereby providing the user with information about their own equipment and physical condition.

[0830] Step 5:

[0831] When the user touches the body temperature sensor, the terminal's body temperature measurement means measures the user's body temperature and sends the data to the server. The body temperature data obtained as input is then sent to the physical condition evaluation means.

[0832] Step 6:

[0833] The server processes the body temperature measurement data using a physical condition evaluation means to evaluate the user's physical condition. If a temperature above the normal range is detected, an alert is generated stating, "Your body temperature is high. Please do not overexert yourself and take care of your health." This alert is sent to a voice output means.

[0834] Step 7:

[0835] The server uses a weather forecast API to obtain current weather data. Based on the data obtained from the API, it generates advice appropriate to the weather. For example, it generates advice such as "Rain is expected today, so please wear appropriate waterproof gear." The generated advice is sent to the audio output means.

[0836] Step 8:

[0837] The server uses the lost item confirmation means to prompt the user to check their belongings based on the list of important belongings, generating questions such as "Did you bring your helmet and gloves?" and notifying the user through the voice output means.

[0838] Step 9:

[0839] Users can respond to voice prompts to check their belongings and take necessary actions, and the system will analyze their responses and provide appropriate feedback.

[0840] 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.

[0841] The present invention is a system for enabling a user to efficiently prepare for going out, and combines a photographing means, an image analysis means, an advice generation means, a voice output means, a weather forecast linkage means, a body temperature measurement means, a physical condition evaluation means, a forgotten item confirmation means, an accessory advice means, and an emotion recognition means. Specific embodiments of this system are described below.

[0842] Overall Overview

[0843] This system allows the user to walk around in front of the camera before going out, and automatically checks their appearance and belongings, and provides advice based on the weather and their physical condition. It also recognizes the user's emotions and provides adaptive advice. The user simply follows voice instructions and is ready to go out.

[0844] An example of an appearance check

[0845] 1. The user stands in front of the camera and activates the system. The device uses facial recognition technology to identify the user and issues a voice prompt saying, "Turn around once." The user turns around in front of the camera, capturing a full-body image. The device then sends the captured image data to the server.

[0846] 2. The server processes the received data using an image analysis algorithm to detect dirt, wrinkles, dust, and messy hair on the clothes. Based on the detection results, it generates appropriate advice as text data and sends it to the device for voice output.

[0847] 3. The device will then verbally communicate the generated advice to the user.

[0848] For example: "There are wrinkles on the back. A steam iron would help."

[0849] Weather forecast advice implementation form

[0850] 1. The server obtains weather forecast data based on the user's location information, and generates advice based on the forecast, such as whether or not to bring a jacket or an umbrella. The generated advice is sent to the device as text data.

[0851] 2. The device will provide voice weather forecast advice to the user.

[0852] Example: "It's raining today, so you should bring an umbrella."

[0853] Temperature Measurement and Alert Implementation

[0854] 1. The device outputs a voice prompt to the user to measure their temperature.

[0855] For example: "Please take my temperature."

[0856] 2. The user touches the temperature sensor to measure their temperature, and the device sends the measured temperature data to the server.

[0857] 3. The server analyzes the temperature data and evaluates whether it is within the normal range. If it is abnormal, it generates an alert and sends text data to the device for voice output.

[0858] 4. The device will audibly communicate the alert to the user.

[0859] For example: "Your current temperature is 37.8°C. It's a little high, so I recommend you relax or drink a warm drink."

[0860] Implementation of lost item check

[0861] 1. The device outputs a voice prompt to prompt the user to check their belongings based on the lost items list.

[0862] For example: "Did you bring your keys and wallet?"

[0863] 2. The user responds with the confirmation result by voice.

[0864] For example: "Yes, I have it."

[0865] 3. The device converts the received voice into text, confirms that the item has not been left behind, and notifies the user.

[0866] For example: "I made sure you didn't forget anything."

[0867] Accessory color advice implementation example

[0868] 1. The server analyzes the color information of the user's clothing and generates text data on suitable accessory colors. The generated advice is sent to the device.

[0869] 2. The device will provide the user with audio advice on the color of the accessory.

[0870] For example: "The color of accessories that goes well with today's outfit is silver."

[0871] Emotion Recognition Embodiment

[0872] 1. The device captures the user's voice and facial expressions and analyzes the user's emotions using emotion recognition algorithms. Emotions such as stress, satisfaction, dissatisfaction, and tension are recognized.

[0873] 2. The server adjusts the content and tone of the advice based on the user's emotion recognized by the emotion recognition means. For example, if the user is feeling stressed, the server provides advice to relax and slows down the tone and speed of the voice.

[0874] 3. The device will then provide tailored advice to the user via voice.

[0875] For example: "Why don't you relax a bit?"

[0876] Customization Settings Implementation Example

[0877] 1. The user customizes the voice output settings in the system settings screen, including the gender, impression, and phrasing of the voice.

[0878] 2. The device will save your customization settings and apply them to future audio outputs.

[0879] With the above configuration, users can efficiently prepare before going out, allowing them to go out comfortably, and a system can be realized that also provides psychological support by using emotion recognition.

[0880] The processing flow will be explained below.

[0881] Step 1:

[0882] The user stands in front of the camera and activates the system.

[0883] Step 2:

[0884] The device uses facial recognition technology to identify the user and then issues a voice prompt saying, "Take one lap."

[0885] Step 3:

[0886] The user walks around in front of the camera, capturing their entire body.

[0887] Step 4:

[0888] The device sends the user's photo data to the server.

[0889] Step 5:

[0890] The server uses image analysis algorithms to detect dirt, wrinkles, dust, and messy hair on the clothes.

[0891] Step 6:

[0892] Based on the results of the image analysis, the server generates appropriate advice as text data and sends it to the terminal for voice output.

[0893] Step 7:

[0894] The device will then give the generated advice to the user via voice, for example, "There are wrinkles on your back. You may want to use a steam iron."

[0895] Step 8:

[0896] The server retrieves weather forecast data based on the user's location information.

[0897] Step 9:

[0898] The server generates weather-appropriate advice based on weather forecast data and transmits it to the terminal as text data.

[0899] Step 10:

[0900] The device will then give you weather forecast advice by voice, for example, "It's going to rain today, so you should bring an umbrella."

[0901] Step 11:

[0902] The device will output a voice prompt to the user to take their temperature. For example, "Please take your temperature."

[0903] Step 12:

[0904] The user touches the temperature sensor to measure their temperature.

[0905] Step 13:

[0906] The device sends the measured body temperature data to the server.

[0907] Step 14:

[0908] The server analyzes the temperature data and evaluates whether it is within the normal range. If there is an abnormality, an alert is generated and text data is sent to the device for voice output.

[0909] Step 15:

[0910] The device will then verbally announce the alert to the user, for example, "Your current body temperature is 37.8°C. It's a little high, so we recommend you relax or drink a warm drink."

[0911] Step 16:

[0912] The device will then output a voice prompt based on the list of lost items to remind the user to check their belongings, for example, "Did you bring your keys and wallet?"

[0913] Step 17:

[0914] The user responds with a voice confirmation, for example, "Yes, I have it."

[0915] Step 18:

[0916] The device converts the received voice into text, confirms that the item has not been left behind, and notifies the user.

[0917] Step 19:

[0918] The server analyzes the color information of the user's clothing, generates suitable accessory colors as text data, and sends it to the terminal.

[0919] Step 20:

[0920] The device will give the user audio advice on the color of the accessories, for example, "The color of the accessories that matches your outfit today is silver."

[0921] Step 21:

[0922] The device captures the user's voice and facial expressions, and analyzes the user's emotions using emotion recognition algorithms to recognize emotions such as stress, satisfaction, dissatisfaction, and tension.

[0923] Step 22:

[0924] The server adjusts the content and tone of the advice based on the user's emotion recognized by the emotion recognition means. For example, if the user is feeling stressed, the server provides advice to relax and slows down the tone and speed of the voice.

[0925] Step 23:

[0926] The device will then give tailored advice to the user, such as "Why don't you try to relax a bit?"

[0927] Step 24:

[0928] Users can customize voice output settings in the system settings screen, including voice gender, impression, and phrasing.

[0929] Step 25:

[0930] The device will save your customization settings and apply them to future audio outputs.

[0931] Example 2

[0932] 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."

[0933] For users to prepare for going out efficiently and reliably, they need to check many factors. These include checking their appearance, preparing appropriate gear for the weather, managing their physical condition, checking for forgotten items, and providing advice that adapts to the user's emotions. Performing these tasks manually takes time and effort, hindering efficient preparation for going out. The objective of this invention is to comprehensively solve these problems with a single system.

[0934] 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.

[0935] In this invention, the server includes: an imaging means for imaging the user's body; an image analysis means for analyzing the image of the user captured by the imaging means and detecting stains, wrinkles, dust, and messy hair on the clothes; an advice generation means for generating appropriate advice for the user based on the detection results of the image analysis means; an audio output means for outputting the advice generated by the advice generation means as audio; an emotion recognition means for acquiring the user's voice and facial expression and recognizing their emotion; and an advice generation means for adjusting the content and tone of the advice based on the user's emotion recognized by the emotion recognition means. This enables the user to prepare to go out efficiently and comprehensively using a single system.

[0936] The "system" is an integrated device that combines multiple means to help users efficiently prepare for going out.

[0937] "Photographing means" refers to a device for photographing the user's body, and includes cameras and image capture devices.

[0938] The "image analysis means" is an algorithm or system for analyzing image data acquired by the imaging means and extracting specific information.

[0939] The "advice generation means" is a device or program for generating appropriate advice for the user based on the results of the image analysis means, the weather forecast linkage means, and the emotion recognition means.

[0940] The "audio output means" is a device for conveying the generated advice to the user by voice, and includes a speaker and a voice synthesis system.

[0941] An "emotion recognition means" is an algorithm or system that acquires the user's voice and facial expressions and determines the user's emotions based on them.

[0942] The "weather forecast linking means" is a device or program for acquiring weather forecast data based on the user's location information and generating advice based on that data.

[0943] "Temperature measurement means" refers to a device for measuring the user's temperature, and includes a thermometer and a sensor.

[0944] The "physical condition evaluation means" is a system for analyzing the measured body temperature data and evaluating the user's physical condition.

[0945] The "lost item confirmation means" is a device or program that allows the user to confirm whether or not they have the necessary items.

[0946] The present invention is a system for enabling a user to efficiently prepare for going out, and is realized by combining multiple pieces of hardware and software. Specific embodiments will be described below.

[0947] This system is mainly composed of a terminal and a server. The terminal is connected to input and output devices such as a camera, microphone, speaker, and thermometer. The server also functions as a processing device for executing various analysis and generation algorithms.

[0948] Hardware and software used

[0949] 1. Terminal

[0950] Camera: To capture the user's entire body. For example, a typical webcam or smartphone camera can be used.

[0951] Microphone: To capture the user's voice input, using the built-in microphone on your smartphone or laptop.

[0952] Speakers: For system sound output, using headphones or the device's built-in speakers.

[0953] Thermometer: Use a Bluetooth-connected thermometer.

[0954] 2. Server

[0955] Image analysis algorithm: The captured image data is analyzed using TensorFlow and PyTorch.

[0956] Emotion recognition algorithm: Recognizes user emotions using Microsoft Azure Emotion API, etc.

[0957] Weather forecast data: Obtain weather information using the OpenWeatherMap API.

[0958] Specific processing of the program

[0959] When a user starts the system, the device uses a camera to capture a full-body image of the user. A voice prompt is played saying, "Please turn around in front of the camera." As the user turns around, image data of the entire body is acquired. This data is sent to the server in real time.

[0960] An image analysis model using TensorFlow and PyTorch runs on the server and analyzes the captured image data. This detects dirt, wrinkles, dust, and messy hair on the clothes. Based on the analysis results, appropriate advice is generated and sent to the device as text data. For example, "There are wrinkles on the back. It would be a good idea to use a steam iron."

[0961] As a means of weather forecast integration, the server calls the OpenWeatherMap API based on the user's location information to obtain weather forecast data. Advice for going out based on the weather is generated and sent to the device. Example: "It's going to rain today, so you should bring an umbrella."

[0962] To measure body temperature, the device will issue a voice prompt saying, "Please measure your temperature." When the user measures their temperature using a Bluetooth-connected thermometer, the data is sent to the server, which evaluates their physical condition. For example, "Your current body temperature is 37.8 degrees. It's a little high, so we recommend you relax or drink a warm drink."

[0963] To recognize emotions, the device captures the user's voice and facial expressions and uses the Microsoft Azure Emotion API to recognize their emotions. The server then adjusts the tone and content of the advice based on this emotional information to generate the most appropriate advice. Example: "Why don't you try relaxing a bit?"

[0964] Prompt Sentence Examples

[0965] "I want to use this system to get ready to go out. Can you explain how the system works?"

[0966] "What are the steps to generate weather advice?"

[0967] Please explain with examples how to recognize users' emotions and give advice based on them.

[0968] With the above configuration, users can efficiently prepare before going out, ensuring a comfortable outing. In addition, by using emotion recognition, a system can be realized that also provides psychological support.

[0969] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0970] Step 1: Boot the system

[0971] The user starts the system. The terminal initializes devices such as the camera, microphone, speaker, and thermometer. The input is the user's startup operation, and the output is a notification that each device is ready. Specifically, the terminal checks the connection status of each device and verifies that it is operating normally.

[0972] Step 2: Photographing the user's entire body

[0973] The device uses a voice prompt to instruct the user to "turn around in front of the camera." The camera captures the user's position and movements as input and generates full-body image data as output. The user turns around in front of the camera, and the camera captures multiple images in succession. These images are temporarily stored on the device and immediately sent to the server.

[0974] Step 3: Analyze image data and generate advice

[0975] The image data received by the server is processed using an image analysis algorithm using TensorFlow or PyTorch. Image data of the entire body is sent to the server as input, and the output generates detection results for stains, wrinkles, dust, and messy hair on clothes. Specifically, the analysis algorithm extracts features from the image and performs recognition and classification using a trained model. Based on the results, appropriate advice is generated and sent to the device as text data.

[0976] Step 4: Obtaining weather forecast data and generating advice

[0977] The server retrieves weather forecast data from the OpenWeatherMap API based on the user's location information. Location information is provided as input, and weather forecast data and advice based on it are generated as output. Specifically, the server sends an API request based on the location information and receives weather forecast data. It then analyzes the data and generates appropriate advice (e.g., "Bring an umbrella") and sends it to the device.

