system

Abstract

To support achievement of a diet goal while suppressing useless expenditures by providing an appropriate diet plan corresponding to a health condition or a diet goal of a client.SOLUTION: A system includes: means for a client to input present height and weight and a diet goal; means for the client to submit a purchase receipt after shopping; means for correcting commodities that can be determined unnecessary in the shopping, on the basis of the height, weight and diet goal of the client which are inputted by the client; means for visualizing a saved sum of money, which can be saved if the unnecessary commodities are not bought, and an estimated weight reduction amount in a case where the commodities are not ingested; means for generating a prompt sentence instructing a proposal of a diet plan on the basis of the present height, weight and diet goal inputted by the client and proposing the diet plan using the generated prompt sentence and a generative AI model; and means for transmitting the diet plan and the information of the saved sum of money and the estimated weight reduction amount to a terminal of the client.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] Today, consumers need to select and purchase the foods they need based on their health and diet goals. However, these choices depend on individual knowledge and experience, making the right choice can often be difficult. Furthermore, purchasing unnecessary products results in unnecessary expenses, and many consumers feel a financial burden. [Means for solving the problem]

[0005] In this system, consumers enter their height, weight, and goals, and then submit their purchase receipt after shopping. The system then identifies items that are deemed unnecessary for that purchase and visualizes the money saved and weight loss that would result if the unnecessary items were not purchased. This allows consumers to select and purchase appropriate products that suit their health condition and diet goals, thereby reducing unnecessary spending. [Brief explanation of the drawings]

[0006] [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. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] 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.

[0008] First, the terms used in the following description will be explained.

[0009] 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, the 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), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] 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.

[0011] 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.

[0012] 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.

[0013] 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."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 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.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1" This embodiment of the present invention provides a dedicated input form as a means for consumers to enter their height, weight, and diet goals. This input form is provided on a website or smartphone application, and allows consumers to directly input their height, weight, diet goals, etc.

[0028] "Example 2" Next, as a means for consumers to submit their purchase receipts after shopping, the system provides a function for them to take an image of the receipt using their smartphone camera and upload it to the application. This function allows consumers to communicate purchase information to the system without having to submit a physical receipt directly.

[0029] "Example 3" Then, as a means of correcting items that are deemed unnecessary for this shopping trip, the system automatically detects unnecessary items based on the consumer's height, weight, and diet goal entered by the consumer, as well as the submitted receipt information. For example, if the diet goal is to "limit carbohydrates," the system will detect items on the receipt that are high in carbohydrates, such as "bread" and "sweets," as unnecessary items.

[0030] "Example 4" Finally, to visualize the money saved and weight lost by not purchasing unnecessary products, the system calculates the total cost of the detected unnecessary products and the estimated weight loss if those products were not consumed, and displays this information to consumers in the form of graphs, charts, etc. This allows consumers to concretely understand both their health management and savings.

[0031] The processing flow of each embodiment will be described below.

[0032] "Example 1"

[0033] Step 1: The consumer enters their height, weight, diet goal, etc. into a dedicated input form. For example, a height of 170 cm, weight of 65 kg, and diet goal of "restricting carbohydrates" may be entered.

[0034] Step 2: Once completed, the consumer presses the "Submit" button to send the information to the system.

[0035] "Example 2"

[0036] Step 1: The consumer makes a purchase and gets a receipt for the items purchased.

[0037] Step 2: The consumer takes a picture of the receipt using their smartphone camera.

[0038] Step 3: The captured image is uploaded to the application and the system reads the receipt information.

[0039] "Example 3"

[0040] Step 1: The system automatically detects unwanted products based on the consumer's height, weight, and goals entered, as well as the submitted receipt information.

[0041] Step 2: For example, if the diet goal is to "limit carbohydrates," the system will detect high-carbohydrate items on the receipt, such as "bread" and "sweets," as unnecessary items.

[0042] "Example 4"

[0043] Step 1: The system calculates the total value of the detected unwanted products and the estimated weight loss if the product was not consumed.

[0044] Step 2: The calculation results are displayed to the consumer in the form of graphs, charts, etc. This allows the consumer to concretely understand both their health management and savings.

[0045] Example 1

[0046] Next, a description will be given of Example 1 of Form 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."

[0047] Conventional diet support systems required users to not only input their height, weight, and diet goals, but also to submit purchase receipts after shopping and determine which items they no longer needed. However, these systems were time-consuming for users, making it difficult for them to use them continuously. In addition, they lacked the functionality to propose an appropriate individual diet plan based on the data entered by the user, which meant that they were unable to provide effective diet support.

[0048] 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.

[0049] In this invention, the server includes a means for the customer to enter their current height and weight and goals, a means for the customer to submit a purchase receipt after shopping, a means for correcting items that are determined to be unnecessary in this shopping trip, a means for visualizing the money saved and weight lost if the unnecessary items are not purchased, a means for receiving and saving the data entered by the customer, a means for generating prompts for the generative AI model based on the saved data, and a means for the generative AI model to suggest a diet plan.This allows the user to continue using the service without any hassle, and makes it possible to suggest an appropriate diet plan individually.

[0050] "Customer" refers to a user of the system.

[0051] "Height and Weight" refers to the customer's current height and weight data.

[0052] "Goals" refers to diet and health goals set by the Customer.

[0053] "Input form" refers to the interface through which customers enter data such as height, weight, and goals.

[0054] "Purchase Receipt" means a detailed statement of purchases received by a Customer after making a purchase.

[0055] "Means of correction" refers to the function of determining unnecessary products based on the customer's height, weight, and goals, and removing them from the list.

[0056] "Visualization means" refers to a function that visually displays the money you can save or the weight you will lose if you don't buy unnecessary products.

[0057] "Means of receiving and storing data" refers to the function by which the server receives data entered by the customer and stores it in a database, etc.

[0058] A "generative AI model" refers to an artificial intelligence model that generates an appropriate diet plan based on input data.

[0059] A "prompt sentence" refers to an instruction sentence generated for a generative AI model based on input data.

[0060] "Diet Plan" refers to a specific action plan proposed by the generative AI model to help customers achieve their goals.

[0061] This invention is a system that provides a dedicated input form for customers to enter their height, weight, and diet goals. The system is installed on a website or smartphone application, and a generative AI model proposes an appropriate diet plan based on the data entered by the customer.

[0062] Hardware and software used

[0063] Hardware: Servers (e.g., AWS (registered trademark) EC2), user devices (e.g., smartphones, PCs)

[0064] Software: Web servers (e.g., Apache (registered trademark), Nginx), databases (e.g., MySQL (registered trademark), PostgreSQL), smartphone applications (e.g., iOS apps, ANDROID (registered trademark) apps)

[0065] Specific operation of the system

[0066] server

[0067] The server provides a dedicated input form on a website or smartphone application, where customers can enter their height, weight, diet goals, etc. The server receives the input data and stores it in a database. The stored data is used as prompts for the generative AI model.

[0068] Terminal

[0069] The device displays the websites and smartphone applications that the user accesses. When the user enters their height, weight, and diet goals into an input form, the device sends the data to the server. The device then displays the data that the user has entered in real time, allowing them to check it.

[0070] User

[0071] Users access a website or smartphone application and enter their height, weight, and diet goals into a dedicated input form. Once the user has completed the input, the data is sent to the server. The user can then review the data they have entered and make any necessary corrections.

[0072] Specific examples

[0073] Example 1: Website use

[0074] A user visits a website and fills out a form with the following information:

[0075] Height: 170 cm Weight: 70 kg Diet goal: Lose 5 kg

[0076] Once the input is complete, the device sends this data to the server, which receives it and stores it in a database. The server then generates the following prompt for the generative AI model:

[0077] Example prompt sentence:

[0078] "The user is 170 cm tall, weighs 70 kg, and wants to lose 5 kg. Based on this information, please suggest an appropriate diet plan."

[0079] Example 2: Use in a smartphone application

[0080] A user opens a smartphone application and enters the following information into the input form:

[0081] Height: 160 cm Weight: 60 kg Diet goal: Lose 3 kg

[0082] Once the input is complete, the device sends this data to the server, which receives it and stores it in a database. The server then generates the following prompt for the generative AI model:

[0083] Example prompt sentence:

[0084] "The user is 160 cm tall, weighs 60 kg, and wants to lose 3 kg. Based on this information, please suggest an appropriate diet plan."

[0085] In this way, a system is constructed in which a generative AI model suggests an appropriate diet plan based on the data entered by the user.

[0086] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0087] Step 1:

[0088] The user accesses the input form.

[0089] A user opens a website or smartphone application and accesses an input form. The input form is an interface where the user can enter their height, weight, and diet goals. Once the input form is displayed, the user is ready to enter the required information.

[0090] Step 2:

[0091] The user enters the data.

[0092] The user enters their height, weight, and diet goal in the input form. For example, the user enters "Height: 170 cm", "Weight: 70 kg", and "Diet goal: Lose 5 kg". Once the input is complete, the user taps the "Submit" button. The input data is saved on the device in JSON format.

[0093] Step 3:

[0094] The device sends the data to the server.

[0095] The device sends the data entered by the user to the server. Specifically, the device uses an HTTP POST request to send the input data to the server. At this time, the data is sent in JSON format. The input data (height, weight, diet goal) is sent to the server.

[0096] Step 4:

[0097] The server receives and stores the data.

[0098] The server receives the data sent from the device. The received data is stored in a database. For example, the server connects to a MySQL database and executes the following SQL query:

[0099] sql

[0100] INSERT INTO user_data (height, weight, goal) VALUES (170, 70, '5 kg weight loss');

[0101] This process saves the user's input data in the database.

[0102] Step 5:

[0103] The server generates a prompt for the generative AI model.

[0104] The server generates prompts for the generative AI model based on the stored data. For example, it generates prompts like the following:

[0105] "The user is 170 cm tall, weighs 70 kg, and wants to lose 5 kg. Based on this information, please suggest an appropriate diet plan."

[0106] This prompt is sent to a generative AI model.

[0107] Step 6:

[0108] A generative AI model suggests diet plans.

[0109] The generative AI model generates a diet plan based on the prompt it receives. For example, the generative AI model might suggest the following diet plan:

[0110] 1. Do 30 minutes of aerobic exercise every day

[0111] 2. Limit your daily calorie intake to 1500 kcal

[0112] 3. Strength train three times a week

[0113] This diet plan is sent to the user's terminal via the server and displayed to the user.

[0114] In this way, a system is constructed in which a generative AI model suggests an appropriate diet plan based on the data entered by the user.

[0115] (Application example 1)

[0116] Next, a description will be given of Application Example 1 of Embodiment 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."

[0117] Conventional food delivery systems have difficulty providing meal plans based on customers' health conditions and diet goals, making it difficult to provide services tailored to individual needs. Furthermore, customers often end up buying unnecessary items, resulting in wasteful spending, and food choices that hinder the achievement of diet goals.

[0118] 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.

[0119] In this invention, the server includes a means for the customer to enter their current height and weight and goals, a means for the customer to submit a purchase receipt after shopping, a means for correcting items that are determined to be unnecessary in this shopping trip, a means for visualizing the money saved and weight lost if unnecessary items are not purchased, a means for generating an appropriate meal plan based on the customer's height, weight, and goals, and a means for presenting the generated meal plan to the customer. This makes it possible to provide an appropriate meal plan based on the customer's health condition and diet goals, and to support the achievement of the diet goals while reducing unnecessary spending.

[0120] "Customer" refers to the consumer who uses the service.

[0121] "Height and Weight" refers to the physical height and weight of the customer.

[0122] "Goals" refer to specific health or diet objectives that a customer wants to achieve.

[0123] "Purchase receipt" refers to a detailed list of purchases received by a customer when making a purchase.

[0124] "Means for correction" refers to a method or system for evaluating products purchased by customers and identifying unwanted products.

[0125] "Visualization tools" refers to methods or systems that visually display the money saved or weight lost.

[0126] "Meal Plan" refers to the meal content and schedule suggested based on the customer's health and diet goals.

[0127] "Means for generating" refers to a method or system for generating a meal plan based on customer input data.

[0128] "Presenting means" refers to a method or system for showing the generated meal plan to the customer.

[0129] The following system configuration is proposed as an embodiment of the present invention.

[0130] System Configuration

[0131] The system includes a smartphone application used by customers, a server, and a generative AI model. The smartphone application provides an interface for customers to input their height, weight, and diet goals. The server receives the input data and sends prompts to the generative AI model to generate an appropriate meal plan. The generated meal plan is then presented to the customer via the smartphone application.

[0132] Hardware and software used

[0133] Hardware: Smartphones, servers

[0134] Software: Smartphone applications, generative AI models (e.g., OpenAI® GPT-3®)

[0135] Data processing and calculation

[0136] 1. Data entry: Customers use a smartphone application to enter their height, weight, and diet goals.

[0137] 2. Data transmission: The smartphone application sends the entered data to the server.

[0138] 3. Prompt generation: Based on the data received by the server, a prompt sentence is generated to be sent to the generative AI model.

[0139] 4. Meal plan generation: The generative AI model receives the prompt and generates an appropriate meal plan.

[0140] 5. Data reception and presentation: The server receives the generated meal plan and presents it to the customer via the smartphone application.

[0141] Specific examples

[0142] For example, if a customer inputs their height as 170cm, weight as 70kg, and their diet goal as "lose 5kg," the server will send the following prompt to the generative AI model:

[0143] Prompt Sentence Examples

[0144] "Please suggest an appropriate meal plan based on height: 170 cm, weight: 70 kg, goal: to lose 5 kg."

[0145] Based on this prompt, the generative AI model generates a balanced meal plan, suggesting specific meal options such as "Breakfast - oatmeal, Lunch - salad, Dinner - chicken breast and vegetables." This meal plan is presented to the customer via a smartphone application.

[0146] In this way, it is possible to provide customers with appropriate meal plans according to their health condition and diet goals, helping them achieve their diet goals while reducing unnecessary spending.

[0147] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0148] Step 1:

[0149] A user starts a smartphone application and inputs their height, weight, and diet goal. The input data is temporarily saved in the smartphone application. An example of input data is a height of 170 cm, a weight of 70 kg, and a diet goal of "lose 5 kg."

[0150] Step 2:

[0151] The smartphone application sends the entered data, including the user's height, weight, and diet goal, to the server. The server analyzes the received data and proceeds to the next processing step.

[0152] Step 3:

[0153] The server generates a prompt based on the received data. Specifically, it combines the user's height, weight, and diet goal to create a prompt to send to the generative AI model. For example, the generated prompt might read, "Based on height: 170 cm, weight: 70 kg, goal: to lose 5 kg, please suggest an appropriate meal plan."

[0154] Step 4:

[0155] The server sends the generated prompt to the generative AI model, which then performs data calculations based on the received prompt and generates an appropriate meal plan. The generative AI model uses, for example, OpenAI GPT-3.

[0156] Step 5:

[0157] The generative AI model generates a meal plan based on the prompt and sends the result back to the server. An example of a generated meal plan is "Breakfast - oatmeal, Lunch - salad, Dinner - chicken breast and vegetables."

[0158] Step 6:

[0159] The server analyzes the meal plan received from the generative AI model and transmits it to the smartphone application, where the transmitted data includes the generated meal plan.

[0160] Step 7:

[0161] The smartphone application presents the meal plan received from the server to the user, who can then review and implement the proposed meal plan through the application.

[0162] Example 2

[0163] Next, a description will be given of Example 2 of Form 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."

[0164] In the previous system, customers had to physically submit receipts for their purchases, which was time-consuming and risked loss or damage. Furthermore, there were insufficient methods for identifying unnecessary purchases and visualizing savings and weight loss. This made it difficult for customers to effectively manage their shopping to achieve their goals.

[0165] 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.

[0166] In this invention, the server includes a means for the customer to enter their current height and weight and their goals, a means for the customer to take an image of their purchase receipt after shopping and upload it to the application so that they can submit it, a means for correcting items that are determined to be unnecessary in this purchase, and a means for visualizing the amount of money saved and the weight loss that would be achieved if they did not purchase the unnecessary items. This allows the customer to easily communicate their purchase information to the system without having to go through the trouble of submitting physical receipts. In addition, by identifying unnecessary items and visualizing the amount of money saved and the weight loss that would be achieved, the customer can effectively manage their shopping toward their goals.

[0167] "Customer" means an individual who uses the System to make purchases and manages purchase information.

[0168] "Height and Weight" refers to the customer's current physical height and weight.

[0169] "Goal" refers to a specific physical or financial goal that the client wishes to achieve.

[0170] "Purchase Receipt" means a paper or electronic record issued to a customer when they make a purchase that details the items purchased.

[0171] "Taking an image" refers to the act of taking a photo of a physical receipt using a device such as a smartphone or camera.

[0172] "Application" refers to a software program that runs on a device such as a smartphone or tablet.

[0173] "Uploading" refers to the act of sending a captured image to a server via the Internet.

[0174] "Server" refers to a computer system for receiving, processing, and storing data over a network.

[0175] "Analyzing an image" refers to the act of using image recognition technology to extract the contents of a photographed receipt as digital data.

[0176] "Unnecessary products" refer to products that are determined not to be necessary for the customer's goals.

[0177] "Savings" refers to the amount of money you can save by not purchasing unnecessary items.

[0178] "Weight loss" refers to the amount of weight loss you would expect if you didn't purchase unnecessary items.

[0179] "Visualizing" refers to the act of displaying data visually so that it can be easily understood by customers.

[0180] "Graphically displaying" refers to the act of displaying data in a visual format such as a graph or chart.

[0181] The present invention provides a system that allows customers to take pictures of their purchases after shopping and upload them to an application in order to submit a receipt. A specific embodiment of this system will be described below.

[0182] The user takes a picture of the purchase receipt using the camera on their smartphone. The image is then uploaded using a dedicated application (e.g., "ReceiptUploader"). The application has the function of sending the image taken by the user to a server.

[0183] The server receives the image of the receipt sent from the terminal. After receiving it, the server analyzes the contents of the receipt using image recognition software such as Google® Cloud Vision API. Optical character recognition (OCR) technology is used for the analysis, and information such as the product name, price, and purchase date and time written on the receipt is extracted.

[0184] The analyzed data is stored in a database by the server. The stored data includes the product name, price, purchase date and time, store name, etc. This allows the user's purchase history to be accumulated in the database.

[0185] Users can use the application to check their purchase history. By opening the "Purchase History" section in the application, data retrieved from the server is displayed. Users can view a list of past purchases.

[0186] As a concrete example, consider a scenario where a user has just finished shopping at a supermarket. The user takes a picture of the receipt using their smartphone camera and opens the "ReceiptUploader" application. Within the application, the user taps the "Upload" button, selects the image of the receipt, and uploads it. The application sends the image to a server, which uses the Google Cloud Vision API to analyze the contents of the receipt. The analyzed data is stored in a database, and the user can view recent purchases by opening the "Purchase History" section within the application.

[0187] Examples of prompts to be input to a generative AI model include:

[0188] "Please describe the functionality that allows users to take a picture of a receipt using their smartphone camera and upload it to your application. Please include the names of any specific hardware or software."

[0189] Using this prompt, the generative AI model can generate sentences that explain in detail the system's operations.

[0190] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0191] Step 1:

[0192] The user takes a picture of the receipt.

[0193] The user uses the smartphone camera to take a picture of the receipt for the item they purchased, taking care to capture the entire receipt clearly. The input is the physical receipt, and the output is a digital image.

[0194] Step 2:

[0195] The device uploads the image to the application.

[0196] The device (smartphone) uploads the captured image of the receipt to the "ReceiptUploader" application. The user opens the application, taps the "Upload" button, and selects the captured image. The input is a digital image, and the output is the transmission of image data to the server.

[0197] Step 3:

[0198] The server receives and analyzes the images.

[0199] The server receives the image of the receipt sent from the terminal. After receiving it, the server uses image recognition software such as Google Cloud Vision API to analyze the contents of the receipt. Optical character recognition (OCR) technology is used for the analysis, and information such as the product name, price, and purchase date and time written on the receipt is extracted. The input is image data, and the output is analyzed text data.

[0200] Step 4:

[0201] The server stores the analysis results in a database.

[0202] The server saves the analyzed data in a database. The saved data includes the product name, price, purchase date and time, store name, etc. This allows the user's purchase history to be accumulated in the database. The input is the analyzed text data, and the output is saved in the database.

[0203] Step 5:

[0204] The user checks their purchase history.

[0205] The user can use the "ReceiptUploader" application to check their purchase history. When they open the "Purchase History" section in the application, the data retrieved from the server is displayed. The user can view a list of past purchases. The input is the data retrieved from the database, and the output is what is displayed in the application.

[0206] (Application example 2)

[0207] Next, a description will be given of Application Example 2 of Form 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."

[0208] In conventional shopping systems, customers had to physically submit receipts for the products they purchased, which was time-consuming and made managing purchase information cumbersome. Furthermore, there was a lack of systems that could identify unnecessary products based on the customer's health goals and visualize the savings and health benefits.

[0209] The specific processing by the specific 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 a means for the customer to enter their current height and weight and goals, a means for the customer to take a photo of their purchase receipt with their smartphone camera after shopping and upload it to the application, a means for correcting items determined to be unnecessary for the current purchase, a means for visualizing the money saved and weight lost if the unnecessary items were not purchased, a means for analyzing the contents of the purchase receipt and automatically extracting purchase information, a means for rewarding points to the customer based on the extracted purchase information, and a means for allowing the rewarded points to be used for the next purchase. This eliminates the need for customers to submit physical receipts, simplifies management of purchase information, and enables visualization of point rewards and savings. Furthermore, unnecessary items can be identified based on the customer's health goals, and savings and health benefits can be visualized.

[0210] "Customer" means a consumer who purchases goods or services.

[0211] "Height and weight" is basic physical information that refers to the customer's physical height and weight.

[0212] A "goal" is a specific numerical value or state that a customer wants to achieve.

[0213] "Purchase Receipt" means a paper or electronic record detailing a transaction issued to a customer when they purchase goods.

[0214] A "smartphone" is a type of mobile phone that can connect to the Internet and use applications.

[0215] A "camera" is a device for taking pictures and videos.

[0216] An "application" is a software program that runs on a smartphone or computer.

[0217] "Uploading" is the act of transferring data from a local device to a server or cloud.

[0218] "Unnecessary products" are products that are deemed not necessary for the customer to achieve their goals.

[0219] "Correction" is the act of checking the content and making corrections or improvements.

[0220] "Money saved" is the amount of money you would save if you didn't buy the unnecessary item.

[0221] "Weight lost" is the weight lost as a result of not purchasing unnecessary items.

[0222] "Visualization" refers to the visual display of data or information.

[0223] "Analysis" is the act of examining data or information in detail to clarify its structure and meaning.

[0224] "Purchase information" is detailed information about the products purchased by the customer.

[0225] "Automatic extraction" means that the system extracts data without human intervention.

[0226] "Point redemption" refers to the act of giving points to customers according to the amount of their purchase.

[0227] "Can be used on next purchase" means that the customer can use the points the next time they purchase a product.

[0228] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail below with reference to the accompanying drawings.

[0229] First, a smartphone application is used by the customer to enter their current height, weight, and goals. The customer launches the application and inputs their height, weight, and goals. This registers the customer's health goals in the system.

[0230] Next, after shopping, customers are provided with a means to take a photo of their purchase receipt with their smartphone camera and upload it to the application. Customers take a photo of their receipt and use the upload function within the application to send the image to the server.

[0231] The server receives the uploaded receipt image and preprocesses it using OpenCV. Specifically, it converts the image to grayscale and performs binarization. Next, it uses pytesseract to extract text from the preprocessed image. It then analyzes and automatically extracts purchase information (product name, price, etc.) from the extracted text.

[0232] Based on the analyzed purchase information, a method is provided for redeeming points to customers. The server calculates the points according to the purchase amount and adds them to the customer's account. The redeemed points are managed within the application so that they can be used for the next purchase.

[0233] Furthermore, as a means of correcting items that may be deemed unnecessary for this shopping trip, an algorithm is implemented to determine unnecessary items based on the customer's height, weight, and goals. The server compares the purchase information with the customer's health goals to identify unnecessary items.

[0234] To visualize the money saved and weight lost by not buying unnecessary products, the server calculates and graphically displays the amount saved and weight lost, allowing customers to visually see the savings and health benefits.

[0235] As a concrete example, consider the case where a user purchases a drink at a convenience store, takes a photo of the receipt, and uploads it to the app. The app extracts "drink" and "150 yen" from the receipt and rewards 15 points. If the app determines that the drink is an unnecessary item based on the user's health goals, it displays the amount of money saved and the weight lost.

