system

Abstract

Provide a system. The method includes: receiving feedback from nutrition experts and creating menus; A means of contracting seasonal ingredients from food suppliers and controlling their safety and quality; The means to apply the latest refrigeration technology to maintain the freshness of received ingredients; A means to optimize delivery routes by linking with existing delivery systems, A means of collecting customer feedback through QR codes and reflecting it in product improvements, A system including:

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, there is a demand for efficient and safe provision of nutritionally balanced meals. However, there are currently no systems in place to develop menus that incorporate the knowledge of nutrition experts, safely manage high-quality ingredients from producers, keep them refrigerated to maintain freshness, efficiently distribute them, or quickly incorporate customer feedback. Therefore, the challenge is to provide a system that can manage and improve this entire process in an integrated manner. [Means for solving the problem]

[0005] The present invention solves the above problems by providing the following means: A system that efficiently provides nutritionally balanced, safe, and fresh meals is realized by receiving feedback from nutrition experts and creating menus, contracting seasonal ingredients from food suppliers and managing their safety and quality, applying the latest refrigeration technology to maintain the freshness of received ingredients, optimizing delivery routes in cooperation with existing home delivery systems, and collecting customer feedback via QR Codes (registered trademark) and reflecting it in product improvements.

[0006] A "nutrition expert" is a professional who has knowledge and experience in nutrition and who plans and provides dietary guidance.

[0007] "Feedback" refers to opinions and evaluations of a specific subject, and is information used for improvement and evaluation.

[0008] A "menu" refers to a list or plan of dishes served at a restaurant, school lunch, etc.

[0009] "Food suppliers" are businesses that cultivate, produce, and sell food ingredients such as agricultural and livestock products.

[0010] "Seasonal ingredients" are ingredients that can only be harvested during a particular season or ingredients that are said to be most delicious during that season.

[0011] A "contract" is a legal agreement that sets out obligations between parties under certain conditions.

[0012] "Safety" is the property that ensures that something will not cause harm to people or animals.

[0013] "Quality" is a characteristic that indicates whether a product or service meets certain standards.

[0014] "Freshness" refers to the state in which food, plants, etc. are fresh and their quality has not deteriorated.

[0015] "Refrigeration technology" means technology used to keep food and other items cool.

[0016] A "delivery system" is a logistics system for delivering ordered products to a location specified by a customer.

[0017] A "delivery route" refers to the route or path taken when delivering an item.

[0018] "Optimization" is a technique or method for achieving the best or optimal state under certain conditions.

[0019] A "QR code" is a type of two-dimensional barcode that allows information to be read quickly.

[0020] "Customer" is a general term that refers to people who purchase goods or services.

[0021] A "system" refers to a whole that integrates interrelated elements and is constructed to achieve a specific function or purpose. [Brief explanation of the drawings]

[0022] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6]FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0023] 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.

[0024] First, the terms used in the following description will be explained.

[0025] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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."

[0030] [First embodiment]

[0031] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0032] 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.

[0033] 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).

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0039] 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.

[0040] 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.

[0041] 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.

[0042] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0043] The present invention is a system that includes menu development based on feedback from nutrition experts, safety and quality control of ingredients based on contracts with producers, freshness maintenance using the latest refrigeration technology, logistics optimization through integration with existing bento delivery systems, and a process for collecting customer feedback and improving products using QR codes.

[0044] Program processing explanation

[0045] Menu development with nutrition experts

[0046] 1. Gathering feedback

[0047] The server stores the feedback from the nutrition experts in a database.

[0048] The terminal inputs feedback through the nutrition expert interface and transmits it to the server.

[0049] 2. Comparison with nutritional data

[0050] The server compares the stored feedback with an in-house nutrition database.

[0051] The server searches for matching ingredients and menu items.

[0052] 3. Creating a recommended menu

[0053] The server creates and stores new recommended menus based on the results of comparison with the nutrition database.

[0054] Ingredient contracts and management

[0055] 1. Collecting producer information

[0056] The terminal collects information from the producer and transmits it to the server.

[0057] 2. Contract conclusion and management

[0058] The server concludes a contract with the producer and registers the contract information in the management system.

[0059] Preserving freshness with refrigeration technology

[0060] 1. Receiving and checking ingredients

[0061] The user (producer) sends ingredients to the distribution center.

[0062] The terminal checks the freshness of the received ingredients and sends the information to the server.

[0063] 2. Application of refrigeration technology

[0064] The server connects the food ingredient data to the refrigeration equipment and applies the optimal refrigeration technology.

[0065] 3. Freshness monitoring

[0066] The terminal periodically monitors the freshness of the food items being kept refrigerated and sends this information to the server.

[0067] Logistics Optimization

[0068] 1. Calculating delivery routes

[0069] The server calculates the optimal delivery route based on data from the existing delivery system.

[0070] 2. Create a delivery schedule

[0071] The server creates a delivery schedule based on the calculated delivery route and transmits it to the terminal.

[0072] 3. Track your delivery

[0073] The device uses GPS to track the current location of the lunch box during delivery and transmits that information to the server in real time.

[0074] Collecting and analyzing customer feedback

[0075] 1. Distribution of the questionnaire

[0076] The server generates a QR code for the survey and prints it on the lunch box packaging.

[0077] 2. Gathering Feedback

[0078] Users scan the QR code to answer the survey.

[0079] The server stores the user's feedback in a database.

[0080] 3. Analyzing feedback and identifying areas for improvement

[0081] The server analyzes the collected feedback and extracts low-rated items and areas for improvement.

[0082] Specific examples

[0083] As a specific example, the following series of processes can be considered.

[0084] 1. Nutrition experts propose new menu items based on the theme of "high protein, low fat." The server registers this feedback in a database and compares it with the nutrition database to create recommended menu items.

[0085] 2. A local farmer signs a contract to provide fresh tomatoes during the summer season. The terminal sends this contract information to the server and registers it in the management system.

[0086] 3. Strawberries received at the distribution center are stored in the latest refrigeration equipment and temperature controlled to maintain freshness. The terminal monitors the freshness of the strawberries and periodically reports this to the server.

[0087] 4. The server uses an optimization algorithm to calculate the fastest delivery route and create a delivery schedule. The device tracks the location of the bento box in real time during delivery and sends it to the server.

[0088] 5. The user scans the QR code and sends feedback that the food tastes bland. The server analyzes this feedback and reflects it in improving the menu for the next time.

[0089] This system makes it possible to efficiently provide nutritionally balanced, safe, and fresh meals.

[0090] The processing flow will be explained below.

[0091] Menu development with nutrition experts

[0092] Step 1:

[0093] The server provides an interface for storing feedback from nutrition experts in a database, and the experts input their feedback through terminals.

[0094] Step 2:

[0095] The device receives expert feedback and sends it to a server, which includes specific nutritional information and areas for improvement.

[0096] Step 3:

[0097] The server registers the expert's feedback in a database, which is used to match the feedback with the nutrition database.

[0098] Step 4:

[0099] The server will refer to the nutrition database and compare it with the registered feedback, searching for matching ingredients and menu items.

[0100] Step 5:

[0101] The server generates a new recommended menu based on the matching results and stores it in a database.

[0102] Ingredient contracts and management

[0103] Step 1:

[0104] The terminal collects information from producers (for example, information on available ingredients and seasonal information) and sends it to the server.

[0105] Step 2:

[0106] The server registers the information sent from the producers in a database, including the type of food and the supply period.

[0107] Step 3:

[0108] The server performs the procedure to conclude a contract with the producer, confirms the contract details, and saves them in the database.

[0109] Step 4:

[0110] The server monitors the status of contract fulfillment and displays the seasonal food supply status on the management system.

[0111] Preserving freshness with refrigeration technology

[0112] Step 1:

[0113] The user (producer) sends ingredients to the distribution center, where they are scanned at a receiving terminal.

[0114] Step 2:

[0115] The terminal scans the received ingredients to determine their condition (e.g., temperature, humidity) and sends the data to the server.

[0116] Step 3:

[0117] The server receives the food ingredient data and starts communicating with the refrigeration equipment, determining the optimal refrigeration technology (temperature and humidity settings).

[0118] Step 4:

[0119] The terminal receives instructions from the server and sets the cooling device appropriately, creating an environment that keeps food fresh.

[0120] Step 5:

[0121] The terminal periodically monitors the freshness of the food in the refrigerator and sends the status to the server, issuing an alert if there is an abnormality.

[0122] Logistics Optimization

[0123] Step 1:

[0124] The server receives data from existing delivery systems and delivery partners, including current delivery status and past delivery data.

[0125] Step 2:

[0126] Based on the data received by the server, an optimization algorithm is used to calculate the optimal delivery route.

[0127] Step 3:

[0128] The server creates a delivery schedule based on the calculation results and sends it to the terminal.

[0129] Step 4:

[0130] The terminal receives delivery schedules and assists in executing deliveries, while the driver uses the terminal to check route information in real time.

[0131] Step 5:

[0132] The device uses GPS to track the current location of the bento and ingredients being delivered and sends that data to a server, which updates the delivery status in real time.

[0133] Collecting and analyzing customer feedback

[0134] Step 1:

[0135] The server generates a QR code for the survey and prints it on the lunch box packaging, which contains a specific survey link.

[0136] Step 2:

[0137] Users scan the QR code to access the survey on their smartphone or PC, which includes a field to rate the diet and provide suggestions for improvement.

[0138] Step 3:

[0139] The server receives the survey data from users and stores it in a database, where the feedback is later analyzed.

[0140] Step 4:

[0141] The server analyzes the collected feedback data and extracts low-rated items and specific areas for improvement.

[0142] Step 5:

[0143] Based on the identified improvements, the server creates a plan to improve the next menu or service. The plan is shared with experts and staff.

[0144] In this way, a system is realized that efficiently provides nutritionally balanced, safe, and fresh meals through each processing step.

[0145] Example 1

[0146] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0147] In recent years, growing health consciousness has led to an increasing demand for systems that efficiently provide nutritionally balanced meals. However, conventional systems have not been able to fully incorporate feedback from nutrition experts, resulting in insufficient optimization of ingredient freshness management and logistics. Furthermore, there is a lack of means to efficiently collect and incorporate customer feedback. Furthermore, automating contract management with ingredient suppliers and freshness monitoring has also been an issue. There is a need to solve these issues.

[0148] 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.