[0978] Step 5: Temperature check and health assessment

[0979] The device issues a voice prompt saying "Please measure your temperature." The user measures their temperature using a Bluetooth-connected thermometer. The measurement result is sent to the device as input, and temperature data and a health assessment are generated as output. Specifically, the device receives the thermometer measurement data via Bluetooth and sends it to the server. The server analyzes the temperature data, evaluates whether it is within the normal range, and sends the result to the device.

[0980] Step 6: Emotion recognition and advice adjustment

[0981] The device captures the user's voice and facial expressions and analyzes them using an emotion recognition algorithm. Voice and image data are provided as input, and advice tailored to the user's emotions is generated as output. Specifically, the device collects voice and facial expression data and sends it to a server. The server analyzes it using an emotion recognition algorithm (for example, Microsoft Azure Emotion API) and adjusts the tone and content of the advice based on the results. As a result, advice tailored to the user is generated and sent to the device.

[0982] Step 7: Final output of the advice

[0983] The device will then verbally communicate to the user all the advice it has generated so far. Various analysis results and advice data are provided as input, and voice guidance is provided to the user as output. Specifically, it uses a speech synthesis engine (e.g., Google Text-to-Speech API) to convert text data into speech, which is then transmitted to the user through the speaker.

[0984] Through the above processing steps, the user can easily prepare to go out efficiently and effectively.

[0985] (Application example 2)

[0986] 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."

[0987] Conventional outing preparation systems require time and effort for users to check their appearance and belongings, and are unable to provide a wide range of support in a unified manner, such as advice based on weather and physical condition, or emotional support. This can lead to problems such as users feeling anxious before going out and needing time to get ready. The present invention aims to solve these problems and provide a system that allows users to prepare for going out more efficiently and comfortably.

[0988] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: an imaging means for capturing an image of the user's body; an image analysis means for analyzing the image of the user captured by the imaging means and detecting stains, wrinkles, dust, and messy hair on the user's clothes; an advice generation means for generating appropriate advice for the user based on the detection results of the image analysis means; an audio output means for outputting the advice generated by the advice generation means as audio; an accessory advice means for advising the user on appropriate accessory colors based on color information of the user's clothing analyzed by the image analysis means; and an emotion recognition means for acquiring the user's voice and facial expression, analyzing the user's emotions using emotion recognition means, and adjusting the content and tone of the advice based on the recognized emotions. This improves the efficiency of the user's preparations for going out and enables appropriate advice to be provided according to individual needs and emotions.

[0989] "Photographing means" refers to a device for photographing the user's body.

[0990] The "image analysis means" is a device or software that analyzes the image of the user captured by the image capture means and detects stains, wrinkles, dust, and messy hair on the clothes.

[0991] The "advice generating means" is a device or software for generating appropriate advice for the user based on the detection results of the image analyzing means.

[0992] The "audio output means" is a device or software for audibly outputting the advice generated by the advice generating means.

[0993] The "accessory advice means" is a device or software that advises on suitable accessory colors based on the color information of the user's clothing analyzed by the image analysis means.

[0994] "Emotion recognition means" refers to a device or software that acquires the user's voice and facial expressions and analyzes and recognizes their emotions.

[0995] The "weather forecast linking means" is a device or software that acquires weather forecast data based on the user's location information and generates advice for going out based on the weather forecast.

[0996] "Temperature measuring means" refers to a device for measuring the user's temperature.

[0997] The "physical condition evaluation means" is a device or software for evaluating the physical condition of the user based on the body temperature data measured by the body temperature measurement means.

[0998] The present invention is a system for helping users get ready to go out more efficiently, combining a photography unit, an image analysis unit, an advice generation unit, a voice output unit, an accessory advice unit, and an emotion recognition unit. This system can be applied to smart fitting rooms in apparel shops, in particular, to improve customer experience.

[0999] The main components of the system are:

[1000] 1. Photography Method:

[1001] When a user enters a fitting room, a camera installed in the fitting room automatically captures the user's entire body.

[1002] The captured image is sent to a server.

[1003] 2. Image analysis methods:

[1004] The server analyzes the received images using an image analysis algorithm (e.g., a model using TensorFlow).

[1005] It detects wrinkles and stains on clothes and messy hair and generates the necessary advice.

[1006] 3. Advice Generation Methods:

[1007] Based on the results obtained by the image analysis means, appropriate advice is automatically generated for the user.

[1008] For example: "There are wrinkles on the back. A steam iron would help."

[1009] 4. Audio output means:

[1010] The generated advice is communicated to the user via audio through a speaker in the fitting room.

[1011] Use a speech synthesis library such as Python's pyttsx3.

[1012] 5. Accessory advice:

[1013] Based on the color information of the user's clothing obtained through image analysis, the system advises on the appropriate color of accessories.

[1014] For example: "A silver necklace would go well with this outfit."

[1015] 6. Emotion recognition means:

[1016] It captures the user's facial expressions and voice and analyzes their emotions using an emotion recognition model.

[1017] If the user is anxious, they are given advice to help them relax.

[1018] For example: "Please relax and feel free to try things on."

[1019] 7. Weather forecast integration methods:

[1020] The server obtains weather forecast data based on the user's location information (using WeatherAPI, etc.).

[1021] Generate advice for going out based on weather forecasts.

[1022] For example: "It's raining outside, so I recommend a waterproof coat."

[1023] The specific hardware is a fitting room device equipped with a camera, speaker, and microphone. The software uses Python, OpenCV, TensorFlow, pyttsx3, etc. The fitting room camera captures the user's image, which is then sent to a server for analysis. Advice generated based on the analysis results is communicated to the user using audio output.

[1024] This system allows users to receive detailed advice when preparing to go out, enabling a stress-free shopping experience. It also has an emotion recognition function that can provide psychological support to users, improving customer satisfaction.

[1025] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1026] Step 1:

[1027] When a user enters a fitting room, the device uses a camera to take a full-body image of the user, which is then sent to the server as input for further processing.

[1028] Step 2:

[1029] The server analyzes the received full-body image using image analysis tools. Specifically, it uses image analysis models such as TensorFlow to detect dirt, wrinkles, dust, and messy hair on the clothes. The data obtained from this analysis becomes the input for the next process.

[1030] Step 3:

[1031] Based on the analysis results, the server uses the advice generation means to generate appropriate advice for the user. This advice generation includes the user's clothing status and detailed comments. The generated advice becomes the input for the next step.

[1032] Step 4:

[1033] The device communicates the generated advice to the user through a voice output means. Specifically, the advice is output as voice using a voice synthesis library such as Python's pyttsx3. The user receives this voice advice.

[1034] Step 5:

[1035] The server acquires color information of the user's clothing using the image analysis means, and advises the user on the appropriate accessory color using the accessory advice means. This advice is also conveyed to the user by the voice output means, and is output as advice to the user.

[1036] Step 6:

[1037] The user's facial expressions and voice are acquired by the device and analyzed by the emotion recognition means. Based on the analysis results, the server analyzes the user's emotions and generates advice on how to relax as needed. The advice generated by this emotion recognition is conveyed to the user by the voice output means.

[1038] Step 7:

[1039] The server uses the weather forecast linking means to acquire weather forecast data from the user's location information. Based on the acquired weather data, advice for going out is generated. This advice based on the weather forecast is also conveyed to the user by the voice output means.

[1040] 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.

[1041] 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.

[1042] 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.

[1043] [Third embodiment]

[1044] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1045] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1046] 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).

[1047] 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.

[1048] 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.

[1049] 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).

[1050] 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.

[1051] 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.

[1052] 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.

[1053] 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.

[1054] 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.

[1055] 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."

[1056] The present invention is a system for enabling a user to efficiently prepare for going out, and it combines a photographing means, an image analysis means, an advice generation means, a voice output means, a weather forecast linkage means, a body temperature measurement means, a physical condition evaluation means, a forgotten item confirmation means, and an accessory advice means. Specific embodiments of this system are described below.

[1057] Overall Overview

[1058] This system allows users to walk around in front of the camera before going out, and automatically checks their appearance and belongings, and provides advice based on the weather and their physical condition. Users simply follow voice instructions and are ready to go out.

[1059] An example of an appearance check

[1060] 1. Terminal

[1061] When the user stands in front of the camera, it automatically activates and takes a picture of the user, with voice prompts to walk around in a circle.

[1062] 2. Server

[1063] It receives the captured image data and uses an image analysis algorithm to detect dirt, wrinkles, dust, and messy hair on the clothes, then generates necessary advice based on the results and generates text data for voice output.

[1064] 3. Terminal

[1065] The generated advice is communicated to the user as audio.

[1066] For example: "There are wrinkles on the back. A steam iron would help."

[1067] Weather forecast advice implementation form

[1068] 1. Server

[1069] The system obtains the latest weather forecast data based on the user's location, and generates advice on whether they need a jacket or an umbrella based on the forecast.

[1070] 2. Terminal

[1071] The message is conveyed to the user as audio.

[1072] Example: "It's raining today, so you should bring an umbrella."

[1073] Temperature Measurement and Alert Implementation

[1074] 1. Terminal

[1075] The user is prompted by voice to take their temperature, and their temperature is measured by touching the temperature sensor.

[1076] 2. Server

[1077] Receives the measured body temperature data and evaluates whether it is within the normal range. If it is abnormal, it generates an alert and generates text data for voice output.

[1078] 3. Terminal

[1079] The content of the alert is announced to the user through audio.

[1080] For example: "Your current temperature is 37.8°C. It's a little high, so I recommend you relax or drink a warm drink."

[1081] Implementation of lost item check

[1082] 1. Terminal

[1083] Based on the loaded lost item list, it outputs a voice prompt to remind the user to check their belongings.

[1084] For example: "Did you bring your keys and wallet?"

[1085] 2. Users

[1086] You will receive a voice confirmation, which the system will analyze to determine if you are fully prepared.

[1087] For example: "Yes, I have it."

[1088] Accessory color advice implementation example

[1089] 1. Server

[1090] It analyzes the user's clothing color information and generates color advice for suitable accessories based on fashion rules.

[1091] 2. Terminal

[1092] The generated advice is communicated to the user as audio.

[1093] For example: "The color of accessories that goes well with today's outfit is silver."

[1094] Customization Settings Implementation Example

[1095] 1. Users

[1096] Customize your voice output settings to adjust the gender, tone, and phrasing of the voice.

[1097] 2. Terminal

[1098] The received customization settings will be saved and reflected from the next time onwards.

[1099] The above configuration allows the user to efficiently prepare before going out, realizing a system that allows for a comfortable outing.

[1100] The processing flow will be explained below.

[1101] Step 1:

[1102] The user stands in front of the camera and activates the system.

[1103] Step 2:

[1104] The device uses facial recognition technology to identify the user and then issues a voice prompt saying, "Take one lap."

[1105] Step 3:

[1106] The user walks around in front of the camera, capturing their entire body.

[1107] Step 4:

[1108] The device sends the captured data from the user's entire rotation to the server.

[1109] Step 5:

[1110] The server processes the received data based on image analysis algorithms to detect dirt, wrinkles, dust, and messy hair on the clothes.

[1111] Step 6:

[1112] Based on the results of image analysis, the server generates appropriate advice for the user as text data and sends it to the terminal for voice output.

[1113] Step 7:

[1114] The device will communicate the advice it receives to the user via voice.

[1115] For example: "There are wrinkles on the back. A steam iron would help."

[1116] Step 8:

[1117] The server retrieves weather forecast data based on the user's location information.

[1118] Step 9:

[1119] The server generates text data based on weather forecast data, giving advice on whether a jacket is needed or whether an umbrella should be carried, and transmits the text data to the terminal for voice output.

[1120] Step 10:

[1121] The device will then communicate the weather forecast advice received to the user via voice.

[1122] Example: "It's raining today, so you should bring an umbrella."

[1123] Step 11:

[1124] The device will output a voice prompt to the user to take their temperature.

[1125] For example: "Please take my temperature."

[1126] Step 12:

[1127] The user touches the temperature sensor to measure their temperature.

[1128] Step 13:

[1129] The device sends the measured body temperature data to the server.

[1130] Step 14:

[1131] The server analyzes the temperature data and determines whether it is within the normal range. If it is abnormal, it generates an alert and generates text data for voice output and sends it to the device.

[1132] Step 15:

[1133] The device will communicate any alerts received to the user via voice.

[1134] For example: "Your current temperature is 37.8°C. It's a little high, so I recommend you relax or drink a warm drink."

[1135] Step 16:

[1136] The device loads the registered lost item list and outputs a voice prompt to ask the user to confirm.

[1137] For example: "Did you bring your keys and wallet?"

[1138] Step 17:

[1139] The user responds with the confirmation result by voice.

[1140] For example: "Yes, I have it."

[1141] Step 18:

[1142] The device converts the received voice into text, confirms that the item has not been left behind, and notifies the user.

[1143] For example: "I made sure you didn't forget anything."

[1144] Step 19:

[1145] The server analyzes the color information of the user's clothing, generates suitable accessory colors as text data, and sends it to the terminal for voice output.

[1146] Step 20:

[1147] The device will then provide the user with audio color advice for the accessory it receives.

[1148] For example: "The color of accessories that goes well with today's outfit is silver."

[1149] Step 21:

[1150] Users can customize voice output settings and adjust the gender, impression, and phrasing of the voice.

[1151] Step 22:

[1152] The device will save your customization settings and apply them the next time.

[1153] Example 1

[1154] 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."

[1155] Previously, preparing to go out required users to individually check their appearance, the weather, their physical condition, and their belongings, which took a lot of time and effort. This often caused stress for users before going out, and was inefficient. There was also a need for a system that could centrally automate these check tasks.

[1156] 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.

[1157] In this invention, the server includes: an imaging means for capturing an image of the user's body; an image analysis means for analyzing the image of the user captured by the imaging means to detect stains, wrinkles, dust, and messy hair on the user's clothes; an advice generation means for generating appropriate advice for the user based on the detection results of the image analysis means; an audio output means for outputting the advice generated by the advice generation means as audio; a weather forecast linkage means for acquiring weather forecast data based on the user's location information and generating advice for the user when going out based on the acquired weather forecast; a temperature measurement means for outputting an audio prompt urging the user to measure their temperature and measuring the user's temperature; a physical condition evaluation means for evaluating the user's physical condition based on the measured temperature data and generating an alert if an abnormality is detected; a forgotten item confirmation means for outputting an audio prompt urging the user to check their belongings; and an accessory advice means for analyzing the color information of the user's clothing and generating color advice for appropriate accessories. This allows the user to efficiently prepare before going out and enjoy a comfortable outing.

[1158] "Photographing means" refers to equipment or devices for photographing the user's body.

[1159] "Image analysis means" refers to a technology or device that analyzes a photographed image of a user and detects stains, wrinkles, dust, and messy hair on the clothes.