[0236] An example of a prompt for a generative AI model is:

[0237] "A user has uploaded an image of a receipt taken with their smartphone camera. Please create a program that extracts purchase information from this image and returns points. 10% of the purchase amount will be returned as points."

[0238] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0239] Step 1:

[0240] The user starts the smartphone application and inputs their current height, weight, and goals. The input data is temporarily saved in the application and sent to the server. The input data is used as the basis for setting the user's health goals.

[0241] Step 2:

[0242] After shopping, a user takes a photo of the purchase receipt with their smartphone camera and uploads it to the application. The captured receipt image is temporarily saved in the application and then sent to the server. The input data is the receipt image.

[0243] Step 3:

[0244] The server receives the uploaded receipt image and preprocesses it using OpenCV. Specifically, it converts the image to grayscale and performs binarization. The input data is the receipt image, and the output data is the preprocessed image.

[0245] Step 4:

[0246] The server extracts text from the preprocessed image using pytesseract. The input data is the preprocessed image, and the output data is the extracted text. Specifically, it uses OCR (Optical Character Recognition) technology to read the text information in the image.

[0247] Step 5:

[0248] The server analyzes and automatically extracts purchase information (product name, price, etc.) from the extracted text. The input data is the extracted text, and the output data is the analyzed purchase information. Specifically, the required information is extracted using a text analysis algorithm.

[0249] Step 6:

[0250] The server rewards the customer with points based on the analyzed purchase information. The input data is the analyzed purchase information, and the output data is the rewarded points. Specifically, the server calculates points based on the purchase amount and adds the points to the customer's account.

[0251] Step 7:

[0252] The server determines unnecessary products based on the customer's height, weight, and goals. The input data is the customer's health goals and purchase information, and the output data is a list of unnecessary products. Specifically, the server runs an algorithm that compares the health goals with the purchase information and identifies unnecessary products.

[0253] Step 8:

[0254] The server calculates the amount of money saved and the weight lost if you don't buy unnecessary items, and displays them graphically. The input data is a list of unnecessary items and their purchase information, and the output data is the amount saved and the weight lost. The specific operation is to calculate the savings and health benefits, and display them visually to the user.

[0255] Step 9:

[0256] The user uses the points they have earned on their next purchase. The input data is the points earned, and the output data is the balance after the points have been used. The specific operation is to use the points to discount the purchase amount and update the balance.

[0257] Example 3

[0258] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0259] Modern consumers find it difficult to balance health management and saving money. In particular, consumers who have diet or health goals have difficulty determining which products they do not need when shopping. In addition, there is a lack of means to specifically understand the amount of savings and health benefits they will achieve if they do not purchase unnecessary products. For this reason, a system that allows consumers to effectively manage their health and save money is needed.

[0260] The identification process by the identification processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes a means for a customer to enter their current height and weight and their goals, a means for the customer to submit a purchase receipt after shopping, a means for converting the submitted receipt information into text data using optical character recognition technology, a means for identifying unnecessary products based on the customer's height, weight, and goals, a means for calculating the amount of money saved and the weight lost if the unnecessary products are not purchased, and a means for graphically displaying the calculation results. This allows consumers to easily identify unnecessary products when shopping and specifically understand the amount of money saved and the health benefits.

[0261] "Customers" are consumers who use the system to manage their health and save money.

[0262] "Height and weight" are the customer's current physical measurements and are used as basic data for health management.

[0263] "Goals" are specific health and diet-related objectives set by customers, and include, for example, "restricting carbohydrates" and "restricting calories."

[0264] A "receipt" is a detailed list of purchased items that a customer receives after shopping, listing the item names and prices.

[0265] "Optical character recognition technology" is a technology that extracts character information from image data and is used to convert receipt images into text data.

[0266] "Text data" refers to character information converted using optical character recognition technology, and includes information such as product names and prices.

[0267] "Unnecessary products" are products that are determined not to be necessary to purchase from the perspective of health management or dieting, based on the customer's height, weight, and goals.

[0268] "Savings" is the total amount of money you can save by not purchasing unnecessary items.

[0269] "Weight loss" is the amount of weight loss predicted if the unnecessary product was not consumed.

[0270] "Displaying graphically" means displaying the calculation results in the form of a graph, chart, or the like to make them visually easy to understand.

[0271] MODE FOR CARRYING OUT THE INVENTION

[0272] The present invention is a system for enabling consumers to effectively manage their health and save money. A specific embodiment of this system will be described below.

[0273] System configuration

[0274] The system consists of the following major components:

[0275] 1. A device for users to input their height, weight, and goals

[0276] 2. A terminal where users can submit receipts after shopping

[0277] 3. Hardware and software for the server to receive and process data

[0278] Hardware and software used

[0279] Device: Mobile device such as a smartphone or tablet

[0280] Server: High-performance data processing server

[0281] OCR technology: Optical character recognition technology such as Google® Cloud Vision API

[0282] Database: A relational database such as MySQL or PostgreSQL

[0283] Data visualization libraries: D3.js, Chart.js, etc.

[0284] Program processing

[0285] The server receives the height, weight, and goal information entered by the user, as well as the submitted receipt. The server uses this data to process and calculate data to detect unwanted products. Specifically, the process is carried out as follows:

[0286] 1. Data reception and analysis:

[0287] The server receives the height, weight, and goal (e.g., carbohydrate restriction) entered by the user.

[0288] The server converts the information on the submitted receipt into text data using OCR technology.

[0289] 2. Unwanted product detection:

[0290] The server detects unnecessary products based on the goal. For example, if the goal is to "limit carbohydrates," the server lists products with high carbohydrate content, such as "bread" and "sweets," on the receipt as unnecessary products.

[0291] 3. Savings and Weight Loss Calculation:

[0292] The server calculates the total price of the detected unwanted items.

[0293] The server calculates the estimated weight loss that would occur if the unnecessary products were not consumed.

[0294] 4. Visualizing the results:

[0295] The server displays the calculation results to the consumer in the form of graphs, charts, etc.

[0296] Specific examples

[0297] Suppose a user is 170 cm tall, weighs 70 kg, sets their goal to "restrict carbohydrates," and submits a receipt. The receipt includes "bread (300 yen)," "sweets (200 yen)," and "vegetables (100 yen)." The system detects "bread" and "sweets" as unnecessary items and calculates that a total of 500 yen can be saved. The system also calculates the estimated weight loss if these items were not consumed as 0.5 kg and displays this in a graph.

[0298] Prompt Sentence Examples

[0299] "Height 170cm, weight 70kg, goal is carbohydrate restriction. Please detect unnecessary items based on the following receipt information and calculate the amount saved and weight loss. Receipt information: bread (300 yen), sweets (200 yen), vegetables (100 yen)." The flow of the identification process in Example 3 will be explained using Figure 15.

[0300] Step 1:

[0301] The user enters their height, weight, and goal, and submits a receipt.

[0302] Input: The user opens the app on their smartphone and enters their height (170 cm), weight (70 kg), and goal ("carbohydrate restriction"). After shopping, they also take a photo of their receipt with their smartphone camera and upload it to the server via the app.

[0303] Output: The user's input data and the receipt image are sent to the server.

[0304] Step 2:

[0305] The server receives the input data and receipt information.

[0306] Input: Height, weight, goal, and receipt image submitted by the user.

[0307] Output: User input data and receipt image stored in a database on the server.

[0308] Step 3:

[0309] The server converts the receipt information into text data using OCR technology.

[0310] Input: Receipt image stored on the server.

[0311] Data processing: The server calls the Google Cloud Vision API, analyzes the receipt image, and extracts the product name and price.

[0312] Output: Converted text data (e.g., "Bread (300 yen)", "Sweets (200 yen)", "Vegetables (100 yen)").

[0313] Step 4:

[0314] The server detects unwanted items based on the target.

[0315] Input: User goal (e.g., "Limit carbohydrate intake") and converted text data.

[0316] Data calculation: The server performs rule-based filtering based on predefined food categories and goals to list unwanted products.

[0317] Output: A list of unwanted products (e.g. "bread", "sweets").

[0318] Step 5:

[0319] The server calculates the total price of unwanted items and the estimated weight loss.

[0320] Input: A list of unwanted items and their respective prices.

[0321] Data calculation: The server calculates the total price of unnecessary products and the estimated weight loss if unnecessary products were not consumed. The model used here is a simulation model based on the relationship between calorie consumption and weight loss.

[0322] Output: Amount saved (e.g., 500 yen) and estimated weight loss (e.g., 0.5 kg).

[0323] Step 6:

[0324] The server visualizes the calculation results in graphs and charts and displays them to the user.

[0325] Input: Amount saved and estimated weight loss.

[0326] Data processing: The server uses data visualization libraries such as D3.js and Chart.js to visualize the calculation results in graphs and charts.

[0327] Output: Graphs and charts displayed on the user's device.

[0328] (Application example 3)

[0329] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0330] Modern consumers find it difficult to manage their health and save money at the same time. In particular, consumers with dietary goals need to identify unnecessary products among their purchases and avoid them to achieve health and financial benefits. However, doing this manually is time-consuming and inaccurate. Therefore, a system is needed that allows consumers to easily identify unnecessary products and efficiently manage their savings and health.

[0331] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0332] In this invention, the server includes a means for a customer to enter their current height and weight and goals, a means for the customer to submit a purchase receipt after shopping, a means for correcting items determined to be unnecessary in this purchase, a means for visualizing the money saved and weight lost if unnecessary items are not purchased, a means for analyzing receipt information and automatically detecting unnecessary items based on diet goals, a means for calculating the amount of money saved and estimated weight loss if unnecessary items are not purchased and displaying them in graphs and charts, and an application installed on a smartphone. This allows consumers to easily identify unnecessary items and efficiently save money and manage their health.

[0333] "Customer" refers to the consumer who uses the system.

[0334] "Height and Weight" is data indicating the physical height and weight of a customer.

[0335] "Goals" refer to specific health or diet-related objectives that a customer wants to achieve.

[0336] A "purchase receipt" is paper or electronic data showing the purchase details of a product that a customer receives when making a purchase.

[0337] "Unwanted products" refer to products that are deemed inappropriate or unnecessary for the customer's goals.

[0338] "Money saved" refers to the amount of money you would save if you didn't buy unnecessary items.

[0339] "Weight loss" refers to the amount of weight loss predicted if the unnecessary product was not consumed.

[0340] "Receipt information" refers to data such as the product name, price, and quantity listed on the purchase receipt.

[0341] "Diet Goal" means a health goal set by a customer, such as weight loss or specific nutritional restrictions.

[0342] "Automatically detect" means that the system programmatically identifies unwanted products without human intervention.

[0343] "Graphs and charts" refer to diagrams that visually display data.

[0344] "Applications installed on a smartphone" refers to software programs that run on a smartphone.

[0345] The present invention is a system for enabling consumers to efficiently manage their health and save money. Specific embodiments for implementing this system will be described below.

[0346] System configuration

[0347] The system consists of the following main components:

[0348] 1. User device: A mobile device such as a smartphone.

[0349] 2. Server: A central server that processes and analyzes data.

[0350] 3. Application: A dedicated application installed on a smartphone.

[0351] Program processing

[0352] User Device

[0353] The user terminal has the following features:

[0354] User information input: Users enter their height, weight, and diet goals through the application.

[0355] Receipt scanning: The user scans the receipt for the purchased item with their smartphone camera and obtains the image data.

[0356] server

[0357] The server does the following:

[0358] Receipt information analysis: The acquired receipt image is converted into text data using OCR (Optical Character Recognition) technology. This process is performed using the pytesseract library.

[0359] Detection of unnecessary products: Based on the user's diet goal, the system automatically detects unnecessary products from the text data of the receipt. For example, for a user who is trying to limit their carbohydrate intake, the system detects high-carbohydrate products such as "bread" and "sweets."

[0360] Calculation of savings and weight loss: The total cost of the detected unnecessary products and the estimated weight loss if you did not consume those products are calculated. The weight loss calculation is based on the calories required to lose 1 kg of weight (approximately 7700 kcal).

[0361] application

[0362] The application has the following features:

[0363] Visualization of results: The calculated savings and estimated weight loss are displayed in graphs and charts, allowing users to visually see the effects of their health management and savings.

[0364] Specific examples

[0365] For example, if a user sets a goal of "restricting carbohydrates" and the receipt includes "bread" and "sweets," these items will be detected as unnecessary products. Let's say the total amount of the detected unnecessary products is 500 yen, and the estimated weight loss is 0.2 kg.

[0366] Prompt Sentence Examples

[0367] Enter your user information:

[0368] Height: 170 cm Weight: 70 kg Diet goal: Carbohydrate restriction

[0369] Scan your receipt:

[0370] (Upload a receipt image)

[0371] Detecting unwanted items...

[0372] Detected unwanted items:

[0373] Bread: 200 yen Sweets: 300 yen Savings: 500 yen

[0374] Estimated weight loss: 0.2kg

[0375] The results are displayed in a graph.

[0376] In this way, users can easily identify unnecessary products and efficiently save money and manage their health.

[0377] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0378] Step 1:

[0379] The user launches the smartphone application and enters their height, weight, and diet goals.

[0380] Input: User's height, weight, and diet goal

[0381] Output: User information data

[0382] Specific operation: The user enters their height, weight, and diet goal (e.g., carbohydrate restriction) into the application's input form and presses the submit button. This generates user information data and sends it to the server.

[0383] Step 2:

[0384] After shopping, the user scans the receipt for the purchased items with the smartphone camera.

[0385] Input: Receipt image

[0386] Output: Receipt image data

[0387] Specific operation: The user takes a photo of the purchase receipt using the camera function in the application. The captured image of the receipt is saved in the application and sent to the server.

[0388] Step 3:

[0389] The server receives the receipt image and converts it into text data using OCR technology.

[0390] Input: Receipt image data

[0391] Output: Receipt text data

[0392] Specific operation: The server uses the pytesseract library to extract text from the received receipt image data. The extracted text data is saved as receipt text data.

[0393] Step 4:

[0394] The server automatically detects unnecessary products from receipt text data based on the user's diet goal.

[0395] Input: User information data, receipt text data

[0396] Output: List of unwanted items

[0397] Specific operation: The server analyzes the receipt text data based on the user's diet goal (e.g., carbohydrate restriction). It lists products containing specific keywords (e.g., "bread" or "sweets") as unwanted items.

[0398] Step 5:

[0399] The server calculates the amount of money saved and the estimated weight loss if unnecessary items are not purchased.

[0400] Input: List of unwanted items

[0401] Output: Money saved, estimated weight loss

[0402] Specific operation: The server calculates the savings amount by adding up the prices of each product based on the list of unwanted products. It also calculates the estimated weight loss amount based on the calorie information of each product. The weight loss amount is calculated based on the calories required to lose 1 kg (approximately 7700 kcal).

[0403] Step 6:

[0404] The server visualizes the calculation results in graphs and charts and displays them on the user's smartphone.

[0405] Input: Amount saved, Estimated weight loss

[0406] Output: Image data of graphs and charts

[0407] Specific operation: Based on the calculation results, the server generates graphs and charts showing the savings and estimated weight loss. Image data of the generated graphs and charts is sent to the user's smartphone and displayed within the application.

[0408] In this way, users can easily identify unnecessary products and efficiently save money and manage their health.

[0409] 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.

[0410] "Example 1"

[0411] As one embodiment of the present invention, a system incorporating an emotion engine is provided. This system recognizes the user's emotions and determines unnecessary products based on the emotions. Specifically, when a user is feeling stressed, the system can prevent the user from purchasing unhealthy foods such as sweets.

[0412] It also recommends healthy foods when the user is relaxing.

[0413] "Example 2"

[0414] Furthermore, the emotion engine graphically displays the amount of money saved and weight lost based on the user's emotions. Specifically, it displays the amount of money saved and the amount of weight lost if the user refrains from buying unnecessary products when feeling stressed. This allows users to visually understand the relationship between their emotions, health management, and saving money.

[0415] "Example 3"

[0416] For example, if a user buys chocolate when they are stressed, the emotion engine will detect it as an unnecessary item and display a graph of the amount of money saved and weight lost if they had not bought the chocolate. This helps users recognize their tendency to buy unhealthy foods when they are stressed and understand the resulting financial and health impacts.

[0417] The processing flow of each embodiment will be described below.

[0418] "Example 1"

[0419] Step 1: The user enters their current height, weight, and goal into the system.

[0420] Step 2: The user makes a purchase and submits the receipt to the system.

[0421] Step 3: The emotion engine recognizes the user's emotion.

[0422] Step 4: The emotion engine determines which products are unnecessary based on the user's emotions and notifies the user of the results.

[0423] "Example 2"

[0424] Step 1: The user enters their current height, weight, and goal into the system.

[0425] Step 2: The user makes a purchase and submits the receipt to the system.

[0426] Step 3: The emotion engine recognizes the user's emotion.

[0427] Step 4: The emotion engine graphically displays the money saved and weight lost based on the user's emotions.

[0428] "Example 3"

[0429] Step 1: Buy chocolate when the user is feeling stressed.

[0430] Step 2: The emotion engine recognizes the user's emotions and detects chocolate as an unwanted product.

[0431] Step 3: The emotion engine will display a graph of the amount of money saved and the amount of weight lost if you don't buy the chocolate.

[0432] Example 1

[0433] Next, a description will be given of Example 1 of Form 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."

[0434] The previous system provided a way for customers to enter their height, weight, and goals, and to submit purchase receipts after shopping, but it lacked the functionality to determine unnecessary products based on the customer's emotions and recommend healthy products. This made it difficult for customers to select appropriate products when they were stressed or relaxed. There was also insufficient means to visualize the money saved and weight lost by not purchasing unnecessary products. This made it difficult to raise customers' awareness of health management and saving money.

[0435] 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.

[0436] In this invention, the server includes a means for the customer to enter their current height and weight and goals, a means for the customer to submit a purchase receipt after shopping, a means for correcting items that are determined to be unnecessary in this purchase, a means for visualizing the money saved and weight lost if the unnecessary items are not purchased, a means for recognizing the customer's emotions and determining unnecessary items based on those emotions, and a means for recommending healthy products based on the customer's emotions. This enables the customer to select appropriate products according to their emotional state, thereby increasing their awareness of health management and saving money.

[0437] "Customer" refers to an individual who uses the system to enter their height, weight, and diet goals, and then submits a purchase receipt after shopping.

[0438] "Height and Weight" refers to the customer's current physical height and weight.

[0439] "Goals" refer to specific numbers or conditions related to dieting or health that a customer wants to achieve.

[0440] "Input means" refers to the interface through which customers input their height, weight, and goals into the system.

[0441] "Purchase receipt" refers to paper or electronic data containing details of the purchase of goods that a customer receives when making a purchase.

[0442] "Submission means" refers to the interface through which a customer submits a purchase receipt to the system.

[0443] "Correction means" refers to the function by which the system determines unnecessary products based on the customer's input data and emotional data and notifies the customer.

[0444] "Visualization means" refers to the system's ability to graphically display the amount of money saved and weight lost if unnecessary products are not purchased.

[0445] "Emotion recognition means" refers to the system's ability to analyze customer emotions and determine which products are unnecessary based on those emotions.

[0446] "Healthy product recommendation means" refers to the system's ability to recommend healthy products based on customer sentiment.

[0447] This invention is a system that provides a dedicated input form for customers to enter their height, weight, and diet goals. This system is installed on a website or smartphone application, and allows customers to directly input their height, weight, diet goals, etc. In addition, by combining it with an emotion engine, it has the function of determining unnecessary products based on the customer's emotions and recommending healthy products.

[0448] The server places an input form on a website or smartphone application. This input form is created using HTML and CSS, and input data is validated in real time using JavaScript (registered trademark). When a user enters data into the input form, the server receives the data and stores it in a database (e.g., MySQL or PostgreSQL).

[0449] Next, the server uses an emotion engine (for example, Microsoft® Azure® Emotion API or Google Cloud's Natural Language API) to analyze the user's emotions. The emotion engine recognizes the user's current emotions based on the user's input data and past behavioral data. For example, if the user is feeling stressed, the server will use that information to determine that unhealthy foods such as sweets are unnecessary. On the other hand, if the user is relaxed, the server will recommend healthy foods.

[0450] As a concrete example, suppose a user uses a smartphone application to input their height as 170 cm, weight as 70 kg, and diet goal as "lose 5 kg." This data is sent to the server and stored in a database. The emotion engine then analyzes the user's emotions, and if it determines that the user is feeling stressed, the server displays a message such as "Avoid sweets such as chocolate and cookies."

[0451] Example prompts to input to a generative AI model:

[0452] A user enters their height as 170cm, weight as 70kg, and their diet goal as "lose 5kg." The emotion engine analyzes the user's emotions and determines that the user is feeling stressed. In this case, what products will be deemed unnecessary and what products will be recommended?

[0453] By inputting this prompt into a generative AI model, specific product recommendations and a determination of unnecessary products can be obtained. In this way, the system can make appropriate product recommendations based on the user's input data and emotional data.

[0454] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0455] Step 1:

[0456] The user accesses the input form.

[0457] A user opens a website or smartphone application. The device sends a request to the server through the browser or application to retrieve an input form. The server generates the input form using HTML and CSS and sends it to the device. The device renders the received HTML and CSS and displays the input form to the user.

[0458] Input: User's access request

[0459] Output: Display of input form

[0460] Step 2:

[0461] The user inputs their height, weight, and diet goal.

[0462] The user enters their height, weight, and diet goals into the displayed input form. The device uses JavaScript to validate the input data format in real time to ensure there are no errors.

[0463] Input: User's height, weight, and diet goal

[0464] Output: Validated input data

[0465] Step 3:

[0466] The server receives the input data and stores it in a database.

[0467] When the user presses the send button, the device sends the input data in JSON format to the server. The server parses the received data and saves it in a MySQL database. Specifically, it adds the data to the database using the INSERT statement.

[0468] Input: Input data in JSON format

[0469] Output: Data stored in the database

[0470] Step 4:

[0471] The server invokes the emotion engine to analyze the user's emotions.

[0472] The server calls an emotion engine (such as Microsoft Azure's Emotion API or Google Cloud's Natural Language API) based on the stored data. The data is sent to the API, which analyzes the user's emotions. The API determines that the user is feeling stressed and returns the result to the server.

[0473] Input: Data stored in a database

[0474] Output: Sentiment analysis results from the sentiment engine

[0475] Step 5:

[0476] The server judges unnecessary products based on emotions and determines recommended products.

[0477] The server determines which products are unnecessary and which are recommended based on the emotional data obtained from the emotion engine. For example, if the user is feeling stressed, the server will determine that "you should avoid sweets such as chocolate and cookies" and recommend "healthy foods such as fruits and nuts."

[0478] Input: Sentiment analysis results from the sentiment engine

[0479] Output: List of unwanted and recommended products

[0480] Step 6:

[0481] The server displays the results to the user.

[0482] The server generates HTML to display the results of the decision to the user and sends it to the terminal. The terminal renders the received HTML and displays unwanted products and recommended products to the user. The user checks the displayed results and decides on their next action.

[0483] Input: List of unwanted and recommended products

[0484] Output: The result displayed to the user

[0485] (Application example 1)

[0486] Next, a description will be given of Application Example 1 of Embodiment 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."

[0487] Conventional food delivery systems do not recommend foods based on the user's health status or emotions, which can lead to unhealthy food choices when users are stressed. Furthermore, there is a lack of support for users to choose foods that are in line with their diet goals, making it difficult to diet effectively.

[0488] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes a means for the customer to enter their current height and weight and their goals, a means for the customer to submit a purchase receipt after shopping, a means for correcting products that are determined to be unnecessary in this shopping trip, a means for visualizing the money saved and weight lost if the unnecessary products are not purchased, and a means for recognizing the customer's emotions and determining unnecessary products based on those emotions. This makes it possible to recommend foods based on the user's health condition and emotions, allowing the user to avoid unhealthy foods when feeling stressed and to select foods that are in line with their diet goals.

[0489] "Customer" refers to a consumer who uses a service or product.

[0490] "Height and weight" is a numerical value that indicates an individual's physical height and weight.

[0491] A "goal" is a specific objective or state that a customer wants to achieve.

[0492] A "purchase receipt" is a paper or electronic record of a transaction issued when a customer purchases a product.

[0493] "Unnecessary products" are products that are deemed inappropriate for a customer's health condition or goals.