[0149] In this invention, the server includes a means for receiving feedback from nutrition experts and creating menus, a means for comparing the feedback with a nutrition database, and a means for applying the latest refrigeration technology to maintain the freshness of the received ingredients, thereby enabling the proposal of nutritionally balanced menus, the management of the freshness of ingredients, the optimization of logistics, and the collection and analysis of customer feedback.

[0150] A "nutritionist" is a professional with specialized knowledge of nutrition who optimizes the nutritional balance of meals and designs menus tailored to specific health goals.

[0151] "Feedback" refers to opinions and evaluation information provided by nutrition experts and customers, based on which the system and menus are improved.

[0152] "Menu" refers to a list of meals or dishes, including ingredients and cooking methods, organized around a particular theme or with nutritional balance in mind.

[0153] "Food suppliers" refers to producers and businesses that provide seasonal food ingredients and are subject to safety and quality control.

[0154] "Contract" means a formal agreement between a food supplier and a system operator that provides for the supply of food of a specified quality and quantity within a specified period of time.

[0155] "Cold storage technology" is a technique for maintaining a low temperature environment and is a means used to keep food ingredients fresh for a long period of time.

[0156] "Delivery system" refers to the infrastructure and procedures for delivering goods, and is the existing delivery network used to streamline logistics.

[0157] A "QR code" is a type of two-dimensional barcode that can be read with a camera on a smartphone or other device to quickly access information.

[0158] "Customer feedback" refers to the opinions and evaluations that customers submit about services and products, and is valuable data for product improvement.

[0159] A "nutrition database" is a database that stores detailed information on the nutritional components contained in various ingredients and dishes, and is used to optimize nutritional balance.

[0160] "Freshness monitoring" refers to the process of regularly monitoring the quality status of food ingredients (e.g., color, temperature, humidity, etc.) and sending that information to a server for analysis.

[0161] "Delivery route" refers to the route along which goods are transported to their destination, and is optimized for efficient delivery.

[0162] "Smartphone" is an abbreviation for smartphone, a type of mobile phone equipped with GPS functionality and internet connectivity.

[0163] "Real-time tracking" refers to the ability to check the current location of an object in real time, especially for goods being delivered.

[0164] The present invention is a system that includes menu development based on feedback from nutrition experts, safety and quality control of ingredients based on contracts with producers, freshness maintenance using the latest refrigeration technology, logistics optimization through integration with existing home delivery systems, and a process for collecting customer feedback and improving products using QR codes.

[0165] Menu development with nutrition experts

[0166] The server stores the feedback from nutrition experts in a database. Feedback is provided as a URL, document file, or XML feed, and the server automatically analyzes and registers it in the database. The terminal provides an administration screen for nutrition experts, where they can enter their feedback using text boxes and check boxes. The entered information is sent to the server via an HTTP request.

[0167] The server then matches the feedback stored in the database with a nutrition database (e.g., MySQL®) and uses a keyword search algorithm to find matching ingredients and menu items. The matched data is statistically analyzed using Python or R to generate new menu recommendations. This menu is then stored back in the database and formatted for screen output.

[0168] A specific example includes a process in which a nutritionist submits feedback on the theme "high protein, low fat" via an administration screen, and the server generates a recommended menu item, "chicken breast salad," based on this information.

[0169] Ingredient contracts and management

[0170] The terminal provides a dedicated web form for collecting information from producers. This form is an interface for entering information such as the farmer's name, location, and list of ingredients they can provide. This information is sent from the terminal to the server via an HTTP request and automatically registered in a database.

[0171] The server registers contract information with producers (contract start date, end date, supply volume, etc.) in the management system. The contract is saved as a PDF, and various conditions are stored in the database in JSON format.

[0172] A specific example involves a process in which a local farmer enters a contract to "provide fresh tomatoes during the summer season" through a web form, and the server registers the information in a database.

[0173] Preserving freshness with refrigeration technology

[0174] The user (producer) sends the harvested ingredients to the distribution center. The terminal provides a smartphone app to check the freshness of the ingredients received at the distribution center. The app checks color, aroma, temperature, etc., and sends the results digitally to the server.

[0175] The server can determine the optimal refrigeration method (temperature, humidity, etc.) based on the received food information and issue instructions to the refrigeration device. The terminal also periodically monitors the freshness of the food using cameras and sensors in the refrigeration device and sends this data to the server.

[0176] A specific example is a process that measures the color and temperature of strawberries received at a distribution center and allows the server to set the optimal refrigeration temperature. Sensors in the refrigeration equipment monitor freshness and periodically send data to the server.

[0177] Logistics Optimization

[0178] The server acquires data from existing delivery systems and calculates optimal delivery routes using the Google® Maps API and a proprietary optimization algorithm. It automatically generates a delivery schedule based on the route information and sends the results to the terminal. The delivery schedule includes estimated delivery times and orders.

[0179] The device uses the GPS function installed on the delivery driver's smartphone to track the current location of the bento boxes being delivered in real time and transmits this information to a server at regular intervals.

[0180] For example, the server uses the Google Maps API to calculate the optimal route, generate a delivery schedule, and send it to the driver's smartphone. The device periodically uploads GPS information to the server, allowing the driver to check the delivery status in real time.

[0181] Collecting and analyzing customer feedback

[0182] The server generates a QR code for customer feedback and prints it on the lunch box package label. Users scan the QR code with their smartphone to access the survey form and enter their opinions. The server saves the entered feedback data in a database in real time.

[0183] The server analyzes the collected feedback data using machine learning algorithms in Python and R to identify low-rated items and areas for improvement. The analysis results are visualized on a management screen and reflected in menu development and logistics management.

[0184] A specific example includes a process where a user scans a QR code and sends feedback such as "the flavor is bland," which the server analyzes and reflects in the next menu revision, adjusting the "optimal amount of seasoning."

[0185] Example prompt sentence:

[0186] "I would like to create a new, nutritionally balanced menu. Please suggest recipes that use high-protein, low-fat ingredients."

[0187] Thus, the system of the present invention comprehensively covers all the steps required to efficiently provide nutritionally balanced, safe and fresh meals.

[0188] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0189] Program processing flow

[0190] Step 1: Gather expert feedback

[0191] explanation:

[0192] The device provides a dedicated management screen for receiving feedback from nutrition experts. The management screen has text boxes and check boxes where experts can enter their opinions and suggestions. The entered data is sent to the server via an HTTP request. The server stores the received data in a database.

[0193] input:

[0194] Nutrition expert feedback (text and multiple choice answers)

[0195] output:

[0196] Feedback information stored in a database

[0197] Specific behavior:

[0198] When an expert enters feedback such as "high protein, low fat" into the management screen and presses the send button, the data is sent to the server.

[0199] Step 2: Check against nutritional data

[0200] explanation:

[0201] The server retrieves the feedback stored in the database and compares it with the company's internal nutrition database. Specifically, it performs text analysis of the feedback and searches for related ingredients and menu items using keyword searches. The search results are temporarily stored.

[0202] input:

[0203] Feedback information stored in a database

[0204] output:

[0205] Matched ingredients and menu list

[0206] Specific behavior:

[0207] Based on the keywords "high protein, low fat," the server checks a nutritional database to extract information on ingredients such as "chicken breast" and "lean fish."

[0208] Step 3: Create a recommended menu

[0209] explanation:

[0210] The server generates new recommended menus based on the matching results. Using Python and R, the menus are constructed to meet nutritional balance and calorie constraints. The generated menus are saved in a database and can be viewed on the management screen.

[0211] input:

[0212] Matched ingredients and menu list

[0213] output:

[0214] Recommendations stored in a database

[0215] Specific behavior:

[0216] The server generates a menu list including "chicken breast salad" and stores it in a database.

[0217] Step 4: Collecting producer information and managing contracts

[0218] explanation:

[0219] The terminal provides an interface where producers can enter information through a dedicated web form, including, for example, the farmer's name, location, and available ingredients list. The entered information is sent via an HTTP request to the server, which then registers it in a database.

[0220] input:

[0221] Information from producer (name, location, list of ingredients)

[0222] output:

[0223] Producer information and contract information registered in the database

[0224] Specific behavior:

[0225] Producers enter information such as "providing fresh tomatoes during the summer season" into a web form, and the server registers the information in a database.

[0226] Step 5: Receive ingredients and check freshness

[0227] explanation:

[0228] The user (producer) sends the harvested ingredients to the distribution center. The terminal provides an interface for checking the freshness of the ingredients that arrive at the center using a smartphone app. Check items include color, aroma, temperature, etc. The terminal then digitally transmits the results to the server.

[0229] input:

[0230] Freshness information for ingredients received at the distribution center

[0231] output:

[0232] Freshness data sent to the server

[0233] Specific behavior:

[0234] At the distribution center, users measure the color and temperature of strawberries using a smartphone app and send the data to the server.

[0235] Step 6: Applying cooling technology

[0236] explanation:

[0237] The server determines the optimal refrigeration method based on the received food information, sets temperature and humidity conditions, and issues instructions to the refrigeration device. It also monitors sensors to maintain freshness under the set environment, and continuously sends this data to the server.

[0238] input:

[0239] Freshness data and ingredient information

[0240] output:

[0241] Setting data that gives instructions to the cooling device

[0242] Specific behavior:

[0243] The server sets the temperature and humidity conditions for the strawberries and instructs the refrigeration device to "store them at the preset temperature."

[0244] Step 7: Optimize delivery routes

[0245] explanation:

[0246] The server acquires data from existing delivery systems and calculates optimal delivery routes using the Google Maps API and proprietary algorithms. Based on the results of the calculations, it automatically generates a delivery schedule and sends the results to the device.

[0247] input:

[0248] Delivery system data and customer delivery information

[0249] output:

[0250] Optimal delivery routes and schedules

[0251] Specific behavior:

[0252] The server uses the Google Maps API to calculate the "fastest route," generate a schedule, and send it to the driver's smartphone.

[0253] Step 8: Track your shipment

[0254] explanation:

[0255] The device uses the GPS function installed on the delivery driver's smartphone to periodically track the current location of the lunch box during delivery. The location information is sent to a server at regular intervals and displayed in real time on the management screen.

[0256] input:

[0257] GPS location information from the driver's smartphone

[0258] output:

[0259] Real-time location tracking data

[0260] Specific behavior:

[0261] The device acquires the location information of the lunch box being delivered and periodically uploads it to the server, allowing delivery status to be checked in real time.