[1160] The "advice generation means" is a technology or device for generating appropriate advice for the user based on the detection results obtained by the image analysis means.

[1161] The "audio output means" is a technique or device for outputting the advice generated by the advice generating means as audio.

[1162] The "weather forecast linking means" is a technology or device for acquiring weather forecast data based on the user's location information and generating advice for the user when going out based on the acquired weather forecast.

[1163] "Temperature measurement means" means any technology or device for measuring a user's temperature.

[1164] The "physical condition evaluation means" is a technology or device for evaluating the user's physical condition based on measured body temperature data and generating an alert if any abnormalities are detected.

[1165] A "lost property verification means" is a technology or device that outputs a voice prompt to prompt the user to verify their belongings.

[1166] The "accessory advice means" is a technology or device for analyzing the user's clothing color information and generating color advice for suitable accessories.

[1167] A "user" is a person who uses this system to prepare for going out.

[1168] The present invention is a system for enabling users to efficiently prepare for going out. By combining a photographing means, an image analysis means, a means for generating advice, a means for outputting audio, a means for linking with weather forecasts, a means for measuring body temperature, a means for evaluating physical condition, a means for checking for lost items, and a means for providing advice on accessories, the system allows users to centrally automate their preparations before going out. Specific embodiments of the present invention are described below.

[1169] System Hardware and Software

[1170] Hardware

[1171] Photography method: Uses the camera on a smartphone or tablet to capture a photo of the user's body.

[1172] Body temperature measurement method: A smartwatch or dedicated body temperature sensor is used to measure the user's body temperature.

[1173] software

[1174] Image analysis method: The OpenCV library is used for image analysis, which detects dirt, wrinkles, dust, and messy hair from captured images.

[1175] Advice generation method: The advice is generated using a script written in "Python" or "JavaScript."

[1176] Voice output method: "Google Text-to-Speech" and "Amazon Polly" are used for voice output, which convert text data into voice.

[1177] Weather forecast integration method: The OpenWeatherMap API is used to obtain weather forecast data, which allows users to obtain weather forecasts based on their location.

[1178] Physical condition evaluation method: An analysis system linked to "Raspberry Pi" is used to evaluate body temperature data, which determines whether the body temperature is within the normal range.

[1179] How to check for lost items: To check for lost items, a voice prompt is output through Google Assistant, prompting the user to check for their belongings.

[1180] Accessory advice method: IBM Watson Visual Recognition is used to analyze and advise on clothing colors, suggesting accessory colors that match the user's outfit.

[1181] Example of operation

[1182] 1. Grooming check

[1183] When a user stands in front of the camera, it automatically starts up and takes a picture of the user.

[1184] The device will play a voice prompt saying "Take a turn."

[1185] The server uses OpenCV's image analysis algorithm to detect stains and wrinkles on the clothes.

[1186] The server generates the advice "There are wrinkles on the back. You may want to use a steam iron."

[1187] The device uses Google Text-to-Speech to convert advice into audio and convey it to the user.

[1188] 2. Weather Forecast Advice

[1189] The server uses the OpenWeatherMap API to get the latest weather forecast.

[1190] The server generates the advice "It's raining today, so please take an umbrella."

[1191] The device uses Amazon Polly to convert advice into voice and convey it to the user.

[1192] 3. Temperature measurement and alerts

[1193] The device will play a voice prompt saying, "Please take your temperature."

[1194] The user measures their temperature by touching the temperature sensor on the smartwatch.

[1195] The server receives the body temperature data and analyzes it using a Raspberry Pi.

[1196] The server generates an alert saying, "Your current temperature is 37.8 degrees. It's a little high, so we recommend you relax or drink a warm drink."

[1197] The device converts the alert into audio and relays it to the user.

[1198] 4. Check for lost items

[1199] The device will play a voice prompt asking, "Did you bring your keys and wallet?"

[1200] The user responds by voice, "Yes, I have it."

[1201] The device uses Azure Speech to Text to convert speech into text and analyze it.

[1202] 5. Accessory advice

[1203] The server uses IBM Watson Visual Recognition to analyze clothing colors.

[1204] The server generates advice such as "The color of the accessory that matches your outfit today is silver."

[1205] The device uses Amazon Alexa to convert advice into voice and convey it to the user.

[1206] According to the above-mentioned specific examples, the system of the present invention makes it possible for the user to efficiently prepare for going out and reduces stress.

[1207] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1208] Step 1: The user stands in front of the camera

[1209] Input: The user stands in front of the camera.

[1210] Action: The device detects the user's presence using a sensor.

[1211] Output: The camera starts automatically.

[1212] What it does: Your smartphone or tablet's camera app will automatically launch and you'll hear a voice prompt saying, "Take a full turn."

[1213] Step 2: The device takes a photo of the user

[1214] Input: The user moves around in a circle.

[1215] Processing: The device takes continuous shots and records the footage.

[1216] Output: Video data is generated.

[1217] Specific operation: The smartphone takes continuous shots and sends the video data to the server.

[1218] Step 3: The server performs image analysis

[1219] Input: Video data sent from the device.

[1220] Processing: The server uses the OpenCV library to analyze the images and detect stains, wrinkles, dust, and messy hair on the clothes.

[1221] Output: The detection results are generated.

[1222] Specific operation: The server analyzes the video data frame by frame and identifies problem areas.

[1223] Step 4: Server generates advice

[1224] Input: Detection results from image analysis.

[1225] Processing: The server generates advice for the user based on the analysis results.

[1226] Output: Text data of advice is generated.

[1227] Specific behavior: If dirt is detected, generate advice such as "There is dirt on the back. It may be a good idea to use a brush."

[1228] Step 5: Your device will speak the advice

[1229] Input: Text data of advice sent from the server.

[1230] Processing: Your device uses Google Text-to-Speech to convert the text data into audio.

[1231] Output: A spoken advice is generated.

[1232] Specific behavior: The smartphone conveys the generated voice advice to the user.

[1233] Step 6: Server retrieves weather forecast data

[1234] Input: User's location.

[1235] Process: The server retrieves weather forecast data using the OpenWeatherMap API.

[1236] Output: Weather forecast data is generated.

[1237] Specific operation: The server retrieves the latest weather forecast based on the location information.

[1238] Step 7: Server generates weather-based advice

[1239] Input: Weather forecast data.

[1240] Processing: The server generates advice for going out based on the weather forecast data.

[1241] Output: Weather-based advice text data is generated.

[1242] Specific behavior: If rain is forecast, generate advice such as "It's going to rain today, so please bring an umbrella."

[1243] Step 8: Your device will speak weather advice

[1244] Input: Weather advice text data sent from the server.

[1245] Processing: The device uses Amazon Polly to convert the text data into speech.

[1246] Output: A spoken advice is generated.

[1247] Specific behavior: The smartphone conveys the generated voice advice to the user.

[1248] Step 9: The device prompts you to take your temperature

[1249] Input: The act of the user hearing a voice prompt.

[1250] Action: The device outputs a voice prompt saying "Please take your temperature."

[1251] Output: The user begins taking their temperature.

[1252] What it does: The smartwatch will play a voice prompt to remind the user to take their temperature.

[1253] Step 10: User takes temperature

[1254] Input: Touching the temperature sensor.

[1255] Processing: The temperature sensor measures the user's temperature and generates the data.

[1256] Output: Temperature data is generated.

[1257] What happens: The user touches the sensor on the smartwatch to measure their body temperature.

[1258] Step 11: Server evaluates temperature data

[1259] Input: Temperature measurement data.

[1260] Processing: The server analyzes the received temperature data and evaluates whether it is within the normal range.

[1261] Output: Text data of health alert is generated.

[1262] What it does: The server analyzes data from the temperature sensor connected to the Raspberry Pi and generates alerts as needed.

[1263] Step 12: Your device will output a health alert

[1264] Input: Text data of health alert sent from the server.

[1265] Action: The device uses iOS VoiceOver to convert the alert into audio.

[1266] Output: An audio alert is generated.

[1267] What it does: The smartphone plays the generated audio alert to the user.

[1268] Step 13: The device will output a lost item confirmation prompt

[1269] Input: System loaded lost item checklist.

[1270] Action: Your device uses Google Assistant to speak a prompt to check your belongings.

[1271] Output: A voice prompt is generated.

[1272] What happens: Your smartphone will play a voice prompt saying, "Did you bring your keys and wallet?"

[1273] Step 14: User responds with confirmation by voice

[1274] Input: User's voice input.

[1275] Processing: The device converts the user's voice into text using Azure Speech to Text, which is then analyzed by the system.

[1276] Output: Text data of the belongings check result is generated.

[1277] Specific operation: The user replies "Yes, I have it," and the device converts the speech into text and analyzes it.

[1278] Step 15: Check that your device is ready

[1279] Input: Text data of the inventory check results.

[1280] Processing: The device checks the lost item checklist against the user's voice response to determine if they are ready.

[1281] Output: A text message is generated to notify you that the device is ready.

[1282] What it does: The device checks the checklist and the user's responses, then notifies them that all items are in order.

[1283] Step 16: Server analyzes clothing color

[1284] Input: User's clothing image data.

[1285] Processing: The server analyzes the clothing color using IBM Watson Visual Recognition.

[1286] Output: Color analysis results are generated.

[1287] Specific operation: The server analyzes the user's clothing image and obtains color information.

[1288] Step 17: Server generates color advice for accessories

[1289] Input: Color analysis results.

[1290] Processing: The server generates color advice for suitable accessories based on the analysis results.

[1291] Output: Text data of accessory advice is generated.

[1292] Specific behavior: Generates advice such as "The color of accessories that goes well with today's outfit is silver."

[1293] Step 18: Your device will speak accessory advice

[1294] Input: Text data of accessory advice sent from the server.

[1295] Processing: The device uses Amazon Alexa to convert the advice into voice.

[1296] Output: A spoken advice is generated.

[1297] Specific operation: The smart speaker outputs advice aloud and conveys it to the user.

[1298] Through the above steps, the system of the present invention enables the user to efficiently prepare for going out and ensure a comfortable outing.

[1299] (Application example 1)

[1300] 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."

[1301] In the past, factory workers' work preparation required individual checking of equipment, temperature checks, and checking for forgotten items, which was inefficient and required a great deal of time and effort. Furthermore, there was a lack of appropriate advice regarding weather changes, which led to a decline in worker safety and efficiency. To solve these issues, a system was needed that centralized the worker preparation process and made it possible to do so quickly and efficiently.

[1302] 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.

[1303] In this invention, the server includes a photographing means for photographing the user's body, an image analysis means for analyzing the image of the user photographed by the photographing means to detect stains, wrinkles, dust, and messy hair on the clothes, and an advice generation means for generating appropriate advice for the user based on the detection results of the image analysis means. This makes it possible to streamline work preparation for factory workers and to centrally manage equipment checks, temperature measurements, and forgotten item checks.

[1304] "Photographing means" is a mechanism for photographing the user's body and equipment, and is a device for obtaining the user's appearance as digital data.

[1305] The "image analysis means" is a mechanism that processes and analyzes the image data acquired by the photographing means and detects specific features (for example, dirt, wrinkles, dust, or messy hair).

[1306] The "advice generator" is a mechanism or algorithm for generating appropriate advice for a user based on the image analysis means and other data inputs.

[1307] The "audio output means" is a device or software for conveying the advice generated by the advice generating means to the user in audio form.

[1308] "Temperature measurement means" means a sensor or device for measuring a user's temperature and providing the data necessary to assess the user's health condition.

[1309] The "physical condition assessment means" is an algorithm or mechanism that assesses the user's health condition based on the body temperature data obtained by the body temperature measurement means and generates appropriate advice or warnings.

[1310] The "weather forecast linking means" is an information processing system that acquires current weather forecast data and generates appropriate advice for the user when going out or working.

[1311] The "lost item confirmation means" is a system that checks whether all important belongings are present based on the user's belongings list and notifies the user of the results.

[1312] The present invention is a system for improving the efficiency of work preparation by factory workers. Each means and its processing will be described in detail below.

[1313] Photography and image analysis methods

[1314] A camera that captures images of the user's body and equipment is connected to the server. The camera automatically activates when the worker stands in front of the camera, capturing images of the worker in all 360-degree directions. This captured image data is immediately sent to the image analysis means, which uses an open-source image processing library (e.g., OpenCV) to detect dirt, wrinkles, dust, and messy hair on the equipment.

[1315] Advice generation means and voice output means

[1316] Based on the results obtained by the image analysis means, the advice generation means of the server generates appropriate advice for the worker. The generated advice is communicated to the worker in real time by the voice output means. A library that converts text to voice (e.g., pyttsx3) is used for the voice output.

[1317] For example, the advice "Dirt has been detected on your equipment. Please clean it" is output as voice.

[1318] Temperature measurement and health assessment methods

[1319] The system is equipped with a sensor for measuring the worker's body temperature. The body temperature measurement means measures the worker's body temperature when the worker touches the sensor and sends the data to a server. The physical condition evaluation means evaluates the worker's physical condition based on this body temperature data and generates an alert if there is an abnormality. The worker is also notified of this alert by voice.

[1320] For example, advice such as "Your body temperature is high. Don't push yourself and take care of your health" is output as audio.

[1321] Weather forecast linkage method

[1322] The server retrieves current weather forecast data via an Internet connection and generates advice based on the worker's working environment. For this purpose, a weather forecast API is used. If the weather is bad (e.g., rainy), the server will give the worker appropriate warnings.

[1323] For example, advice such as "Rain is expected today, so please wear appropriate waterproof gear" may be output via voice.

[1324] How to check for lost items

[1325] A list of important items that the worker should have is loaded onto the server, and the lost item confirmation means prompts the worker by voice to check the items he or she has brought with him or her based on this list.

[1326] For example, a question such as "Did you bring your helmet and gloves?" is output by voice, and the worker confirms this.

[1327] Examples of prompt statements

[1328] By inputting the following prompt sentence into the generative AI model, appropriate advice can be generated.

[1329] "Get data from a weather forecast API and generate weather-based advice. Data includes conditions like sunny, rainy, snowy, cloudy, etc. Generate appropriate voice prompts for each."

[1330] Based on this prompt, the system can provide appropriate advice to workers in real time, helping them prepare for work efficiently and safely.

[1331] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1332] Step 1:

[1333] When a user stands in front of the camera, the server automatically activates the camera. The camera captures a 360-degree image of the user's entire body. The image data obtained as input is then sent to the next step.

[1334] Step 2:

[1335] The server sends the captured image data to the image analysis means, which uses an image processing library such as OpenCV to detect features such as dirt, wrinkles, dust, and messy hair from the input image data. The analysis results are sent to the advice generation means.