[0494] "Money saved" refers to the amount of money you would save if you didn't buy unnecessary items.

[0495] "Weight Loss" is a numerical value that represents the weight loss a customer can achieve by avoiding unnecessary products.

[0496] "Emotion recognition means" refers to technology or devices that detect a customer's emotional state and make decisions based on that.

[0497] "Visualization tools" refers to technologies or devices that visually display the money saved or weight lost.

[0498] The system for implementing this invention is configured as follows: First, a dedicated form is provided for users to enter their height, weight, and diet goals. This form is provided on a website or smartphone application, allowing users to easily enter information.

[0499] Next, we present a system that combines an emotion engine. This system recognizes the user's emotions in real time and determines which products are unnecessary based on those emotions. Specifically, when the user is feeling stressed, it detects unhealthy foods such as sweets as unnecessary products, and when the user is relaxed, it recommends healthy foods.

[0500] The following hardware and software are used to implement this system:

[0501] Hardware: Smartphone, tablet, or PC

[0502] Software: Python, EmotionRecognizer library, FoodRecommender library

[0503] The server receives the user's input data of height, weight, and diet goal, recognizes the user's emotions in real time using the EmotionRecognizer library, and then recommends appropriate foods based on the user's input data and the recognized emotions using the FoodRecommender library.

[0504] For example, if a user inputs that they are 170cm tall, weigh 65kg, and their diet goal is to "lose weight," and the emotion engine recognizes that the user is feeling stressed, the system will avoid unhealthy foods (e.g., sweet snacks) and instead recommend healthy foods (e.g., salads and fruit).

[0505] An example of a prompt is as follows:

[0506] "If a user inputs that they are 170cm tall, weigh 65kg, and their diet goal is to lose weight, and the emotion engine recognizes that the user is stressed, what foods will be recommended?"

[0507] In this way, food recommendations can be made based on the user's health status and emotions, helping users avoid unhealthy foods when they are stressed and choosing foods that are in line with their diet goals.

[0508] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0509] Step 1:

[0510] The user uses the terminal to input their height, weight, and diet goal. The input data is sent to the server. The input data includes the user's height (e.g., 170 cm), weight (e.g., 65 kg), and diet goal (e.g., "lose weight").

[0511] Step 2:

[0512] The server stores the received user input data and uses the EmotionRecognizer library to recognize the user's emotions in real time. For emotion recognition, the user's facial expressions and voice data are used as input. The output is the user's emotional state (e.g., stressed, relaxed).

[0513] Step 3:

[0514] The server uses the FoodRecommender library to recommend appropriate foods based on the recognized emotional state and the user's input data. The input data includes the user's height, weight, diet goal, and emotional state. The output is a list of recommended foods (e.g., salads, fruits).

[0515] Step 4:

[0516] The server sends the recommended food list to the user's device, where the user can check the recommended food list on the device. Specifically, if the user is feeling stressed, the system will avoid unhealthy foods and recommend healthy foods.

[0517] Step 5:

[0518] A user makes a purchase and submits the purchase receipt to the server using a terminal. The server analyzes the submitted receipt data and generates a list of the purchased items. Input data includes receipt images or electronic data. The output is a list of the purchased items.

[0519] Step 6:

[0520] The server compares the list of purchased items with the user's diet goals and emotional state to determine which items are unnecessary. Specifically, it detects items that are inappropriate for the user's goals (e.g., sweet snacks). Input data includes the list of purchased items, the user's diet goals, and the user's emotional state. The output is a list of unnecessary items.

[0521] Step 7:

[0522] The server calculates and visualizes the money saved and weight lost if unnecessary items are not purchased. Specifically, it graphically displays the amount saved and weight lost. The input data includes a list of unnecessary items. The output is a graphical representation of the amount saved and weight lost.

[0523] Step 8:

[0524] The server sends the visualized data to the user's device, where the user can check the amount of money saved and the weight loss achieved. Specifically, the user can visually understand the benefits of avoiding unnecessary products.

[0525] Example 2

[0526] Next, a description will be given of Example 2 of Form 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."

[0527] Conventional health management systems have the problem that customers have to submit physical proof of purchase after shopping, which is time-consuming.In addition, the system does not take into account the customer's emotional state to visualize the amount of savings or weight loss, making it difficult for customers to understand the relationship between their emotions, health management, and savings.

[0528] 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.

[0529] In this invention, the server includes: means for the customer to enter their current physical information and goals; means for the customer to submit a proof of purchase after shopping; means for the customer to take an image of the proof of purchase using the image capture function of their mobile device and upload it to the application; means for the server to convert the contents of the proof of purchase into text data using image processing technology; means for the server to save the converted text data; means for the customer to input emotional data; means for the server to analyze the customer's emotional data using emotion analysis technology; means for the server to determine unnecessary products based on the analysis results and calculate the amount of savings and weight loss; and means for the server to graphically display the calculation results. This allows customers to communicate their purchase information to the system without directly submitting a physical proof of purchase, and further enables them to visually understand the relationship between their emotions, health management, and savings.

[0530] "Customer" refers to an individual who uses the system to manage their own health and save money.

[0531] "Physical information" refers to physical data such as a customer's height, weight, and body fat percentage.

[0532] "Goals" refer to the health or savings goals the customer wants to achieve.

[0533] "Proof of purchase" refers to a document that proves a purchase, such as a receipt or invoice, that a customer receives after shopping.

[0534] "Mobile device" refers to a portable electronic device such as a smartphone or tablet.

[0535] "Photography function" refers to the camera function installed in the mobile terminal.

[0536] "Application" refers to a software program that runs on a mobile device.

[0537] "Image processing technology" refers to the technology of analyzing image data and extracting necessary information.

[0538] "Text data" refers to character information extracted using image processing technology.

[0539] "Emotional data" refers to data that indicates a customer's emotional state.

[0540] "Emotion analysis technology" refers to technology that analyzes emotional data and evaluates a customer's emotional state.

[0541] "Unnecessary products" are products that are determined not to be necessary for a customer's health or savings goals.

[0542] "Savings" refers to the amount of money you can save by not purchasing unnecessary items.

[0543] "Weight lost" refers to the weight you would lose if you didn't purchase unnecessary items.

[0544] "Displaying graphically" refers to displaying the calculation results in a visually easy-to-understand manner.

[0545] MODE FOR CARRYING OUT THE INVENTION

[0546] This invention is a system in which a customer submits a purchase certificate after shopping and visualizes the amount of savings and weight loss based on emotion data. A specific embodiment of this system will be described below.

[0547] System configuration

[0548] This system mainly uses the following hardware and software:

[0549] Mobile devices (smartphones and tablets)

[0550] Camera features

[0551] application

[0552] server

[0553] Image processing software (e.g., OpenCV, Tesseract)

[0554] Emotion analysis technology

[0555] Program processing

[0556] After shopping, the user takes a picture of the purchase certificate using the camera function of their mobile device. The image is then uploaded to the server via the application. The server then uses image processing software (e.g., OpenCV or Tesseract) to extract the text from the image and convert information such as the name, price, and quantity of the purchased item into text data. The server then stores this text data in a database.

[0557] Next, the user inputs their emotional data through the application. The emotional data may be entered manually by the user or automatically obtained from the wearable device. The server then analyzes the emotional data using emotion analysis technology to evaluate whether the user is feeling stressed and to what extent.

[0558] Based on the results of the emotion analysis, the server calculates the amount of money saved and the amount of weight lost if the user refrains from buying unnecessary items when feeling stressed. For example, if the user refrains from buying chocolate when feeling stressed, the calculation is based on the price (200 yen) and calories (300 kcal). The calculation results are displayed graphically by the server, and the user can check them through the application.

[0559] Specific examples

[0560] As a concrete example, consider the case where a user refrains from buying chocolate when they are feeling stressed. The user takes a photo of the receipt with their smartphone camera and uploads it to an application. The server uses image processing software to convert the contents of the receipt into text data and stores it in a database. Next, the user enters emotional data into the application, which the server analyzes using emotion analysis technology. Based on the analysis results, the server calculates the amount of savings and weight loss based on the price (200 yen) and calories (300 kcal) of the chocolate. Finally, the server displays the calculation results graphically, and the user can check them through the application.

[0561] Prompt Sentence Examples

[0562] Example prompts to input to a generative AI model:

[0563] "Generate a program that calculates and graphically displays the amount of money saved and weight lost if the user avoids buying unnecessary items when they are stressed."

[0564] In this way, users can visually understand the relationship between their emotions, health management, and savings.

[0565] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0566] Step 1:

[0567] The user takes a photo of the proof of purchase using their smartphone camera.

[0568] Input: Proof of purchase

[0569] Output: Image of proof of purchase

[0570] Specific operation: The user activates the smartphone camera, frames the purchase certificate, and presses the capture button. The captured image is saved in the smartphone's gallery.

[0571] Step 2:

[0572] The device takes a picture of the proof of purchase and uploads it to the application.

[0573] Input: Image of proof of purchase

[0574] Output: Image data sent to the server

[0575] Specific operation: The user starts the application, selects an image of the purchase certificate, and presses the upload button. The device then sends the selected image to the server.

[0576] Step 3:

[0577] The server uses image processing technology to convert the contents of the purchase certificate into text data.

[0578] Input: Image data of purchase certificate

[0579] Output: Text data

[0580] Specific operation: The server analyzes the received image data using image processing software (e.g., OpenCV, Tesseract) and extracts text information from the image. The extracted text information is converted into text data such as the name, price, and quantity of the purchased item.

[0581] Step 4:

[0582] The server stores the converted text data in a database.

[0583] Input: Text data

[0584] Output: Purchase information stored in a database

[0585] Specific operation: The server saves the converted text data in a database, including the purchase date and time, store name, product information, etc.

[0586] Step 5:

[0587] The user inputs emotion data into the application.

[0588] Input: Emotion data

[0589] Output: Emotion data sent to the server

[0590] How it works: Users input their emotional state through the application. Emotional data includes information such as stress level and mood, and may also be automatically obtained from a wearable device.

[0591] Step 6:

[0592] The server analyzes the user's emotional data using emotion analysis technology.

[0593] Input: Emotion data

[0594] Output: Analysis results

[0595] Specific operation: The server analyzes the emotional data using emotion analysis technology to evaluate whether the user is feeling stressed and how stressed they are. The analysis results are displayed as numbers and graphs.

[0596] Step 7:

[0597] The server determines unnecessary products based on the analysis results and calculates the amount of money saved and the weight lost.

[0598] Input: Analysis results, text data

[0599] Output: Data on savings and weight loss

[0600] Specific operation: Based on the results of emotion analysis and purchase information, the server calculates the amount of money saved and the amount of weight lost if the user does not buy unnecessary products when feeling stressed. For example, it calculates the amount of money saved and the amount of weight lost based on the price (200 yen) and calories (300 kcal) of chocolate.

[0601] Step 8:

[0602] The server displays the calculation results graphically.

[0603] Input: Data on savings and weight loss

[0604] Output: Graphical display

[0605] Specific operation: The server generates data for graphically displaying the calculation results and provides it to the user through the application, allowing the user to visually check the amount of savings and weight loss through the application.

[0606] (Application example 2)

[0607] Next, a description will be given of Application Example 2 of Form 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."

[0608] Conventional shopping support systems require customers to physically submit receipts for purchased items, which is a time-consuming process. Furthermore, the system does not take into consideration the customer's emotions or health status, leading to unnecessary purchases when they are stressed. This leads to wasteful spending and negative health effects, which is an issue.

[0609] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0610] In this invention, the server includes a means for the customer to enter their current height and weight and goals, a means for the customer to take a photo of their purchase receipt using their smartphone camera after shopping and upload it to the application, a means for correcting items that are determined to be unnecessary in this purchase, a means for visualizing the money saved and weight lost if the customer does not buy unnecessary items, and a means for analyzing the customer's emotions and graphically displaying the amount of money saved and weight lost if the customer does not buy unnecessary items when they are feeling stressed. This saves the customer the trouble of submitting a physical receipt and enables shopping support that takes their emotions and health state into consideration.

[0611] A "customer" is a consumer who purchases goods or services.

[0612] "Height and Weight" refers to the customer's height and weight.

[0613] A "goal" is a specific number or state that a customer wants to achieve.

[0614] A "purchase receipt" is a proof of purchase issued when a customer purchases a product.

[0615] A "smartphone camera" is a photographic device built into a smartphone.

[0616] An "application" is a software program that runs on a smartphone or other device.

[0617] "Uploading" is the act of transferring data from a local device to a server or cloud.

[0618] "Correction" is the act of checking the content and correcting or deleting unnecessary parts.

[0619] "Unnecessary products" are products that the customer has determined not to need to purchase.

[0620] "Money saved" is the amount of money you would save if you didn't buy the unnecessary item.

[0621] "Weight lost" is the weight lost as a result of not purchasing unnecessary items.

[0622] "Visualization" is the act of visually displaying data or information.

[0623] "Analyzing emotions" is the process of assessing and understanding a customer's emotional state.

[0624] "Stress" refers to mental or physical tension or strain.

[0625] "Graphically displayed" means displaying information in a visual format such as a graph or chart.

[0626] This invention provides a system that allows customers to take a photo of their purchase receipt using a smartphone camera after shopping and upload it to an application. It also includes a function that analyzes the customer's emotions and graphically displays the amount of money saved and the amount of weight lost if they avoid buying unnecessary items when they are feeling stressed.

[0627] System configuration

[0628] 1. Hardware:

[0629] Smartphone: Use the camera to take a photo of your purchase receipt.

[0630] Server: Serves as the backend for the application, storing and processing data.

[0631] 2. Software:

[0632] Application: Installed on a smartphone, it takes a photo of a receipt, uploads it, analyzes its sentiment, and displays it graphically.

[0633] OpenCV: A library for loading and preprocessing receipt images.

[0634] Tesseract OCR: Optical character recognition software for extracting text from receipt images.

[0635] EmotionRecognizer: Emotion recognition software for analyzing customer emotions.

[0636] Matplotlib: A library for graphically displaying savings and weight loss.

[0637] System Operation

[0638] 1. Take a photo of your receipt and upload it:

[0639] The user takes a photo of the purchase receipt using the smartphone camera.

[0640] The captured images are uploaded to the server through the application.

[0641] 2. Text extraction:

[0642] The server preprocesses the images using OpenCV and extracts text from the receipt using Tesseract OCR.

[0643] 3. Sentiment analysis:

[0644] The server analyzes the user's emotions using EmotionRecognizer.

[0645] If you're feeling stressed, calculate how much money you'll save and how much weight you'll lose if you don't buy the item you don't need.

[0646] 4. Graphical display:

[0647] The server generates data using Matplotlib to graphically display the savings and weight loss and sends it to the application.

[0648] The application will display this visually to the user.

[0649] Specific examples

[0650] For example, if a user avoids buying unnecessary items when feeling stressed, the application will graphically display a savings of 1,000 yen and a weight loss of 0.5 kg.

[0651] Prompt Sentence Examples

[0652] Create a program that calculates and graphically displays the savings and weight loss a user could achieve by not buying unnecessary items when they are feeling stressed. Take a photo of the receipt with a smartphone camera and extract the text using Tesseract OCR. Analyze the user's emotions using EmotionRecognizer and display the results using Matplotlib.

[0653] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0654] Step 1:

[0655] The user takes a photo of the purchase receipt using the smartphone camera.

[0656] Input: Physical image of purchase receipt

[0657] Output: Receipt image saved on the smartphone

[0658] Specific operation: The user launches the smartphone's camera app and takes a picture of the purchase receipt. The captured image is saved in the smartphone's storage.

[0659] Step 2:

[0660] The device uploads the captured receipt image to the application.

[0661] Input: Receipt image saved on your smartphone

[0662] Output: Receipt image uploaded to the server

[0663] Specific operation: The user launches the application, selects the image of the receipt they have taken, and presses the upload button. The image is then sent to the server via the Internet.

[0664] Step 3:

[0665] The server preprocesses the receipt image using OpenCV and extracts text using Tesseract OCR.

[0666] Input: Receipt image uploaded to the server

[0667] Output: Extracted text data

[0668] What it does: The server uses OpenCV to remove noise from the image and highlight the text, then uses Tesseract OCR to extract the text from the image.

[0669] Step 4:

[0670] The server analyzes the user's emotions using EmotionRecognizer.

[0671] Input: User emotional data (e.g., the emotional state the user inputs into the application)

[0672] Output: Analyzed emotional state

[0673] Specific operation: The server uses EmotionRecognizer to analyze the user's emotional data and determine whether they are under stress.

[0674] Step 5:

[0675] If the server is stressed, it calculates the amount of money saved and weight loss that would result from not buying unnecessary items.

[0676] Input: Analyzed emotional state, extracted text data

[0677] Output: Savings and weight loss data

[0678] Specific operation: If the emotional state is stressed, the server identifies unnecessary products from the extracted text data and calculates the amount of money saved and the amount of weight lost if the product is not purchased.

[0679] Step 6:

[0680] The server generates data using Matplotlib to graphically display the savings and weight loss and sends it to the application.

[0681] Input: Savings and weight loss data

[0682] Output: Image data for graphical display

[0683] What it does: The server uses Matplotlib to generate an image that visually displays the savings and weight loss in the form of a bar graph or similar, and then sends the image data to the application.

[0684] Step 7:

[0685] The terminal displays the graphical data received from the server to the user.

[0686] Input: Graphical image data sent from the server

[0687] Output: Graphical information displayed on a smartphone screen

[0688] Specific operation: The application displays the image data received from the server on the smartphone screen, allowing the user to visually check the amount of savings and weight loss.

[0689] Example 3

[0690] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0691] Modern consumers aim to balance health management with saving money, but they often end up buying unnecessary products in their daily shopping. These unnecessary products not only go against health goals but also cause wasteful spending. However, it is not easy for consumers to identify and avoid these unnecessary products. Therefore, there is a need for a system that automatically detects unnecessary products based on consumers' health goals and visualizes the amount of money they can save and their impact on their health.

[0692] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0693] In this invention, the server includes means for a customer to input their current height and weight and goals, means for the customer to upload an image of their purchase receipt after shopping, means for converting the receipt image into digital data using optical character recognition technology, means for analyzing product information from the digital data and detecting unnecessary products, means for calculating the total price of the unnecessary products and the estimated weight loss amount, and means for visualizing the calculation results in graphs and charts. This allows consumers to automatically detect unnecessary products based on their own health goals and specifically understand the amount of money they can save and the impact on their health.

[0694] "Customers" are consumers who use the system to manage their own health and save money.

[0695] "Height and weight" is the customer's basic physical data and is basic information for setting health goals.

[0696] "Goals" are health and weight management goals that a customer wants to achieve, such as carbohydrate restriction and calorie restriction.

[0697] "Receipt image" is photo data of the purchase details that a customer obtains after shopping.

[0698] "Optical character recognition technology" is a technology that converts character information in an image into digital data, and is also known as OCR (Optical Character Recognition).

[0699] "Digital data" is textual information that has been converted using optical character recognition technology.

[0700] "Product information" refers to data such as the product name, price, and nutritional information listed on the receipt.

[0701] "Unnecessary products" are products that are contrary to the customer's health goals and should be avoided.

[0702] "Total amount" is the total price of the detected unwanted items.

[0703] "Estimated weight loss" is the amount of weight loss predicted if the unnecessary product was not consumed.

[0704] "Graphs and charts" are diagrams that visually display the results of calculations.

[0705] The present invention is a system for enabling consumers to efficiently manage their own health and save money. A specific embodiment of this system will be described below.

[0706] First, a user accesses the system's web page using a terminal. The user inputs their height, weight, and health goal (e.g., carbohydrate restriction). This data is sent to the server and stored in a database.

[0707] Next, the user uploads an image of the receipt they have taken after shopping to the system from their device. The uploaded image is then sent to the server, which uses optical character recognition technology such as Google Cloud Vision API to convert the image into digital data. This digital data includes the text information on the receipt.

[0708] The server analyzes the converted digital data and extracts product names and their nutritional information. For example, if a receipt includes "bread" or "sweets," these items are listed as unnecessary because they go against the goal of carbohydrate restriction.

[0709] The server then calculates the total cost of the unnecessary items and the estimated weight loss that would occur if these items were not consumed. A standard calorie expenditure model is used to calculate weight loss. The results are visualized as graphs and charts using a data visualization library such as D3.js.

[0710] The user can use their device to check the graphs and charts sent from the server, which allows them to visually understand the amount of money they would save and the amount of weight they would lose if they did not buy unnecessary products.

[0711] As a concrete example, consider the case where a user purchases chocolate when feeling stressed. The emotion engine analyzes the user's emotional state and determines that stress is high. In this case, it detects chocolate as an unnecessary product and displays a graph of the amount of money saved and weight loss that would have been achieved if the user had not purchased the chocolate. This helps the user recognize that they tend to purchase unhealthy foods when they are stressed, and understand the resulting financial and health impacts.

[0712] Example prompt sentence:

[0713] Detect the foods the user buys when they are stressed, calculate how much money they would save and how much weight they would lose if they had avoided buying those foods, and display the results in a graph.

[0714] This system allows the user to specifically understand both their own health management and savings. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0715] Step 1:

[0716] The user inputs their height, weight, and goal.

[0717] A user accesses the system's web page using a terminal and enters their height (e.g., 170 cm), weight (e.g., 70 kg), and health goal (e.g., carbohydrate restriction) into the form. The entered data is sent to the server and stored in the database.

[0718] Input: Height, Weight, Health Goals

[0719] Output: User information stored in the database

[0720] Step 2:

[0721] The user uploads an image of the receipt.

[0722] Users use their terminals to upload receipt images from recent purchases to the system, which are then sent to the server.

[0723] Input: Receipt image

[0724] Output: Receipt image saved on the server

[0725] Step 3:

[0726] The server performs OCR on the receipt image.

[0727] The server converts the receipt image into digital data using optical character recognition (OCR) technology, specifically by calling the Google Cloud Vision API.

[0728] Input: Receipt image

[0729] Output: Digital data (text information)

[0730] Step 4:

[0731] The server analyzes the product information and detects unnecessary products.

[0732] The server analyzes the digital data obtained through OCR processing and extracts product names and their nutritional information. For example, if a receipt includes "bread" or "sweets," these items are not in line with the goal of limiting carbohydrate intake, so they are listed as unnecessary items.

[0733] Input: Digital data (text information), user's health goals

[0734] Output: List of unwanted items

[0735] Step 5:

[0736] The server calculates the total price of unwanted items and the estimated weight loss.

[0737] The server calculates the total value of the detected unwanted products and the estimated weight loss that would occur if the user did not consume these products, using a standard calorie expenditure model.

[0738] Input: List of unwanted items, product price, calorie information

[0739] Output: Total amount, estimated weight loss

[0740] Step 6:

[0741] The server visualizes the calculation results in graphs and charts.

[0742] The server uses a data visualization library such as D3.js to generate graphs and charts of the total value of unwanted items and the estimated weight loss.

[0743] Input: Total amount, estimated weight loss

[0744] Output: Graphs and charts

[0745] Step 7:

[0746] The user checks the results.

[0747] The user can use their device to check the graphs and charts sent from the server, which allows them to visually understand the amount of money they would save and the amount of weight they would lose if they did not buy unnecessary products.

[0748] Input: Graphs and charts

[0749] Output: User understanding and recognition

[0750] (Application example 3)

[0751] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0752] Today's consumers are expected to manage their health and save money at the same time, but it is difficult to determine which products are unnecessary when shopping. Furthermore, there is a lack of ways to grasp the specific amount of savings and weight loss that can be achieved by not purchasing unnecessary products. Therefore, a system that allows consumers to make healthy choices and realize the savings is needed.

[0753] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0754] In this invention, the server includes a means for a customer to enter their current height and weight and goals, a means for the customer to submit a purchase receipt after shopping, a means for correcting items that are determined to be unnecessary in this shopping trip, a means for visualizing the money saved and weight lost if the unnecessary items are not purchased, a means for detecting unnecessary items and calculating the amount of savings and weight loss, and a means for displaying the detection results in a graph. This allows consumers to easily identify unnecessary items when shopping and specifically understand both health management and saving.

[0755] "Customer" refers to a consumer who makes a purchase using the system.

[0756] "Height and Weight" refers to the customer's current physical height and weight.

[0757] "Goals" refer to specific health or diet-related objectives that a customer wants to achieve.

[0758] "Purchase receipt" refers to paper or electronic data showing the purchase details of goods received by a customer when making a purchase.