[0262] Step 9: Collect and analyze customer feedback

[0263] explanation:

[0264] The server generates a QR code for customer feedback and prints it on the lunch box package label. The customer scans the QR code with their smartphone, accesses the survey form, and enters their feedback. The entered data is saved on the server in real time.

[0265] input:

[0266] Customer feedback (survey responses)

[0267] output:

[0268] Feedback data stored on the server

[0269] Specific behavior:

[0270] The user scans the QR code printed on the bento box and sends feedback such as "the taste is bland," which the server then stores in a database.

[0271] Step 10: Analyze feedback and identify areas for improvement

[0272] explanation:

[0273] The server analyzes the collected feedback data using machine learning algorithms in Python and R to identify low-rated items and areas for improvement. The analysis results are visualized on a management screen and reflected in the next menu development and logistics management.

[0274] input:

[0275] Collected customer feedback data

[0276] output:

[0277] Analysis results and list of improvements

[0278] Specific behavior:

[0279] The server will analyze the feedback that the food is "bland" and implement a process to reflect the "optimal amount of seasoning" in the next menu.

[0280] In this way, each step works together to create a system that efficiently provides nutritionally balanced, safe, and fresh meals.

[0281] (Application example 1)

[0282] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0283] Providing nutritionally balanced meals and delivering them efficiently is an important issue in modern society. However, currently, menu development that appropriately reflects expert feedback, managing the safety and quality of ingredients, applying refrigeration technology to ensure fast delivery and freshness, and even collecting customer feedback and improving products are all fragmented at each stage, resulting in insufficient coordination as a comprehensive system. Furthermore, achieving efficient food delivery using smartphones and other devices remains a challenge.

[0284] 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.

[0285] In this invention, the server includes means for receiving feedback from nutrition experts and creating menus, means for contracting seasonal ingredients from ingredient suppliers and managing their safety and quality, means for applying the latest refrigeration technology to maintain the freshness of received ingredients, means for optimizing delivery routes in cooperation with existing home delivery systems, means for collecting customer feedback via QR codes and reflecting it in product improvements, and means for installing a food delivery application on smartphones to provide nutritionally balanced, health-conscious meals, thereby enabling the efficient provision of nutritionally balanced, healthy meals and increasing customer satisfaction.

[0286] "Nutrition experts" are people with specialized knowledge about the nutritional value and health benefits of foods.

[0287] "Feedback" refers to an evaluation or opinion provided based on specific information or experience.

[0288] A "menu" is a list of specific meals or dishes, specifying the food offerings.

[0289] "Food supplier" refers to a company or individual that produces and supplies food to restaurants and consumers.

[0290] "Seasonal ingredients" refer to ingredients that are harvested in a particular season due to natural conditions.

[0291] A "contract" is a formal agreement between two parties.

[0292] "Safety" refers to the quality of food that does not adversely affect people's health.

[0293] "Quality" evaluates the superior characteristics of food, such as taste, freshness, and nutritional value.

[0294] "Freshness" refers to the degree of freshness of food between the time it is harvested and the time it is consumed.

[0295] "Cold storage technology" refers to the technology of maintaining food at low temperatures by cooling or freezing, thereby preserving its freshness.

[0296] "Delivery system" refers to a logistics system for delivering goods to a designated location.

[0297] "Delivery route" refers to the route or path planned for efficient delivery of goods.

[0298] "Optimization" refers to adjusting or improving something to achieve the best results for a particular purpose.

[0299] A "QR code" is a type of two-dimensional barcode that allows information to be read quickly.

[0300] "Customer feedback" refers to the means of collecting customer ratings and opinions about products and services.

[0301] "Product improvement" refers to the process of improving a product or service based on collected feedback.

[0302] A "food delivery application" is mobile software that allows you to order food online and have it delivered.

[0303] A "smartphone" refers to a portable information device with advanced computing power and connectivity.

[0304] The system for implementing this invention includes a server that receives feedback from nutrition experts and creates menus, terminals and servers equipped with means for contracting seasonal ingredients provided by food suppliers and managing their safety and quality, equipment that applies the latest refrigeration technology to maintain the freshness of received ingredients, means for optimizing delivery routes in cooperation with existing home delivery systems, and a mechanism for collecting customer feedback via QR codes and reflecting it in product improvements.

[0305] 1. Collaboration with nutrition experts

[0306] The server creates menus based on feedback from nutrition experts. Nutrition experts enter their feedback through a dedicated interface, which is then sent to the server. The server receives this feedback, compares it with its internal nutrition database, and generates new, nutritionally balanced menus. This information is also stored in a database for future reference.

[0307] 2. Ingredient contracts and management

[0308] The terminal collects information about ingredients provided by producers and sends it to a server. The server uses this information to conclude contracts with producers and registers the contract information in a management system. This management system constantly monitors the safety and quality of ingredients and provides feedback as needed.

[0309] 3. Cooling technology to maintain freshness

[0310] The received ingredients are stored in a device that uses the latest refrigeration technology to maintain freshness. The terminal regularly monitors the freshness of the ingredients and sends the information to the server. The server uses this information to optimize the settings of the refrigeration device and adjust it to maintain the maximum freshness of the ingredients.

[0311] 4. Logistics optimization

[0312] The server works with existing delivery systems to calculate optimal delivery routes and create delivery schedules. This schedule is sent to the terminals to improve delivery efficiency. The terminals use GPS to track the location of food during delivery and send it to the server in real time.

[0313] 5. Collecting and incorporating customer feedback

[0314] The server also generates a QR code and prints it on the bento packaging. Users can scan the QR code and provide feedback through the application. The server analyzes this feedback, identifies poorly rated items, and uses them to improve the next menu.

[0315] Specific examples

[0316] Specifically, when a nutrition expert suggests a "low-calorie, high-nutrition" menu, the server registers this feedback in a database and compares it to create new recommended menus. The server also sends contract information for fresh tomatoes provided by local farmers in the summer to the server and registers it in the management system. The received tomatoes are stored in a state-of-the-art refrigeration system, and their freshness is regularly monitored via terminals. The server calculates the fastest delivery route and provides the schedule to the terminals, ensuring efficient delivery. When a user scans a QR code and provides feedback that the flavor is "a little bland," the server analyzes the opinion and uses it to improve the next menu.

[0317] Prompt Sentence Examples

[0318] 1. Nutrition experts, please suggest new menu items based on the theme of "high protein, low fat."

[0319] 2. Send the Fresh Tomato contract information to the server and register it in the management system.

[0320] 3. Monitor the freshness of tomatoes and report it to the server.

[0321] 4. Calculate the fastest delivery route and generate a delivery schedule.

[0322] 5. Scan the QR code and give your feedback on the taste of the dish.

[0323] This approach makes it possible to efficiently provide nutritionally balanced and healthy meals and increase customer satisfaction.

[0324] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0325] Step 1:

[0326] The server receives feedback from nutrition experts. As input, it receives feedback data entered by nutrition experts through a dedicated interface. As data processing, the server takes in the feedback data, compares it with an existing nutrition database, and generates a new nutritionally balanced menu. As output, the new recommended menu is registered in the database.

[0327] Step 2:

[0328] The terminal collects information provided by food ingredient suppliers and sends it to the server. The input includes food ingredient information provided by producers. As a data calculation, the terminal sends the information to the server, and the server uses this information to conclude a contract with the producer and registers the contract information in the management system. As an output, information on food ingredients that have been safety and quality controlled is stored on the server.

[0329] Step 3:

[0330] The server applies the latest refrigeration technology to maintain the freshness of the received ingredients. The input includes data indicating the freshness status of the ingredients. For data processing, the terminal periodically monitors the freshness and sends the information to the server. The server uses this information to optimize the settings of the refrigeration equipment and adjust it to maintain the best possible freshness. The output holds information about ingredients whose freshness has been guaranteed.

[0331] Step 4:

[0332] The server works in conjunction with an existing delivery system to calculate the optimal delivery route. The input includes delivery data obtained from the existing delivery system. As a data calculation, the server analyzes this data and calculates the optimal delivery route. As an output, the optimal delivery route and schedule are created and sent to the terminal.

[0333] Step 5:

[0334] The terminal uses GPS to track the location information of the food being delivered. The input includes the current location information of the food being delivered. The data is processed by sending the location information to the server in real time. The output is the real-time tracking information of the food being delivered, which is stored on the server.

[0335] Step 6:

[0336] Users provide feedback through QR codes. The input includes the feedback information provided by users by scanning the QR code. As a data calculation, the server collects this feedback, evaluates it, and extracts improvements. As an output, the results are reflected in the next menu improvement.

[0337] This series of steps makes it possible to efficiently provide nutritionally balanced and healthy meals and increase customer satisfaction.

[0338] 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.

[0339] The present invention is an integrated system that includes menu development based on feedback from nutrition experts, provision of safe, high-quality meals using local, seasonal ingredients, preservation of freshness of ingredients using the latest refrigeration technology, optimization of logistics by linking with existing bento delivery systems, collection of customer feedback using QR codes, and a process of recognizing user emotions and improving products using an emotion engine.

[0340] Program processing explanation

[0341] Menu development with nutrition experts

[0342] 1. Gathering feedback

[0343] The server provides an interface for registering feedback from nutrition experts in a database, and the experts input their feedback through their terminals.

[0344] 2. Comparison with nutritional data

[0345] The server compares the nutritional database and generates menu recommendations based on expert feedback.

[0346] Ingredient contracts and management

[0347] 1. Collecting producer information

[0348] The terminal collects information from the producer and sends it to the server.

[0349] 2. Contract conclusion and management

[0350] The server enters into a contract with the producer and registers and manages that information in a database.

[0351] Preserving freshness with refrigeration technology

[0352] 1. Receiving and checking ingredients

[0353] The user (producer) sends ingredients to the distribution center.

[0354] 2. Application of refrigeration technology

[0355] The server uses refrigeration technology to set up the food to keep it fresh.

[0356] 3. Freshness monitoring

[0357] The terminal monitors the freshness of the food being kept refrigerated and sends the data to the server.

[0358] Logistics Optimization

[0359] 1. Calculating delivery routes

[0360] The server calculates the optimal delivery route based on data from the existing delivery system.

[0361] 2. Executing and tracking deliveries

[0362] The terminal receives a delivery schedule based on the calculation results and carries out the delivery.