[1336] Step 3:

[1337] The server generates appropriate advice through the advice generating means based on the image analysis results. For example, if dirt is detected, the server generates advice such as "Dirt has been detected on the equipment. Please clean it." The generated advice is sent to the voice output means.

[1338] Step 4:

[1339] The server notifies the generated advice to the user by voice using the voice output means, thereby providing the user with information about their own equipment and physical condition.

[1340] Step 5:

[1341] When the user touches the body temperature sensor, the terminal's body temperature measurement means measures the user's body temperature and sends the data to the server. The body temperature data obtained as input is then sent to the physical condition evaluation means.

[1342] Step 6:

[1343] The server processes the body temperature measurement data using a physical condition evaluation means to evaluate the user's physical condition. If a temperature above the normal range is detected, an alert is generated stating, "Your body temperature is high. Please do not overexert yourself and take care of your health." This alert is sent to a voice output means.

[1344] Step 7:

[1345] The server uses a weather forecast API to obtain current weather data. Based on the data obtained from the API, it generates advice appropriate to the weather. For example, it generates advice such as "Rain is expected today, so please wear appropriate waterproof gear." The generated advice is sent to the audio output means.

[1346] Step 8:

[1347] The server uses the lost item confirmation means to prompt the user to check their belongings based on the list of important belongings, generating questions such as "Did you bring your helmet and gloves?" and notifying the user through the voice output means.

[1348] Step 9:

[1349] Users can respond to voice prompts to check their belongings and take necessary actions, and the system will analyze their responses and provide appropriate feedback.

[1350] 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.

[1351] The present invention is a system for enabling a user to efficiently prepare for going out, and combines a photographing means, an image analysis means, an advice generation means, a voice output means, a weather forecast linkage means, a body temperature measurement means, a physical condition evaluation means, a forgotten item confirmation means, an accessory advice means, and an emotion recognition means. Specific embodiments of this system are described below.

[1352] Overall Overview

[1353] This system allows the user to walk around in front of the camera before going out, and automatically checks their appearance and belongings, and provides advice based on the weather and their physical condition. It also recognizes the user's emotions and provides adaptive advice. The user simply follows voice instructions and is ready to go out.

[1354] An example of an appearance check

[1355] 1. The user stands in front of the camera and activates the system. The device uses facial recognition technology to identify the user and issues a voice prompt saying, "Turn around once." The user turns around in front of the camera, capturing a full-body image. The device then sends the captured image data to the server.

[1356] 2. The server processes the received data using an image analysis algorithm to detect dirt, wrinkles, dust, and messy hair on the clothes. Based on the detection results, it generates appropriate advice as text data and sends it to the device for voice output.

[1357] 3. The device will then verbally communicate the generated advice to the user.

[1358] For example: "There are wrinkles on the back. A steam iron would help."

[1359] Weather forecast advice implementation form

[1360] 1. The server obtains weather forecast data based on the user's location information, and generates advice based on the forecast, such as whether or not to bring a jacket or an umbrella. The generated advice is sent to the device as text data.

[1361] 2. The device will provide voice weather forecast advice to the user.

[1362] Example: "It's raining today, so you should bring an umbrella."

[1363] Temperature Measurement and Alert Implementation

[1364] 1. The device outputs a voice prompt to the user to measure their temperature.

[1365] For example: "Please take my temperature."

[1366] 2. The user touches the temperature sensor to measure their temperature, and the device sends the measured temperature data to the server.

[1367] 3. The server analyzes the temperature data and evaluates whether it is within the normal range. If it is abnormal, it generates an alert and sends text data to the device for voice output.

[1368] 4. The device will audibly communicate the alert to the user.

[1369] For example: "Your current temperature is 37.8°C. It's a little high, so I recommend you relax or drink a warm drink."

[1370] Implementation of lost item check

[1371] 1. The device outputs a voice prompt to prompt the user to check their belongings based on the lost items list.

[1372] For example: "Did you bring your keys and wallet?"

[1373] 2. The user responds with the confirmation result by voice.

[1374] For example: "Yes, I have it."

[1375] 3. The device converts the received voice into text, confirms that the item has not been left behind, and notifies the user.

[1376] For example: "I made sure you didn't forget anything."

[1377] Accessory color advice implementation example

[1378] 1. The server analyzes the color information of the user's clothing and generates text data on suitable accessory colors. The generated advice is sent to the device.

[1379] 2. The device will provide the user with audio advice on the color of the accessory.

[1380] For example: "The color of accessories that goes well with today's outfit is silver."

[1381] Emotion Recognition Embodiment

[1382] 1. The device captures the user's voice and facial expressions and analyzes the user's emotions using emotion recognition algorithms. Emotions such as stress, satisfaction, dissatisfaction, and tension are recognized.

[1383] 2. The server adjusts the content and tone of the advice based on the user's emotion recognized by the emotion recognition means. For example, if the user is feeling stressed, the server provides advice to relax and slows down the tone and speed of the voice.

[1384] 3. The device will then provide tailored advice to the user via voice.

[1385] For example: "Why don't you relax a bit?"

[1386] Customization Settings Implementation Example

[1387] 1. The user customizes the voice output settings in the system settings screen, including the gender, impression, and phrasing of the voice.

[1388] 2. The device will save your customization settings and apply them to future audio outputs.

[1389] With the above configuration, users can efficiently prepare before going out, allowing them to go out comfortably, and a system can be realized that also provides psychological support by using emotion recognition.

[1390] The processing flow will be explained below.

[1391] Step 1:

[1392] The user stands in front of the camera and activates the system.

[1393] Step 2:

[1394] The device uses facial recognition technology to identify the user and then issues a voice prompt saying, "Take one lap."

[1395] Step 3:

[1396] The user walks around in front of the camera, capturing their entire body.

[1397] Step 4:

[1398] The device sends the user's photo data to the server.

[1399] Step 5:

[1400] The server uses image analysis algorithms to detect dirt, wrinkles, dust, and messy hair on the clothes.

[1401] Step 6:

[1402] Based on the results of the image analysis, the server generates appropriate advice as text data and sends it to the terminal for voice output.

[1403] Step 7:

[1404] The device will then give the generated advice to the user via voice, for example, "There are wrinkles on your back. You may want to use a steam iron."

[1405] Step 8:

[1406] The server retrieves weather forecast data based on the user's location information.

[1407] Step 9:

[1408] The server generates weather-appropriate advice based on weather forecast data and transmits it to the terminal as text data.

[1409] Step 10:

[1410] The device will then give you weather forecast advice by voice, for example, "It's going to rain today, so you should bring an umbrella."

[1411] Step 11:

[1412] The device will output a voice prompt to the user to take their temperature. For example, "Please take your temperature."

[1413] Step 12:

[1414] The user touches the temperature sensor to measure their temperature.

[1415] Step 13:

[1416] The device sends the measured body temperature data to the server.

[1417] Step 14:

[1418] The server analyzes the temperature data and evaluates whether it is within the normal range. If there is an abnormality, an alert is generated and text data is sent to the device for voice output.

[1419] Step 15:

[1420] The device will then verbally announce the alert to the user, for example, "Your current body temperature is 37.8°C. It's a little high, so we recommend you relax or drink a warm drink."

[1421] Step 16:

[1422] The device will then output a voice prompt based on the list of lost items to remind the user to check their belongings, for example, "Did you bring your keys and wallet?"

[1423] Step 17:

[1424] The user responds with a voice confirmation, for example, "Yes, I have it."

[1425] Step 18:

[1426] The device converts the received voice into text, confirms that the item has not been left behind, and notifies the user.

[1427] Step 19:

[1428] The server analyzes the color information of the user's clothing, generates suitable accessory colors as text data, and sends it to the terminal.

[1429] Step 20:

[1430] The device will give the user audio advice on the color of the accessories, for example, "The color of the accessories that matches your outfit today is silver."

[1431] Step 21:

[1432] The device captures the user's voice and facial expressions, and analyzes the user's emotions using emotion recognition algorithms to recognize emotions such as stress, satisfaction, dissatisfaction, and tension.

[1433] Step 22:

[1434] The server adjusts the content and tone of the advice based on the user's emotion recognized by the emotion recognition means. For example, if the user is feeling stressed, the server provides advice to relax and slows down the tone and speed of the voice.

[1435] Step 23:

[1436] The device will then give tailored advice to the user, such as "Why don't you try to relax a bit?"

[1437] Step 24:

[1438] Users can customize voice output settings in the system settings screen, including voice gender, impression, and phrasing.

[1439] Step 25:

[1440] The device will save your customization settings and apply them to future audio outputs.

[1441] Example 2

[1442] 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."

[1443] For users to prepare for going out efficiently and reliably, they need to check many factors. These include checking their appearance, preparing appropriate gear for the weather, managing their physical condition, checking for forgotten items, and providing advice that adapts to the user's emotions. Performing these tasks manually takes time and effort, hindering efficient preparation for going out. The objective of this invention is to comprehensively solve these problems with a single system.

[1444] 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.

[1445] In this invention, the server includes: an imaging means for imaging the user's body; an image analysis means for analyzing the image of the user captured by the imaging means and detecting stains, wrinkles, dust, and messy hair on the clothes; an advice generation means for generating appropriate advice for the user based on the detection results of the image analysis means; an audio output means for outputting the advice generated by the advice generation means as audio; an emotion recognition means for acquiring the user's voice and facial expression and recognizing their emotion; and an advice generation means for adjusting the content and tone of the advice based on the user's emotion recognized by the emotion recognition means. This enables the user to prepare to go out efficiently and comprehensively using a single system.

[1446] The "system" is an integrated device that combines multiple means to help users efficiently prepare for going out.

[1447] "Photographing means" refers to a device for photographing the user's body, and includes cameras and image capture devices.

[1448] The "image analysis means" is an algorithm or system for analyzing image data acquired by the imaging means and extracting specific information.

[1449] The "advice generation means" is a device or program for generating appropriate advice for the user based on the results of the image analysis means, the weather forecast linkage means, and the emotion recognition means.

[1450] The "audio output means" is a device for conveying the generated advice to the user by voice, and includes a speaker and a voice synthesis system.

[1451] An "emotion recognition means" is an algorithm or system that acquires the user's voice and facial expressions and determines the user's emotions based on them.

[1452] The "weather forecast linking means" is a device or program for acquiring weather forecast data based on the user's location information and generating advice based on that data.

[1453] "Temperature measurement means" refers to a device for measuring the user's temperature, and includes a thermometer and a sensor.

[1454] The "physical condition evaluation means" is a system for analyzing the measured body temperature data and evaluating the user's physical condition.

[1455] The "lost item confirmation means" is a device or program that allows the user to confirm whether or not they have the necessary items.

[1456] The present invention is a system for enabling a user to efficiently prepare for going out, and is realized by combining multiple pieces of hardware and software. Specific embodiments will be described below.

[1457] This system is mainly composed of a terminal and a server. The terminal is connected to input and output devices such as a camera, microphone, speaker, and thermometer. The server also functions as a processing device for executing various analysis and generation algorithms.

[1458] Hardware and software used

[1459] 1. Terminal

[1460] Camera: To capture the user's entire body. For example, a typical webcam or smartphone camera can be used.

[1461] Microphone: To capture the user's voice input, using the built-in microphone on your smartphone or laptop.

[1462] Speakers: For system sound output, using headphones or the device's built-in speakers.

[1463] Thermometer: Use a Bluetooth-connected thermometer.

[1464] 2. Server

[1465] Image analysis algorithm: The captured image data is analyzed using TensorFlow and PyTorch.

[1466] Emotion recognition algorithm: Recognizes user emotions using Microsoft Azure Emotion API, etc.

[1467] Weather forecast data: Obtain weather information using the OpenWeatherMap API.

[1468] Specific processing of the program

[1469] When a user starts the system, the device uses a camera to capture a full-body image of the user. A voice prompt is played saying, "Please turn around in front of the camera." As the user turns around, image data of the entire body is acquired. This data is sent to the server in real time.

[1470] An image analysis model using TensorFlow and PyTorch runs on the server and analyzes the captured image data. This detects dirt, wrinkles, dust, and messy hair on the clothes. Based on the analysis results, appropriate advice is generated and sent to the device as text data. For example, "There are wrinkles on the back. It would be a good idea to use a steam iron."

[1471] As a means of weather forecast integration, the server calls the OpenWeatherMap API based on the user's location information to obtain weather forecast data. Advice for going out based on the weather is generated and sent to the device. Example: "It's going to rain today, so you should bring an umbrella."

[1472] To measure body temperature, the device will issue a voice prompt saying, "Please measure your temperature." When the user measures their temperature using a Bluetooth-connected thermometer, the data is sent to the server, which evaluates their physical condition. For example, "Your current body temperature is 37.8 degrees. It's a little high, so we recommend you relax or drink a warm drink."

[1473] To recognize emotions, the device captures the user's voice and facial expressions and uses the Microsoft Azure Emotion API to recognize their emotions. The server then adjusts the tone and content of the advice based on this emotional information to generate the most appropriate advice. Example: "Why don't you try relaxing a bit?"

[1474] Prompt Sentence Examples

[1475] "I want to use this system to get ready to go out. Can you explain how the system works?"

[1476] "What are the steps to generate weather advice?"

[1477] Please explain with examples how to recognize users' emotions and give advice based on them.

[1478] With the above configuration, users can efficiently prepare before going out, ensuring a comfortable outing. In addition, by using emotion recognition, a system can be realized that also provides psychological support.

[1479] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1480] Step 1: Boot the system

[1481] The user starts the system. The terminal initializes devices such as the camera, microphone, speaker, and thermometer. The input is the user's startup operation, and the output is a notification that each device is ready. Specifically, the terminal checks the connection status of each device and verifies that it is operating normally.

[1482] Step 2: Photographing the user's entire body

[1483] The device uses a voice prompt to instruct the user to "turn around in front of the camera." The camera captures the user's position and movements as input and generates full-body image data as output. The user turns around in front of the camera, and the camera captures multiple images in succession. These images are temporarily stored on the device and immediately sent to the server.

[1484] Step 3: Analyze image data and generate advice

[1485] The image data received by the server is processed using an image analysis algorithm using TensorFlow or PyTorch. Image data of the entire body is sent to the server as input, and the output generates detection results for stains, wrinkles, dust, and messy hair on clothes. Specifically, the analysis algorithm extracts features from the image and performs recognition and classification using a trained model. Based on the results, appropriate advice is generated and sent to the device as text data.