[0759] "Unnecessary items" are items that should be removed from the shopping list based on the customer's height, weight, and goals.

[0760] "Money saved" refers to the amount of money you would save if you didn't buy unnecessary items.

[0761] "Weight loss" refers to the amount of weight loss predicted if the unnecessary product was not consumed.

[0762] "Visualization tools" refers to ways to display the money saved and weight lost in visual form, such as graphs or charts.

[0763] "Means of detection" refers to a method for identifying unwanted products based on a customer's height, weight, and goals.

[0764] "Means of calculation" refers to a method for calculating the amount of money saved and the amount of weight lost by not buying unnecessary items.

[0765] "Graphical display means" refers to a method for displaying detection results in a visually easy-to-understand format.

[0766] A system for implementing this invention includes means for a customer to enter their current height and weight and their goal, means for the customer to submit a purchase receipt after shopping, means for correcting items that are determined to be unnecessary for this purchase, means for visualizing the money saved and weight lost if the unnecessary items are not purchased, means for detecting unnecessary items and calculating the amount saved and the amount of weight lost, and means for displaying the detection results in a graph.

[0767] System configuration

[0768] The system is implemented as a smartphone application. The application is built using Python and Flask, and performs data processing on the server side. The smartphone sends the height, weight, and goal information entered by the user, as well as receipt information, to the server.

[0769] Data processing and calculation

[0770] The server receives the data sent by the user and performs the following processing.

[0771] 1. Unwanted product detection:

[0772] The server identifies unnecessary items on the receipt based on the user's height, weight, and goals. For example, if the user's goal is to "limit carbohydrates," the server detects "bread" and "sweets" on the receipt as unnecessary items.

[0773] 2. Savings and Weight Loss Calculation:

[0774] The server calculates the amount of money saved and the amount of weight lost if the unnecessary items were not purchased, for example, by adding up the prices of the unnecessary items and calculating the amount of weight lost based on the calories in those items.

[0775] 3. Visualizing the results:

[0776] The server generates the calculation results in the form of graphs and charts and sends them to a smartphone application, where users can visually check the results.

[0777] Hardware and software used

[0778] Hardware: Smartphone

[0779] Software: Python, Flask

[0780] Specific examples

[0781] If the user's goal is to "limit carbohydrates" and the receipt includes "bread" and "sweets," the system will detect these as unnecessary items. The savings will be calculated as 350 yen (bread 150 yen + sweets 200 yen) and the weight loss will be 0.064 kg (500 kcal / 7700 kcal). These results are displayed as a graph on the smartphone application.

[0782] Prompt Sentence Examples

[0783] If the user is aiming to limit carbohydrates, detect unnecessary items in the receipt and calculate the savings and weight loss. Use the following data:

[0784] Height: 170cm Weight: 70kg Goal: Carbohydrate restriction Receipt items: ["Bread", "Sweets", "Vegetables"]

[0785] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0786] Step 1:

[0787] The user starts the smartphone application and inputs their current height and weight and their goal.

[0788] Input: Height, Weight, Goal

[0789] Output: Height, weight, goal data

[0790] Specific actions: The user enters their height, weight, and goal into the application's input form and presses the submit button.

[0791] Step 2:

[0792] After shopping, the user scans the purchase receipt with their smartphone and uploads it to the application.

[0793] Input: Purchase receipt image

[0794] Output: Receipt text data

[0795] How it works: A user takes a photo of a receipt using their smartphone camera and uploads it to the application, which then uses OCR technology to extract text data from the image.

[0796] Step 3:

[0797] The server receives the text data of the height, weight, goal, and receipt sent by the user.

[0798] Input: Height, weight, goal, receipt text data

[0799] Output: Save received data

[0800] What happens: The server receives the HTTP request and stores the data in a database.

[0801] Step 4:

[0802] The server detects unwanted items on the receipt based on the user's goals.

[0803] Input: Height, weight, goal, receipt text data

[0804] Output: List of unwanted items

[0805] Specific operation: The server references the list of unwanted items related to the goal and identifies the unwanted items by matching them with the text data on the receipt.

[0806] Step 5:

[0807] The server calculates the amount of savings and weight loss if unnecessary items are not purchased.

[0808] Input: List of unwanted items

[0809] Output: Savings, weight loss

[0810] Specific operation: The server adds up the prices of the unwanted items and calculates the weight loss amount based on the calories of the unwanted items. For example, if the total price of the unwanted items is 350 yen and the total calories are 500 kcal, the weight loss amount will be calculated as 0.064 kg (500 kcal / 7700 kcal).

[0811] Step 6:

[0812] The server generates the calculation results in the form of graphs or charts and sends them to the smartphone application.

[0813] Input: Amount saved, Weight lost

[0814] Output: Image data for graphs and charts

[0815] Specific operation: The server generates graphs and charts based on the calculation results and sends them to the smartphone application as image data.

[0816] Step 7:

[0817] Users can visually check the savings and weight loss results through a smartphone application.

[0818] Input: Image data of graphs and charts

[0819] Output: Visual results

[0820] What it does: The user opens the app and sees the graphs and charts that show them how much money they could save and how much weight they could lose if they didn't buy the unnecessary items.

[0821] 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.

[0822] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) 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.

[0823] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0824] 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.

[0825] [Second embodiment]

[0826] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0827] 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.

[0828] 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).

[0829] 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.

[0830] 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.

[0831] 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).

[0832] 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.

[0833] 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.

[0834] 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.

[0835] 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.

[0836] 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.

[0837] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0838] "Example 1"

[0839] This embodiment of the present invention provides a dedicated input form as a means for consumers to enter their height, weight, and diet goals. This input form is provided on a website or smartphone application, and allows consumers to directly input their height, weight, diet goals, etc.

[0840] "Example 2"

[0841] Next, as a means for consumers to submit their purchase receipts after shopping, the system provides a function for them to take an image of the receipt using their smartphone camera and upload it to the application. This function allows consumers to communicate purchase information to the system without having to submit a physical receipt directly.

[0842] "Example 3"

[0843] Then, as a means of correcting items that are deemed unnecessary for this shopping trip, the system automatically detects unnecessary items based on the consumer's height, weight, and goal entered by the consumer, as well as the submitted receipt information. For example, if the diet goal is to "limit carbohydrates," the system will detect items on the receipt that are high in carbohydrates, such as "bread" and "sweets," as unnecessary items.

[0844] "Example 4"

[0845] Finally, to visualize the money saved and weight lost by not purchasing unnecessary products, the system calculates the total cost of the detected unnecessary products and the estimated weight loss if those products were not consumed, and displays this information to consumers in the form of graphs, charts, etc. This allows consumers to concretely understand both their health management and savings.

[0846] The processing flow of each embodiment will be described below.

[0847] "Example 1"

[0848] Step 1: The consumer enters their height, weight, diet goal, etc. into a dedicated input form. For example, a height of 170 cm, weight of 65 kg, and diet goal of "restricting carbohydrates" may be entered.

[0849] Step 2: Once completed, the consumer presses the "Submit" button to send the information to the system.

[0850] "Example 2"

[0851] Step 1: The consumer makes a purchase and gets a receipt for the items purchased.

[0852] Step 2: The consumer takes a picture of the receipt using their smartphone camera.

[0853] Step 3: The captured image is uploaded to the application and the system reads the receipt information.

[0854] "Example 3"

[0855] Step 1: The system automatically detects unwanted products based on the consumer's height, weight, and goals entered, as well as the submitted receipt information.

[0856] Step 2: For example, if the diet goal is to "limit carbohydrates," the system will detect high-carbohydrate items on the receipt, such as "bread" and "sweets," as unnecessary items.

[0857] "Example 4"

[0858] Step 1: The system calculates the total value of the detected unwanted products and the estimated weight loss if the product was not consumed.

[0859] Step 2: The calculation results are displayed to the consumer in the form of graphs, charts, etc. This allows the consumer to concretely understand both their health management and savings.

[0860] Example 1

[0861] Next, a description will be given of Example 1 of Form 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."

[0862] Conventional diet support systems require users to input their height, weight, and diet goals, as well as submit purchase receipts after shopping to identify unnecessary items. However, these systems are time-consuming for users, making continuous use difficult. Furthermore, they lack the functionality to propose an appropriate individual diet plan based on the data entered by the user, which makes it difficult to provide effective diet support.

[0863] 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.

[0864] In this invention, the server includes a means for the customer to enter their current height and weight and goals, a means for the customer to submit a purchase receipt after shopping, a means for correcting items that are determined to be unnecessary in this shopping trip, a means for visualizing the money saved and weight lost if the unnecessary items are not purchased, a means for receiving and saving the data entered by the customer, a means for generating prompts for the generative AI model based on the saved data, and a means for the generative AI model to suggest a diet plan.This allows the user to continue using the service without any hassle, and makes it possible to suggest an appropriate diet plan individually.

[0865] "Customer" refers to a user of the system.

[0866] "Height and Weight" refers to the customer's current height and weight data.

[0867] "Goals" refers to diet and health goals set by the Customer.

[0868] "Input form" refers to the interface through which customers enter data such as height, weight, and goals.

[0869] "Purchase Receipt" means a detailed statement of purchases received by a Customer after making a purchase.

[0870] "Means of correction" refers to the function of determining unnecessary products based on the customer's height, weight, and goals, and removing them from the list.

[0871] "Visualization means" refers to a function that visually displays the money you can save or the weight you will lose if you don't buy unnecessary products.

[0872] "Means of receiving and storing data" refers to the function by which the server receives data entered by the customer and stores it in a database, etc.

[0873] A "generative AI model" refers to an artificial intelligence model that generates an appropriate diet plan based on input data.

[0874] A "prompt sentence" refers to an instruction sentence generated for a generative AI model based on input data.

[0875] "Diet Plan" refers to a specific action plan proposed by the generative AI model to help customers achieve their goals.

[0876] This invention is a system that provides a dedicated input form for customers to enter their height, weight, and diet goals. The system is installed on a website or smartphone application, and a generative AI model proposes an appropriate diet plan based on the data entered by the customer.

[0877] Hardware and software used

[0878] Hardware: Servers (e.g., AWS (registered trademark) EC2), user devices (e.g., smartphones, PCs)

[0879] Software: Web servers (e.g., Apache, Nginx), databases (e.g., MySQL, PostgreSQL), smartphone applications (e.g., iOS apps, Android apps)

[0880] Specific operation of the system

[0881] server

[0882] The server provides a dedicated input form on a website or smartphone application, where customers can enter their height, weight, diet goals, etc. The server receives the input data and stores it in a database. The stored data is used as prompts for the generative AI model.

[0883] Terminal

[0884] The device displays the websites and smartphone applications that the user accesses. When the user enters their height, weight, and diet goals into an input form, the device sends the data to the server. The device then displays the data that the user has entered in real time, allowing them to check it.

[0885] User

[0886] Users access a website or smartphone application and enter their height, weight, and diet goals into a dedicated input form. Once the user has completed the input, the data is sent to the server. The user can then review the data they have entered and make any necessary corrections.

[0887] Specific examples

[0888] Example 1: Website use

[0889] A user visits a website and fills out a form with the following information:

[0890] Height: 170 cm Weight: 70 kg Diet goal: Lose 5 kg

[0891] Once the input is complete, the device sends this data to the server, which receives it and stores it in a database. The server then generates the following prompt for the generative AI model:

[0892] Example prompt sentence:

[0893] "The user is 170 cm tall, weighs 70 kg, and wants to lose 5 kg. Based on this information, please suggest an appropriate diet plan."

[0894] Example 2: Use in a smartphone application

[0895] A user opens a smartphone application and enters the following information into the input form:

[0896] Height: 160 cm Weight: 60 kg Diet goal: Lose 3 kg

[0897] Once the input is complete, the device sends this data to the server, which receives it and stores it in a database. The server then generates the following prompt for the generative AI model:

[0898] Example prompt sentence:

[0899] "The user is 160 cm tall, weighs 60 kg, and wants to lose 3 kg. Based on this information, please suggest an appropriate diet plan."

[0900] In this way, a system is constructed in which a generative AI model suggests an appropriate diet plan based on the data entered by the user.

[0901] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0902] Step 1:

[0903] The user accesses the input form.

[0904] A user opens a website or smartphone application and accesses an input form. The input form is an interface where the user can enter their height, weight, and diet goals. Once the input form is displayed, the user is ready to enter the required information.

[0905] Step 2:

[0906] The user enters the data.

[0907] The user enters their height, weight, and diet goal in the input form. For example, the user enters "Height: 170 cm", "Weight: 70 kg", and "Diet goal: Lose 5 kg". Once the input is complete, the user taps the "Submit" button. The input data is saved on the device in JSON format.

[0908] Step 3:

[0909] The device sends the data to the server.

[0910] The device sends the data entered by the user to the server. Specifically, the device uses an HTTP POST request to send the input data to the server. At this time, the data is sent in JSON format. The input data (height, weight, diet goal) is sent to the server.

[0911] Step 4:

[0912] The server receives and stores the data.

[0913] The server receives the data sent from the device. The received data is stored in a database. For example, the server connects to a MySQL database and executes the following SQL query:

[0914] sql

[0915] INSERT INTO user_data (height, weight, goal) VALUES (170, 70, '5 kg weight loss');

[0916] This process saves the user's input data in the database.

[0917] Step 5:

[0918] The server generates a prompt for the generative AI model.

[0919] The server generates prompts for the generative AI model based on the stored data. For example, it generates prompts like the following:

[0920] The user is 170 cm tall, weighs 70 kg, and has a goal of losing 5 kg. Based on this information, please suggest an appropriate diet plan.

[0921] This prompt is sent to a generative AI model.

[0922] Step 6:

[0923] A generative AI model suggests diet plans.

[0924] The generative AI model generates a diet plan based on the prompt it receives. For example, the generative AI model might suggest the following diet plan:

[0925] 1. Do 30 minutes of aerobic exercise every day

[0926] 2. Limit your daily calorie intake to 1500 kcal

[0927] 3. Strength train three times a week

[0928] This diet plan is sent to the user's terminal via the server and displayed to the user.

[0929] In this way, a system is constructed in which a generative AI model suggests an appropriate diet plan based on the data entered by the user.

[0930] (Application example 1)

[0931] Next, a description will be given of Application Example 1 of Form 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."

[0932] Conventional food delivery systems have difficulty providing meal plans based on customers' health conditions and diet goals, making it difficult to provide services tailored to individual needs. Furthermore, customers often end up buying unnecessary items, resulting in wasteful spending, and food choices that hinder the achievement of diet goals.

[0933] 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.

[0934] In this invention, the server includes a means for the customer to enter their current height and weight and goals, a means for the customer to submit a purchase receipt after shopping, a means for correcting items that are determined to be unnecessary in this shopping trip, a means for visualizing the money saved and weight lost if unnecessary items are not purchased, a means for generating an appropriate meal plan based on the customer's height, weight, and goals, and a means for presenting the generated meal plan to the customer. This makes it possible to provide an appropriate meal plan based on the customer's health condition and diet goals, and to support the achievement of the diet goals while reducing unnecessary spending.

[0935] "Customer" refers to the consumer who uses the service.

[0936] "Height and Weight" refers to the physical height and weight of the customer.

[0937] "Goals" refer to specific health or diet objectives that a customer wants to achieve.

[0938] "Purchase receipt" refers to a detailed list of purchases received by a customer when making a purchase.

[0939] "Means for correction" refers to a method or system for evaluating products purchased by customers and identifying unwanted products.

[0940] "Visualization tools" refers to methods or systems that visually display the money saved or weight lost.

[0941] "Meal Plan" refers to the meal content and schedule suggested based on the customer's health and diet goals.

[0942] "Means for generating" refers to a method or system for generating a meal plan based on customer input data.

[0943] "Presenting means" refers to a method or system for showing the generated meal plan to the customer.

[0944] The following system configuration is proposed as an embodiment of the present invention.

[0945] System Configuration

[0946] The system includes a smartphone application used by customers, a server, and a generative AI model. The smartphone application provides an interface for customers to input their height, weight, and diet goals. The server receives the input data and sends prompts to the generative AI model to generate an appropriate meal plan. The generated meal plan is then presented to the customer via the smartphone application.

[0947] Hardware and software used

[0948] Hardware: Smartphones, servers

[0949] Software: smartphone applications, generative AI models (e.g., OpenAI GPT-3)

[0950] Data processing and calculation

[0951] 1. Data entry: Customers use a smartphone application to enter their height, weight, and diet goals.

[0952] 2. Data transmission: The smartphone application sends the entered data to the server.

[0953] 3. Prompt generation: Based on the data received by the server, a prompt sentence is generated to be sent to the generative AI model.

[0954] 4. Meal plan generation: The generative AI model receives the prompt and generates an appropriate meal plan.

[0955] 5. Data reception and presentation: The server receives the generated meal plan and presents it to the customer via the smartphone application.

[0956] Specific examples

[0957] For example, if a customer inputs their height as 170cm, weight as 70kg, and their diet goal as "lose 5kg," the server will send the following prompt to the generative AI model:

[0958] Prompt Sentence Examples

[0959] Please suggest a suitable meal plan based on height: 170 cm, weight: 70 kg, goal: 5 kg weight loss.

[0960] Based on this prompt, the generative AI model generates a balanced meal plan, suggesting specific meal options such as "Breakfast - oatmeal, Lunch - salad, Dinner - chicken breast and vegetables." This meal plan is presented to the customer via a smartphone application.

[0961] In this way, it is possible to provide customers with appropriate meal plans according to their health condition and diet goals, helping them achieve their diet goals while reducing unnecessary spending.

[0962] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0963] Step 1:

[0964] A user starts a smartphone application and inputs their height, weight, and diet goal. The input data is temporarily saved in the smartphone application. An example of input data is a height of 170 cm, a weight of 70 kg, and a diet goal of "lose 5 kg."

[0965] Step 2:

[0966] The smartphone application sends the entered data, including the user's height, weight, and diet goal, to the server. The server analyzes the received data and proceeds to the next processing step.

[0967] Step 3:

[0968] The server generates a prompt based on the received data. Specifically, it combines the user's height, weight, and diet goal to create a prompt to send to the generative AI model. For example, the generated prompt might read, "Based on height: 170 cm, weight: 70 kg, goal: to lose 5 kg, please suggest an appropriate meal plan."

[0969] Step 4:

[0970] The server sends the generated prompt to the generative AI model, which then performs data calculations based on the received prompt and generates an appropriate meal plan. The generative AI model uses, for example, OpenAI GPT-3.

[0971] Step 5:

[0972] The generative AI model generates a meal plan based on the prompt and sends the result back to the server. An example of a generated meal plan is "Breakfast - oatmeal, Lunch - salad, Dinner - chicken breast and vegetables."

[0973] Step 6:

[0974] The server analyzes the meal plan received from the generative AI model and transmits it to the smartphone application, where the transmitted data includes the generated meal plan.

[0975] Step 7:

[0976] The smartphone application presents the meal plan received from the server to the user, who can then review and implement the proposed meal plan through the application.

[0977] Example 2

[0978] Next, a description will be given of Example 2 of Form 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."

[0979] In the previous system, customers had to physically submit receipts for their purchases, which was time-consuming and risked loss or damage. Furthermore, there were insufficient methods for identifying unnecessary purchases and visualizing savings and weight loss. This made it difficult for customers to effectively manage their shopping to achieve their goals.

[0980] 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.

[0981] In this invention, the server includes a means for the customer to enter their current height and weight and their goals, a means for the customer to take an image of their purchase receipt after shopping and upload it to the application so that they can submit it, a means for correcting items that are determined to be unnecessary in this purchase, and a means for visualizing the amount of money saved and the weight loss that would be achieved if they did not purchase the unnecessary items. This allows the customer to easily communicate their purchase information to the system without having to go through the trouble of submitting physical receipts. In addition, by identifying unnecessary items and visualizing the amount of money saved and the weight loss that would be achieved, the customer can effectively manage their shopping toward their goals.

[0982] "Customer" means an individual who uses the System to make purchases and manages purchase information.

[0983] "Height and Weight" refers to the customer's current physical height and weight.

[0984] "Goal" refers to a specific physical or financial goal that the client wishes to achieve.

[0985] "Purchase Receipt" means a paper or electronic record issued to a customer when they make a purchase that details the items purchased.

[0986] "Taking an image" refers to the act of taking a photo of a physical receipt using a device such as a smartphone or camera.

[0987] "Application" refers to a software program that runs on a device such as a smartphone or tablet.

[0988] "Uploading" refers to the act of sending a captured image to a server via the Internet.

[0989] "Server" refers to a computer system for receiving, processing, and storing data over a network.

[0990] "Analyzing an image" refers to the act of using image recognition technology to extract the contents of a photographed receipt as digital data.

[0991] "Unnecessary products" refer to products that are determined not to be necessary for the customer's goals.

[0992] "Savings" refers to the amount of money you can save by not purchasing unnecessary items.

[0993] "Weight loss" refers to the amount of weight loss you would expect if you didn't purchase unnecessary items.

[0994] "Visualizing" refers to the act of displaying data visually so that it can be easily understood by customers.

[0995] "Graphically displaying" refers to the act of displaying data in a visual format such as a graph or chart.

[0996] The present invention provides a system that allows customers to take pictures of their purchases after shopping and upload them to an application in order to submit a receipt. A specific embodiment of this system will be described below.

[0997] The user takes a picture of the purchase receipt using the camera on their smartphone. The image is then uploaded using a dedicated application (e.g., "ReceiptUploader"). The application has the function of sending the image taken by the user to a server.

[0998] The server receives the image of the receipt sent from the device. After receiving it, the server analyzes the contents of the receipt using image recognition software such as Google Cloud Vision API. Optical character recognition (OCR) technology is used for the analysis, and information such as the product name, price, and purchase date and time written on the receipt is extracted.

[0999] The analyzed data is stored in a database by the server. The stored data includes the product name, price, purchase date and time, store name, etc. This allows the user's purchase history to be accumulated in the database.

[1000] Users can use the application to check their purchase history. By opening the "Purchase History" section in the application, data retrieved from the server is displayed. Users can view a list of past purchases.

[1001] As a concrete example, consider a scenario where a user has just finished shopping at a supermarket. The user takes a picture of the receipt using their smartphone camera and opens the "ReceiptUploader" application. Within the application, the user taps the "Upload" button, selects the image of the receipt, and uploads it. The application sends the image to a server, which uses the Google Cloud Vision API to analyze the contents of the receipt. The analyzed data is stored in a database, and the user can view recent purchases by opening the "Purchase History" section within the application.

[1002] Examples of prompts to be input to a generative AI model include:

[1003] "Please describe the functionality that allows users to take a picture of a receipt using their smartphone camera and upload it to your application. Please include the names of any specific hardware or software."

[1004] Using this prompt, the generative AI model can generate sentences that explain in detail the system's operations.

[1005] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1006] Step 1:

[1007] The user takes a picture of the receipt.

[1008] The user uses the smartphone camera to take a picture of the receipt for the item they purchased, taking care to capture the entire receipt clearly. The input is the physical receipt, and the output is a digital image.

[1009] Step 2:

[1010] The device uploads the image to the application.

[1011] The device (smartphone) uploads the captured image of the receipt to the "ReceiptUploader" application. The user opens the application, taps the "Upload" button, and selects the captured image. The input is a digital image, and the output is the transmission of image data to the server.

[1012] Step 3:

[1013] The server receives and analyzes the images.

[1014] The server receives the image of the receipt sent from the terminal. After receiving it, the server uses image recognition software such as Google Cloud Vision API to analyze the contents of the receipt. Optical character recognition (OCR) technology is used for the analysis, and information such as the product name, price, and purchase date and time written on the receipt is extracted. The input is image data, and the output is analyzed text data.

[1015] Step 4:

[1016] The server stores the analysis results in a database.

[1017] The server saves the analyzed data in a database. The saved data includes the product name, price, purchase date and time, store name, etc. This allows the user's purchase history to be accumulated in the database. The input is the analyzed text data, and the output is saved in the database.

[1018] Step 5:

[1019] The user checks their purchase history.

[1020] The user can use the "ReceiptUploader" application to check their purchase history. When they open the "Purchase History" section in the application, the data retrieved from the server is displayed. The user can view a list of past purchases. The input is the data retrieved from the database, and the output is what is displayed in the application.

[1021] (Application example 2)

[1022] Next, a description will be given of Application Example 2 of Form 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."