[0363] Collecting customer feedback

[0364] 1. Distribution of the questionnaire

[0365] The server generates a QR code and prints the questionnaire on the lunch box packaging.

[0366] 2. Gathering Feedback

[0367] The user scans the QR code to answer the survey.

[0368] Emotion recognition by emotion engine

[0369] 1. Sentiment analysis of feedback

[0370] The feedback data collected by the server is analyzed by an emotion engine to recognize the user's emotions.

[0371] 2. Identifying areas for improvement

[0372] The server extracts areas for improvement in menus and services based on the results of sentiment analysis.

[0373] 3. Implementation of improvements

[0374] Based on the identified areas for improvement, the server plans and implements the next menu and service improvements.

[0375] Specific examples

[0376] Menu development with nutrition experts

[0377] Step 1:

[0378] The server registers the feedback of "high protein, low fat" from nutrition experts in a database. The experts input their feedback using a terminal, and the server stores it in the database.

[0379] Step 2:

[0380] The server compares the registered feedback with the company's nutritional database to search for matching ingredients and menu items.

[0381] Step 3:

[0382] The server generates a new recommended menu item, "High-protein, low-fat salad," based on the matching results and stores it in the database.

[0383] Ingredient contracts and management

[0384] Step 1:

[0385] The terminal collects information sent by the producer (for example, whether fresh tomatoes are available in summer) and transmits it to the server.

[0386] Step 2:

[0387] The server concludes a contract with the producer and registers this contract information in the management system.

[0388] Preserving freshness with refrigeration technology

[0389] Step 1:

[0390] A user (producer) sends fresh strawberries to a distribution center. The strawberries are scanned by a terminal and the information is sent to the server.

[0391] Step 2:

[0392] The server sets the optimum temperature and humidity based on the condition of the strawberries and sends this setting information to the cooling device.

[0393] Step 3:

[0394] The terminal periodically monitors the freshness of the strawberries and sends the information to the server, which then adjusts the cooling device to maintain the optimum environment.

[0395] Logistics Optimization

[0396] Step 1:

[0397] The server retrieves information from the existing delivery system, including past delivery data and current delivery status.

[0398] Step 2:

[0399] The server calculates the optimal delivery route based on past and current data and sends the results to the terminal.

[0400] Step 3:

[0401] The terminal receives delivery schedules and provides drivers with the optimal route in real time.

[0402] Collecting and analyzing customer feedback

[0403] Step 1:

[0404] The server generates a QR code and prints the questionnaire on the lunch box packaging.

[0405] Step 2:

[0406] Users scan the QR code and answer a questionnaire on their smartphone or PC, which includes a rating of their diet and suggestions for improvement.

[0407] Step 3:

[0408] The server stores the user feedback in a database for later analysis.

[0409] Emotion recognition and improvement with emotion engine

[0410] Step 1:

[0411] The server inputs the collected feedback data into an emotion engine and analyzes the user's emotions. For example, it recognizes the emotion of "dissatisfaction" from feedback such as "the flavor is bland."

[0412] Step 2:

[0413] The server extracts specific areas for improvement (e.g., "The seasoning needs to be improved") based on the results of sentiment analysis.

[0414] Step 3:

[0415] Based on the identified improvements, the server creates a plan to improve the next menu or service. This plan is shared with relevant experts and staff and reflected in actual improvements.

[0416] This system can efficiently provide nutritionally balanced, safe, and fresh meals and quickly reflect user feedback based on their emotions.

[0417] The processing flow will be explained below.

[0418] Menu development with nutrition experts

[0419] Step 1:

[0420] The server provides an interface for registering feedback from nutrition experts in the database, who input nutritional information and food recommendations via their terminals.

[0421] Step 2:

[0422] The device receives input from experts and sends it to a server, where feedback includes recommendations for specific nutritious ingredients and healthy recipes.

[0423] Step 3:

[0424] The server stores the received feedback in a database, which is used in subsequent processes.

[0425] Step 4:

[0426] The server then consults the nutrition database and matches it with expert feedback, specifically searching for data that matches the recommended ingredients and recipes.

[0427] Step 5:

[0428] The server generates new menu recommendations based on the matching results and stores them in the database. For example, a new menu item might be "high-protein, low-fat salad."

[0429] Ingredient contracts and management

[0430] Step 1:

[0431] The terminal collects information provided by producers (e.g., available ingredients, supply period) and transmits it to the server.

[0432] Step 2:

[0433] The server stores the received producer information in a database, including the types of ingredients each producer offers and the seasons in which they are available.

[0434] Step 3:

[0435] The server enters into a contract with a producer and registers the contract information in a database. For example, a contract may be made to supply fresh tomatoes in the summer.

[0436] Step 4:

[0437] The server monitors the status of contract fulfillment and manages whether ingredients are being supplied appropriately according to the supply schedule.

[0438] Preserving freshness with refrigeration technology

[0439] Step 1:

[0440] A user (producer) sends fresh produce (e.g., strawberries) to a distribution center. The produce is scanned at a terminal dedicated to receiving the produce.

[0441] Step 2:

[0442] The terminal scans the condition of the received ingredients (e.g., temperature, humidity) and sends the data to the server.

[0443] Step 3:

[0444] The server uses the scan data to determine optimal cooling settings, such as calculating the ideal temperature and humidity for storing strawberries.

[0445] Step 4:

[0446] The terminal receives instructions from the server and sets the refrigeration device, thereby keeping the food optimally fresh.

[0447] Step 5:

[0448] The terminal periodically monitors the freshness of the food in the refrigerator and sends the data to the server. If an abnormality is detected, an alert is sent immediately.

[0449] Logistics Optimization

[0450] Step 1:

[0451] The server receives data from existing delivery systems and delivery partners, including delivery times and past delivery routes.

[0452] Step 2:

[0453] The server calculates the optimal delivery route based on the received data, including real-time traffic information.

[0454] Step 3:

[0455] The server creates a delivery schedule based on the calculation results and sends it to the terminal. The delivery schedule includes detailed routes for each delivery.

[0456] Step 4:

[0457] The terminal receives delivery schedules and provides the optimal delivery route to the driver, who receives real-time instructions using the terminal.

[0458] Step 5:

[0459] The device uses GPS to track the location of the bento during delivery and sends this information in real time to a server, which continuously updates the delivery status.

[0460] Collecting and analyzing customer feedback

[0461] Step 1:

[0462] The server generates a QR code for the survey and prints it on the lunch box packaging, which contains a specific survey link.

[0463] Step 2:

[0464] Users scan the QR code and access the survey using their smartphone or PC, which includes fields for rating their diet and providing suggestions for improvement.

[0465] Step 3:

[0466] The server receives the survey data from users and stores it in a database, where the feedback is later analyzed by the emotion engine.

[0467] Emotion recognition and improvement with emotion engine

[0468] Step 1:

[0469] The server inputs the collected feedback data into an emotion engine and analyzes the user's emotions. For example, it recognizes the emotion of "dissatisfaction" from feedback such as "the flavor is bland."

[0470] Step 2:

[0471] The server extracts specific improvements based on the results of sentiment analysis, for example, determining that "the flavor needs to be improved."

[0472] Step 3:

[0473] Based on the identified improvements, the server creates an improvement plan for the next menu or service. The improvement plan is shared with relevant experts and staff and is reflected in actual improvements.

[0474] In this way, it is possible to efficiently provide nutritionally balanced, safe and fresh meals through each processing step, and to quickly reflect the user's emotional feedback.

[0475] Example 2

[0476] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0477] Modern eating habits demand the provision of nutritionally balanced, safe, and fresh meals. However, conventional systems have difficulty effectively incorporating feedback from nutrition experts into menus, and have issues with contract management of ingredients, maintaining freshness, efficient logistics, and insufficient collection and analysis of customer feedback. Furthermore, they lack a mechanism for improving products that reflect user sentiment. As a result, improvements in customer satisfaction and continuous product improvement have not been fully achieved.

[0478] 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.

[0479] In this invention, the server includes means for receiving feedback from nutrition experts and registering it in a database, means for comparing the expert feedback with the nutrition database to create recommended menus, means for contracting for ingredients provided by ingredient suppliers and managing the contract information, means for applying refrigeration technology to maintain the freshness of received ingredients, means for monitoring the status of ingredients while maintaining freshness using refrigeration technology and sending the data to the server, means for calculating the optimal delivery route in cooperation with an existing delivery system and executing and tracking delivery, means for collecting customer feedback via QR codes and analyzing the data to utilize for product improvement, and means for analyzing the collected feedback using an emotion engine, recognizing user emotions, and extracting areas for improvement. This enables the efficient provision of nutritionally balanced, safe, and fresh meals and rapid product improvement.

[0480] A "nutrition expert" refers to a person who has specialized knowledge about nutrition and whose job is to evaluate and provide guidance on the nutritional balance of meals.

[0481] "Feedback" refers to opinions and evaluations provided by users, experts, etc.

[0482] A "database" refers to a system that stores data and enables it to be efficiently managed and searched.

[0483] "Verification" refers to the act of comparing different information or data and checking whether they match.

[0484] "Recommended Menu" refers to meal suggestions made based on specific criteria or conditions.

[0485] "Food supplier" refers to a professional company that produces and supplies fresh food ingredients.

[0486] "Agreement" means any legally recognized document or process of agreement.

[0487] "Cold storage technology" refers to the technology and equipment used to maintain a low temperature environment.

[0488] "Monitoring" refers to the act of continuously watching over and checking the status.

[0489] A "delivery system" refers to a system or network for efficiently transporting goods.

[0490] "Delivery route" refers to the optimal route connecting delivery destinations.

[0491] A "QR code" is a type of two-dimensional barcode that allows information to be easily read.

[0492] "Customer feedback" refers to opinions and evaluations provided by customers regarding products and services.

[0493] "Data analysis" refers to the process of analyzing collected data and finding meaning and patterns.

[0494] "Product improvement" refers to improving the quality of products and services in order to increase customer satisfaction.

[0495] An "emotion engine" refers to a system that uses natural language processing technology to analyze emotions from text data.

[0496] "User emotions" refers to the impressions and feelings that users have about a product or service.

[0497] "Improvements" refers to changes or corrections that are needed to improve the current situation.

[0498] The present invention is an integrated system that efficiently provides nutritionally balanced meals and can quickly reflect customer feedback in improving products. This system is mainly composed of a server, terminals, and users.