[1486] Step 4: Obtaining weather forecast data and generating advice

[1487] The server retrieves weather forecast data from the OpenWeatherMap API based on the user's location information. Location information is provided as input, and weather forecast data and advice based on it are generated as output. Specifically, the server sends an API request based on the location information and receives weather forecast data. It then analyzes the data and generates appropriate advice (e.g., "Bring an umbrella") and sends it to the device.

[1488] Step 5: Temperature check and health assessment

[1489] The device issues a voice prompt saying "Please measure your temperature." The user measures their temperature using a Bluetooth-connected thermometer. The measurement result is sent to the device as input, and temperature data and a health assessment are generated as output. Specifically, the device receives the thermometer measurement data via Bluetooth and sends it to the server. The server analyzes the temperature data, evaluates whether it is within the normal range, and sends the result to the device.

[1490] Step 6: Emotion recognition and advice adjustment

[1491] The device captures the user's voice and facial expressions and analyzes them using an emotion recognition algorithm. Voice and image data are provided as input, and advice tailored to the user's emotions is generated as output. Specifically, the device collects voice and facial expression data and sends it to a server. The server analyzes it using an emotion recognition algorithm (for example, Microsoft Azure Emotion API) and adjusts the tone and content of the advice based on the results. As a result, advice tailored to the user is generated and sent to the device.

[1492] Step 7: Final output of the advice

[1493] The device will then verbally communicate to the user all the advice it has generated so far. Various analysis results and advice data are provided as input, and voice guidance is provided to the user as output. Specifically, it uses a speech synthesis engine (e.g., Google Text-to-Speech API) to convert text data into speech, which is then transmitted to the user through the speaker.

[1494] Through the above processing steps, the user can easily prepare to go out efficiently and effectively.

[1495] (Application example 2)

[1496] 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."

[1497] Conventional outing preparation systems require time and effort for users to check their appearance and belongings, and are unable to provide a wide range of support in a unified manner, such as advice based on weather and physical condition, or emotional support. This can lead to problems such as users feeling anxious before going out and needing time to get ready. The present invention aims to solve these problems and provide a system that allows users to prepare for going out more efficiently and comfortably.

[1498] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: an imaging means for capturing an image of the user's body; an image analysis means for analyzing the image of the user captured by the imaging means and detecting stains, wrinkles, dust, and messy hair on the user's clothes; an advice generation means for generating appropriate advice for the user based on the detection results of the image analysis means; an audio output means for outputting the advice generated by the advice generation means as audio; an accessory advice means for advising the user on appropriate accessory colors based on color information of the user's clothing analyzed by the image analysis means; and an emotion recognition means for acquiring the user's voice and facial expression, analyzing the user's emotions using emotion recognition means, and adjusting the content and tone of the advice based on the recognized emotions. This improves the efficiency of the user's preparations for going out and enables appropriate advice to be provided according to individual needs and emotions.

[1499] "Photographing means" refers to a device for photographing the user's body.

[1500] The "image analysis means" is a device or software that analyzes the image of the user captured by the image capture means and detects stains, wrinkles, dust, and messy hair on the clothes.

[1501] The "advice generating means" is a device or software for generating appropriate advice for the user based on the detection results of the image analyzing means.

[1502] The "audio output means" is a device or software for audibly outputting the advice generated by the advice generating means.

[1503] The "accessory advice means" is a device or software that advises on suitable accessory colors based on the color information of the user's clothing analyzed by the image analysis means.

[1504] "Emotion recognition means" refers to a device or software that acquires the user's voice and facial expressions and analyzes and recognizes their emotions.

[1505] The "weather forecast linking means" is a device or software that acquires weather forecast data based on the user's location information and generates advice for going out based on the weather forecast.

[1506] "Temperature measuring means" refers to a device for measuring the user's temperature.

[1507] The "physical condition evaluation means" is a device or software for evaluating the physical condition of the user based on the body temperature data measured by the body temperature measurement means.

[1508] The present invention is a system for helping users get ready to go out more efficiently, combining a photography unit, an image analysis unit, an advice generation unit, a voice output unit, an accessory advice unit, and an emotion recognition unit. This system can be applied to smart fitting rooms in apparel shops, in particular, to improve customer experience.

[1509] The main components of the system are:

[1510] 1. Photography Method:

[1511] When a user enters a fitting room, a camera installed in the fitting room automatically captures the user's entire body.

[1512] The captured image is sent to a server.

[1513] 2. Image analysis methods:

[1514] The server analyzes the received images using an image analysis algorithm (e.g., a model using TensorFlow).

[1515] It detects wrinkles and stains on clothes and messy hair and generates the necessary advice.

[1516] 3. Advice Generation Methods:

[1517] Based on the results obtained by the image analysis means, appropriate advice is automatically generated for the user.

[1518] For example: "There are wrinkles on the back. A steam iron would help."

[1519] 4. Audio output means:

[1520] The generated advice is communicated to the user via audio through a speaker in the fitting room.

[1521] Use a speech synthesis library such as Python's pyttsx3.

[1522] 5. Accessory advice:

[1523] Based on the color information of the user's clothing obtained through image analysis, the system advises on the appropriate color of accessories.

[1524] For example: "A silver necklace would go well with this outfit."

[1525] 6. Emotion recognition means:

[1526] It captures the user's facial expressions and voice and analyzes their emotions using an emotion recognition model.

[1527] If the user is anxious, they are given advice to help them relax.

[1528] For example: "Please relax and feel free to try things on."

[1529] 7. Weather forecast integration methods:

[1530] The server obtains weather forecast data based on the user's location information (using WeatherAPI, etc.).

[1531] Generate advice for going out based on weather forecasts.

[1532] For example: "It's raining outside, so I recommend a waterproof coat."

[1533] The specific hardware is a fitting room device equipped with a camera, speaker, and microphone. The software uses Python, OpenCV, TensorFlow, pyttsx3, etc. The fitting room camera captures the user's image, which is then sent to a server for analysis. Advice generated based on the analysis results is communicated to the user using audio output.

[1534] This system allows users to receive detailed advice when preparing to go out, enabling a stress-free shopping experience. It also has an emotion recognition function that can provide psychological support to users, improving customer satisfaction.

[1535] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1536] Step 1:

[1537] When a user enters a fitting room, the device uses a camera to take a full-body image of the user, which is then sent to the server as input for further processing.

[1538] Step 2:

[1539] The server analyzes the received full-body image using image analysis tools. Specifically, it uses image analysis models such as TensorFlow to detect dirt, wrinkles, dust, and messy hair on the clothes. The data obtained from this analysis becomes the input for the next process.

[1540] Step 3:

[1541] Based on the analysis results, the server uses the advice generation means to generate appropriate advice for the user. This advice generation includes the user's clothing status and detailed comments. The generated advice becomes the input for the next step.

[1542] Step 4:

[1543] The device communicates the generated advice to the user through a voice output means. Specifically, the advice is output as voice using a voice synthesis library such as Python's pyttsx3. The user receives this voice advice.

[1544] Step 5:

[1545] The server acquires color information of the user's clothing using the image analysis means, and advises the user on the appropriate accessory color using the accessory advice means. This advice is also conveyed to the user by the voice output means, and is output as advice to the user.

[1546] Step 6:

[1547] The user's facial expressions and voice are acquired by the device and analyzed by the emotion recognition means. Based on the analysis results, the server analyzes the user's emotions and generates advice on how to relax as needed. The advice generated by this emotion recognition is conveyed to the user by the voice output means.

[1548] Step 7:

[1549] The server uses the weather forecast linking means to acquire weather forecast data from the user's location information. Based on the acquired weather data, advice for going out is generated. This advice based on the weather forecast is also conveyed to the user by the voice output means.

[1550] 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.

[1551] 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.

[1552] 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.

[1553] [Fourth embodiment]

[1554] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1555] 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.

[1556] 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).

[1557] 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.

[1558] 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.

[1559] 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).

[1560] 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.

[1561] 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.

[1562] 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.

[1563] 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.

[1564] 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.

[1565] 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.

[1566] 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."

[1567] The present invention is a system for enabling a user to efficiently prepare for going out, and it combines a photographing means, an image analysis means, an advice generation means, a voice output means, a weather forecast linkage means, a body temperature measurement means, a physical condition evaluation means, a forgotten item confirmation means, and an accessory advice means. Specific embodiments of this system are described below.

[1568] Overall Overview

[1569] This system allows users to walk around in front of the camera before going out, and automatically checks their appearance and belongings, and provides advice based on the weather and their physical condition. Users simply follow voice instructions and are ready to go out.

[1570] An example of an appearance check

[1571] 1. Terminal

[1572] When the user stands in front of the camera, it automatically activates and takes a picture of the user, with voice prompts to walk around in a circle.

[1573] 2. Server

[1574] It receives the captured image data and uses an image analysis algorithm to detect dirt, wrinkles, dust, and messy hair on the clothes, then generates necessary advice based on the results and generates text data for voice output.

[1575] 3. Terminal

[1576] The generated advice is communicated to the user as audio.

[1577] For example: "There are wrinkles on the back. A steam iron would help."

[1578] Weather forecast advice implementation form

[1579] 1. Server

[1580] The system obtains the latest weather forecast data based on the user's location, and generates advice on whether they need a jacket or an umbrella based on the forecast.

[1581] 2. Terminal

[1582] The message is conveyed to the user as audio.

[1583] Example: "It's raining today, so you should bring an umbrella."

[1584] Temperature Measurement and Alert Implementation

[1585] 1. Terminal

[1586] The user is prompted by voice to take their temperature, and their temperature is measured by touching the temperature sensor.

[1587] 2. Server

[1588] Receives the measured body temperature data and evaluates whether it is within the normal range. If it is abnormal, it generates an alert and generates text data for voice output.

[1589] 3. Terminal

[1590] The content of the alert is announced to the user through audio.

[1591] For example: "Your current temperature is 37.8°C. It's a little high, so I recommend you relax or drink a warm drink."

[1592] Implementation of lost item check

[1593] 1. Terminal

[1594] Based on the loaded lost item list, it outputs a voice prompt to remind the user to check their belongings.

[1595] For example: "Did you bring your keys and wallet?"

[1596] 2. Users

[1597] You will receive a voice confirmation, which the system will analyze to determine if you are fully prepared.

[1598] For example: "Yes, I have it."

[1599] Accessory color advice implementation example

[1600] 1. Server

[1601] It analyzes the user's clothing color information and generates color advice for suitable accessories based on fashion rules.

[1602] 2. Terminal

[1603] The generated advice is communicated to the user as audio.

[1604] For example: "The color of accessories that goes well with today's outfit is silver."

[1605] Customization Settings Implementation Example

[1606] 1. Users

[1607] Customize your voice output settings to adjust the gender, tone, and phrasing of the voice.

[1608] 2. Terminal

[1609] The received customization settings will be saved and reflected from the next time onwards.

[1610] The above configuration allows the user to efficiently prepare before going out, realizing a system that allows for a comfortable outing.

[1611] The processing flow will be explained below.

[1612] Step 1:

[1613] The user stands in front of the camera and activates the system.

[1614] Step 2:

[1615] The device uses facial recognition technology to identify the user and then issues a voice prompt saying, "Take one lap."

[1616] Step 3:

[1617] The user walks around in front of the camera, capturing their entire body.

[1618] Step 4:

[1619] The device sends the captured data from the user's entire rotation to the server.

[1620] Step 5:

[1621] The server processes the received data based on image analysis algorithms to detect dirt, wrinkles, dust, and messy hair on the clothes.

[1622] Step 6:

[1623] Based on the results of image analysis, the server generates appropriate advice for the user as text data and sends it to the terminal for voice output.

[1624] Step 7:

[1625] The device will communicate the advice it receives to the user via voice.

[1626] For example: "There are wrinkles on the back. A steam iron would help."

[1627] Step 8:

[1628] The server retrieves weather forecast data based on the user's location information.

[1629] Step 9:

[1630] The server generates text data based on weather forecast data, giving advice on whether a jacket is needed or whether an umbrella should be carried, and transmits the text data to the terminal for voice output.

[1631] Step 10:

[1632] The device will then communicate the weather forecast advice received to the user via voice.

[1633] Example: "It's raining today, so you should bring an umbrella."

[1634] Step 11:

[1635] The device will output a voice prompt to the user to take their temperature.

[1636] For example: "Please take my temperature."

[1637] Step 12:

[1638] The user touches the temperature sensor to measure their temperature.

[1639] Step 13:

[1640] The device sends the measured body temperature data to the server.

[1641] Step 14:

[1642] The server analyzes the temperature data and determines whether it is within the normal range. If it is abnormal, it generates an alert and generates text data for voice output and sends it to the device.

[1643] Step 15:

[1644] The device will communicate any alerts received to the user via voice.

[1645] For example: "Your current temperature is 37.8°C. It's a little high, so I recommend you relax or drink a warm drink."

[1646] Step 16:

[1647] The device loads the registered lost item list and outputs a voice prompt to ask the user to confirm.

[1648] For example: "Did you bring your keys and wallet?"

[1649] Step 17:

[1650] The user responds with the confirmation result by voice.

[1651] For example: "Yes, I have it."

[1652] Step 18:

[1653] The device converts the received voice into text, confirms that the item has not been left behind, and notifies the user.

[1654] For example: "I made sure you didn't forget anything."

[1655] Step 19:

[1656] The server analyzes the color information of the user's clothing, generates suitable accessory colors as text data, and sends it to the terminal for voice output.

[1657] Step 20:

[1658] The device will then provide the user with audio color advice for the accessory it receives.

[1659] For example: "The color of accessories that goes well with today's outfit is silver."

[1660] Step 21:

[1661] Users can customize voice output settings and adjust the gender, impression, and phrasing of the voice.

[1662] Step 22:

[1663] The device will save your customization settings and apply them the next time.

[1664] Example 1

[1665] 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."

[1666] Previously, preparing to go out required users to individually check their appearance, the weather, their physical condition, and their belongings, which took a lot of time and effort. This often caused stress for users before going out, and was inefficient. There was also a need for a system that could centrally automate these check tasks.

[1667] 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.

[1668] In this invention, the server includes: an imaging means for capturing an image of the user's body; an image analysis means for analyzing the image of the user captured by the imaging means to detect stains, wrinkles, dust, and messy hair on the user's clothes; an advice generation means for generating appropriate advice for the user based on the detection results of the image analysis means; an audio output means for outputting the advice generated by the advice generation means as audio; a weather forecast linkage means for acquiring weather forecast data based on the user's location information and generating advice for the user when going out based on the acquired weather forecast; a temperature measurement means for outputting an audio prompt urging the user to measure their temperature and measuring the user's temperature; a physical condition evaluation means for evaluating the user's physical condition based on the measured temperature data and generating an alert if an abnormality is detected; a forgotten item confirmation means for outputting an audio prompt urging the user to check their belongings; and an accessory advice means for analyzing the color information of the user's clothing and generating color advice for appropriate accessories. This allows the user to efficiently prepare before going out and enjoy a comfortable outing.