[1023] In conventional shopping systems, customers had to physically submit receipts for the products they purchased, which was time-consuming and made managing purchase information cumbersome. Furthermore, there was a lack of systems that could identify unnecessary products based on the customer's health goals and visualize the savings and health benefits.

[1024] The specific processing by the specific 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 a means for the customer to enter their current height and weight and goals, a means for the customer to take a photo of their purchase receipt with their smartphone camera after shopping and upload it to the application, a means for correcting items determined to be unnecessary for the current purchase, a means for visualizing the money saved and weight lost if the unnecessary items were not purchased, a means for analyzing the contents of the purchase receipt and automatically extracting purchase information, a means for rewarding points to the customer based on the extracted purchase information, and a means for allowing the rewarded points to be used for the next purchase. This eliminates the need for customers to submit physical receipts, simplifies management of purchase information, and enables visualization of point rewards and savings. Furthermore, unnecessary items can be identified based on the customer's health goals, and savings and health benefits can be visualized.

[1025] "Customer" means a consumer who purchases goods or services.

[1026] "Height and weight" is basic physical information that refers to the customer's physical height and weight.

[1027] A "goal" is a specific numerical value or state that a customer wants to achieve.

[1028] "Purchase Receipt" means a paper or electronic record detailing a transaction issued to a customer when they purchase goods.

[1029] A "smartphone" is a type of mobile phone that can connect to the Internet and use applications.

[1030] A "camera" is a device for taking pictures and videos.

[1031] An "application" is a software program that runs on a smartphone or computer.

[1032] "Uploading" is the act of transferring data from a local device to a server or cloud.

[1033] "Unnecessary products" are products that are deemed not necessary for the customer to achieve their goals.

[1034] "Correction" is the act of checking the content and making corrections or improvements.

[1035] "Money saved" is the amount of money you would save if you didn't buy the unnecessary item.

[1036] "Weight lost" is the weight lost as a result of not purchasing unnecessary items.

[1037] "Visualization" refers to the visual display of data or information.

[1038] "Analysis" is the act of examining data or information in detail to clarify its structure and meaning.

[1039] "Purchase information" is detailed information about the products purchased by the customer.

[1040] "Automatic extraction" means that the system extracts data without human intervention.

[1041] "Point redemption" refers to the act of giving points to customers according to the amount of their purchase.

[1042] "Can be used on next purchase" means that the customer can use the points the next time they purchase a product.

[1043] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail below with reference to the accompanying drawings.

[1044] First, a smartphone application is used by the customer to enter their current height, weight, and goals. The customer launches the application and inputs their height, weight, and goals. This registers the customer's health goals in the system.

[1045] Next, after shopping, customers are provided with a means to take a photo of their purchase receipt with their smartphone camera and upload it to the application. Customers take a photo of their receipt and use the upload function within the application to send the image to the server.

[1046] The server receives the uploaded receipt image and preprocesses it using OpenCV. Specifically, it converts the image to grayscale and performs binarization. Next, it uses pytesseract to extract text from the preprocessed image. It then analyzes and automatically extracts purchase information (product name, price, etc.) from the extracted text.

[1047] Based on the analyzed purchase information, a method is provided for redeeming points to customers. The server calculates the points according to the purchase amount and adds them to the customer's account. The redeemed points are managed within the application so that they can be used for the next purchase.

[1048] Furthermore, as a means of correcting items that may be deemed unnecessary for this shopping trip, an algorithm is implemented to determine unnecessary items based on the customer's height, weight, and goals. The server compares the purchase information with the customer's health goals to identify unnecessary items.

[1049] To visualize the money saved and weight lost by not buying unnecessary products, the server calculates and graphically displays the amount saved and weight lost, allowing customers to visually see the savings and health benefits.

[1050] As a concrete example, consider the case where a user purchases a drink at a convenience store, takes a photo of the receipt, and uploads it to the app. The app extracts "drink" and "150 yen" from the receipt and rewards 15 points. If the app determines that the drink is an unnecessary item based on the user's health goals, it displays the amount of money saved and the weight lost.

[1051] An example of a prompt for a generative AI model is:

[1052] "A user has uploaded an image of a receipt taken with their smartphone camera. Please create a program that extracts purchase information from this image and returns points. 10% of the purchase amount will be returned as points."

[1053] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1054] Step 1:

[1055] The user starts the smartphone application and inputs their current height, weight, and goals. The input data is temporarily saved in the application and sent to the server. The input data is used as the basis for setting the user's health goals.

[1056] Step 2:

[1057] After shopping, a user takes a photo of the purchase receipt with their smartphone camera and uploads it to the application. The captured receipt image is temporarily saved in the application and then sent to the server. The input data is the receipt image.

[1058] Step 3:

[1059] The server receives the uploaded receipt image and preprocesses it using OpenCV. Specifically, it converts the image to grayscale and performs binarization. The input data is the receipt image, and the output data is the preprocessed image.

[1060] Step 4:

[1061] The server extracts text from the preprocessed image using pytesseract. The input data is the preprocessed image, and the output data is the extracted text. Specifically, it uses OCR (Optical Character Recognition) technology to read the text information in the image.

[1062] Step 5:

[1063] The server analyzes and automatically extracts purchase information (product name, price, etc.) from the extracted text. The input data is the extracted text, and the output data is the analyzed purchase information. Specifically, the required information is extracted using a text analysis algorithm.

[1064] Step 6:

[1065] The server rewards the customer with points based on the analyzed purchase information. The input data is the analyzed purchase information, and the output data is the rewarded points. Specifically, the server calculates points based on the purchase amount and adds the points to the customer's account.

[1066] Step 7:

[1067] The server determines unnecessary products based on the customer's height, weight, and goals. The input data is the customer's health goals and purchase information, and the output data is a list of unnecessary products. Specifically, the server runs an algorithm that compares the health goals with the purchase information and identifies unnecessary products.

[1068] Step 8:

[1069] The server calculates the amount of money saved and the weight lost if you don't buy unnecessary items, and displays them graphically. The input data is a list of unnecessary items and their purchase information, and the output data is the amount saved and the weight lost. The specific operation is to calculate the savings and health benefits, and display them visually to the user.

[1070] Step 9:

[1071] The user uses the points they have earned on their next purchase. The input data is the points earned, and the output data is the balance after the points have been used. The specific operation is to use the points to discount the purchase amount and update the balance.

[1072] Example 3

[1073] Next, a description will be given of Example 3 of Form Example 3. 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."

[1074] Modern consumers find it difficult to balance health management and saving money. In particular, consumers who have diet or health goals have difficulty determining which products they do not need when shopping. In addition, there is a lack of means to specifically understand the amount of savings and health benefits they will achieve if they do not purchase unnecessary products. For this reason, a system that allows consumers to effectively manage their health and save money is needed.

[1075] The identification process by the identification processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes a means for a customer to enter their current height and weight and their goals, a means for the customer to submit a purchase receipt after shopping, a means for converting the submitted receipt information into text data using optical character recognition technology, a means for identifying unnecessary products based on the customer's height, weight, and goals, a means for calculating the amount of money saved and the weight lost if the unnecessary products are not purchased, and a means for graphically displaying the calculation results. This allows consumers to easily identify unnecessary products when shopping and specifically understand the amount of money saved and the health benefits.

[1076] "Customers" are consumers who use the system to manage their health and save money.

[1077] "Height and weight" are the customer's current physical measurements and are used as basic data for health management.

[1078] "Goals" are specific health and diet-related objectives set by customers, and include, for example, "restricting carbohydrates" and "restricting calories."

[1079] A "receipt" is a detailed list of purchased items that a customer receives after shopping, listing the item names and prices.

[1080] "Optical character recognition technology" is a technology that extracts character information from image data and is used to convert receipt images into text data.

[1081] "Text data" refers to character information converted using optical character recognition technology, and includes information such as product names and prices.

[1082] "Unnecessary products" are products that are determined not to be necessary to purchase from the perspective of health management or dieting, based on the customer's height, weight, and goals.

[1083] "Savings" is the total amount of money you can save by not purchasing unnecessary items.

[1084] "Weight loss" is the amount of weight loss predicted if the unnecessary product was not consumed.

[1085] "Displaying graphically" means displaying the calculation results in the form of a graph, chart, or the like to make them visually easy to understand.

[1086] MODE FOR CARRYING OUT THE INVENTION

[1087] The present invention is a system for enabling consumers to effectively manage their health and save money. A specific embodiment of this system will be described below.

[1088] System configuration

[1089] The system consists of the following major components:

[1090] 1. A device for users to input their height, weight, and goals

[1091] 2. A terminal where users can submit receipts after shopping

[1092] 3. Hardware and software for the server to receive and process data

[1093] Hardware and software used

[1094] Device: Mobile device such as a smartphone or tablet

[1095] Server: High-performance data processing server

[1096] OCR technology: Optical character recognition technology such as Google Cloud Vision API

[1097] Database: A relational database such as MySQL or PostgreSQL

[1098] Data visualization libraries: D3.js, Chart.js, etc.

[1099] Program processing

[1100] The server receives the height, weight, and goal information entered by the user, as well as the submitted receipt. The server uses this data to process and calculate data to detect unwanted products. Specifically, the process is carried out as follows:

[1101] 1. Data reception and analysis:

[1102] The server receives the height, weight, and goal (e.g., carbohydrate restriction) entered by the user.

[1103] The server converts the information on the submitted receipt into text data using OCR technology.

[1104] 2. Unwanted product detection:

[1105] The server detects unnecessary products based on the goal. For example, if the goal is to "limit carbohydrates," the server lists products with high carbohydrate content, such as "bread" and "sweets," on the receipt as unnecessary products.

[1106] 3. Savings and Weight Loss Calculation:

[1107] The server calculates the total price of the detected unwanted items.

[1108] The server calculates the estimated weight loss that would occur if the unnecessary products were not consumed.

[1109] 4. Visualizing the results:

[1110] The server displays the calculation results to the consumer in the form of graphs, charts, etc.

[1111] Specific examples

[1112] Suppose a user is 170 cm tall, weighs 70 kg, sets their goal to "restrict carbohydrates," and submits a receipt. The receipt includes "bread (300 yen)," "sweets (200 yen)," and "vegetables (100 yen)." The system detects "bread" and "sweets" as unnecessary items and calculates that a total of 500 yen can be saved. The system also calculates the estimated weight loss if these items were not consumed as 0.5 kg and displays this in a graph.

[1113] Prompt Sentence Examples

[1114] "Height 170cm, weight 70kg, goal is carbohydrate restriction. Please detect unnecessary items based on the following receipt information and calculate the amount saved and weight loss. Receipt information: bread (300 yen), sweets (200 yen), vegetables (100 yen)." The flow of the identification process in Example 3 will be explained using Figure 15.

[1115] Step 1:

[1116] The user enters their height, weight, and goal, and submits a receipt.

[1117] Input: The user opens the app on their smartphone and enters their height (170 cm), weight (70 kg), and goal ("carbohydrate restriction"). After shopping, they also take a photo of their receipt with their smartphone camera and upload it to the server via the app.

[1118] Output: The user's input data and the receipt image are sent to the server.

[1119] Step 2:

[1120] The server receives the input data and receipt information.

[1121] Input: Height, weight, goal, and receipt image submitted by the user.

[1122] Output: User input data and receipt image stored in a database on the server.

[1123] Step 3:

[1124] The server converts the receipt information into text data using OCR technology.

[1125] Input: Receipt image stored on the server.

[1126] Data processing: The server calls the Google Cloud Vision API, analyzes the receipt image, and extracts the product name and price.

[1127] Output: Converted text data (e.g., "Bread (300 yen)", "Sweets (200 yen)", "Vegetables (100 yen)").

[1128] Step 4:

[1129] The server detects unwanted items based on the target.

[1130] Input: User goal (e.g., "Limit carbohydrate intake") and converted text data.

[1131] Data calculation: The server performs rule-based filtering based on predefined food categories and goals to list unwanted products.

[1132] Output: A list of unwanted products (e.g. "bread", "sweets").

[1133] Step 5:

[1134] The server calculates the total price of unwanted items and the estimated weight loss.

[1135] Input: A list of unwanted items and their respective prices.

[1136] Data calculation: The server calculates the total price of unnecessary products and the estimated weight loss if unnecessary products were not consumed. The model used here is a simulation model based on the relationship between calorie consumption and weight loss.

[1137] Output: Amount saved (e.g., 500 yen) and estimated weight loss (e.g., 0.5 kg).

[1138] Step 6:

[1139] The server visualizes the calculation results in graphs and charts and displays them to the user.

[1140] Input: Amount saved and estimated weight loss.

[1141] Data processing: The server uses data visualization libraries such as D3.js and Chart.js to visualize the calculation results in graphs and charts.

[1142] Output: Graphs and charts displayed on the user's device.

[1143] (Application example 3)

[1144] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1145] Modern consumers find it difficult to manage their health and save money at the same time. In particular, consumers with dietary goals need to identify unnecessary products among their purchases and avoid them to achieve health and financial benefits. However, doing this manually is time-consuming and inaccurate. Therefore, a system is needed that allows consumers to easily identify unnecessary products and efficiently manage their savings and health.

[1146] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1147] In this invention, the server includes a means for a customer to enter their current height and weight and goals, a means for the customer to submit a purchase receipt after shopping, a means for correcting items determined to be unnecessary in this purchase, a means for visualizing the money saved and weight lost if unnecessary items are not purchased, a means for analyzing receipt information and automatically detecting unnecessary items based on diet goals, a means for calculating the amount of money saved and estimated weight loss if unnecessary items are not purchased and displaying them in graphs and charts, and an application installed on a smartphone. This allows consumers to easily identify unnecessary items and efficiently save money and manage their health.

[1148] "Customer" refers to the consumer who uses the system.

[1149] "Height and Weight" is data indicating the physical height and weight of a customer.

[1150] "Goals" refer to specific health or diet-related objectives that a customer wants to achieve.

[1151] A "purchase receipt" is paper or electronic data showing the purchase details of a product that a customer receives when making a purchase.

[1152] "Unwanted products" refer to products that are deemed inappropriate or unnecessary for the customer's goals.

[1153] "Money saved" refers to the amount of money you would save if you didn't buy unnecessary items.

[1154] "Weight loss" refers to the amount of weight loss predicted if the unnecessary product was not consumed.

[1155] "Receipt information" refers to data such as the product name, price, and quantity listed on the purchase receipt.

[1156] "Diet Goal" means a health goal set by a customer, such as weight loss or specific nutritional restrictions.

[1157] "Automatically detect" means that the system programmatically identifies unwanted products without human intervention.

[1158] "Graphs and charts" refer to diagrams that visually display data.

[1159] "Applications installed on a smartphone" refers to software programs that run on a smartphone.

[1160] The present invention is a system for enabling consumers to efficiently manage their health and save money. Specific embodiments for implementing this system will be described below.

[1161] System configuration

[1162] The system consists of the following main components:

[1163] 1. User device: A mobile device such as a smartphone.

[1164] 2. Server: A central server that processes and analyzes data.

[1165] 3. Application: A dedicated application installed on a smartphone.

[1166] Program processing

[1167] User Device

[1168] The user terminal has the following features:

[1169] User information input: Users enter their height, weight, and diet goals through the application.

[1170] Receipt scanning: The user scans the receipt for the purchased item with their smartphone camera and obtains the image data.

[1171] server

[1172] The server does the following:

[1173] Receipt information analysis: The acquired receipt image is converted into text data using OCR (Optical Character Recognition) technology. This process is performed using the pytesseract library.

[1174] Detection of unnecessary products: Based on the user's diet goal, the system automatically detects unnecessary products from the text data of the receipt. For example, for a user who is trying to limit their carbohydrate intake, the system detects high-carbohydrate products such as "bread" and "sweets."

[1175] Calculation of savings and weight loss: The total cost of the detected unnecessary products and the estimated weight loss if you did not consume those products are calculated. The weight loss calculation is based on the calories required to lose 1 kg of weight (approximately 7700 kcal).

[1176] application

[1177] The application has the following features:

[1178] Visualization of results: The calculated savings and estimated weight loss are displayed in graphs and charts, allowing users to visually see the effects of their health management and savings.

[1179] Specific examples

[1180] For example, if a user sets a goal of "restricting carbohydrates" and the receipt includes "bread" and "sweets," these items will be detected as unnecessary products. Let's say the total amount of the detected unnecessary products is 500 yen, and the estimated weight loss is 0.2 kg.

[1181] Prompt Sentence Examples

[1182] Enter your user information:

[1183] Height: 170 cm

[1184] Weight: 70 kg

[1185] Diet goal: Carbohydrate restriction

[1186] Scan your receipt:

[1187] (Upload a receipt image)

[1188] Detecting unwanted items...

[1189] Detected unwanted items:

[1190] Bread: 200 yen Sweets: 300 yen Savings: 500 yen

[1191] Estimated weight loss: 0.2kg

[1192] The results are displayed in a graph.

[1193] In this way, users can easily identify unnecessary products and efficiently save money and manage their health.

[1194] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1195] Step 1:

[1196] The user launches the smartphone application and enters their height, weight, and diet goals.

[1197] Input: User's height, weight, and diet goal

[1198] Output: User information data

[1199] Specific operation: The user enters their height, weight, and diet goal (e.g., carbohydrate restriction) into the application's input form and presses the submit button. This generates user information data and sends it to the server.

[1200] Step 2:

[1201] After shopping, the user scans the receipt for the purchased items with the smartphone camera.

[1202] Input: Receipt image

[1203] Output: Receipt image data

[1204] Specific operation: The user takes a photo of the purchase receipt using the camera function in the application. The captured image of the receipt is saved in the application and sent to the server.

[1205] Step 3:

[1206] The server receives the receipt image and converts it into text data using OCR technology.

[1207] Input: Receipt image data

[1208] Output: Receipt text data

[1209] Specific operation: The server uses the pytesseract library to extract text from the received receipt image data. The extracted text data is saved as receipt text data.

[1210] Step 4:

[1211] The server automatically detects unnecessary products from receipt text data based on the user's diet goal.

[1212] Input: User information data, receipt text data

[1213] Output: List of unwanted items

[1214] Specific operation: The server analyzes the receipt text data based on the user's diet goal (e.g., carbohydrate restriction). It lists products containing specific keywords (e.g., "bread" or "sweets") as unwanted items.

[1215] Step 5:

[1216] The server calculates the amount of money saved and the estimated weight loss if unnecessary items are not purchased.

[1217] Input: List of unwanted items

[1218] Output: Money saved, estimated weight loss

[1219] Specific operation: The server calculates the savings amount by adding up the prices of each product based on the list of unwanted products. It also calculates the estimated weight loss amount based on the calorie information of each product. The weight loss amount is calculated based on the calories required to lose 1 kg (approximately 7700 kcal).

[1220] Step 6:

[1221] The server visualizes the calculation results in graphs and charts and displays them on the user's smartphone.

[1222] Input: Amount saved, Estimated weight loss

[1223] Output: Image data of graphs and charts

[1224] Specific operation: Based on the calculation results, the server generates graphs and charts showing the savings and estimated weight loss. Image data of the generated graphs and charts is sent to the user's smartphone and displayed within the application.

[1225] In this way, users can easily identify unnecessary products and efficiently save money and manage their health.

[1226] 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.

[1227] "Example 1"

[1228] As one embodiment of the present invention, a system incorporating an emotion engine is provided. This system recognizes a user's emotions and determines unnecessary products based on those emotions. Specifically, when the user is feeling stressed, the system detects unhealthy foods such as sweets as unnecessary products. When the user is relaxed, the system recommends healthy foods.

[1229] "Example 2"

[1230] Furthermore, the emotion engine graphically displays the amount of money saved and weight lost based on the user's emotions. Specifically, it displays the amount of money saved and the amount of weight lost if the user refrains from buying unnecessary products when feeling stressed. This allows users to visually understand the relationship between their emotions, health management, and saving money.

[1231] "Example 3"

[1232] For example, if a user buys chocolate when they are stressed, the emotion engine will detect it as an unnecessary item and display a graph of the amount of money saved and weight lost if they had not bought the chocolate. This helps users recognize their tendency to buy unhealthy foods when they are stressed and understand the resulting financial and health impacts.

[1233] The processing flow of each embodiment will be described below.

[1234] "Example 1"

[1235] Step 1: The user enters their current height, weight, and goal into the system.

[1236] Step 2: The user makes a purchase and submits the receipt to the system.

[1237] Step 3: The emotion engine recognizes the user's emotion.

[1238] Step 4: The emotion engine determines which products are unnecessary based on the user's emotions and notifies the user of the results.

[1239] "Example 2"

[1240] Step 1: The user enters their current height, weight, and goal into the system.

[1241] Step 2: The user makes a purchase and submits the receipt to the system.

[1242] Step 3: The emotion engine recognizes the user's emotion.

[1243] Step 4: The emotion engine graphically displays the money saved and weight lost based on the user's emotions.

[1244] "Example 3"

[1245] Step 1: Buy chocolate when the user is feeling stressed.

[1246] Step 2: The emotion engine recognizes the user's emotions and detects chocolate as an unwanted product.

[1247] Step 3: The emotion engine will display a graph of the amount of money saved and the amount of weight lost if you don't buy the chocolate.

[1248] Example 1

[1249] Next, a description will be given of Example 1 of Form 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."

[1250] The previous system provided a way for customers to enter their height, weight, and goals, and to submit purchase receipts after shopping, but it lacked the functionality to determine unnecessary products based on the customer's emotions and recommend healthy products. This made it difficult for customers to select appropriate products when they were stressed or relaxed. There was also insufficient means to visualize the money saved and weight lost by not purchasing unnecessary products. This made it difficult to raise customers' awareness of health management and saving money.

[1251] 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.

[1252] In this invention, the server includes a means for the customer to enter their current height and weight and goals, a means for the customer to submit a purchase receipt after shopping, a means for correcting items that are determined to be unnecessary in this purchase, a means for visualizing the money saved and weight lost if the unnecessary items are not purchased, a means for recognizing the customer's emotions and determining unnecessary items based on those emotions, and a means for recommending healthy products based on the customer's emotions. This enables the customer to select appropriate products according to their emotional state, thereby increasing their awareness of health management and saving money.

[1253] "Customer" refers to an individual who uses the system to enter their height, weight, and diet goals, and then submits a purchase receipt after shopping.

[1254] "Height and Weight" refers to the customer's current physical height and weight.

[1255] "Goals" refer to specific numbers or conditions related to dieting or health that a customer wants to achieve.

[1256] "Input means" refers to the interface through which customers input their height, weight, and goals into the system.

[1257] "Purchase receipt" refers to paper or electronic data containing details of the purchase of goods that a customer receives when making a purchase.

[1258] "Submission means" refers to the interface through which a customer submits a purchase receipt to the system.

[1259] "Correction means" refers to the function by which the system determines unnecessary products based on the customer's input data and emotional data and notifies the customer.

[1260] "Visualization means" refers to the system's ability to graphically display the amount of money saved and weight lost if unnecessary products are not purchased.

[1261] "Emotion recognition means" refers to the system's ability to analyze customer emotions and determine which products are unnecessary based on those emotions.

[1262] "Healthy product recommendation means" refers to the system's ability to recommend healthy products based on customer sentiment.

[1263] This invention is a system that provides a dedicated input form for customers to enter their height, weight, and diet goals. This system is installed on a website or smartphone application, and allows customers to directly input their height, weight, diet goals, etc. In addition, by combining it with an emotion engine, it has the function of determining unnecessary products based on the customer's emotions and recommending healthy products.

[1264] The server places an input form on a website or smartphone application. This input form is created using HTML and CSS, and JavaScript is used to validate the input data in real time. When a user enters data into the input form, the server receives the data and stores it in a database (for example, MySQL or PostgreSQL).

[1265] Next, the server uses an emotion engine (for example, Microsoft Azure's Emotion API or Google Cloud's Natural Language API) to analyze the user's emotions. The emotion engine recognizes the user's current emotions based on the user's input data and past behavioral data. For example, if the user is feeling stressed, the server will use that information to determine that unhealthy foods such as sweets are unnecessary. On the other hand, if the user is relaxed, the server will recommend healthy foods.

[1266] As a concrete example, suppose a user uses a smartphone application to input their height as 170 cm, weight as 70 kg, and diet goal as "lose 5 kg." This data is sent to the server and stored in a database. The emotion engine then analyzes the user's emotions, and if it determines that the user is feeling stressed, the server displays a message such as "Avoid sweets such as chocolate and cookies."