[0499] The server performs the following functions: It provides an interface for nutrition experts to input their feedback into the database. Experts use a browser to input their feedback, which is then sent to the server and stored in the database. It also compares the feedback with the existing nutrition database to generate recommended menus. These menus are then stored in the database along with a list of ingredients and their nutritional information.

[0500] The server then concludes contracts with producers based on information provided by food suppliers and registers the contract information in the management system. After receiving the ingredients, it uses refrigeration technology to set the appropriate temperature and humidity, adjusting the environment to maintain freshness. It also optimizes logistics and calculates the optimal delivery route based on past and current delivery data.

[0501] Meanwhile, the terminal is responsible for collecting information from producers and sending it to the server. For example, if a producer can supply fresh tomatoes, the information is entered into the terminal and sent to the server. When receiving ingredients, the terminal is used to scan the ingredients and the information is sent to the server. When applying refrigeration technology, the terminal also monitors the freshness of the ingredients and continuously sends this data to the server. This allows the refrigeration device to maintain an optimal environment.

[0502] Users scan the QR code using their smartphone and answer the questionnaire. The feedback is sent to the server and stored in a database. The server inputs this feedback data into an emotion engine and uses natural language processing technology to analyze the user's emotions. For example, feedback such as "the flavor is bland" can be recognized as an emotion of "dissatisfaction." Based on the analysis results, specific areas for improvement are extracted and reflected in the next menu or service.

[0503] Specific examples

[0504] Menu development with nutrition experts

[0505] The server registers the feedback of "high protein, low fat" from nutrition experts in a database. The experts input their feedback using a terminal, and the server stores it in the database.

[0506] The server compares the registered feedback with the company's nutritional database to search for matching ingredients and menu items.

[0507] The server generates a new recommended menu item, "High-protein, low-fat salad," based on the matching results and stores it in the database.

[0508] Ingredient contracts and management

[0509] The terminal collects information sent by the producer (for example, whether fresh tomatoes are available in summer) and transmits it to the server.

[0510] The server concludes a contract with the producer and registers this contract information in the management system.

[0511] Preserving freshness with refrigeration technology

[0512] A user (producer) sends fresh strawberries to a distribution center. The strawberries are scanned by a terminal and the information is sent to the server.

[0513] The server sets the optimum temperature and humidity based on the condition of the strawberries and sends this setting information to the cooling device.

[0514] The terminal periodically monitors the freshness of the strawberries and sends the information to the server, which then adjusts the cooling device to maintain the optimal environment.

[0515] Logistics Optimization

[0516] The server retrieves information from the existing delivery system, including past delivery data and current delivery status.

[0517] The server calculates the optimal delivery route based on past and current data and sends the results to the terminal.

[0518] The terminal receives delivery schedules and provides drivers with the optimal route in real time.

[0519] Collecting and analyzing customer feedback

[0520] The server generates a QR code and prints the questionnaire on the lunch box packaging.

[0521] Users scan the QR code and answer a questionnaire on their smartphone or PC, which includes a rating of their diet and suggestions for improvement.

[0522] The server stores the user feedback in a database for later analysis.

[0523] Emotion recognition and improvement with emotion engine

[0524] The server inputs the collected feedback data into an emotion engine and analyzes the user's emotions. For example, it recognizes the emotion of "dissatisfaction" from feedback such as "the flavor is bland."

[0525] The server extracts specific areas for improvement (e.g., "The seasoning needs to be improved") based on the results of sentiment analysis.

[0526] Based on the identified improvements, the server creates a plan to improve the next menu or service. This plan is shared with relevant experts and staff and reflected in actual improvements.

[0527] This system can efficiently provide nutritionally balanced, safe, and fresh meals and quickly reflect user feedback based on their emotions.

[0528] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0529] Menu development with nutrition experts

[0530] Step 1:

[0531] The server collects feedback from nutrition experts, who input feedback such as "high-protein, low-fat menus are recommended" using a terminal, which is then sent to the server's database.

[0532] Input: Expert feedback

[0533] Output: Feedback data stored in a database

[0534] Step 2:

[0535] The server compares the feedback stored in the database with a nutrition database using a pre-defined algorithm.

[0536] Input: Expert feedback, nutrition database

[0537] Output: Matching result

[0538] Step 3:

[0539] The server generates new menu recommendations based on the match, including specific ingredient lists and nutritional information.

[0540] Input: Matching result

[0541] Output: Menu recommendations, new cooking recipes

[0542] Ingredient contracts and management

[0543] Step 1:

[0544] The terminal collects information from producers and sends it to the server, for example, by inputting detailed information about available ingredients and when they will be available.

[0545] Input: Supply information from producers

[0546] Output: The feed sent to the server

[0547] Step 2:

[0548] The server generates a contract based on the collected producer information and concludes the contract using an electronic signature system. The contract details are then registered in the management system.

[0549] Input: Supply information from producers

[0550] Output: Registered contract information

[0551] Preserving freshness with refrigeration technology

[0552] Step 1:

[0553] The user (producer) sends fresh ingredients to the distribution center. The received ingredients are scanned by a terminal and the information is sent to the server.

[0554] Input: Ingredients sent

[0555] Output: Scanned food data

[0556] Step 2:

[0557] The server calculates the optimal cooling settings based on the scanned food data and sends the setting information to the cooling device.

[0558] Input: scanned food data

[0559] Output: Cooling setting information

[0560] Step 3:

[0561] The terminal periodically collects data from the refrigerator to monitor the freshness of the ingredients. This data is then sent to a server, which then appropriately manages the environment to maintain freshness.

[0562] Input: Data from refrigeration equipment

[0563] Output: Monitoring data

[0564] Logistics Optimization

[0565] Step 1:

[0566] The server acquires existing delivery system data and calculates the optimal delivery route based on past and current delivery status.

[0567] Input: Existing delivery system data

[0568] Output: Optimal delivery route information

[0569] Step 2:

[0570] The terminal provides the driver with optimal delivery route information and real-time route instructions, while simultaneously transmitting delivery status information to the server.

[0571] Input: Optimal delivery route information

[0572] Output: Real-time delivery instructions, location data

[0573] Collecting and analyzing customer feedback

[0574] Step 1:

[0575] The server generates a QR code and prints it on the lunch box package, which contains a link to the survey form.

[0576] Input: QR code generation information

[0577] Output: QR code printed on the bento package

[0578] Step 2:

[0579] Users scan the QR code with their smartphone to access the survey form and submit their answers.

[0580] Input: Customer feedback

[0581] Output: Survey data saved on the server

[0582] Emotion recognition and improvement with emotion engine

[0583] Step 1:

[0584] The server inputs the collected feedback data into an emotion engine, which then analyzes the user's emotions using natural language processing technology.

[0585] Input: Customer feedback data

[0586] Output: Emotion analysis results

[0587] Step 2:

[0588] The server extracts specific areas for improvement based on the results of sentiment analysis. For example, from feedback that the food tastes bland, it identifies the need to improve the seasoning.

[0589] Input: Sentiment analysis results

[0590] Output: Extracted improvements

[0591] Step 3:

[0592] The server will then create a plan to improve the next menu or service based on the identified improvements, and share this plan with experts and staff. This plan will be reflected in future product offerings.

[0593] Input: Improvements

[0594] Output: Improvement plan

[0595] In this way, the system can quickly reflect user feedback and efficiently provide nutritionally balanced, safe, and fresh meals.

[0596] (Application example 2)

[0597] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0598] In recent years, consumers have become increasingly health-conscious, leading to an increased demand for nutritionally balanced meals and fresh ingredients. However, previous systems made it difficult to effectively incorporate feedback from nutrition experts, and were inadequate in maintaining the freshness of ingredients and in quickly collecting and analyzing customer feedback. Furthermore, there was a lack of efficient methods for optimizing logistics and managing the freshness of ingredients. This made it difficult to provide high-quality meals that met the needs of individual customers. Furthermore, there was a lack of sufficient efforts to improve service based on customer sentiment. As a result, there were problems with reduced satisfaction and lost opportunities.

[0599] 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 means for receiving feedback from nutrition experts and creating menus, means for contracting for seasonal ingredients from ingredient suppliers and managing their safety and quality, means for applying the latest refrigeration technology to maintain the freshness of received ingredients, means for optimizing delivery routes in cooperation with existing home delivery systems, means for collecting customer feedback via QR codes and reflecting it in product improvements, means for collecting customer feedback using QR codes, analyzing it with a sentiment analysis engine, and reflecting it in service improvements, and means for optimizing logistics and monitoring freshness using smart devices. This not only enables efficient and high-quality meal provision, but also enables rapid service improvements based on customer sentiment, thereby improving customer satisfaction.

[0600] A "nutrition expert" is a professional with knowledge and experience regarding the nutritional balance and health of meals, who provides feedback on menu creation and ingredient selection.

[0601] "Feedback" refers to opinions, evaluations, and suggestions for improvement provided by users and experts regarding systems and services, and is information that is used to improve quality and efficiency.

[0602] A "menu" is a list of meals that take into account a specific purpose and nutritional balance, and is a meal plan created with feedback from nutrition experts.

[0603] A "food supplier" is a business that produces or sells food ingredients and provides seasonal ingredients through contracts, and is required to manage safety and quality.

[0604] "Contract" means an agreement between a food supplier and a service provider under which food is promised to be provided for a specified period and under specified conditions.

[0605] "Cold storage technology" is a technique used to maintain the freshness of received ingredients for a long period of time, and includes temperature control and humidity control.

[0606] "Existing delivery system" refers to a logistics system that is already in operation to efficiently deliver ingredients and products to customers.

[0607] A "delivery route" is the route a product takes from its departure point to its destination, and optimizing it improves delivery efficiency and reduces time and costs.

[0608] A QR code is a type of two-dimensional barcode that can be scanned to access information or collect feedback.

[0609] An "emotion analysis engine" is a computer system that analyzes collected feedback data and automatically recognizes users' emotions and satisfaction levels.

[0610] A "smart device" is an electronic device that has Internet connectivity and can send, receive, and process various types of information, including smartphones and tablets.

[0611] "Logistics optimization" is the process of optimizing delivery routes, times, and resources for the efficient transportation of goods.

[0612] "Freshness monitoring" is the process of using refrigeration technology to monitor the freshness of ingredients in real time and collect freshness information.

[0613] "Service improvement" refers to ongoing activities to improve the quality and efficiency of the services we provide based on collected feedback and analytical results.