[1669] "Photographing means" refers to equipment or devices for photographing the user's body.

[1670] "Image analysis means" refers to a technology or device that analyzes a photographed image of a user and detects stains, wrinkles, dust, and messy hair on the clothes.

[1671] The "advice generation means" is a technology or device for generating appropriate advice for the user based on the detection results obtained by the image analysis means.

[1672] The "audio output means" is a technique or device for outputting the advice generated by the advice generating means as audio.

[1673] The "weather forecast linking means" is a technology or device for acquiring weather forecast data based on the user's location information and generating advice for the user when going out based on the acquired weather forecast.

[1674] "Temperature measurement means" means any technology or device for measuring a user's temperature.

[1675] The "physical condition evaluation means" is a technology or device for evaluating the user's physical condition based on measured body temperature data and generating an alert if any abnormalities are detected.

[1676] A "lost property verification means" is a technology or device that outputs a voice prompt to prompt the user to verify their belongings.

[1677] The "accessory advice means" is a technology or device for analyzing the user's clothing color information and generating color advice for suitable accessories.

[1678] A "user" is a person who uses this system to prepare for going out.

[1679] The present invention is a system for enabling users to efficiently prepare for going out. By combining a photographing means, an image analysis means, a means for generating advice, a means for outputting audio, a means for linking with weather forecasts, a means for measuring body temperature, a means for evaluating physical condition, a means for checking for lost items, and a means for providing advice on accessories, the system allows users to centrally automate their preparations before going out. Specific embodiments of the present invention are described below.

[1680] System Hardware and Software

[1681] Hardware

[1682] Photography method: Uses the camera on a smartphone or tablet to capture a photo of the user's body.

[1683] Body temperature measurement method: A smartwatch or dedicated body temperature sensor is used to measure the user's body temperature.

[1684] software

[1685] Image analysis method: The OpenCV library is used for image analysis, which detects dirt, wrinkles, dust, and messy hair from captured images.

[1686] Advice generation method: The advice is generated using a script written in "Python" or "JavaScript."

[1687] Voice output method: "Google Text-to-Speech" and "Amazon Polly" are used for voice output, which convert text data into voice.

[1688] Weather forecast integration method: The OpenWeatherMap API is used to obtain weather forecast data, which allows users to obtain weather forecasts based on their location.

[1689] Physical condition evaluation method: An analysis system linked to "Raspberry Pi" is used to evaluate body temperature data, which determines whether the body temperature is within the normal range.

[1690] How to check for lost items: To check for lost items, a voice prompt is output through Google Assistant, prompting the user to check for their belongings.

[1691] Accessory advice method: IBM Watson Visual Recognition is used to analyze and advise on clothing colors, suggesting accessory colors that match the user's outfit.

[1692] Example of operation

[1693] 1. Grooming check

[1694] When a user stands in front of the camera, it automatically starts up and takes a picture of the user.

[1695] The device will play a voice prompt saying "Take a turn."

[1696] The server uses OpenCV's image analysis algorithm to detect stains and wrinkles on the clothes.

[1697] The server generates the advice "There are wrinkles on the back. You may want to use a steam iron."

[1698] The device uses Google Text-to-Speech to convert advice into audio and convey it to the user.

[1699] 2. Weather Forecast Advice

[1700] The server uses the OpenWeatherMap API to get the latest weather forecast.

[1701] The server generates the advice "It's raining today, so please take an umbrella."

[1702] The device uses Amazon Polly to convert advice into voice and convey it to the user.

[1703] 3. Temperature measurement and alerts

[1704] The device will play a voice prompt saying, "Please take your temperature."

[1705] The user measures their temperature by touching the temperature sensor on the smartwatch.

[1706] The server receives the body temperature data and analyzes it using a Raspberry Pi.

[1707] The server generates an alert saying, "Your current temperature is 37.8 degrees. It's a little high, so we recommend you relax or drink a warm drink."

[1708] The device converts the alert into audio and relays it to the user.

[1709] 4. Check for lost items

[1710] The device will play a voice prompt asking, "Did you bring your keys and wallet?"

[1711] The user responds by voice, "Yes, I have it."

[1712] The device uses Azure Speech to Text to convert speech into text and analyze it.

[1713] 5. Accessory advice

[1714] The server uses IBM Watson Visual Recognition to analyze clothing colors.

[1715] The server generates advice such as "The color of the accessory that matches your outfit today is silver."

[1716] The device uses Amazon Alexa to convert advice into voice and convey it to the user.

[1717] According to the above-mentioned specific examples, the system of the present invention makes it possible for the user to efficiently prepare for going out and reduces stress.

[1718] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1719] Step 1: The user stands in front of the camera

[1720] Input: The user stands in front of the camera.

[1721] Action: The device detects the user's presence using a sensor.

[1722] Output: The camera starts automatically.

[1723] What it does: Your smartphone or tablet's camera app will automatically launch and you'll hear a voice prompt saying, "Take a full turn."

[1724] Step 2: The device takes a photo of the user

[1725] Input: The user moves around in a circle.

[1726] Processing: The device takes continuous shots and records the footage.

[1727] Output: Video data is generated.

[1728] Specific operation: The smartphone takes continuous shots and sends the video data to the server.

[1729] Step 3: The server performs image analysis

[1730] Input: Video data sent from the device.

[1731] Processing: The server uses the OpenCV library to analyze the images and detect stains, wrinkles, dust, and messy hair on the clothes.

[1732] Output: The detection results are generated.

[1733] Specific operation: The server analyzes the video data frame by frame and identifies problem areas.

[1734] Step 4: Server generates advice

[1735] Input: Detection results from image analysis.

[1736] Processing: The server generates advice for the user based on the analysis results.

[1737] Output: Text data of advice is generated.

[1738] Specific behavior: If dirt is detected, generate advice such as "There is dirt on the back. It may be a good idea to use a brush."

[1739] Step 5: Your device will speak the advice

[1740] Input: Text data of advice sent from the server.

[1741] Processing: Your device uses Google Text-to-Speech to convert the text data into audio.

[1742] Output: A spoken advice is generated.

[1743] Specific behavior: The smartphone conveys the generated voice advice to the user.

[1744] Step 6: Server retrieves weather forecast data

[1745] Input: User's location.

[1746] Process: The server retrieves weather forecast data using the OpenWeatherMap API.

[1747] Output: Weather forecast data is generated.

[1748] Specific operation: The server retrieves the latest weather forecast based on the location information.

[1749] Step 7: Server generates weather-based advice

[1750] Input: Weather forecast data.

[1751] Processing: The server generates advice for going out based on the weather forecast data.

[1752] Output: Weather-based advice text data is generated.

[1753] Specific behavior: If rain is forecast, generate advice such as "It's going to rain today, so please bring an umbrella."

[1754] Step 8: Your device will speak weather advice

[1755] Input: Weather advice text data sent from the server.

[1756] Processing: The device uses Amazon Polly to convert the text data into speech.

[1757] Output: A spoken advice is generated.

[1758] Specific behavior: The smartphone conveys the generated voice advice to the user.

[1759] Step 9: The device prompts you to take your temperature

[1760] Input: The act of the user hearing a voice prompt.

[1761] Action: The device outputs a voice prompt saying "Please take your temperature."

[1762] Output: The user begins taking their temperature.

[1763] What it does: The smartwatch will play a voice prompt to remind the user to take their temperature.

[1764] Step 10: User takes temperature

[1765] Input: Touching the temperature sensor.

[1766] Processing: The temperature sensor measures the user's temperature and generates the data.

[1767] Output: Temperature data is generated.

[1768] What happens: The user touches the sensor on the smartwatch to measure their body temperature.

[1769] Step 11: Server evaluates temperature data

[1770] Input: Temperature measurement data.

[1771] Processing: The server analyzes the received temperature data and evaluates whether it is within the normal range.

[1772] Output: Text data of health alert is generated.

[1773] What it does: The server analyzes data from the temperature sensor connected to the Raspberry Pi and generates alerts as needed.

[1774] Step 12: Your device will output a health alert

[1775] Input: Text data of health alert sent from the server.

[1776] Action: The device uses iOS VoiceOver to convert the alert into audio.

[1777] Output: An audio alert is generated.

[1778] What it does: The smartphone plays the generated audio alert to the user.

[1779] Step 13: The device will output a lost item confirmation prompt

[1780] Input: System loaded lost item checklist.

[1781] Action: Your device uses Google Assistant to speak a prompt to check your belongings.

[1782] Output: A voice prompt is generated.

[1783] What happens: Your smartphone will play a voice prompt saying, "Did you bring your keys and wallet?"

[1784] Step 14: User responds with confirmation by voice

[1785] Input: User's voice input.

[1786] Processing: The device converts the user's voice into text using Azure Speech to Text, which is then analyzed by the system.

[1787] Output: Text data of the belongings check result is generated.

[1788] Specific operation: The user replies "Yes, I have it," and the device converts the speech into text and analyzes it.

[1789] Step 15: Check that your device is ready

[1790] Input: Text data of the inventory check results.

[1791] Processing: The device checks the lost item checklist against the user's voice response to determine if they are ready.

[1792] Output: A text message is generated to notify you that the device is ready.

[1793] What it does: The device checks the checklist and the user's responses, then notifies them that all items are in order.

[1794] Step 16: Server analyzes clothing color

[1795] Input: User's clothing image data.

[1796] Processing: The server analyzes the clothing color using IBM Watson Visual Recognition.

[1797] Output: Color analysis results are generated.

[1798] Specific operation: The server analyzes the user's clothing image and obtains color information.

[1799] Step 17: Server generates color advice for accessories

[1800] Input: Color analysis results.

[1801] Processing: The server generates color advice for suitable accessories based on the analysis results.

[1802] Output: Text data of accessory advice is generated.

[1803] Specific behavior: Generates advice such as "The color of accessories that goes well with today's outfit is silver."

[1804] Step 18: Your device will speak accessory advice

[1805] Input: Text data of accessory advice sent from the server.

[1806] Processing: The device uses Amazon Alexa to convert the advice into voice.

[1807] Output: A spoken advice is generated.

[1808] Specific operation: The smart speaker outputs advice aloud and conveys it to the user.

[1809] Through the above steps, the system of the present invention enables the user to efficiently prepare for going out and ensure a comfortable outing.

[1810] (Application example 1)

[1811] 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."

[1812] In the past, factory workers' work preparation required individual checking of equipment, temperature checks, and checking for forgotten items, which was inefficient and required a great deal of time and effort. Furthermore, there was a lack of appropriate advice regarding weather changes, which led to a decline in worker safety and efficiency. To solve these issues, a system was needed that centralized the worker preparation process and made it possible to do so quickly and efficiently.

[1813] 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.

[1814] In this invention, the server includes a photographing means for photographing the user's body, an image analysis means for analyzing the image of the user photographed by the photographing means to detect stains, wrinkles, dust, and messy hair on the clothes, and an advice generation means for generating appropriate advice for the user based on the detection results of the image analysis means. This makes it possible to streamline work preparation for factory workers and to centrally manage equipment checks, temperature measurements, and forgotten item checks.

[1815] "Photographing means" is a mechanism for photographing the user's body and equipment, and is a device for obtaining the user's appearance as digital data.

[1816] The "image analysis means" is a mechanism that processes and analyzes the image data acquired by the photographing means and detects specific features (for example, dirt, wrinkles, dust, or messy hair).

[1817] The "advice generator" is a mechanism or algorithm for generating appropriate advice for a user based on the image analysis means and other data inputs.

[1818] The "audio output means" is a device or software for conveying the advice generated by the advice generating means to the user in audio form.

[1819] "Temperature measurement means" means a sensor or device for measuring a user's temperature and providing the data necessary to assess the user's health condition.

[1820] The "physical condition assessment means" is an algorithm or mechanism that assesses the user's health condition based on the body temperature data obtained by the body temperature measurement means and generates appropriate advice or warnings.

[1821] The "weather forecast linking means" is an information processing system that acquires current weather forecast data and generates appropriate advice for the user when going out or working.

[1822] The "lost item confirmation means" is a system that checks whether all important belongings are present based on the user's belongings list and notifies the user of the results.

[1823] The present invention is a system for improving the efficiency of work preparation by factory workers. Each means and its processing will be described in detail below.

[1824] Photography and image analysis methods

[1825] A camera that captures images of the user's body and equipment is connected to the server. The camera automatically activates when the worker stands in front of the camera, capturing images of the worker in all 360-degree directions. This captured image data is immediately sent to the image analysis means, which uses an open-source image processing library (e.g., OpenCV) to detect dirt, wrinkles, dust, and messy hair on the equipment.

[1826] Advice generation means and voice output means

[1827] Based on the results obtained by the image analysis means, the advice generation means of the server generates appropriate advice for the worker. The generated advice is communicated to the worker in real time by the voice output means. A library that converts text to voice (e.g., pyttsx3) is used for the voice output.

[1828] For example, the advice "Dirt has been detected on your equipment. Please clean it" is output as voice.

[1829] Temperature measurement and health assessment methods

[1830] The system is equipped with a sensor for measuring the worker's body temperature. The body temperature measurement means measures the worker's body temperature when the worker touches the sensor and sends the data to a server. The physical condition evaluation means evaluates the worker's physical condition based on this body temperature data and generates an alert if there is an abnormality. The worker is also notified of this alert by voice.

[1831] For example, advice such as "Your body temperature is high. Don't push yourself and take care of your health" is output as audio.

[1832] Weather forecast linkage method

[1833] The server retrieves current weather forecast data via an Internet connection and generates advice based on the worker's working environment. For this purpose, a weather forecast API is used. If the weather is bad (e.g., rainy), the server will give the worker appropriate warnings.

[1834] For example, advice such as "Rain is expected today, so please wear appropriate waterproof gear" may be output via voice.

[1835] How to check for lost items

[1836] A list of important items that the worker should have is loaded onto the server, and the lost item confirmation means prompts the worker by voice to check the items he or she has brought with him or her based on this list.

[1837] For example, a question such as "Did you bring your helmet and gloves?" is output by voice, and the worker confirms this.

[1838] Examples of prompt statements

[1839] By inputting the following prompt sentence into the generative AI model, appropriate advice can be generated.

[1840] "Get data from a weather forecast API and generate weather-based advice. Data includes conditions like sunny, rainy, snowy, cloudy, etc. Generate appropriate voice prompts for each."

[1841] Based on this prompt, the system can provide appropriate advice to workers in real time, helping them prepare for work efficiently and safely.