[1267] Example prompts to input to a generative AI model:

[1268] A user enters their height as 170cm, weight as 70kg, and their diet goal as "lose 5kg." The emotion engine analyzes the user's emotions and determines that the user is feeling stressed. In this case, what products will be deemed unnecessary and what products will be recommended?

[1269] By inputting this prompt into a generative AI model, specific product recommendations and a determination of unnecessary products can be obtained. In this way, the system can make appropriate product recommendations based on the user's input data and emotional data.

[1270] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1271] Step 1:

[1272] The user accesses the input form.

[1273] A user opens a website or smartphone application. The device sends a request to the server through the browser or application to retrieve an input form. The server generates the input form using HTML and CSS and sends it to the device. The device renders the received HTML and CSS and displays the input form to the user.

[1274] Input: User's access request

[1275] Output: Display of input form

[1276] Step 2:

[1277] The user inputs their height, weight, and diet goal.

[1278] The user enters their height, weight, and diet goals into the displayed input form. The device uses JavaScript to validate the input data format in real time to ensure there are no errors.

[1279] Input: User's height, weight, and diet goal

[1280] Output: Validated input data

[1281] Step 3:

[1282] The server receives the input data and stores it in a database.

[1283] When the user presses the send button, the device sends the input data in JSON format to the server. The server parses the received data and saves it in a MySQL database. Specifically, it adds the data to the database using the INSERT statement.

[1284] Input: Input data in JSON format

[1285] Output: Data stored in the database

[1286] Step 4:

[1287] The server invokes the emotion engine to analyze the user's emotions.

[1288] The server calls an emotion engine (such as Microsoft Azure's Emotion API or Google Cloud's Natural Language API) based on the stored data. The data is sent to the API, which analyzes the user's emotions. The API determines that the user is feeling stressed and returns the result to the server.

[1289] Input: Data stored in a database

[1290] Output: Sentiment analysis results from the sentiment engine

[1291] Step 5:

[1292] The server judges unnecessary products based on emotions and determines recommended products.

[1293] The server determines which products are unnecessary and which are recommended based on the emotional data obtained from the emotion engine. For example, if the user is feeling stressed, the server will determine that "you should avoid sweets such as chocolate and cookies" and recommend "healthy foods such as fruits and nuts."

[1294] Input: Sentiment analysis results from the sentiment engine

[1295] Output: List of unwanted and recommended products

[1296] Step 6:

[1297] The server displays the results to the user.

[1298] The server generates HTML to display the results of the decision to the user and sends it to the terminal. The terminal renders the received HTML and displays unwanted products and recommended products to the user. The user checks the displayed results and decides on their next action.

[1299] Input: List of unwanted and recommended products

[1300] Output: The result displayed to the user

[1301] (Application example 1)

[1302] Next, a description will be given of Application Example 1 of Form 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."

[1303] Conventional food delivery systems do not recommend foods based on the user's health status or emotions, which can lead to unhealthy food choices when users are stressed. Furthermore, there is a lack of support for users to choose foods that are in line with their diet goals, making it difficult to diet effectively.

[1304] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes a means for the customer to enter their current height and weight and their goals, a means for the customer to submit a purchase receipt after shopping, a means for correcting products that are determined to be unnecessary in this shopping trip, a means for visualizing the money saved and weight lost if the unnecessary products are not purchased, and a means for recognizing the customer's emotions and determining unnecessary products based on those emotions. This makes it possible to recommend foods based on the user's health condition and emotions, allowing the user to avoid unhealthy foods when feeling stressed and to select foods that are in line with their diet goals.

[1305] "Customer" refers to a consumer who uses a service or product.

[1306] "Height and weight" is a numerical value that indicates an individual's physical height and weight.

[1307] A "goal" is a specific objective or state that a customer wants to achieve.

[1308] A "purchase receipt" is a paper or electronic record of a transaction issued when a customer purchases a product.

[1309] "Unnecessary products" are products that are deemed inappropriate for a customer's health condition or goals.

[1310] "Money saved" refers to the amount of money you would save if you didn't buy unnecessary items.

[1311] "Weight Loss" is a numerical value that represents the weight loss a customer can achieve by avoiding unnecessary products.

[1312] "Emotion recognition means" refers to technology or devices that detect a customer's emotional state and make decisions based on that.

[1313] "Visualization tools" refers to technologies or devices that visually display the money saved or weight lost.

[1314] The system for implementing this invention is configured as follows: First, a dedicated form is provided for users to enter their height, weight, and diet goals. This form is provided on a website or smartphone application, allowing users to easily enter information.

[1315] Next, we present a system that combines an emotion engine. This system recognizes the user's emotions in real time and determines which products are unnecessary based on those emotions. Specifically, when the user is feeling stressed, it detects unhealthy foods such as sweets as unnecessary products, and when the user is relaxed, it recommends healthy foods.

[1316] The following hardware and software are used to implement this system:

[1317] Hardware: Smartphone, tablet, or PC

[1318] Software: Python, EmotionRecognizer library, FoodRecommender library

[1319] The server receives the user's input data of height, weight, and diet goal, recognizes the user's emotions in real time using the EmotionRecognizer library, and then recommends appropriate foods based on the user's input data and the recognized emotions using the FoodRecommender library.

[1320] For example, if a user inputs that they are 170cm tall, weigh 65kg, and their diet goal is to "lose weight," and the emotion engine recognizes that the user is feeling stressed, the system will avoid unhealthy foods (e.g., sweet snacks) and instead recommend healthy foods (e.g., salads and fruit).

[1321] An example of a prompt is as follows:

[1322] "If a user inputs that they are 170cm tall, weigh 65kg, and their diet goal is to lose weight, and the emotion engine recognizes that the user is stressed, what foods will be recommended?"

[1323] In this way, food recommendations can be made based on the user's health status and emotions, helping users avoid unhealthy foods when they are stressed and choosing foods that are in line with their diet goals.

[1324] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1325] Step 1:

[1326] The user uses the terminal to input their height, weight, and diet goal. The input data is sent to the server. The input data includes the user's height (e.g., 170 cm), weight (e.g., 65 kg), and diet goal (e.g., "lose weight").

[1327] Step 2:

[1328] The server stores the received user input data and uses the EmotionRecognizer library to recognize the user's emotions in real time. For emotion recognition, the user's facial expressions and voice data are used as input. The output is the user's emotional state (e.g., stressed, relaxed).

[1329] Step 3:

[1330] The server uses the FoodRecommender library to recommend appropriate foods based on the recognized emotional state and the user's input data. The input data includes the user's height, weight, diet goal, and emotional state. The output is a list of recommended foods (e.g., salads, fruits).

[1331] Step 4:

[1332] The server sends the recommended food list to the user's device, where the user can check the recommended food list on the device. Specifically, if the user is feeling stressed, the system will avoid unhealthy foods and recommend healthy foods.

[1333] Step 5:

[1334] A user makes a purchase and submits the purchase receipt to the server using a terminal. The server analyzes the submitted receipt data and generates a list of the purchased items. Input data includes receipt images or electronic data. The output is a list of the purchased items.

[1335] Step 6:

[1336] The server compares the list of purchased items with the user's diet goals and emotional state to determine which items are unnecessary. Specifically, it detects items that are inappropriate for the user's goals (e.g., sweet snacks). Input data includes the list of purchased items, the user's diet goals, and the user's emotional state. The output is a list of unnecessary items.

[1337] Step 7:

[1338] The server calculates and visualizes the money saved and weight lost if unnecessary items are not purchased. Specifically, it graphically displays the amount saved and weight lost. The input data includes a list of unnecessary items. The output is a graphical representation of the amount saved and weight lost.

[1339] Step 8:

[1340] The server sends the visualized data to the user's device, where the user can check the amount of money saved and the weight loss achieved. Specifically, the user can visually understand the benefits of avoiding unnecessary products.

[1341] Example 2

[1342] Next, a description will be given of Example 2 of Form 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."

[1343] Conventional health management systems have the problem that customers have to submit physical proof of purchase after shopping, which is time-consuming.In addition, the system does not take into account the customer's emotional state to visualize the amount of savings or weight loss, making it difficult for customers to understand the relationship between their emotions, health management, and savings.

[1344] 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.

[1345] In this invention, the server includes: means for the customer to enter their current physical information and goals; means for the customer to submit a proof of purchase after shopping; means for the customer to take an image of the proof of purchase using the image capture function of their mobile device and upload it to the application; means for the server to convert the contents of the proof of purchase into text data using image processing technology; means for the server to save the converted text data; means for the customer to input emotional data; means for the server to analyze the customer's emotional data using emotion analysis technology; means for the server to determine unnecessary products based on the analysis results and calculate the amount of savings and weight loss; and means for the server to graphically display the calculation results. This allows customers to communicate their purchase information to the system without directly submitting a physical proof of purchase, and further enables them to visually understand the relationship between their emotions, health management, and savings.

[1346] "Customer" refers to an individual who uses the system to manage their own health and save money.

[1347] "Physical information" refers to physical data such as a customer's height, weight, and body fat percentage.

[1348] "Goals" refer to the health or savings goals the customer wants to achieve.

[1349] "Proof of purchase" refers to a document that proves a purchase, such as a receipt or invoice, that a customer receives after shopping.

[1350] "Mobile device" refers to a portable electronic device such as a smartphone or tablet.

[1351] "Photography function" refers to the camera function installed in the mobile terminal.

[1352] "Application" refers to a software program that runs on a mobile device.

[1353] "Image processing technology" refers to the technology of analyzing image data and extracting necessary information.

[1354] "Text data" refers to character information extracted using image processing technology.

[1355] "Emotional data" refers to data that indicates a customer's emotional state.

[1356] "Emotion analysis technology" refers to technology that analyzes emotional data and evaluates a customer's emotional state.

[1357] "Unnecessary products" are products that are determined not to be necessary for a customer's health or savings goals.

[1358] "Savings" refers to the amount of money you can save by not purchasing unnecessary items.

[1359] "Weight lost" refers to the weight you would lose if you didn't purchase unnecessary items.

[1360] "Displaying graphically" refers to displaying the calculation results in a visually easy-to-understand manner.

[1361] MODE FOR CARRYING OUT THE INVENTION

[1362] This invention is a system in which a customer submits a purchase certificate after shopping and visualizes the amount of savings and weight loss based on emotion data. A specific embodiment of this system will be described below.

[1363] System configuration

[1364] This system mainly uses the following hardware and software:

[1365] Mobile devices (smartphones and tablets)

[1366] Camera features

[1367] application

[1368] server

[1369] Image processing software (e.g., OpenCV, Tesseract)

[1370] Emotion analysis technology

[1371] Program processing

[1372] After shopping, the user takes a picture of the purchase certificate using the camera function of their mobile device. The image is then uploaded to the server via the application. The server then uses image processing software (e.g., OpenCV or Tesseract) to extract the text from the image and convert information such as the name, price, and quantity of the purchased item into text data. The server then stores this text data in a database.

[1373] Next, the user inputs their emotional data through the application. The emotional data may be entered manually by the user or automatically obtained from the wearable device. The server then analyzes the emotional data using emotion analysis technology to evaluate whether the user is feeling stressed and to what extent.

[1374] Based on the results of the emotion analysis, the server calculates the amount of money saved and the amount of weight lost if the user refrains from buying unnecessary items when feeling stressed. For example, if the user refrains from buying chocolate when feeling stressed, the calculation is based on the price (200 yen) and calories (300 kcal). The calculation results are displayed graphically by the server, and the user can check them through the application.

[1375] Specific examples

[1376] As a concrete example, consider the case where a user refrains from buying chocolate when they are feeling stressed. The user takes a photo of the receipt with their smartphone camera and uploads it to an application. The server uses image processing software to convert the contents of the receipt into text data and stores it in a database. Next, the user enters emotional data into the application, which the server analyzes using emotion analysis technology. Based on the analysis results, the server calculates the amount of savings and weight loss based on the price (200 yen) and calories (300 kcal) of the chocolate. Finally, the server displays the calculation results graphically, and the user can check them through the application.

[1377] Prompt Sentence Examples

[1378] Example prompts to input to a generative AI model:

[1379] "Generate a program that calculates and graphically displays the amount of money saved and weight lost if the user avoids buying unnecessary items when they are stressed."

[1380] In this way, users can visually understand the relationship between their emotions, health management, and savings.

[1381] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1382] Step 1:

[1383] The user takes a photo of the proof of purchase using their smartphone camera.

[1384] Input: Proof of purchase

[1385] Output: Image of proof of purchase

[1386] Specific operation: The user activates the smartphone camera, frames the purchase certificate, and presses the capture button. The captured image is saved in the smartphone's gallery.

[1387] Step 2:

[1388] The device takes a picture of the proof of purchase and uploads it to the application.

[1389] Input: Image of proof of purchase

[1390] Output: Image data sent to the server

[1391] Specific operation: The user starts the application, selects an image of the purchase certificate, and presses the upload button. The device then sends the selected image to the server.

[1392] Step 3:

[1393] The server uses image processing technology to convert the contents of the purchase certificate into text data.

[1394] Input: Image data of purchase certificate

[1395] Output: Text data

[1396] Specific operation: The server analyzes the received image data using image processing software (e.g., OpenCV, Tesseract) and extracts text information from the image. The extracted text information is converted into text data such as the name, price, and quantity of the purchased item.

[1397] Step 4:

[1398] The server stores the converted text data in a database.

[1399] Input: Text data

[1400] Output: Purchase information stored in a database

[1401] Specific operation: The server saves the converted text data in a database, including the purchase date and time, store name, product information, etc.

[1402] Step 5:

[1403] The user inputs emotion data into the application.

[1404] Input: Emotion data

[1405] Output: Emotion data sent to the server

[1406] How it works: Users input their emotional state through the application. Emotional data includes information such as stress level and mood, and may also be automatically obtained from a wearable device.

[1407] Step 6:

[1408] The server analyzes the user's emotional data using emotion analysis technology.

[1409] Input: Emotion data

[1410] Output: Analysis results

[1411] Specific operation: The server analyzes the emotional data using emotion analysis technology to evaluate whether the user is feeling stressed and how stressed they are. The analysis results are displayed as numbers and graphs.

[1412] Step 7:

[1413] The server determines unnecessary products based on the analysis results and calculates the amount of money saved and the weight lost.

[1414] Input: Analysis results, text data

[1415] Output: Data on savings and weight loss

[1416] Specific operation: Based on the results of emotion analysis and purchase information, the server calculates the amount of money saved and the amount of weight lost if the user does not buy unnecessary products when feeling stressed. For example, it calculates the amount of money saved and the amount of weight lost based on the price (200 yen) and calories (300 kcal) of chocolate.

[1417] Step 8:

[1418] The server displays the calculation results graphically.

[1419] Input: Data on savings and weight loss

[1420] Output: Graphical display

[1421] Specific operation: The server generates data for graphically displaying the calculation results and provides it to the user through the application, allowing the user to visually check the amount of savings and weight loss through the application.

[1422] (Application example 2)

[1423] Next, a description will be given of Application Example 2 of Form 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."

[1424] Conventional shopping support systems require customers to physically submit receipts for purchased items, which is a time-consuming process. Furthermore, the system does not take into consideration the customer's emotions or health status, leading to unnecessary purchases when they are stressed. This leads to wasteful spending and negative health effects, which is an issue.

[1425] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1426] In this invention, the server includes a means for the customer to enter their current height and weight and goals, a means for the customer to take a photo of their purchase receipt using their smartphone camera after shopping and upload it to the application, a means for correcting items that are determined to be unnecessary in this purchase, a means for visualizing the money saved and weight lost if the customer does not buy unnecessary items, and a means for analyzing the customer's emotions and graphically displaying the amount of money saved and weight lost if the customer does not buy unnecessary items when they are feeling stressed. This saves the customer the trouble of submitting a physical receipt and enables shopping support that takes their emotions and health state into consideration.

[1427] A "customer" is a consumer who purchases goods or services.

[1428] "Height and Weight" refers to the customer's height and weight.

[1429] A "goal" is a specific number or state that a customer wants to achieve.

[1430] A "purchase receipt" is a proof of purchase issued when a customer purchases a product.

[1431] A "smartphone camera" is a photographic device built into a smartphone.

[1432] An "application" is a software program that runs on a smartphone or other device.

[1433] "Uploading" is the act of transferring data from a local device to a server or cloud.

[1434] "Correction" is the act of checking the content and correcting or deleting unnecessary parts.

[1435] "Unnecessary products" are products that the customer has determined not to need to purchase.

[1436] "Money saved" is the amount of money you would save if you didn't buy the unnecessary item.

[1437] "Weight lost" is the weight lost as a result of not purchasing unnecessary items.

[1438] "Visualization" is the act of visually displaying data or information.

[1439] "Analyzing emotions" is the process of assessing and understanding a customer's emotional state.

[1440] "Stress" refers to mental or physical tension or strain.

[1441] "Graphically displayed" means displaying information in a visual format such as a graph or chart.

[1442] This invention provides a system that allows customers to take a photo of their purchase receipt using a smartphone camera after shopping and upload it to an application. It also includes a function that analyzes the customer's emotions and graphically displays the amount of money saved and the amount of weight lost if they avoid buying unnecessary items when they are feeling stressed.

[1443] System configuration

[1444] 1. Hardware:

[1445] Smartphone: Use the camera to take a photo of your purchase receipt.

[1446] Server: Serves as the backend for the application, storing and processing data.

[1447] 2. Software:

[1448] Application: Installed on a smartphone, it takes a photo of a receipt, uploads it, analyzes its sentiment, and displays it graphically.

[1449] OpenCV: A library for loading and preprocessing receipt images.

[1450] Tesseract OCR: Optical character recognition software for extracting text from receipt images.

[1451] EmotionRecognizer: Emotion recognition software for analyzing customer emotions.

[1452] Matplotlib: A library for graphically displaying savings and weight loss.

[1453] System Operation

[1454] 1. Take a photo of your receipt and upload it:

[1455] The user takes a photo of the purchase receipt using the smartphone camera.

[1456] The captured images are uploaded to the server through the application.

[1457] 2. Text extraction:

[1458] The server preprocesses the images using OpenCV and extracts text from the receipt using Tesseract OCR.

[1459] 3. Sentiment analysis:

[1460] The server analyzes the user's emotions using EmotionRecognizer.

[1461] If you're feeling stressed, calculate how much money you'll save and how much weight you'll lose if you don't buy the item you don't need.

[1462] 4. Graphical display:

[1463] The server generates data using Matplotlib to graphically display the savings and weight loss and sends it to the application.

[1464] The application will display this visually to the user.

[1465] Specific examples

[1466] For example, if a user avoids buying unnecessary items when feeling stressed, the application will graphically display a savings of 1,000 yen and a weight loss of 0.5 kg.

[1467] Prompt Sentence Examples

[1468] Create a program that calculates and graphically displays the savings and weight loss a user could achieve by not buying unnecessary items when they are feeling stressed. Take a photo of the receipt with a smartphone camera and extract the text using Tesseract OCR. Analyze the user's emotions using EmotionRecognizer and display the results using Matplotlib.

[1469] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1470] Step 1:

[1471] The user takes a photo of the purchase receipt using the smartphone camera.

[1472] Input: Physical image of purchase receipt

[1473] Output: Receipt image saved on the smartphone

[1474] Specific operation: The user launches the smartphone's camera app and takes a picture of the purchase receipt. The captured image is saved in the smartphone's storage.

[1475] Step 2:

[1476] The device uploads the captured receipt image to the application.

[1477] Input: Receipt image saved on your smartphone

[1478] Output: Receipt image uploaded to the server

[1479] Specific operation: The user launches the application, selects the image of the receipt they have taken, and presses the upload button. The image is then sent to the server via the Internet.

[1480] Step 3:

[1481] The server preprocesses the receipt image using OpenCV and extracts text using Tesseract OCR.

[1482] Input: Receipt image uploaded to the server

[1483] Output: Extracted text data

[1484] What it does: The server uses OpenCV to remove noise from the image and highlight the text, then uses Tesseract OCR to extract the text from the image.

[1485] Step 4:

[1486] The server analyzes the user's emotions using EmotionRecognizer.

[1487] Input: User emotional data (e.g., the emotional state the user inputs into the application)

[1488] Output: Analyzed emotional state

[1489] Specific operation: The server uses EmotionRecognizer to analyze the user's emotional data and determine whether they are under stress.

[1490] Step 5:

[1491] If the server is stressed, it calculates the amount of money saved and weight loss that would result from not buying unnecessary items.

[1492] Input: Analyzed emotional state, extracted text data

[1493] Output: Savings and weight loss data

[1494] Specific operation: If the emotional state is stressed, the server identifies unnecessary products from the extracted text data and calculates the amount of money saved and the amount of weight lost if the product is not purchased.

[1495] Step 6:

[1496] The server generates data using Matplotlib to graphically display the savings and weight loss and sends it to the application.

[1497] Input: Savings and weight loss data

[1498] Output: Image data for graphical display

[1499] What it does: The server uses Matplotlib to generate an image that visually displays the savings and weight loss in the form of a bar graph or similar, and then sends the image data to the application.

[1500] Step 7:

[1501] The terminal displays the graphical data received from the server to the user.

[1502] Input: Graphical image data sent from the server

[1503] Output: Graphical information displayed on a smartphone screen

[1504] Specific operation: The application displays the image data received from the server on the smartphone screen, allowing the user to visually check the amount of savings and weight loss.

[1505] Example 3

[1506] Next, a description will be given of Example 3 of Form Example 3. 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."

[1507] Modern consumers aim to balance health management with saving money, but they often end up buying unnecessary products in their daily shopping. These unnecessary products not only go against health goals but also cause wasteful spending. However, it is not easy for consumers to identify and avoid these unnecessary products. Therefore, there is a need for a system that automatically detects unnecessary products based on consumers' health goals and visualizes the amount of money they can save and their impact on their health.

[1508] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1509] In this invention, the server includes means for a customer to input their current height and weight and goals, means for the customer to upload an image of their purchase receipt after shopping, means for converting the receipt image into digital data using optical character recognition technology, means for analyzing product information from the digital data and detecting unnecessary products, means for calculating the total price of the unnecessary products and the estimated weight loss amount, and means for visualizing the calculation results in graphs and charts. This allows consumers to automatically detect unnecessary products based on their own health goals and specifically understand the amount of money they can save and the impact on their health.

[1510] "Customers" are consumers who use the system to manage their own health and save money.

[1511] "Height and weight" is the customer's basic physical data and is basic information for setting health goals.

[1512] "Goals" are health and weight management goals that a customer wants to achieve, such as carbohydrate restriction and calorie restriction.

[1513] "Receipt image" is photo data of the purchase details that a customer obtains after shopping.

[1514] "Optical character recognition technology" is a technology that converts character information in an image into digital data, and is also known as OCR (Optical Character Recognition).

[1515] "Digital data" is textual information that has been converted using optical character recognition technology.

[1516] "Product information" refers to data such as the product name, price, and nutritional information listed on the receipt.

[1517] "Unnecessary products" are products that are contrary to the customer's health goals and should be avoided.

[1518] "Total amount" is the total price of the detected unwanted items.

[1519] "Estimated weight loss" is the amount of weight loss predicted if the unnecessary product was not consumed.

[1520] "Graphs and charts" are diagrams that visually display the results of calculations.

[1521] The present invention is a system for enabling consumers to efficiently manage their own health and save money. A specific embodiment of this system will be described below.

[1522] First, a user accesses the system's web page using a terminal. The user inputs their height, weight, and health goal (e.g., carbohydrate restriction). This data is sent to the server and stored in a database.

[1523] Next, the user uploads an image of the receipt they have taken after shopping to the system from their device. The uploaded image is then sent to the server, which uses optical character recognition technology such as Google Cloud Vision API to convert the image into digital data. This digital data includes the text information on the receipt.

[1524] The server analyzes the converted digital data and extracts product names and their nutritional information. For example, if a receipt includes "bread" or "sweets," these items are listed as unnecessary because they go against the goal of carbohydrate restriction.

[1525] The server then calculates the total cost of the unnecessary items and the estimated weight loss that would occur if these items were not consumed. A standard calorie expenditure model is used to calculate weight loss. The results are visualized as graphs and charts using a data visualization library such as D3.js.

[1526] The user can use their device to check the graphs and charts sent from the server, which allows them to visually understand the amount of money they would save and the amount of weight they would lose if they did not buy unnecessary products.