[0614] This invention is a system that integrates menu development based on feedback from nutrition experts, seasonal ingredient contracts, safety and quality control, preserving the freshness of ingredients using the latest refrigeration technology, optimizing delivery routes by linking with existing delivery systems, collecting customer feedback using QR codes, and improving services using a sentiment analysis engine.

[0615] Menu development with nutrition experts

[0616] The server receives feedback from nutrition experts and registers the feedback in a database. The server then compares it with the company's nutrition database and generates recommended menu items based on the expert's feedback. For example, if the server receives feedback such as "high protein, low fat," it can generate a recommended menu item: "high protein, low fat salad."

[0617] Ingredient contracts and management

[0618] The terminal collects information provided by producers and sends it to the server. The server then uses this information to conclude contracts with food suppliers and registers the contract information in a system that manages such information. For example, the server may collect information from a producer that "fresh tomatoes are available" and conclude a supply contract based on this information.

[0619] Preserving freshness with refrigeration technology

[0620] Food suppliers use the latest refrigeration technology to maintain freshness. The server sets the optimal temperature and humidity based on the condition of the food and sends this setting information to the refrigeration device. The terminal periodically monitors the freshness of the food and sends the information to the server. For example, to maintain the freshness of fresh strawberries, the refrigeration device can be set to the optimal environment.

[0621] Logistics Optimization

[0622] The server acquires information from existing delivery systems and calculates the optimal delivery route based on past delivery data and current delivery status. The terminal receives the delivery schedule based on the calculation results and provides the driver with the optimal route in real time. For example, the most efficient delivery route can be calculated based on past delivery data.

[0623] Customer feedback collection and sentiment analysis

[0624] The server generates a QR code and prints a questionnaire on the lunch box packaging. The user scans this QR code with their smartphone and answers the questionnaire. The server then analyzes the collected feedback using a sentiment analysis engine to recognize the user's emotions. Based on this, the server identifies areas for improvement in the service and creates plans to improve the next menu or service. For example, in response to feedback that the flavor is "bland," the server can identify specific areas for improvement such as "the seasoning needs to be improved."

[0625] Examples of concrete examples and prompts

[0626] Specific examples include developing a "high-protein, low-fat salad" menu, signing a contract to supply fresh tomatoes, setting up an optimal refrigeration environment, calculating delivery routes, collecting feedback using QR codes, and analyzing emotions such as "the taste is bland" to "dissatisfied."

[0627] An example prompt might be, "Please provide the code that will help us analyze user feedback, analyze it with our sentiment engine, and improve our menu next time."

[0628] The above-mentioned system not only enables efficient and high-quality food service, but also allows for quick service improvements based on customer sentiment, thereby increasing customer satisfaction.

[0629] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0630] Step 1:

[0631] The server receives feedback from nutrition experts and registers it in a database. First, the server provides a feedback input interface to the experts, who then use their terminals to input specific feedback such as "high protein, low fat." This input is sent to the server and stored in the database.

[0632] Input: Expert feedback (e.g., "high protein, low fat")

[0633] Data processing / calculation: Feedback content is registered in the database

[0634] Output: Feedback is saved in a database

[0635] Step 2:

[0636] The server compares the feedback with the company's nutrition database and creates menu recommendations based on the feedback. For example, based on the feedback "high protein, low fat," the server searches for matching ingredients and cooking methods, generating a new menu item such as "high protein, low fat salad."

[0637] Input: Nutrition expert feedback data

[0638] Data processing / calculation: Matching feedback with nutritional database, generating new menu items

[0639] Output: Recommended menu (e.g. "High protein, low fat salad")

[0640] Step 3:

[0641] The terminal collects information about ingredients provided by producers and sends it to the server. For example, a producer inputs into the terminal that they can supply fresh tomatoes, and the information is sent to the server.

[0642] Input: Ingredient information from producers (e.g., "Fresh tomatoes available")

[0643] Data processing / calculation: Sending ingredient information to the server

[0644] Output: Ingredient information is saved on the server

[0645] Step 4:

[0646] The server concludes contracts with food suppliers and registers the contract information in the management system. For example, the server digitizes contracts with producers and registers them in the management system.

[0647] Input: Contract information with food suppliers

[0648] Data processing / calculation: Digitization and registration of contract information

[0649] Output: Contract information is saved in the management system

[0650] Step 5:

[0651] The server sets the optimal temperature and humidity based on the condition of the ingredients and sends this setting information to the refrigeration device. For example, to maintain the freshness of produced strawberries, the server calculates the optimal refrigeration environment (temperature and humidity) and sets it in the device.

[0652] Input: Freshness of ingredients

[0653] Data processing / calculation: Calculation of cooling settings based on freshness status

[0654] Output: Configuration information sent to the refrigerator

[0655] Step 6:

[0656] The device periodically monitors the freshness of the ingredients and sends the information to the server. For example, a sensor in the refrigerator collects freshness data, and the device then forwards the data to the server.

[0657] Input: Freshness data from the refrigerator sensor

[0658] Data processing / calculation: Monitoring and transferring freshness data

[0659] Output: Freshness information sent to the server

[0660] Step 7:

[0661] The server obtains information from existing delivery systems and optimizes delivery routes. Based on past delivery data and current delivery status, the server calculates the optimal delivery route and sends the results to the terminal.

[0662] Input: Data from existing delivery system

[0663] Data processing / calculation: Calculating the optimal delivery route

[0664] Output: The optimal route information is sent to the device.

[0665] Step 8:

[0666] The device generates a QR code and prints the questionnaire on the lunch box package. The user scans the QR code with their smartphone and answers the questionnaire.

[0667] Input: QR code generation request

[0668] Data processing / calculation: QR code generation

[0669] Output: Survey with QR code printed

[0670] Step 9:

[0671] The server analyzes the collected feedback using a sentiment analysis engine to recognize the user's emotions. Feedback such as "the flavor is bland" is recognized as "dissatisfied," and the server identifies areas for improvement in the next menu or service.

[0672] Input: Feedback data

[0673] Data processing / calculation: Sentiment analysis, extraction of areas for improvement

[0674] Output: Next menu or service with improvements reflected

[0675] The above processing steps enable a smooth process of collecting feedback provided by users in real time and using the emotion engine to reflect it in improving the next menu or service.

[0676] 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.

[0677] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0678] 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.

[0679] [Second embodiment]

[0680] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0681] 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.

[0682] 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).

[0683] 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.

[0684] 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.

[0685] 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).

[0686] 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. 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.

[0687] 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.

[0688] 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.

[0689] 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.

[0690] 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.

[0691] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0692] The present invention is a system that includes menu development based on feedback from nutrition experts, safety and quality control of ingredients based on contracts with producers, freshness maintenance using the latest refrigeration technology, logistics optimization through integration with existing bento delivery systems, and a process for collecting customer feedback and improving products using QR codes.

[0693] Program processing explanation

[0694] Menu development with nutrition experts

[0695] 1. Gathering feedback

[0696] The server stores the feedback from the nutrition experts in a database.

[0697] The terminal inputs feedback through the nutrition expert interface and transmits it to the server.

[0698] 2. Comparison with nutritional data

[0699] The server compares the stored feedback with an in-house nutrition database.

[0700] The server searches for matching ingredients and menu items.

[0701] 3. Creating a recommended menu

[0702] The server creates and stores new recommended menus based on the results of comparison with the nutrition database.

[0703] Ingredient contracts and management

[0704] 1. Collecting producer information

[0705] The terminal collects information from the producer and transmits it to the server.

[0706] 2. Contract conclusion and management

[0707] The server concludes a contract with the producer and registers the contract information in the management system.

[0708] Preserving freshness with refrigeration technology

[0709] 1. Receiving and checking ingredients

[0710] The user (producer) sends ingredients to the distribution center.

[0711] The terminal checks the freshness of the received ingredients and sends the information to the server.

[0712] 2. Application of refrigeration technology

[0713] The server connects the food ingredient data to the refrigeration equipment and applies the optimal refrigeration technology.

[0714] 3. Freshness monitoring

[0715] The terminal periodically monitors the freshness of the food items being kept refrigerated and sends this information to the server.

[0716] Logistics Optimization

[0717] 1. Calculating delivery routes

[0718] The server calculates the optimal delivery route based on data from the existing delivery system.

[0719] 2. Create a delivery schedule

[0720] The server creates a delivery schedule based on the calculated delivery route and transmits it to the terminal.

[0721] 3. Track your delivery

[0722] The device uses GPS to track the current location of the lunch box during delivery and transmits that information to the server in real time.

[0723] Collecting and analyzing customer feedback

[0724] 1. Distribution of the questionnaire

[0725] The server generates a QR code for the survey and prints it on the lunch box packaging.

[0726] 2. Gathering Feedback

[0727] Users scan the QR code to answer the survey.

[0728] The server stores the user's feedback in a database.

[0729] 3. Analyzing feedback and identifying areas for improvement

[0730] The server analyzes the collected feedback and extracts low-rated items and areas for improvement.

[0731] Specific examples

[0732] As a specific example, the following series of processes can be considered.

[0733] 1. Nutrition experts propose new menu items based on the theme of "high protein, low fat." The server registers this feedback in a database and compares it with the nutrition database to create recommended menu items.

[0734] 2. A local farmer signs a contract to provide fresh tomatoes during the summer season. The terminal sends this contract information to the server and registers it in the management system.

[0735] 3. Strawberries received at the distribution center are stored in the latest refrigeration equipment and temperature controlled to maintain freshness. The terminal monitors the freshness of the strawberries and periodically reports this to the server.

[0736] 4. The server uses an optimization algorithm to calculate the fastest delivery route and create a delivery schedule. The device tracks the location of the bento box in real time during delivery and sends it to the server.

[0737] 5. The user scans the QR code and sends feedback that the food tastes bland. The server analyzes this feedback and reflects it in improving the menu for the next time.

[0738] This system makes it possible to efficiently provide nutritionally balanced, safe, and fresh meals.

[0739] The processing flow will be explained below.

[0740] Menu development with nutrition experts

[0741] Step 1:

[0742] The server provides an interface for storing feedback from nutrition experts in a database, and the experts input their feedback through terminals.

[0743] Step 2:

[0744] The device receives expert feedback and sends it to a server, which includes specific nutritional information and areas for improvement.