[1842] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1843] Step 1:

[1844] When a user stands in front of the camera, the server automatically activates the camera. The camera captures a 360-degree image of the user's entire body. The image data obtained as input is then sent to the next step.

[1845] Step 2:

[1846] The server sends the captured image data to the image analysis means, which uses an image processing library such as OpenCV to detect features such as dirt, wrinkles, dust, and messy hair from the input image data. The analysis results are sent to the advice generation means.

[1847] Step 3:

[1848] The server generates appropriate advice through the advice generating means based on the image analysis results. For example, if dirt is detected, the server generates advice such as "Dirt has been detected on the equipment. Please clean it." The generated advice is sent to the voice output means.

[1849] Step 4:

[1850] The server notifies the generated advice to the user by voice using the voice output means, thereby providing the user with information about their own equipment and physical condition.

[1851] Step 5:

[1852] When the user touches the body temperature sensor, the terminal's body temperature measurement means measures the user's body temperature and sends the data to the server. The body temperature data obtained as input is then sent to the physical condition evaluation means.

[1853] Step 6:

[1854] The server processes the body temperature measurement data using a physical condition evaluation means to evaluate the user's physical condition. If a temperature above the normal range is detected, an alert is generated stating, "Your body temperature is high. Please do not overexert yourself and take care of your health." This alert is sent to a voice output means.

[1855] Step 7:

[1856] The server uses a weather forecast API to obtain current weather data. Based on the data obtained from the API, it generates advice appropriate to the weather. For example, it generates advice such as "Rain is expected today, so please wear appropriate waterproof gear." The generated advice is sent to the audio output means.

[1857] Step 8:

[1858] The server uses the lost item confirmation means to prompt the user to check their belongings based on the list of important belongings, generating questions such as "Did you bring your helmet and gloves?" and notifying the user through the voice output means.

[1859] Step 9:

[1860] Users can respond to voice prompts to check their belongings and take necessary actions, and the system will analyze their responses and provide appropriate feedback.

[1861] 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.

[1862] The present invention is a system for enabling a user to efficiently prepare for going out, and combines a photographing means, an image analysis means, an advice generation means, a voice output means, a weather forecast linkage means, a body temperature measurement means, a physical condition evaluation means, a forgotten item confirmation means, an accessory advice means, and an emotion recognition means. Specific embodiments of this system are described below.

[1863] Overall Overview

[1864] This system allows the user to walk around in front of the camera before going out, and automatically checks their appearance and belongings, and provides advice based on the weather and their physical condition. It also recognizes the user's emotions and provides adaptive advice. The user simply follows voice instructions and is ready to go out.

[1865] An example of an appearance check

[1866] 1. The user stands in front of the camera and activates the system. The device uses facial recognition technology to identify the user and issues a voice prompt saying, "Turn around once." The user turns around in front of the camera, capturing a full-body image. The device then sends the captured image data to the server.

[1867] 2. The server processes the received data using an image analysis algorithm to detect dirt, wrinkles, dust, and messy hair on the clothes. Based on the detection results, it generates appropriate advice as text data and sends it to the device for voice output.

[1868] 3. The device will then verbally communicate the generated advice to the user.

[1869] For example: "There are wrinkles on the back. A steam iron would help."

[1870] Weather forecast advice implementation form

[1871] 1. The server obtains weather forecast data based on the user's location information, and generates advice based on the forecast, such as whether or not to bring a jacket or an umbrella. The generated advice is sent to the device as text data.

[1872] 2. The device will provide voice weather forecast advice to the user.

[1873] Example: "It's raining today, so you should bring an umbrella."

[1874] Temperature Measurement and Alert Implementation

[1875] 1. The device outputs a voice prompt to the user to measure their temperature.

[1876] For example: "Please take my temperature."

[1877] 2. The user touches the temperature sensor to measure their temperature, and the device sends the measured temperature data to the server.

[1878] 3. The server analyzes the temperature data and evaluates whether it is within the normal range. If it is abnormal, it generates an alert and sends text data to the device for voice output.

[1879] 4. The device will audibly communicate the alert to the user.

[1880] For example: "Your current temperature is 37.8°C. It's a little high, so I recommend you relax or drink a warm drink."

[1881] Implementation of lost item check

[1882] 1. The device outputs a voice prompt to prompt the user to check their belongings based on the lost items list.

[1883] For example: "Did you bring your keys and wallet?"

[1884] 2. The user responds with the confirmation result by voice.

[1885] For example: "Yes, I have it."

[1886] 3. The device converts the received voice into text, confirms that the item has not been left behind, and notifies the user.

[1887] For example: "I made sure you didn't forget anything."

[1888] Accessory color advice implementation example

[1889] 1. The server analyzes the color information of the user's clothing and generates text data on suitable accessory colors. The generated advice is sent to the device.

[1890] 2. The device will provide the user with audio advice on the color of the accessory.

[1891] For example: "The color of accessories that goes well with today's outfit is silver."

[1892] Emotion Recognition Embodiment

[1893] 1. The device captures the user's voice and facial expressions and analyzes the user's emotions using emotion recognition algorithms. Emotions such as stress, satisfaction, dissatisfaction, and tension are recognized.

[1894] 2. The server adjusts the content and tone of the advice based on the user's emotion recognized by the emotion recognition means. For example, if the user is feeling stressed, the server provides advice to relax and slows down the tone and speed of the voice.

[1895] 3. The device will then provide tailored advice to the user via voice.

[1896] For example: "Why don't you relax a bit?"

[1897] Customization Settings Implementation Example

[1898] 1. The user customizes the voice output settings in the system settings screen, including the gender, impression, and phrasing of the voice.

[1899] 2. The device will save your customization settings and apply them to future audio outputs.

[1900] With the above configuration, users can efficiently prepare before going out, allowing them to go out comfortably, and a system can be realized that also provides psychological support by using emotion recognition.

[1901] The processing flow will be explained below.

[1902] Step 1:

[1903] The user stands in front of the camera and activates the system.

[1904] Step 2:

[1905] The device uses facial recognition technology to identify the user and then issues a voice prompt saying, "Take one lap."

[1906] Step 3:

[1907] The user walks around in front of the camera, capturing their entire body.

[1908] Step 4:

[1909] The device sends the user's photo data to the server.

[1910] Step 5:

[1911] The server uses image analysis algorithms to detect dirt, wrinkles, dust, and messy hair on the clothes.

[1912] Step 6:

[1913] Based on the results of the image analysis, the server generates appropriate advice as text data and sends it to the terminal for voice output.

[1914] Step 7:

[1915] The device will then give the generated advice to the user via voice, for example, "There are wrinkles on your back. You may want to use a steam iron."

[1916] Step 8:

[1917] The server retrieves weather forecast data based on the user's location information.

[1918] Step 9:

[1919] The server generates weather-appropriate advice based on weather forecast data and transmits it to the terminal as text data.

[1920] Step 10:

[1921] The device will then give you weather forecast advice by voice, for example, "It's going to rain today, so you should bring an umbrella."

[1922] Step 11:

[1923] The device will output a voice prompt to the user to take their temperature. For example, "Please take your temperature."

[1924] Step 12:

[1925] The user touches the temperature sensor to measure their temperature.

[1926] Step 13:

[1927] The device sends the measured body temperature data to the server.

[1928] Step 14:

[1929] The server analyzes the temperature data and evaluates whether it is within the normal range. If there is an abnormality, an alert is generated and text data is sent to the device for voice output.

[1930] Step 15:

[1931] The device will then verbally announce the alert to the user, for example, "Your current body temperature is 37.8°C. It's a little high, so we recommend you relax or drink a warm drink."

[1932] Step 16:

[1933] The device will then output a voice prompt based on the list of lost items to remind the user to check their belongings, for example, "Did you bring your keys and wallet?"

[1934] Step 17:

[1935] The user responds with a voice confirmation, for example, "Yes, I have it."

[1936] Step 18:

[1937] The device converts the received voice into text, confirms that the item has not been left behind, and notifies the user.

[1938] Step 19:

[1939] The server analyzes the color information of the user's clothing, generates suitable accessory colors as text data, and sends it to the terminal.

[1940] Step 20:

[1941] The device will give the user audio advice on the color of the accessories, for example, "The color of the accessories that matches your outfit today is silver."

[1942] Step 21:

[1943] The device captures the user's voice and facial expressions, and analyzes the user's emotions using emotion recognition algorithms to recognize emotions such as stress, satisfaction, dissatisfaction, and tension.

[1944] Step 22:

[1945] The server adjusts the content and tone of the advice based on the user's emotion recognized by the emotion recognition means. For example, if the user is feeling stressed, the server provides advice to relax and slows down the tone and speed of the voice.

[1946] Step 23:

[1947] The device will then give tailored advice to the user, such as "Why don't you try to relax a bit?"

[1948] Step 24:

[1949] Users can customize voice output settings in the system settings screen, including voice gender, impression, and phrasing.

[1950] Step 25:

[1951] The device will save your customization settings and apply them to future audio outputs.

[1952] Example 2

[1953] 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."

[1954] For users to prepare for going out efficiently and reliably, they need to check many factors. These include checking their appearance, preparing appropriate gear for the weather, managing their physical condition, checking for forgotten items, and providing advice that adapts to the user's emotions. Performing these tasks manually takes time and effort, hindering efficient preparation for going out. The objective of this invention is to comprehensively solve these problems with a single system.

[1955] 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.

[1956] In this invention, the server includes: an imaging means for imaging the user's body; an image analysis means for analyzing the image of the user captured by the imaging means and detecting stains, wrinkles, dust, and messy hair on the clothes; an advice generation means for generating appropriate advice for the user based on the detection results of the image analysis means; an audio output means for outputting the advice generated by the advice generation means as audio; an emotion recognition means for acquiring the user's voice and facial expression and recognizing their emotion; and an advice generation means for adjusting the content and tone of the advice based on the user's emotion recognized by the emotion recognition means. This enables the user to prepare to go out efficiently and comprehensively using a single system.

[1957] The "system" is an integrated device that combines multiple means to help users efficiently prepare for going out.

[1958] "Photographing means" refers to a device for photographing the user's body, and includes cameras and image capture devices.

[1959] The "image analysis means" is an algorithm or system for analyzing image data acquired by the imaging means and extracting specific information.

[1960] The "advice generation means" is a device or program for generating appropriate advice for the user based on the results of the image analysis means, the weather forecast linkage means, and the emotion recognition means.

[1961] The "audio output means" is a device for conveying the generated advice to the user by voice, and includes a speaker and a voice synthesis system.

[1962] An "emotion recognition means" is an algorithm or system that acquires the user's voice and facial expressions and determines the user's emotions based on them.

[1963] The "weather forecast linking means" is a device or program for acquiring weather forecast data based on the user's location information and generating advice based on that data.

[1964] "Temperature measurement means" refers to a device for measuring the user's temperature, and includes a thermometer and a sensor.

[1965] The "physical condition evaluation means" is a system for analyzing the measured body temperature data and evaluating the user's physical condition.

[1966] The "lost item confirmation means" is a device or program that allows the user to confirm whether or not they have the necessary items.

[1967] The present invention is a system for enabling a user to efficiently prepare for going out, and is realized by combining multiple pieces of hardware and software. Specific embodiments will be described below.

[1968] This system is mainly composed of a terminal and a server. The terminal is connected to input and output devices such as a camera, microphone, speaker, and thermometer. The server also functions as a processing device for executing various analysis and generation algorithms.

[1969] Hardware and software used

[1970] 1. Terminal

[1971] Camera: To capture the user's entire body. For example, a typical webcam or smartphone camera can be used.

[1972] Microphone: To capture the user's voice input, using the built-in microphone on your smartphone or laptop.

[1973] Speakers: For system sound output, using headphones or the device's built-in speakers.

[1974] Thermometer: Use a Bluetooth-connected thermometer.

[1975] 2. Server

[1976] Image analysis algorithm: The captured image data is analyzed using TensorFlow and PyTorch.

[1977] Emotion recognition algorithm: Recognizes user emotions using Microsoft Azure Emotion API, etc.

[1978] Weather forecast data: Obtain weather information using the OpenWeatherMap API.

[1979] Specific processing of the program

[1980] When a user starts the system, the device uses a camera to capture a full-body image of the user. A voice prompt is played saying, "Please turn around in front of the camera." As the user turns around, image data of the entire body is acquired. This data is sent to the server in real time.

[1981] An image analysis model using TensorFlow and PyTorch runs on the server and analyzes the captured image data. This detects dirt, wrinkles, dust, and messy hair on the clothes. Based on the analysis results, appropriate advice is generated and sent to the device as text data. For example, "There are wrinkles on the back. It would be a good idea to use a steam iron."

[1982] As a means of weather forecast integration, the server calls the OpenWeatherMap API based on the user's location information to obtain weather forecast data. Advice for going out based on the weather is generated and sent to the device. Example: "It's going to rain today, so you should bring an umbrella."

[1983] To measure body temperature, the device will issue a voice prompt saying, "Please measure your temperature." When the user measures their temperature using a Bluetooth-connected thermometer, the data is sent to the server, which evaluates their physical condition. For example, "Your current body temperature is 37.8 degrees. It's a little high, so we recommend you relax or drink a warm drink."

[1984] To recognize emotions, the device captures the user's voice and facial expressions and uses the Microsoft Azure Emotion API to recognize their emotions. The server then adjusts the tone and content of the advice based on this emotional information to generate the most appropriate advice. Example: "Why don't you try relaxing a bit?"

[1985] Prompt Sentence Examples

[1986] "I want to use this system to get ready to go out. Can you explain how the system works?"

[1987] "What are the steps to generate weather advice?"

[1988] Please explain with examples how to recognize users' emotions and give advice based on them.

[1989] With the above configuration, users can efficiently prepare before going out, ensuring a comfortable outing. In addition, by using emotion recognition, a system can be realized that also provides psychological support.

[1990] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1991] Step 1: Boot the system

[1992] The user starts the system. The terminal initializes devices such as the camera, microphone, speaker, and thermometer. The input is the user's startup operation, and the output is a notification that each device is ready. Specifically, the terminal checks the connection status of each device and verifies that it is operating normally.

[1993] Step 2: Photographing the user's entire body

[1994] The device uses a voice prompt to instruct the user to "turn around in front of the camera." The camera captures the user's position and movements as input and generates full-body image data as output. The user turns around in front of the camera, and the camera captures multiple images in succession. These images are temporarily stored on the device and immediately sent to the server.