[1527] As a concrete example, consider the case where a user purchases chocolate when feeling stressed. The emotion engine analyzes the user's emotional state and determines that stress is high. In this case, it detects chocolate as an unnecessary product and displays a graph of the amount of money saved and weight loss that would have been achieved if the user had not purchased the chocolate. This helps the user recognize that they tend to purchase unhealthy foods when they are stressed, and understand the resulting financial and health impacts.

[1528] Example prompt sentence:

[1529] Detect the foods the user buys when they are stressed, calculate how much money they would save and how much weight they would lose if they had avoided buying those foods, and display the results in a graph.

[1530] This system allows the user to specifically understand both their own health management and savings. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1531] Step 1:

[1532] The user inputs their height, weight, and goal.

[1533] A user accesses the system's web page using a terminal and enters their height (e.g., 170 cm), weight (e.g., 70 kg), and health goal (e.g., carbohydrate restriction) into the form. The entered data is sent to the server and stored in the database.

[1534] Input: Height, Weight, Health Goals

[1535] Output: User information stored in the database

[1536] Step 2:

[1537] The user uploads an image of the receipt.

[1538] Users use their terminals to upload receipt images from recent purchases to the system, which are then sent to the server.

[1539] Input: Receipt image

[1540] Output: Receipt image saved on the server

[1541] Step 3:

[1542] The server performs OCR on the receipt image.

[1543] The server converts the receipt image into digital data using optical character recognition (OCR) technology, specifically by calling the Google Cloud Vision API.

[1544] Input: Receipt image

[1545] Output: Digital data (text information)

[1546] Step 4:

[1547] The server analyzes the product information and detects unnecessary products.

[1548] The server analyzes the digital data obtained through OCR processing and extracts product names and their nutritional information. For example, if a receipt includes "bread" or "sweets," these items are not in line with the goal of limiting carbohydrate intake, so they are listed as unnecessary items.

[1549] Input: Digital data (text information), user's health goals

[1550] Output: List of unwanted items

[1551] Step 5:

[1552] The server calculates the total price of unwanted items and the estimated weight loss.

[1553] The server calculates the total value of the detected unwanted products and the estimated weight loss that would occur if the user did not consume these products, using a standard calorie expenditure model.

[1554] Input: List of unwanted items, product price, calorie information

[1555] Output: Total amount, estimated weight loss

[1556] Step 6:

[1557] The server visualizes the calculation results in graphs and charts.

[1558] The server uses a data visualization library such as D3.js to generate graphs and charts of the total value of unwanted items and the estimated weight loss.

[1559] Input: Total amount, estimated weight loss

[1560] Output: Graphs and charts

[1561] Step 7:

[1562] The user checks the results.

[1563] The user can use their device to check the graphs and charts sent from the server, which allows them to visually understand the amount of money they would save and the amount of weight they would lose if they did not buy unnecessary products.

[1564] Input: Graphs and charts

[1565] Output: User understanding and recognition

[1566] (Application example 3)

[1567] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1568] Today's consumers are expected to manage their health and save money at the same time, but it is difficult to determine which products are unnecessary when shopping. Furthermore, there is a lack of ways to grasp the specific amount of savings and weight loss that can be achieved by not purchasing unnecessary products. Therefore, a system that allows consumers to make healthy choices and realize the savings is needed.

[1569] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1570] In this invention, the server includes a means for a customer to enter their current height and weight and goals, a means for the customer to submit a purchase receipt after shopping, a means for correcting items that are determined to be unnecessary in this shopping trip, a means for visualizing the money saved and weight lost if the unnecessary items are not purchased, a means for detecting unnecessary items and calculating the amount of savings and weight loss, and a means for displaying the detection results in a graph. This allows consumers to easily identify unnecessary items when shopping and specifically understand both health management and saving.

[1571] "Customer" refers to a consumer who makes a purchase using the system.

[1572] "Height and Weight" refers to the customer's current physical height and weight.

[1573] "Goals" refer to specific health or diet-related objectives that a customer wants to achieve.

[1574] "Purchase receipt" refers to paper or electronic data showing the purchase details of goods received by a customer when making a purchase.

[1575] "Unnecessary items" are items that should be removed from the shopping list based on the customer's height, weight, and goals.

[1576] "Money saved" refers to the amount of money you would save if you didn't buy unnecessary items.

[1577] "Weight loss" refers to the amount of weight loss predicted if the unnecessary product was not consumed.

[1578] "Visualization tools" refers to ways to display the money saved and weight lost in visual form, such as graphs or charts.

[1579] "Means of detection" refers to a method for identifying unwanted products based on a customer's height, weight, and goals.

[1580] "Means of calculation" refers to a method for calculating the amount of money saved and the amount of weight lost by not buying unnecessary items.

[1581] "Graphical display means" refers to a method for displaying detection results in a visually easy-to-understand format.

[1582] A system for implementing this invention includes means for a customer to enter their current height and weight and their goal, means for the customer to submit a purchase receipt after shopping, means for correcting items that are determined to be unnecessary for this purchase, means for visualizing the money saved and weight lost if the unnecessary items are not purchased, means for detecting unnecessary items and calculating the amount saved and the amount of weight lost, and means for displaying the detection results in a graph.

[1583] System configuration

[1584] The system is implemented as a smartphone application. The application is built using Python and Flask, and performs data processing on the server side. The smartphone sends the height, weight, and goal information entered by the user, as well as receipt information, to the server.

[1585] Data processing and calculation

[1586] The server receives the data sent by the user and performs the following processing.

[1587] 1. Unwanted product detection:

[1588] The server identifies unnecessary items on the receipt based on the user's height, weight, and goals. For example, if the user's goal is to "limit carbohydrates," the server detects "bread" and "sweets" on the receipt as unnecessary items.

[1589] 2. Savings and Weight Loss Calculation:

[1590] The server calculates the amount of money saved and the amount of weight lost if the unnecessary items were not purchased, for example, by adding up the prices of the unnecessary items and calculating the amount of weight lost based on the calories in those items.

[1591] 3. Visualizing the results:

[1592] The server generates the calculation results in the form of graphs and charts and sends them to a smartphone application, where users can visually check the results.

[1593] Hardware and software used

[1594] Hardware: Smartphone

[1595] Software: Python, Flask

[1596] Specific examples

[1597] If the user's goal is to "limit carbohydrates" and the receipt includes "bread" and "sweets," the system will detect these as unnecessary items. The savings will be calculated as 350 yen (bread 150 yen + sweets 200 yen) and the weight loss will be 0.064 kg (500 kcal / 7700 kcal). These results are displayed as a graph on the smartphone application.

[1598] Prompt Sentence Examples

[1599] If the user is aiming to limit carbohydrates, detect unnecessary items in the receipt and calculate the savings and weight loss. Use the following data:

[1600] Height: 170cm

[1601] Weight: 70kg

[1602] Goal: Carbohydrate restriction

[1603] Receipt items: ["Bread", "Sweets", "Vegetables"]

[1604] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1605] Step 1:

[1606] The user starts the smartphone application and inputs their current height and weight and their goal.

[1607] Input: Height, Weight, Goal

[1608] Output: Height, weight, goal data

[1609] Specific actions: The user enters their height, weight, and goal into the application's input form and presses the submit button.

[1610] Step 2:

[1611] After shopping, the user scans the purchase receipt with their smartphone and uploads it to the application.

[1612] Input: Purchase receipt image

[1613] Output: Receipt text data

[1614] How it works: A user takes a photo of a receipt using their smartphone camera and uploads it to the application, which then uses OCR technology to extract text data from the image.

[1615] Step 3:

[1616] The server receives the text data of the height, weight, goal, and receipt sent by the user.

[1617] Input: Height, weight, goal, receipt text data

[1618] Output: Save received data

[1619] What happens: The server receives the HTTP request and stores the data in a database.

[1620] Step 4:

[1621] The server detects unwanted items on the receipt based on the user's goals.

[1622] Input: Height, weight, goal, receipt text data

[1623] Output: List of unwanted items

[1624] Specific operation: The server references the list of unwanted items related to the goal and identifies the unwanted items by matching them with the text data on the receipt.

[1625] Step 5:

[1626] The server calculates the amount of savings and weight loss if unnecessary items are not purchased.

[1627] Input: List of unwanted items

[1628] Output: Savings, weight loss

[1629] Specific operation: The server adds up the prices of the unwanted items and calculates the weight loss amount based on the calories of the unwanted items. For example, if the total price of the unwanted items is 350 yen and the total calories are 500 kcal, the weight loss amount will be calculated as 0.064 kg (500 kcal / 7700 kcal).

[1630] Step 6:

[1631] The server generates the calculation results in the form of graphs or charts and sends them to the smartphone application.

[1632] Input: Amount saved, Weight lost

[1633] Output: Image data for graphs and charts

[1634] Specific operation: The server generates graphs and charts based on the calculation results and sends them to the smartphone application as image data.

[1635] Step 7:

[1636] Users can visually check the savings and weight loss results through a smartphone application.

[1637] Input: Image data of graphs and charts

[1638] Output: Visual results

[1639] What it does: The user opens the app and sees the graphs and charts that show them how much money they could save and how much weight they could lose if they didn't buy the unnecessary items.

[1640] 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.

[1641] 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> ) 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.

[1642] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1643] 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.

[1644] [Third embodiment]

[1645] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1646] 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.

[1647] 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).

[1648] 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.

[1649] The microphone 238 receives the voice uttered by the user 20,

[1650] 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 according to instructions from the processor 46.

[1651] 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).

[1652] 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.

[1653] 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.

[1654] 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.

[1655] 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.

[1656] 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.

[1657] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1658] "Example 1"

[1659] This embodiment of the present invention provides a dedicated input form as a means for consumers to enter their height, weight, and diet goals. This input form is provided on a website or smartphone application, and allows consumers to directly input their height, weight, diet goals, etc.

[1660] "Example 2"

[1661] Next, as a means for consumers to submit their purchase receipts after shopping, the system provides a function for them to take an image of the receipt using their smartphone camera and upload it to the application. This function allows consumers to communicate purchase information to the system without having to submit a physical receipt directly.

[1662] "Example 3"

[1663] The system also uses the consumer's data to identify items that are deemed unnecessary for this shopping trip.

[1664] The system automatically detects unnecessary products based on the height, weight, and goal entered by the user, as well as the submitted receipt information. For example, if the diet goal is to "limit carbohydrates," the system will detect items on the receipt that are high in carbohydrates, such as "bread" and "sweets," as unnecessary products.

[1665] "Example 4"

[1666] Finally, to visualize the money saved and weight lost by not purchasing unnecessary products, the system calculates the total cost of the detected unnecessary products and the estimated weight loss if those products were not consumed, and displays this information to consumers in the form of graphs, charts, etc. This allows consumers to concretely understand both their health management and savings.

[1667] The processing flow of each embodiment will be described below.

[1668] "Example 1"

[1669] Step 1: The consumer enters their height, weight, diet goal, etc. into a dedicated input form. For example, a height of 170 cm, weight of 65 kg, and diet goal of "restricting carbohydrates" may be entered.

[1670] Step 2: Once completed, the consumer presses the "Submit" button to send the information to the system.

[1671] "Example 2"

[1672] Step 1: The consumer makes a purchase and gets a receipt for the items purchased.

[1673] Step 2: The consumer takes a picture of the receipt using their smartphone camera.

[1674] Step 3: The captured image is uploaded to the application and the system reads the receipt information.

[1675] "Example 3"

[1676] Step 1: The system automatically detects unwanted products based on the consumer's height, weight, and goals entered, as well as the submitted receipt information.

[1677] Step 2: For example, if the diet goal is to "limit carbohydrates," the system will detect high-carbohydrate items on the receipt, such as "bread" and "sweets," as unnecessary items.

[1678] "Example 4"

[1679] Step 1: The system calculates the total value of the detected unwanted products and the estimated weight loss if the product was not consumed.

[1680] Step 2: The calculation results are displayed to the consumer in the form of graphs, charts, etc. This allows the consumer to concretely understand both their health management and savings.

[1681] Example 1

[1682] Next, a description will be given of Example 1 of Form 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."

[1683] Conventional diet support systems required users to not only input their height, weight, and diet goals, but also to submit purchase receipts after shopping and determine which items they no longer needed. However, these systems were time-consuming for users, making it difficult for them to use them continuously. In addition, they lacked the functionality to propose an appropriate individual diet plan based on the data entered by the user, which meant that they were unable to provide effective diet support.

[1684] 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.

[1685] In this invention, the server includes a means for the customer to enter their current height and weight and goals, a means for the customer to submit a purchase receipt after shopping, a means for correcting items that are determined to be unnecessary in this shopping trip, a means for visualizing the money saved and weight lost if the unnecessary items are not purchased, a means for receiving and saving the data entered by the customer, a means for generating prompts for the generative AI model based on the saved data, and a means for the generative AI model to suggest a diet plan.This allows the user to continue using the service without any hassle, and makes it possible to suggest an appropriate diet plan individually.

[1686] "Customer" refers to a user of the system.

[1687] "Height and Weight" refers to the customer's current height and weight data.

[1688] "Goals" refers to diet and health goals set by the Customer.

[1689] "Input form" refers to the interface through which customers enter data such as height, weight, and goals.

[1690] "Purchase Receipt" means a detailed statement of purchases received by a Customer after making a purchase.

[1691] "Means of correction" refers to the function of determining unnecessary products based on the customer's height, weight, and goals, and removing them from the list.

[1692] "Visualization means" refers to a function that visually displays the money you can save or the weight you will lose if you don't buy unnecessary products.

[1693] "Means of receiving and storing data" refers to the function by which the server receives data entered by the customer and stores it in a database, etc.

[1694] A "generative AI model" refers to an artificial intelligence model that generates an appropriate diet plan based on input data.

[1695] A "prompt sentence" refers to an instruction sentence generated for a generative AI model based on input data.

[1696] "Diet Plan" refers to a specific action plan proposed by the generative AI model to help customers achieve their goals.

[1697] This invention is a system that provides a dedicated input form for customers to enter their height, weight, and diet goals. The system is installed on a website or smartphone application, and a generative AI model proposes an appropriate diet plan based on the data entered by the customer.

[1698] Hardware and software used

[1699] Hardware: Servers (e.g., AWS EC2), user devices (e.g., smartphones, PCs)

[1700] Software: Web servers (e.g., Apache, Nginx), databases (e.g., MySQL, PostgreSQL), smartphone applications (e.g., iOS apps, Android apps)

[1701] Specific operation of the system

[1702] server

[1703] The server provides a dedicated input form on a website or smartphone application, where customers can enter their height, weight, diet goals, etc. The server receives the input data and stores it in a database. The stored data is used as prompts for the generative AI model.

[1704] Terminal

[1705] The device displays the websites and smartphone applications that the user accesses. When the user enters their height, weight, and diet goals into an input form, the device sends the data to the server. The device then displays the data that the user has entered in real time, allowing them to check it.

[1706] User

[1707] Users access a website or smartphone application and enter their height, weight, and diet goals into a dedicated input form. Once the user has completed the input, the data is sent to the server. The user can then review the data they have entered and make any necessary corrections.

[1708] Specific examples

[1709] Example 1: Website use

[1710] A user visits a website and fills out a form with the following information:

[1711] Height: 170 cm

[1712] Weight: 70 kg

[1713] Diet goal: Lose 5 kg

[1714] Once the input is complete, the device sends this data to the server, which receives it and stores it in a database. The server then generates the following prompt for the generative AI model:

[1715] Example prompt sentence:

[1716] The user is 170 cm tall, weighs 70 kg, and has a goal of losing 5 kg. Based on this information, please suggest an appropriate diet plan.

[1717] Example 2: Use in a smartphone application

[1718] A user opens a smartphone application and enters the following information into the input form:

[1719] Height: 160 cm

[1720] Weight: 60 kg

[1721] Diet goal: Lose 3 kg

[1722] Once the input is complete, the device sends this data to the server, which receives it and stores it in a database. The server then generates the following prompt for the generative AI model:

[1723] Example prompt sentence:

[1724] The user is 160 cm tall, weighs 60 kg, and has a goal of losing 3 kg. Based on this information, please suggest an appropriate diet plan.

[1725] In this way, a system is constructed in which a generative AI model suggests an appropriate diet plan based on the data entered by the user.

[1726] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1727] Step 1:

[1728] The user accesses the input form.

[1729] A user opens a website or smartphone application and accesses an input form. The input form is an interface where the user can enter their height, weight, and diet goals. Once the input form is displayed, the user is ready to enter the required information.

[1730] Step 2:

[1731] The user enters the data.

[1732] The user enters their height, weight, and diet goal in the input form. For example, the user enters "Height: 170 cm", "Weight: 70 kg", and "Diet goal: Lose 5 kg". Once the input is complete, the user taps the "Submit" button. The input data is saved on the device in JSON format.

[1733] Step 3:

[1734] The device sends the data to the server.

[1735] The device sends the data entered by the user to the server. Specifically, the device uses an HTTP POST request to send the input data to the server. At this time, the data is sent in JSON format. The input data (height, weight, diet goal) is sent to the server.

[1736] Step 4:

[1737] The server receives and stores the data.

[1738] The server receives the data sent from the device. The received data is stored in a database. For example, the server connects to a MySQL database and executes the following SQL query:

[1739] sql

[1740] INSERT INTO user_data (height, weight, goal) VALUES (170, 70, '5 kg weight loss');

[1741] This process saves the user's input data in the database.

[1742] Step 5:

[1743] The server generates a prompt for the generative AI model.

[1744] The server generates prompts for the generative AI model based on the stored data. For example, it generates prompts like the following:

[1745] The user is 170 cm tall, weighs 70 kg, and has a goal of losing 5 kg. Based on this information, please suggest an appropriate diet plan.

[1746] This prompt is sent to a generative AI model.

[1747] Step 6:

[1748] A generative AI model suggests diet plans.

[1749] The generative AI model generates a diet plan based on the prompt it receives. For example, the generative AI model might suggest the following diet plan:

[1750] 1. Do 30 minutes of aerobic exercise every day

[1751] 2. Limit your daily calorie intake to 1500 kcal

[1752] 3. Strength train three times a week

[1753] This diet plan is sent to the user's terminal via the server and displayed to the user.

[1754] In this way, a system is constructed in which a generative AI model suggests an appropriate diet plan based on the data entered by the user.

[1755] (Application example 1)

[1756] Next, a description will be given of Application Example 1 of Form 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."

[1757] Conventional food delivery systems have difficulty providing meal plans based on customers' health conditions and diet goals, making it difficult to provide services tailored to individual needs. Furthermore, customers often end up buying unnecessary items, resulting in wasteful spending, and food choices that hinder the achievement of diet goals.

[1758] 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.

[1759] In this invention, the server includes a means for the customer to enter their current height and weight and goals, a means for the customer to submit a purchase receipt after shopping, a means for correcting items that are determined to be unnecessary in this shopping trip, a means for visualizing the money saved and weight lost if unnecessary items are not purchased, a means for generating an appropriate meal plan based on the customer's height, weight, and goals, and a means for presenting the generated meal plan to the customer. This makes it possible to provide an appropriate meal plan based on the customer's health condition and diet goals, and to support the achievement of the diet goals while reducing unnecessary spending.

[1760] "Customer" refers to the consumer who uses the service.

[1761] "Height and Weight" refers to the physical height and weight of the customer.

[1762] "Goals" refer to specific health or diet objectives that a customer wants to achieve.

[1763] "Purchase receipt" refers to a detailed list of purchases received by a customer when making a purchase.

[1764] "Means for correction" refers to a method or system for evaluating products purchased by customers and identifying unwanted products.

[1765] "Visualization tools" refers to methods or systems that visually display the money saved or weight lost.

[1766] "Meal Plan" refers to the meal content and schedule suggested based on the customer's health and diet goals.

[1767] "Means for generating" refers to a method or system for generating a meal plan based on customer input data.

[1768] "Presenting means" refers to a method or system for showing the generated meal plan to the customer.

[1769] The following system configuration is proposed as an embodiment of the present invention.

[1770] System Configuration

[1771] The system includes a smartphone application used by customers, a server, and a generative AI model. The smartphone application provides an interface for customers to input their height, weight, and diet goals. The server receives the input data and sends prompts to the generative AI model to generate an appropriate meal plan. The generated meal plan is then presented to the customer via the smartphone application.

[1772] Hardware and software used

[1773] Hardware: Smartphones, servers

[1774] Software: smartphone applications, generative AI models (e.g., OpenAI GPT-3)

[1775] Data processing and calculation

[1776] 1. Data entry: Customers use a smartphone application to enter their height, weight, and diet goals.

[1777] 2. Data transmission: The smartphone application sends the entered data to the server.

[1778] 3. Prompt generation: Based on the data received by the server, a prompt sentence is generated to be sent to the generative AI model.

[1779] 4. Meal plan generation: The generative AI model receives the prompt and generates an appropriate meal plan.

[1780] 5. Data reception and presentation: The server receives the generated meal plan and presents it to the customer via the smartphone application.

[1781] Specific examples

[1782] For example, if a customer inputs their height as 170cm, weight as 70kg, and their diet goal as "lose 5kg," the server will send the following prompt to the generative AI model:

[1783] Prompt Sentence Examples

[1784] Please suggest a suitable meal plan based on height: 170 cm, weight: 70 kg, goal: 5 kg weight loss.

[1785] Based on this prompt, the generative AI model generates a balanced meal plan, suggesting specific meal options such as "Breakfast - oatmeal, Lunch - salad, Dinner - chicken breast and vegetables." This meal plan is presented to the customer via a smartphone application.

[1786] In this way, it is possible to provide customers with appropriate meal plans according to their health condition and diet goals, helping them achieve their diet goals while reducing unnecessary spending.

[1787] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1788] Step 1:

[1789] A user starts a smartphone application and inputs their height, weight, and diet goal. The input data is temporarily saved in the smartphone application. An example of input data is a height of 170 cm, a weight of 70 kg, and a diet goal of "lose 5 kg."

[1790] Step 2:

[1791] The smartphone application sends the entered data, including the user's height, weight, and diet goal, to the server. The server analyzes the received data and proceeds to the next processing step.

[1792] Step 3:

[1793] The server generates a prompt based on the received data. Specifically, it combines the user's height, weight, and diet goal to create a prompt to send to the generative AI model. For example, the generated prompt might read, "Based on height: 170 cm, weight: 70 kg, goal: to lose 5 kg, please suggest an appropriate meal plan."

[1794] Step 4:

[1795] The server sends the generated prompt to the generative AI model, which then performs data calculations based on the received prompt and generates an appropriate meal plan. The generative AI model uses, for example, OpenAI GPT-3.

[1796] Step 5:

[1797] The generative AI model generates a meal plan based on the prompt and sends the result back to the server. An example of a generated meal plan is "Breakfast - oatmeal, Lunch - salad, Dinner - chicken breast and vegetables."

[1798] Step 6:

[1799] The server analyzes the meal plan received from the generative AI model and transmits it to the smartphone application, where the transmitted data includes the generated meal plan.

[1800] Step 7:

[1801] The smartphone application presents the meal plan received from the server to the user, who can then review and implement the proposed meal plan through the application.

[1802] Example 2

[1803] Next, a description will be given of Example 2 of Form 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."

[1804] In the previous system, customers had to physically submit receipts for their purchases, which was time-consuming and risked loss or damage. Furthermore, there were insufficient methods for identifying unnecessary purchases and visualizing savings and weight loss. This made it difficult for customers to effectively manage their shopping to achieve their goals.

[1805] 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.

[1806] In this invention, the server includes a means for the customer to enter their current height and weight and their goals, a means for the customer to take an image of their purchase receipt after shopping and upload it to the application so that they can submit it, a means for correcting items that are determined to be unnecessary in this purchase, and a means for visualizing the amount of money saved and the weight loss that would be achieved if they did not purchase the unnecessary items. This allows the customer to easily communicate their purchase information to the system without having to go through the trouble of submitting physical receipts. In addition, by identifying unnecessary items and visualizing the amount of money saved and the weight loss that would be achieved, the customer can effectively manage their shopping toward their goals.

[1807] "Customer" means an individual who uses the System to make purchases and manages purchase information.

[1808] "Height and Weight" refers to the customer's current physical height and weight.

[1809] "Goal" refers to a specific physical or financial goal that the client wishes to achieve.

[1810] "Purchase Receipt" means a paper or electronic record issued to a customer when they make a purchase that details the items purchased.

[1811] "Taking an image" refers to the act of taking a photo of a physical receipt using a device such as a smartphone or camera.

[1812] "Application" refers to a software program that runs on a device such as a smartphone or tablet.

[1813] "Uploading" refers to the act of sending a captured image to a server via the Internet.