[0745] Step 3:

[0746] The server registers the expert's feedback in a database, which is used to match the feedback with the nutrition database.

[0747] Step 4:

[0748] The server will refer to the nutrition database and compare it with the registered feedback, searching for matching ingredients and menu items.

[0749] Step 5:

[0750] The server generates a new recommended menu based on the matching results and stores it in a database.

[0751] Ingredient contracts and management

[0752] Step 1:

[0753] The terminal collects information from producers (for example, information on available ingredients and seasonal information) and sends it to the server.

[0754] Step 2:

[0755] The server registers the information sent from the producers in a database, including the type of food and the supply period.

[0756] Step 3:

[0757] The server performs the procedure to conclude a contract with the producer, confirms the contract details, and saves them in the database.

[0758] Step 4:

[0759] The server monitors the status of contract fulfillment and displays the seasonal food supply status on the management system.

[0760] Preserving freshness with refrigeration technology

[0761] Step 1:

[0762] The user (producer) sends ingredients to the distribution center, where they are scanned at a receiving terminal.

[0763] Step 2:

[0764] The terminal scans the received ingredients to determine their condition (e.g., temperature, humidity) and sends the data to the server.

[0765] Step 3:

[0766] The server receives the food ingredient data and starts communicating with the refrigeration equipment, determining the optimal refrigeration technology (temperature and humidity settings).

[0767] Step 4:

[0768] The terminal receives instructions from the server and sets the cooling device appropriately, creating an environment that keeps food fresh.

[0769] Step 5:

[0770] The terminal periodically monitors the freshness of the food in the refrigerator and sends the status to the server, issuing an alert if there is an abnormality.

[0771] Logistics Optimization

[0772] Step 1:

[0773] The server receives data from existing delivery systems and delivery partners, including current delivery status and past delivery data.

[0774] Step 2:

[0775] Based on the data received by the server, an optimization algorithm is used to calculate the optimal delivery route.

[0776] Step 3:

[0777] The server creates a delivery schedule based on the calculation results and sends it to the terminal.

[0778] Step 4:

[0779] The terminal receives delivery schedules and assists in executing deliveries, while the driver uses the terminal to check route information in real time.

[0780] Step 5:

[0781] The device uses GPS to track the current location of the bento and ingredients being delivered and sends that data to a server, which updates the delivery status in real time.

[0782] Collecting and analyzing customer feedback

[0783] Step 1:

[0784] The server generates a QR code for the survey and prints it on the lunch box packaging, which contains a specific survey link.

[0785] Step 2:

[0786] Users scan the QR code to access the survey on their smartphone or PC, which includes a field to rate the diet and provide suggestions for improvement.

[0787] Step 3:

[0788] The server receives the survey data from users and stores it in a database, where the feedback is later analyzed.

[0789] Step 4:

[0790] The server analyzes the collected feedback data and extracts low-rated items and specific areas for improvement.

[0791] Step 5:

[0792] Based on the identified improvements, the server creates a plan to improve the next menu or service. The plan is shared with experts and staff.

[0793] In this way, a system is realized that efficiently provides nutritionally balanced, safe, and fresh meals through each processing step.

[0794] Example 1

[0795] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0796] In recent years, growing health consciousness has led to an increasing demand for systems that efficiently provide nutritionally balanced meals. However, conventional systems have not been able to fully incorporate feedback from nutrition experts, resulting in insufficient optimization of ingredient freshness management and logistics. Furthermore, there is a lack of means to efficiently collect and incorporate customer feedback. Furthermore, automating contract management with ingredient suppliers and freshness monitoring has also been an issue. There is a need to solve these issues.

[0797] 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.

[0798] In this invention, the server includes a means for receiving feedback from nutrition experts and creating menus, a means for comparing the feedback with a nutrition database, and a means for applying the latest refrigeration technology to maintain the freshness of the received ingredients, thereby enabling the proposal of nutritionally balanced menus, the management of the freshness of ingredients, the optimization of logistics, and the collection and analysis of customer feedback.

[0799] A "nutritionist" is a professional with specialized knowledge of nutrition who optimizes the nutritional balance of meals and designs menus tailored to specific health goals.

[0800] "Feedback" refers to opinions and evaluation information provided by nutrition experts and customers, based on which the system and menus are improved.

[0801] "Menu" refers to a list of meals or dishes, including ingredients and cooking methods, organized around a particular theme or with nutritional balance in mind.

[0802] "Food suppliers" refers to producers and businesses that provide seasonal food ingredients and are subject to safety and quality control.

[0803] "Contract" means a formal agreement between a food supplier and a system operator that provides for the supply of food of a specified quality and quantity within a specified period of time.

[0804] "Cold storage technology" is a technique for maintaining a low temperature environment and is a means used to keep food ingredients fresh for a long period of time.

[0805] "Delivery system" refers to the infrastructure and procedures for delivering goods, and is the existing delivery network used to streamline logistics.

[0806] A "QR code" is a type of two-dimensional barcode that can be read with a camera on a smartphone or other device to quickly access information.

[0807] "Customer feedback" refers to the opinions and evaluations that customers submit about services and products, and is valuable data for product improvement.

[0808] A "nutrition database" is a database that stores detailed information on the nutritional components contained in various ingredients and dishes, and is used to optimize nutritional balance.

[0809] "Freshness monitoring" refers to the process of regularly monitoring the quality status of food ingredients (e.g., color, temperature, humidity, etc.) and sending that information to a server for analysis.

[0810] "Delivery route" refers to the route along which goods are transported to their destination, and is optimized for efficient delivery.

[0811] "Smartphone" is an abbreviation for smartphone, a type of mobile phone equipped with GPS functionality and internet connectivity.

[0812] "Real-time tracking" refers to the ability to check the current location of an object in real time, especially for goods being delivered.

[0813] The present invention is a system that includes menu development based on feedback from nutrition experts, safety and quality control of ingredients based on contracts with producers, freshness maintenance using the latest refrigeration technology, logistics optimization through integration with existing home delivery systems, and a process for collecting customer feedback and improving products using QR codes.

[0814] Menu development with nutrition experts

[0815] The server stores the feedback from nutrition experts in a database. Feedback is provided as a URL, document file, or XML feed, and the server automatically analyzes and registers it in the database. The terminal provides an administration screen for nutrition experts, where they can enter their feedback using text boxes and check boxes. The entered information is sent to the server via an HTTP request.

[0816] The server then matches the feedback stored in the database with a nutrition database (e.g., MySQL) and uses a keyword search algorithm to find matching ingredients and menu items. The matched data is statistically analyzed using Python or R to generate new menu recommendations. This menu is then stored again in the database and formatted for screen output.

[0817] A specific example includes a process in which a nutritionist submits feedback on the theme "high protein, low fat" via an administration screen, and the server generates a recommended menu item, "chicken breast salad," based on this information.

[0818] Ingredient contracts and management

[0819] The terminal provides a dedicated web form for collecting information from producers. This form is an interface for entering information such as the farmer's name, location, and list of ingredients they can provide. This information is sent from the terminal to the server via an HTTP request and automatically registered in a database.

[0820] The server registers contract information with producers (contract start date, end date, supply volume, etc.) in the management system. The contract is saved as a PDF, and various conditions are stored in the database in JSON format.

[0821] A specific example involves a process in which a local farmer enters a contract to "provide fresh tomatoes during the summer season" through a web form, and the server registers the information in a database.

[0822] Preserving freshness with refrigeration technology

[0823] The user (producer) sends the harvested ingredients to the distribution center. The terminal provides a smartphone app to check the freshness of the ingredients received at the distribution center. The app checks color, aroma, temperature, etc., and sends the results digitally to the server.

[0824] The server can determine the optimal refrigeration method (temperature, humidity, etc.) based on the received food information and issue instructions to the refrigeration device. The terminal also periodically monitors the freshness of the food using cameras and sensors in the refrigeration device and sends this data to the server.

[0825] A specific example is a process that measures the color and temperature of strawberries received at a distribution center and allows the server to set the optimal refrigeration temperature. Sensors in the refrigeration equipment monitor freshness and periodically send data to the server.

[0826] Logistics Optimization

[0827] The server acquires data from existing delivery systems and calculates optimal delivery routes using the Google Maps API and a proprietary optimization algorithm. It automatically generates a delivery schedule based on the route information and sends the results to the device. The delivery schedule includes estimated delivery times and orders.

[0828] The device uses the GPS function installed on the delivery driver's smartphone to track the current location of the bento boxes being delivered in real time and transmits this information to a server at regular intervals.

[0829] For example, the server uses the Google Maps API to calculate the optimal route, generate a delivery schedule, and send it to the driver's smartphone. The device periodically uploads GPS information to the server, allowing the driver to check the delivery status in real time.

[0830] Collecting and analyzing customer feedback

[0831] The server generates a QR code for customer feedback and prints it on the lunch box package label. Users scan the QR code with their smartphone to access the survey form and enter their opinions. The server saves the entered feedback data in a database in real time.

[0832] The server analyzes the collected feedback data using machine learning algorithms in Python and R to identify low-rated items and areas for improvement. The analysis results are visualized on a management screen and reflected in menu development and logistics management.

[0833] A specific example includes a process where a user scans a QR code and sends feedback such as "the flavor is bland," which the server analyzes and reflects in the next menu revision, adjusting the "optimal amount of seasoning."

[0834] Example prompt sentence:

[0835] "I would like to create a new, nutritionally balanced menu. Please suggest recipes that use high-protein, low-fat ingredients."

[0836] Thus, the system of the present invention comprehensively covers all the steps required to efficiently provide nutritionally balanced, safe and fresh meals.

[0837] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0838] Program processing flow

[0839] Step 1: Gather expert feedback

[0840] explanation:

[0841] The device provides a dedicated management screen for receiving feedback from nutrition experts. The management screen has text boxes and check boxes where experts can enter their opinions and suggestions. The entered data is sent to the server via an HTTP request. The server stores the received data in a database.

[0842] input:

[0843] Nutrition expert feedback (text and multiple choice answers)

[0844] output:

[0845] Feedback information stored in a database

[0846] Specific behavior:

[0847] When an expert enters feedback such as "high protein, low fat" into the management screen and presses the send button, the data is sent to the server.

[0848] Step 2: Check against nutritional data

[0849] explanation:

[0850] The server retrieves the feedback stored in the database and compares it with the company's internal nutrition database. Specifically, it performs text analysis of the feedback and searches for related ingredients and menu items using keyword searches. The search results are temporarily stored.