[1995] Step 3: Analyze image data and generate advice

[1996] The image data received by the server is processed using an image analysis algorithm using TensorFlow or PyTorch. Image data of the entire body is sent to the server as input, and the output generates detection results for stains, wrinkles, dust, and messy hair on clothes. Specifically, the analysis algorithm extracts features from the image and performs recognition and classification using a trained model. Based on the results, appropriate advice is generated and sent to the device as text data.

[1997] Step 4: Obtaining weather forecast data and generating advice

[1998] The server retrieves weather forecast data from the OpenWeatherMap API based on the user's location information. Location information is provided as input, and weather forecast data and advice based on it are generated as output. Specifically, the server sends an API request based on the location information and receives weather forecast data. It then analyzes the data and generates appropriate advice (e.g., "Bring an umbrella") and sends it to the device.

[1999] Step 5: Temperature check and health assessment

[2000] The device issues a voice prompt saying "Please measure your temperature." The user measures their temperature using a Bluetooth-connected thermometer. The measurement result is sent to the device as input, and temperature data and a health assessment are generated as output. Specifically, the device receives the thermometer measurement data via Bluetooth and sends it to the server. The server analyzes the temperature data, evaluates whether it is within the normal range, and sends the result to the device.

[2001] Step 6: Emotion recognition and advice adjustment

[2002] The device captures the user's voice and facial expressions and analyzes them using an emotion recognition algorithm. Voice and image data are provided as input, and advice tailored to the user's emotions is generated as output. Specifically, the device collects voice and facial expression data and sends it to a server. The server analyzes it using an emotion recognition algorithm (for example, Microsoft Azure Emotion API) and adjusts the tone and content of the advice based on the results. As a result, advice tailored to the user is generated and sent to the device.

[2003] Step 7: Final output of the advice

[2004] The device will then verbally communicate to the user all the advice it has generated so far. Various analysis results and advice data are provided as input, and voice guidance is provided to the user as output. Specifically, it uses a speech synthesis engine (e.g., Google Text-to-Speech API) to convert text data into speech, which is then transmitted to the user through the speaker.

[2005] Through the above processing steps, the user can easily prepare to go out efficiently and effectively.

[2006] (Application example 2)

[2007] 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."

[2008] Conventional outing preparation systems require time and effort for users to check their appearance and belongings, and are unable to provide a wide range of support in a unified manner, such as advice based on weather and physical condition, or emotional support. This can lead to problems such as users feeling anxious before going out and needing time to get ready. The present invention aims to solve these problems and provide a system that allows users to prepare for going out more efficiently and comfortably.

[2009] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: an imaging means for capturing an image of the user's body; an image analysis means for analyzing the image of the user captured by the imaging means and detecting stains, wrinkles, dust, and messy hair on the user's clothes; an advice generation means for generating appropriate advice for the user based on the detection results of the image analysis means; an audio output means for outputting the advice generated by the advice generation means as audio; an accessory advice means for advising the user on appropriate accessory colors based on color information of the user's clothing analyzed by the image analysis means; and an emotion recognition means for acquiring the user's voice and facial expression, analyzing the user's emotions using emotion recognition means, and adjusting the content and tone of the advice based on the recognized emotions. This improves the efficiency of the user's preparations for going out and enables appropriate advice to be provided according to individual needs and emotions.

[2010] "Photographing means" refers to a device for photographing the user's body.

[2011] The "image analysis means" is a device or software that analyzes the image of the user captured by the image capture means and detects stains, wrinkles, dust, and messy hair on the clothes.

[2012] The "advice generating means" is a device or software for generating appropriate advice for the user based on the detection results of the image analyzing means.

[2013] The "audio output means" is a device or software for audibly outputting the advice generated by the advice generating means.

[2014] The "accessory advice means" is a device or software that advises on suitable accessory colors based on the color information of the user's clothing analyzed by the image analysis means.

[2015] "Emotion recognition means" refers to a device or software that acquires the user's voice and facial expressions and analyzes and recognizes their emotions.

[2016] The "weather forecast linking means" is a device or software that acquires weather forecast data based on the user's location information and generates advice for going out based on the weather forecast.

[2017] "Temperature measuring means" refers to a device for measuring the user's temperature.

[2018] The "physical condition evaluation means" is a device or software for evaluating the physical condition of the user based on the body temperature data measured by the body temperature measurement means.

[2019] The present invention is a system for helping users get ready to go out more efficiently, combining a photography unit, an image analysis unit, an advice generation unit, a voice output unit, an accessory advice unit, and an emotion recognition unit. This system can be applied to smart fitting rooms in apparel shops, in particular, to improve customer experience.

[2020] The main components of the system are:

[2021] 1. Photography Method:

[2022] When a user enters a fitting room, a camera installed in the fitting room automatically captures the user's entire body.

[2023] The captured image is sent to a server.

[2024] 2. Image analysis methods:

[2025] The server analyzes the received images using an image analysis algorithm (e.g., a model using TensorFlow).

[2026] It detects wrinkles and stains on clothes and messy hair and generates the necessary advice.

[2027] 3. Advice Generation Methods:

[2028] Based on the results obtained by the image analysis means, appropriate advice is automatically generated for the user.

[2029] For example: "There are wrinkles on the back. A steam iron would help."

[2030] 4. Audio output means:

[2031] The generated advice is communicated to the user via audio through a speaker in the fitting room.

[2032] Use a speech synthesis library such as Python's pyttsx3.

[2033] 5. Accessory advice:

[2034] Based on the color information of the user's clothing obtained through image analysis, the system advises on the appropriate color of accessories.

[2035] For example: "A silver necklace would go well with this outfit."

[2036] 6. Emotion recognition means:

[2037] It captures the user's facial expressions and voice and analyzes their emotions using an emotion recognition model.

[2038] If the user is anxious, they are given advice to help them relax.

[2039] For example: "Please relax and feel free to try things on."

[2040] 7. Weather forecast integration methods:

[2041] The server obtains weather forecast data based on the user's location information (using WeatherAPI, etc.).

[2042] Generate advice for going out based on weather forecasts.

[2043] For example: "It's raining outside, so I recommend a waterproof coat."

[2044] The specific hardware is a fitting room device equipped with a camera, speaker, and microphone. The software uses Python, OpenCV, TensorFlow, pyttsx3, etc. The fitting room camera captures the user's image, which is then sent to a server for analysis. Advice generated based on the analysis results is communicated to the user using audio output.

[2045] This system allows users to receive detailed advice when preparing to go out, enabling a stress-free shopping experience. It also has an emotion recognition function that can provide psychological support to users, improving customer satisfaction.

[2046] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2047] Step 1:

[2048] When a user enters a fitting room, the device uses a camera to take a full-body image of the user, which is then sent to the server as input for further processing.

[2049] Step 2:

[2050] The server analyzes the received full-body image using image analysis tools. Specifically, it uses image analysis models such as TensorFlow to detect dirt, wrinkles, dust, and messy hair on the clothes. The data obtained from this analysis becomes the input for the next process.

[2051] Step 3:

[2052] Based on the analysis results, the server uses the advice generation means to generate appropriate advice for the user. This advice generation includes the user's clothing status and detailed comments. The generated advice becomes the input for the next step.

[2053] Step 4:

[2054] The device communicates the generated advice to the user through a voice output means. Specifically, the advice is output as voice using a voice synthesis library such as Python's pyttsx3. The user receives this voice advice.

[2055] Step 5:

[2056] The server acquires color information of the user's clothing using the image analysis means, and advises the user on the appropriate accessory color using the accessory advice means. This advice is also conveyed to the user by the voice output means, and is output as advice to the user.

[2057] Step 6:

[2058] The user's facial expressions and voice are acquired by the device and analyzed by the emotion recognition means. Based on the analysis results, the server analyzes the user's emotions and generates advice on how to relax as needed. The advice generated by this emotion recognition is conveyed to the user by the voice output means.

[2059] Step 7:

[2060] The server uses the weather forecast linking means to acquire weather forecast data from the user's location information. Based on the acquired weather data, advice for going out is generated. This advice based on the weather forecast is also conveyed to the user by the voice output means.

[2061] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice 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 voice data.

[2062] 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.

[2063] 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 robot 414.

[2064] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2065] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2066] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2067] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2068] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2069] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2070] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2071] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2072] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2073] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2074] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2075] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2076] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2077] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2078] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2079] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2080] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2081] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2082] The following is further disclosed regarding the above embodiment.

[2083] (Claim 1)

[2084] To check the user's appearance before going out,

[2085] An imaging means for imaging the user's body;

[2086] an image analysis means for analyzing the image of the user photographed by the photographing means and detecting stains, wrinkles, dust, and messy hair on the clothes;

[2087] an advice generating means for generating appropriate advice for a user based on the detection result of the image analyzing means;

[2088] a voice output means for outputting the advice generated by the advice generating means by voice;

[2089] A system including:

[2090] (Claim 2)

[2091] 2. The system according to claim 1, further comprising a weather forecast linking means for acquiring weather forecast data based on the user's location information and generating advice for going out based on the weather forecast.

[2092] (Claim 3)

[2093] 2. The system according to claim 1, further comprising: a body temperature measuring means for measuring the body temperature of the user; and a physical condition evaluating means for evaluating the physical condition of the user based on the measured body temperature data.

[2094] (Claim 4)

[2095] 2. The system according to claim 1, further comprising a lost property confirmation means for checking lost property based on a previously registered lost property list of the user.

[2096] (Claim 5)

[2097] 10. The system of claim 1, further comprising an accessory advice means for analyzing color information of a user's clothing and generating suitable accessory colors.

[2098] "Example 1"

[2099] (Claim 1)

[2100] To check the user's appearance before going out,

[2101] An imaging means for imaging the user's body;

[2102] an image analysis means for analyzing the image of the user photographed by the photographing means and detecting stains, wrinkles, dust, and messy hair on the clothes;

[2103] an advice generating means for generating appropriate advice for a user based on the detection result of the image analyzing means;

[2104] a voice output means for outputting the advice generated by the advice generating means by voice;

[2105] a weather forecast linking means for acquiring weather forecast data based on the user's location information and generating advice for the user when going out based on the acquired weather forecast;

[2106] a temperature measuring means for measuring the temperature of the user by outputting a voice prompt to prompt the user to measure the temperature;

[2107] A health assessment means for assessing the user's health condition based on the measured body temperature data and generating an alert if an abnormality is detected;

[2108] a lost property checking means for outputting a voice prompt to prompt the user to check their belongings;

[2109] an accessory advice unit that analyzes the user's clothing color information and generates color advice for suitable accessories;

[2110] A system including:

[2111] (Claim 2)

[2112] 10. The system of claim 1, further comprising a weather forecast cooperation means for generating advice for going out based on the weather forecast.

[2113] (Claim 3)

[2114] 2. The system according to claim 1, further comprising: a body temperature measuring means for measuring the body temperature of the user; and a physical condition evaluating means for evaluating the physical condition of the user based on the measured body temperature data.

[2115] "Application Example 1"

[2116] (Claim 1)

[2117] To check the user's appearance before going out,

[2118] An imaging means for imaging the user's body;

[2119] an image analysis means for analyzing the image of the user photographed by the photographing means and detecting stains, wrinkles, dust, and messy hair on the clothes;

[2120] an advice generating means for generating appropriate advice for a user based on the detection result of the image analyzing means;

[2121] a voice output means for outputting the advice generated by the advice generating means by voice;

[2122] To streamline work preparation for factory workers, we check their equipment and take their temperatures.

[2123] a body temperature measuring means for measuring the body temperature of the user; and a physical condition evaluating means for evaluating the physical condition of the user based on the measured body temperature data;

[2124] an advice generating means for generating appropriate work preparation advice for a user based on the body temperature evaluation means;

[2125] A weather forecast integration means for acquiring weather forecast data based on the user's location information and generating advice for going out based on the weather forecast;

[2126] a lost item confirmation means that prompts the user to check their belongings based on a lost item checklist;

[2127] A system including:

[2128] (Claim 2)

[2129] 2. The system according to claim 1, further comprising means for providing advice by voice based on the data generated by said weather forecast linking means.

[2130] (Claim 3)

[2131] The system of claim 1, further comprising hardware and software for implementing the image analysis, advice generation, voice output, temperature measurement, and lost item confirmation means as a factory robot.

[2132] "Example 2: Combining Emotion Engines"

[2133] (Claim 1)

[2134] To check the user's appearance before going out,

[2135] An imaging means for imaging the user's body;

[2136] an image analysis means for analyzing the image of the user photographed by the photographing means and detecting stains, wrinkles, dust, and messy hair on the clothes;

[2137] an advice generating means for generating appropriate advice for a user based on the detection result of the image analyzing means;

[2138] a voice output means for outputting the advice generated by the advice generating means by voice;

[2139] an emotion recognition means for acquiring a user's voice and facial expression and recognizing the user's emotion;

[2140] an advice generating means for adjusting the content and tone of advice based on the user's emotion recognized by the emotion recognition means;

[2141] A system including:

[2142] (Claim 2)

[2143] 2. The system according to claim 1, further comprising a weather forecast linking means for acquiring weather forecast data based on the user's location information and generating advice for going out based on the weather forecast.

[2144] (Claim 3)

[2145] The system according to claim 1, further comprising: a body temperature measuring means for measuring the body temperature of the user; a physical condition evaluating means for evaluating the physical condition of the user based on the measured body temperature data; and an audio output means for prompting the user to measure their body temperature.

[2146] "Application example 2 when combining emotion engines"

[2147] (Claim 1)

[2148] To check the user's appearance before going out,

[2149] An imaging means for imaging the user's body;

[2150] an image analysis means for analyzing the image of the user photographed by the photographing means and detecting stains, wrinkles, dust, and messy hair on the clothes;

[2151] an advice generating means for generating appropriate advice for a user based on the detection result of the image analyzing means;

[2152] a voice output means ...

Claims

1. To check the user's appearance before going out, An imaging means for imaging the user's body; an image analysis means for analyzing the image of the user photographed by the photographing means and detecting stains, wrinkles, dust, and messy hair on the clothes; an advice generating means for generating appropriate advice for a user based on the detection result of the image analyzing means; a voice output means for outputting the advice generated by the advice generating means by voice; A system including:

2. The system according to claim 1 , further comprising a weather forecast linking means for acquiring weather forecast data based on the user's location information and generating advice for going out based on the weather forecast.

3. 2. The system according to claim 1, further comprising: a body temperature measuring means for measuring the body temperature of the user; and a physical condition evaluating means for evaluating the physical condition of the user based on the measured body temperature data.

4. 2. The system according to claim 1, further comprising a lost property confirmation means for checking lost property based on a list of lost property of a user registered in advance.

5. The system according to claim 1 , further comprising an accessory advice means for analyzing color information of a user's clothing and generating suitable accessory colors.

Images