[1814] "Server" refers to a computer system for receiving, processing, and storing data over a network.

[1815] "Analyzing an image" refers to the act of using image recognition technology to extract the contents of a photographed receipt as digital data.

[1816] "Unnecessary products" refer to products that are determined not to be necessary for the customer's goals.

[1817] "Savings" refers to the amount of money you can save by not purchasing unnecessary items.

[1818] "Weight loss" refers to the amount of weight loss you would expect if you didn't purchase unnecessary items.

[1819] "Visualizing" refers to the act of displaying data visually so that it can be easily understood by customers.

[1820] "Graphically displaying" refers to the act of displaying data in a visual format such as a graph or chart.

[1821] The present invention provides a system that allows customers to take pictures of their purchases after shopping and upload them to an application in order to submit a receipt. A specific embodiment of this system will be described below.

[1822] The user takes a picture of the purchase receipt using the camera on their smartphone. The image is then uploaded using a dedicated application (e.g., "ReceiptUploader"). The application has the function of sending the image taken by the user to a server.

[1823] The server receives the image of the receipt sent from the device. After receiving it, the server analyzes the contents of the receipt using image recognition software such as Google Cloud Vision API. Optical character recognition (OCR) technology is used for the analysis, and information such as the product name, price, and purchase date and time written on the receipt is extracted.

[1824] The analyzed data is stored in a database by the server. The stored data includes the product name, price, purchase date and time, store name, etc. This allows the user's purchase history to be accumulated in the database.

[1825] Users can use the application to check their purchase history. By opening the "Purchase History" section in the application, data retrieved from the server is displayed. Users can view a list of past purchases.

[1826] As a concrete example, consider a scenario where a user has just finished shopping at a supermarket. The user takes a picture of the receipt using their smartphone camera and opens the "ReceiptUploader" application. Within the application, the user taps the "Upload" button, selects the image of the receipt, and uploads it. The application sends the image to a server, which uses the Google Cloud Vision API to analyze the contents of the receipt. The analyzed data is stored in a database, and the user can view recent purchases by opening the "Purchase History" section within the application.

[1827] Examples of prompts to be input to a generative AI model include:

[1828] "Please describe the functionality that allows users to take a picture of a receipt using their smartphone camera and upload it to your application. Please include the names of any specific hardware or software."

[1829] Using this prompt, the generative AI model can generate sentences that explain in detail the system's operations.

[1830] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1831] Step 1:

[1832] The user takes a picture of the receipt.

[1833] The user uses the smartphone camera to take a picture of the receipt for the item they purchased, taking care to capture the entire receipt clearly. The input is the physical receipt, and the output is a digital image.

[1834] Step 2:

[1835] The device uploads the image to the application.

[1836] The device (smartphone) uploads the captured image of the receipt to the "ReceiptUploader" application. The user opens the application, taps the "Upload" button, and selects the captured image. The input is a digital image, and the output is the transmission of image data to the server.

[1837] Step 3:

[1838] The server receives and analyzes the images.

[1839] The server receives the image of the receipt sent from the terminal. After receiving it, the server uses image recognition software such as Google Cloud Vision API to analyze the contents of the receipt. Optical character recognition (OCR) technology is used for the analysis, and information such as the product name, price, and purchase date and time written on the receipt is extracted. The input is image data, and the output is analyzed text data.

[1840] Step 4:

[1841] The server stores the analysis results in a database.

[1842] The server saves the analyzed data in a database. The saved data includes the product name, price, purchase date and time, store name, etc. This allows the user's purchase history to be accumulated in the database. The input is the analyzed text data, and the output is saved in the database.

[1843] Step 5:

[1844] The user checks their purchase history.

[1845] The user can use the "ReceiptUploader" application to check their purchase history. When they open the "Purchase History" section in the application, the data retrieved from the server is displayed. The user can view a list of past purchases. The input is the data retrieved from the database, and the output is what is displayed in the application.

[1846] (Application example 2)

[1847] Next, a description will be given of Application Example 2 of Form 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."

[1848] In conventional shopping systems, customers had to physically submit receipts for the products they purchased, which was time-consuming and made managing purchase information cumbersome. Furthermore, there was a lack of systems that could identify unnecessary products based on the customer's health goals and visualize the savings and health benefits.

[1849] The specific processing by the specific 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 a means for the customer to enter their current height and weight and goals, a means for the customer to take a photo of their purchase receipt with their smartphone camera after shopping and upload it to the application, a means for correcting items determined to be unnecessary for the current purchase, a means for visualizing the money saved and weight lost if the unnecessary items were not purchased, a means for analyzing the contents of the purchase receipt and automatically extracting purchase information, a means for rewarding points to the customer based on the extracted purchase information, and a means for allowing the rewarded points to be used for the next purchase. This eliminates the need for customers to submit physical receipts, simplifies management of purchase information, and enables visualization of point rewards and savings. Furthermore, unnecessary items can be identified based on the customer's health goals, and savings and health benefits can be visualized.

[1850] "Customer" means a consumer who purchases goods or services.

[1851] "Height and weight" is basic physical information that refers to the customer's physical height and weight.

[1852] A "goal" is a specific numerical value or state that a customer wants to achieve.

[1853] "Purchase Receipt" means a paper or electronic record detailing a transaction issued to a customer when they purchase goods.

[1854] A "smartphone" is a type of mobile phone that can connect to the Internet and use applications.

[1855] A "camera" is a device for taking pictures and videos.

[1856] An "application" is a software program that runs on a smartphone or computer.

[1857] "Uploading" is the act of transferring data from a local device to a server or cloud.

[1858] "Unnecessary products" are products that are deemed not necessary for the customer to achieve their goals.

[1859] "Correction" is the act of checking the content and making corrections or improvements.

[1860] "Money saved" is the amount of money you would save if you didn't buy the unnecessary item.

[1861] "Weight lost" is the weight lost as a result of not purchasing unnecessary items.

[1862] "Visualization" refers to the visual display of data or information.

[1863] "Analysis" is the act of examining data or information in detail to clarify its structure and meaning.

[1864] "Purchase information" is detailed information about the products purchased by the customer.

[1865] "Automatic extraction" means that the system extracts data without human intervention.

[1866] "Point redemption" refers to the act of giving points to customers according to the amount of their purchase.

[1867] "Can be used on next purchase" means that the customer can use the points the next time they purchase a product.

[1868] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail below with reference to the accompanying drawings.

[1869] First, a smartphone application is used by the customer to enter their current height, weight, and goals. The customer launches the application and inputs their height, weight, and goals. This registers the customer's health goals in the system.

[1870] Next, after shopping, customers are provided with a means to take a photo of their purchase receipt with their smartphone camera and upload it to the application. Customers take a photo of their receipt and use the upload function within the application to send the image to the server.

[1871] The server receives the uploaded receipt image and preprocesses it using OpenCV. Specifically, it converts the image to grayscale and performs binarization. Next, it uses pytesseract to extract text from the preprocessed image. It then analyzes and automatically extracts purchase information (product name, price, etc.) from the extracted text.

[1872] Based on the analyzed purchase information, a method is provided for redeeming points to customers. The server calculates the points according to the purchase amount and adds them to the customer's account. The redeemed points are managed within the application so that they can be used for the next purchase.

[1873] Furthermore, as a means of correcting items that may be deemed unnecessary for this shopping trip, an algorithm is implemented to determine unnecessary items based on the customer's height, weight, and goals. The server compares the purchase information with the customer's health goals to identify unnecessary items.

[1874] To visualize the money saved and weight lost by not buying unnecessary products, the server calculates and graphically displays the amount saved and weight lost, allowing customers to visually see the savings and health benefits.

[1875] As a concrete example, consider the case where a user purchases a drink at a convenience store, takes a photo of the receipt, and uploads it to the app. The app extracts "drink" and "150 yen" from the receipt and rewards 15 points. If the app determines that the drink is an unnecessary item based on the user's health goals, it displays the amount of money saved and the weight lost.

[1876] An example of a prompt for a generative AI model is:

[1877] "A user has uploaded an image of a receipt taken with their smartphone camera. Please create a program that extracts purchase information from this image and returns points. 10% of the purchase amount will be returned as points."

[1878] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1879] Step 1:

[1880] The user starts the smartphone application and inputs their current height and weight and their goal. The input data is temporarily saved in the application and sent to the server. The input data is used as the basis for setting the user's health goal.

[1881] Step 2:

[1882] After shopping, a user takes a photo of the purchase receipt with their smartphone camera and uploads it to the application. The captured receipt image is temporarily saved in the application and then sent to the server. The input data is the receipt image.

[1883] Step 3:

[1884] The server receives the uploaded receipt image and preprocesses it using OpenCV. Specifically, it converts the image to grayscale and performs binarization. The input data is the receipt image, and the output data is the preprocessed image.

[1885] Step 4:

[1886] The server extracts text from the preprocessed image using pytesseract. The input data is the preprocessed image, and the output data is the extracted text. Specifically, it uses OCR (Optical Character Recognition) technology to read the text information in the image.

[1887] Step 5:

[1888] The server analyzes and automatically extracts purchase information (product name, price, etc.) from the extracted text. The input data is the extracted text, and the output data is the analyzed purchase information. Specifically, the required information is extracted using a text analysis algorithm.

[1889] Step 6:

[1890] The server rewards the customer with points based on the analyzed purchase information. The input data is the analyzed purchase information, and the output data is the rewarded points. Specifically, the server calculates points based on the purchase amount and adds the points to the customer's account.

[1891] Step 7:

[1892] The server determines unnecessary products based on the customer's height, weight, and goals. The input data is the customer's health goals and purchase information, and the output data is a list of unnecessary products. Specifically, the server runs an algorithm that compares the health goals with the purchase information and identifies unnecessary products.

[1893] Step 8:

[1894] The server calculates the amount of money saved and the weight lost if you don't buy unnecessary items, and displays them graphically. The input data is a list of unnecessary items and their purchase information, and the output data is the amount saved and the weight lost. The specific operation is to calculate the savings and health benefits, and display them visually to the user.

[1895] Step 9:

[1896] The user uses the points they have earned on their next purchase. The input data is the points earned, and the output data is the balance after the points have been used. The specific operation is to use the points to discount the purchase amount and update the balance.

[1897] Example 3

[1898] Next, a third embodiment of the third embodiment will be described. 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."

[1899] Modern consumers find it difficult to balance health management and saving money. In particular, consumers who have diet or health goals have difficulty determining which products they do not need when shopping. In addition, there is a lack of means to specifically understand the amount of savings and health benefits they will achieve if they do not purchase unnecessary products. For this reason, a system that allows consumers to effectively manage their health and save money is needed.

[1900] The identification process by the identification processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes a means for a customer to enter their current height and weight and their goals, a means for the customer to submit a purchase receipt after shopping, a means for converting the submitted receipt information into text data using optical character recognition technology, a means for identifying unnecessary products based on the customer's height, weight, and goals, a means for calculating the amount of money saved and the weight lost if the unnecessary products are not purchased, and a means for graphically displaying the calculation results. This allows consumers to easily identify unnecessary products when shopping and specifically understand the amount of money saved and the health benefits.

[1901] "Customers" are consumers who use the system to manage their health and save money.

[1902] "Height and weight" are the customer's current physical measurements and are used as basic data for health management.

[1903] "Goals" are specific health and diet-related objectives set by customers, and include, for example, "restricting carbohydrates" and "restricting calories."

[1904] A "receipt" is a detailed list of purchased items that a customer receives after shopping, listing the item names and prices.

[1905] "Optical character recognition technology" is a technology that extracts character information from image data and is used to convert receipt images into text data.

[1906] "Text data" refers to character information converted using optical character recognition technology, and includes information such as product names and prices.

[1907] "Unnecessary products" are products that are determined not to be necessary to purchase from the perspective of health management or dieting, based on the customer's height, weight, and goals.

[1908] "Savings" is the total amount of money you can save by not purchasing unnecessary items.

[1909] "Weight loss" is the amount of weight loss predicted if the unnecessary product was not consumed.

[1910] "Displaying graphically" means displaying the calculation results in the form of a graph, chart, or the like to make them visually easy to understand.

[1911] MODE FOR CARRYING OUT THE INVENTION

[1912] The present invention is a system for enabling consumers to effectively manage their health and save money. A specific embodiment of this system will be described below.

[1913] System configuration

[1914] The system consists of the following major components:

[1915] 1. A device for users to input their height, weight, and goals

[1916] 2. A terminal where users can submit receipts after shopping

[1917] 3. Hardware and software for the server to receive and process data

[1918] Hardware and software used

[1919] Device: Mobile device such as a smartphone or tablet

[1920] Server: High-performance data processing server

[1921] OCR technology: Optical character recognition technology such as Google Cloud Vision API

[1922] Database: A relational database such as MySQL or PostgreSQL

[1923] Data visualization libraries: D3.js, Chart.js, etc.

[1924] Program processing

[1925] The server receives the height, weight, and goal information entered by the user, as well as the submitted receipt. The server uses this data to process and calculate data to detect unwanted products. Specifically, the process is carried out as follows:

[1926] 1. Data reception and analysis:

[1927] The server receives the height, weight, and goal (e.g., carbohydrate restriction) entered by the user.

[1928] The server converts the information on the submitted receipt into text data using OCR technology.

[1929] 2. Unwanted product detection:

[1930] The server detects unnecessary products based on the goal. For example, if the goal is to "limit carbohydrates," the server lists products with a high sugar content, such as "bread" and "sweets," on the receipt as unnecessary products.

[1931] 3. Savings and Weight Loss Calculation:

[1932] The server calculates the total price of the detected unwanted items.

[1933] The server calculates the estimated weight loss that would occur if the unnecessary products were not consumed.

[1934] 4. Visualizing the results:

[1935] The server displays the calculation results to the consumer in the form of graphs, charts, etc.

[1936] Specific examples

[1937] Suppose a user is 170 cm tall, weighs 70 kg, sets their goal to "restrict carbohydrates," and submits a receipt. The receipt includes "bread (300 yen)," "sweets (200 yen)," and "vegetables (100 yen)." The system detects "bread" and "sweets" as unnecessary items and calculates that a total of 500 yen can be saved. The system also calculates the estimated weight loss if these items were not consumed as 0.5 kg and displays this in a graph.

[1938] Prompt Sentence Examples

[1939] "Height 170cm, weight 70kg, goal is carbohydrate restriction. Please detect unnecessary items based on the following receipt information and calculate the amount saved and weight loss. Receipt information: bread (300 yen), sweets (200 yen), vegetables (100 yen)." The flow of the identification process in Example 3 will be explained using Figure 15.

[1940] Step 1:

[1941] The user enters their height, weight, and goal, and submits a receipt.

[1942] Input: The user opens the app on their smartphone and enters their height (170 cm), weight (70 kg), and goal ("carbohydrate restriction"). After shopping, they also take a photo of their receipt with their smartphone camera and upload it to the server via the app.

[1943] Output: The user's input data and the receipt image are sent to the server.

[1944] Step 2:

[1945] The server receives the input data and receipt information.

[1946] Input: Height, weight, goal, and receipt image submitted by the user.

[1947] Output: User input data and receipt image stored in a database on the server.

[1948] Step 3:

[1949] The server converts the receipt information into text data using OCR technology.

[1950] Input: Receipt image stored on the server.

[1951] Data processing: The server calls the Google Cloud Vision API, analyzes the receipt image, and extracts the product name and price.

[1952] Output: Converted text data (e.g., "Bread (300 yen)", "Sweets (200 yen)", "Vegetables (100 yen)").

[1953] Step 4:

[1954] The server detects unwanted items based on the target.

[1955] Input: User goal (e.g., "Limit carbohydrate intake") and converted text data.

[1956] Data calculation: The server performs rule-based filtering based on predefined food categories and goals to list unwanted products.

[1957] Output: A list of unwanted products (e.g. "bread", "sweets").

[1958] Step 5:

[1959] The server calculates the total price of unwanted items and the estimated weight loss.

[1960] Input: A list of unwanted items and their respective prices.

[1961] Data calculation: The server calculates the total price of unnecessary products and the estimated weight loss if unnecessary products were not consumed. The model used here is a simulation model based on the relationship between calorie consumption and weight loss.

[1962] Output: Amount saved (e.g., 500 yen) and estimated weight loss (e.g., 0.5 kg).

[1963] Step 6:

[1964] The server visualizes the calculation results in graphs and charts and displays them to the user.

[1965] Input: Amount saved and estimated weight loss.

[1966] Data processing: The server uses data visualization libraries such as D3.js and Chart.js to visualize the calculation results in graphs and charts.

[1967] Output: Graphs and charts displayed on the user's device.

[1968] (Application example 3)

[1969] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1970] Modern consumers find it difficult to manage their health and save money at the same time. In particular, consumers with dietary goals need to identify unnecessary products among their purchases and avoid them to achieve health and financial benefits. However, doing this manually is time-consuming and inaccurate. Therefore, a system is needed that allows consumers to easily identify unnecessary products and efficiently manage their savings and health.

[1971] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1972] In this invention, the server includes a means for a customer to enter their current height and weight and goals, a means for the customer to submit a purchase receipt after shopping, a means for correcting items determined to be unnecessary in this purchase, a means for visualizing the money saved and weight lost if unnecessary items are not purchased, a means for analyzing receipt information and automatically detecting unnecessary items based on diet goals, a means for calculating the amount of money saved and estimated weight loss if unnecessary items are not purchased and displaying them in graphs and charts, and an application installed on a smartphone. This allows consumers to easily identify unnecessary items and efficiently save money and manage their health.

[1973] "Customer" refers to the consumer who uses the system.

[1974] "Height and Weight" is data indicating the physical height and weight of a customer.

[1975] "Goals" refer to specific health or diet-related objectives that a customer wants to achieve.

[1976] A "purchase receipt" is paper or electronic data showing the purchase details of a product that a customer receives when making a purchase.

[1977] "Unwanted products" refer to products that are deemed inappropriate or unnecessary for the customer's goals.

[1978] "Money saved" refers to the amount of money you would save if you didn't buy unnecessary items.

[1979] "Weight loss" refers to the amount of weight loss predicted if the unnecessary product was not consumed.

[1980] "Receipt information" refers to data such as the product name, price, and quantity listed on the purchase receipt.

[1981] "Diet Goal" means a health goal set by a customer, such as weight loss or specific nutritional restrictions.

[1982] "Automatically detect" means that the system programmatically identifies unwanted products without human intervention.

[1983] "Graphs and charts" refer to diagrams that visually display data.

[1984] "Applications installed on a smartphone" refers to software programs that run on a smartphone.

[1985] The present invention is a system for enabling consumers to efficiently manage their health and save money. Specific embodiments for implementing this system will be described below.

[1986] System configuration

[1987] The system consists of the following main components:

[1988] 1. User device: A mobile device such as a smartphone.

[1989] 2. Server: A central server that processes and analyzes data.

[1990] 3. Application: A dedicated application installed on a smartphone.

[1991] Program processing

[1992] User Device

[1993] The user terminal has the following features:

[1994] User information input: Users enter their height, weight, and diet goals through the application.

[1995] Receipt scanning: The user scans the receipt for the purchased item with their smartphone camera and obtains the image data.

[1996] server

[1997] The server does the following:

[1998] Receipt information analysis: The acquired receipt image is converted into text data using OCR (Optical Character Recognition) technology. This process is performed using the pytesseract library.

[1999] Detection of unnecessary products: Based on the user's diet goal, the system automatically detects unnecessary products from the text data of the receipt. For example, for a user who is trying to limit their carbohydrate intake, the system detects high-carbohydrate products such as "bread" and "sweets."

[2000] Calculation of savings and weight loss: Calculate the total cost of the detected unnecessary products and the estimated weight loss if you did not consume those products. Weight loss is calculated based on the calories required to lose 1 kg of weight (approximately 7700 kcal).

[2001] application

[2002] The application has the following features:

[2003] Visualization of results: The calculated savings and estimated weight loss are displayed in graphs and charts, allowing users to visually confirm the effects of their health management and savings.

[2004] Specific examples

[2005] For example, if a user sets a goal of "restricting carbohydrates" and the receipt includes "bread" and "sweets," these items will be detected as unnecessary products. Let's say the total amount of the detected unnecessary products is 500 yen, and the estimated weight loss is 0.2 kg.

[2006] Prompt Sentence Examples

[2007] Enter your user information:

[2008] Height: 170 cm

[2009] Weight: 70 kg

[2010] Diet goal: Carbohydrate restriction

[2011] Scan your receipt:

[2012] (Upload a receipt image)

[2013] Detecting unwanted items...

[2014] Detected unwanted items:

[2015] Bread: 200 yen

[2016] Sweets: 300 yen

[2017] Savings: 500 yen

[2018] Estimated weight loss: 0.2kg

[2019] The results are displayed in a graph.

[2020] In this way, users can easily identify unnecessary products and efficiently save money and manage their health.

[2021] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[2022] Step 1:

[2023] The user launches the smartphone application and enters their height, weight, and diet goals.

[2024] Input: User's height, weight, and diet goal

[2025] Output: User information data

[2026] Specific operation: The user enters their height, weight, and diet goal (e.g., carbohydrate restriction) into the application's input form and presses the submit button. This generates user information data and sends it to the server.

[2027] Step 2:

[2028] After shopping, the user scans the receipt for the purchased items with the smartphone camera.

[2029] Input: Receipt image

[2030] Output: Receipt image data

[2031] Specific operation: The user takes a photo of the purchase receipt using the camera function in the application. The captured image of the receipt is saved in the application and sent to the server.

[2032] Step 3:

[2033] The server receives the receipt image and converts it into text data using OCR technology.

[2034] Input: Receipt image data

[2035] Output: Receipt text data

[2036] Specific operation: The server uses the pytesseract library to extract text from the received receipt image data. The extracted text data is saved as receipt text data.

[2037] Step 4:

[2038] The server automatically detects unnecessary products from receipt text data based on the user's diet goal.

[2039] Input: User information data, receipt text data

[2040] Output: List of unwanted items

[2041] Specific operation: The server analyzes the receipt text data based on the user's diet goal (e.g., carbohydrate restriction). It lists products containing specific keywords (e.g., "bread" or "sweets") as unwanted items.

[2042] Step 5:

[2043] The server calculates the amount of money saved and the estimated weight loss if unnecessary items are not purchased.

[2044] Input: List of unwanted items

[2045] Output: Money saved, estimated weight loss

[2046] Specific operation: The server calculates the savings amount by adding up the prices of each product based on the list of unwanted products. It also calculates the estimated weight loss amount based on the calorie information of each product. The weight loss amount is calculated based on the calories required to lose 1 kg (approximately 7700 kcal).

[2047] Step 6:

[2048] The server visualizes the calculation results in graphs and charts and displays them on the user's smartphone.

[2049] Input: Amount saved, Estimated weight loss

[2050] Output: Image data of graphs and charts

[2051] Specific operation: Based on the calculation results, the server generates graphs and charts showing the savings and estimated weight loss. Image data of the generated graphs and charts is sent to the user's smartphone and displayed within the application.

[2052] In this way, users can easily identify unnecessary products and efficiently save money and manage their health.

[2053] 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.

[2054] "Example 1"

[2055] As one embodiment of the present invention, a system incorporating an emotion engine is provided. This system recognizes a user's emotions and determines unnecessary products based on those emotions. Specifically, when the user is feeling stressed, the system detects unhealthy foods such as sweets as unnecessary products. When the user is relaxed, the system recommends healthy foods.

[2056] "Example 2"

[2057] Furthermore, the emotion engine gr...

Claims

[Claim 1] A means for the customer to enter their current height, weight and diet goals; a means for the customer to submit a purchase receipt after making a purchase; means for analyzing the emotional state of a customer using an emotion engine; A means for identifying and correcting products that are determined to be unnecessary for the current purchase based on the customer's height, weight, and diet goals entered by the customer and the customer's emotional state analyzed using an emotion engine, by referring to the information on the submitted purchase receipt; A way to visualize the amount of money you could save by not buying unnecessary products and the estimated weight loss you would experience if you didn't consume those products. means for generating a prompt sentence instructing the customer to propose a diet plan based on the customer's current height and weight and diet goal; A means for suggesting a diet plan using the generated prompt sentence and the generative AI model; means for transmitting the proposed diet plan and the visualized savings and estimated weight loss information to the customer's terminal; The correction means determines unnecessary products by inputting a prompt sentence including the height and weight of the customer, a diet goal, and an analysis result of the emotional state of the customer into a generation AI model. system.

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