[0851] input:

[0852] Feedback information stored in a database

[0853] output:

[0854] Matched ingredients and menu list

[0855] Specific behavior:

[0856] Based on the keywords "high protein, low fat," the server checks a nutritional database to extract information on ingredients such as "chicken breast" and "lean fish."

[0857] Step 3: Create a recommended menu

[0858] explanation:

[0859] The server generates new recommended menus based on the matching results. Using Python and R, the menus are constructed to meet nutritional balance and calorie constraints. The generated menus are saved in a database and can be viewed on the management screen.

[0860] input:

[0861] Matched ingredients and menu list

[0862] output:

[0863] Recommendations stored in a database

[0864] Specific behavior:

[0865] The server generates a menu list including "chicken breast salad" and stores it in a database.

[0866] Step 4: Collecting producer information and managing contracts

[0867] explanation:

[0868] The terminal provides an interface where producers can enter information through a dedicated web form, including, for example, the farmer's name, location, and available ingredients list. The entered information is sent via an HTTP request to the server, which then registers it in a database.

[0869] input:

[0870] Information from producer (name, location, list of ingredients)

[0871] output:

[0872] Producer information and contract information registered in the database

[0873] Specific behavior:

[0874] Producers enter information such as "providing fresh tomatoes during the summer season" into a web form, and the server registers the information in a database.

[0875] Step 5: Receive ingredients and check freshness

[0876] explanation:

[0877] The user (producer) sends the harvested ingredients to the distribution center. The terminal provides an interface for checking the freshness of the ingredients that arrive at the center using a smartphone app. Check items include color, aroma, temperature, etc. The terminal then digitally transmits the results to the server.

[0878] input:

[0879] Freshness information for ingredients received at the distribution center

[0880] output:

[0881] Freshness data sent to the server

[0882] Specific behavior:

[0883] At the distribution center, users measure the color and temperature of strawberries using a smartphone app and send the data to the server.

[0884] Step 6: Applying cooling technology

[0885] explanation:

[0886] The server determines the optimal refrigeration method based on the received food information, sets temperature and humidity conditions, and issues instructions to the refrigeration device. It also monitors sensors to maintain freshness under the set environment, and continuously sends this data to the server.

[0887] input:

[0888] Freshness data and ingredient information

[0889] output:

[0890] Setting data that gives instructions to the cooling device

[0891] Specific behavior:

[0892] The server sets the temperature and humidity conditions for the strawberries and instructs the refrigeration device to "store them at the preset temperature."

[0893] Step 7: Optimize delivery routes

[0894] explanation:

[0895] The server acquires data from existing delivery systems and calculates optimal delivery routes using the Google Maps API and proprietary algorithms. Based on the results of the calculations, it automatically generates a delivery schedule and sends the results to the device.

[0896] input:

[0897] Delivery system data and customer delivery information

[0898] output:

[0899] Optimal delivery routes and schedules

[0900] Specific behavior:

[0901] The server uses the Google Maps API to calculate the "fastest route," generate a schedule, and send it to the driver's smartphone.

[0902] Step 8: Track your shipment

[0903] explanation:

[0904] The device uses the GPS function installed on the delivery driver's smartphone to periodically track the current location of the lunch box during delivery. The location information is sent to a server at regular intervals and displayed in real time on the management screen.

[0905] input:

[0906] GPS location information from the driver's smartphone

[0907] output:

[0908] Real-time location tracking data

[0909] Specific behavior:

[0910] The device acquires the location information of the lunch box being delivered and periodically uploads it to the server, allowing delivery status to be checked in real time.

[0911] Step 9: Collect and analyze customer feedback

[0912] explanation:

[0913] The server generates a QR code for customer feedback and prints it on the lunch box package label. The customer scans the QR code with their smartphone, accesses the survey form, and enters their feedback. The entered data is saved on the server in real time.

[0914] input:

[0915] Customer feedback (survey responses)

[0916] output:

[0917] Feedback data stored on the server

[0918] Specific behavior:

[0919] The user scans the QR code printed on the bento box and sends feedback such as "the taste is bland," which the server then stores in a database.

[0920] Step 10: Analyze feedback and identify areas for improvement

[0921] explanation:

[0922] The server analyzes the collected feedback data using machine learning algorithms in Python and R to identify low-rated items and areas for improvement. The analysis results are visualized on a management screen and reflected in the next menu development and logistics management.

[0923] input:

[0924] Collected customer feedback data

[0925] output:

[0926] Analysis results and list of improvements

[0927] Specific behavior:

[0928] The server will analyze the feedback that the food is "bland" and implement a process to reflect the "optimal amount of seasoning" in the next menu.

[0929] In this way, each step works together to create a system that efficiently provides nutritionally balanced, safe, and fresh meals.

[0930] (Application example 1)

[0931] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0932] Providing nutritionally balanced meals and delivering them efficiently is an important issue in modern society. However, currently, menu development that appropriately reflects expert feedback, managing the safety and quality of ingredients, applying refrigeration technology to ensure fast delivery and freshness, and even collecting customer feedback and improving products are all fragmented at each stage, resulting in insufficient coordination as a comprehensive system. Furthermore, achieving efficient food delivery using smartphones and other devices remains a challenge.

[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 means for receiving feedback from nutrition experts and creating menus, means for contracting seasonal ingredients from ingredient suppliers and managing their safety and quality, means for applying the latest refrigeration technology to maintain the freshness of received ingredients, means for optimizing delivery routes in cooperation with existing home delivery systems, means for collecting customer feedback via QR codes and reflecting it in product improvements, and means for installing a food delivery application on smartphones to provide nutritionally balanced, health-conscious meals, thereby enabling the efficient provision of nutritionally balanced, healthy meals and increasing customer satisfaction.

[0935] "Nutrition experts" are people with specialized knowledge about the nutritional value and health benefits of foods.

[0936] "Feedback" refers to an evaluation or opinion provided based on specific information or experience.

[0937] A "menu" is a list of specific meals or dishes, specifying the food offerings.

[0938] "Food supplier" refers to a company or individual that produces and supplies food to restaurants and consumers.

[0939] "Seasonal ingredients" refer to ingredients that are harvested in a particular season due to natural conditions.

[0940] A "contract" is a formal agreement between two parties.

[0941] "Safety" refers to the quality of food that does not adversely affect people's health.

[0942] "Quality" evaluates the superior characteristics of food, such as taste, freshness, and nutritional value.

[0943] "Freshness" refers to the degree of freshness of food between the time it is harvested and the time it is consumed.

[0944] "Cold storage technology" refers to the technology of maintaining food at low temperatures by cooling or freezing, thereby preserving its freshness.

[0945] "Delivery system" refers to a logistics system for delivering goods to a designated location.

[0946] "Delivery route" refers to the route or path planned for efficient delivery of goods.

[0947] "Optimization" refers to adjusting or improving something to achieve the best results for a particular purpose.

[0948] A "QR code" is a type of two-dimensional barcode that allows information to be read quickly.

[0949] "Customer feedback" refers to the means of collecting customer ratings and opinions about products and services.

[0950] "Product improvement" refers to the process of improving a product or service based on collected feedback.

[0951] A "food delivery application" is mobile software that allows you to order food online and have it delivered.

[0952] A "smartphone" refers to a portable information device with advanced computing power and connectivity.

[0953] The system for implementing this invention includes a server that receives feedback from nutrition experts and creates menus, terminals and servers equipped with means for contracting seasonal ingredients provided by food suppliers and managing their safety and quality, equipment that applies the latest refrigeration technology to maintain the freshness of received ingredients, means for optimizing delivery routes in cooperation with existing home delivery systems, and a mechanism for collecting customer feedback via QR codes and reflecting it in product improvements.

[0954] 1. Collaboration with nutrition experts

[0955] The server creates menus based on feedback from nutrition experts. Nutrition experts enter their feedback through a dedicated interface, which is then sent to the server. The server receives this feedback, compares it with its internal nutrition database, and generates new, nutritionally balanced menus. This information is also stored in a database for future reference.

[0956] 2. Ingredient contracts and management

[0957] The terminal collects information about ingredients provided by producers and sends it to a server. The server uses this information to conclude contracts with producers and registers the contract information in a management system. This management system constantly monitors the safety and quality of ingredients and provides feedback as needed.

[0958] 3. Cooling technology to maintain freshness

[0959] The received ingredients are stored in a device that uses the latest refrigeration technology to maintain freshness. The terminal regularly monitors the freshness of the ingredients and sends the information to the server. The server uses this information to optimize the settings of the refrigeration device and adjust it to maintain the maximum freshness of the ingredients.

[0960] 4. Logistics optimization

[0961] The server works with existing delivery systems to calculate optimal delivery routes and create delivery schedules. This schedule is sent to the terminals to improve delivery efficiency. The terminals use GPS to track the location of food during delivery and send it to the server in real time.

[0962] 5. Collecting and incorporating customer feedback

[0963] The server also generates a QR code and prints it on the bento packaging. Users can scan the QR code and provide feedback through the application. The server analyzes this feedback, identifies poorly rated items, and uses them to improve the next menu.

[0964] Specific examples

[0965] Specifically, when a nutrition expert suggests a "low-calorie, high-nutrition" menu, the server registers this feedback in a database and compares it to create new recommended menus. The server also sends contract information for fresh tomatoes provided by local farmers in the summer to the server and registers it in the management system. The received tomatoes are stored in a state-of-the-art refrigeration system, and their freshness is regularly monitored via terminals. The server calculates the fastest delivery route and provides the schedule to the terminals, ensuring efficient delivery. When a user scans a QR code and provides feedback that the flavor is "a little bland," the server analyzes the opinion and uses it to improve the next menu.

[0966] Prompt Sentence Examples

[0967] 1. Nutrition experts, please suggest new menu items based on the theme of "high protein, low fat."

[0968] 2. Send the Fresh Tomato contract information to the server and register it in the management system.

[0969] 3. Monitor the freshness of tomatoes and report it to the server.

[0970] 4. Calculate the fastest delivery route and generate a delivery schedule.

[0971] 5. Scan the QR code and give your feedback on the taste of the dish.

[0972] This approach makes it possible to efficiently provide nutritionally balanced and healthy meals and increase customer satisfaction.

[0973] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0974] Step 1:

[0975] The server receives feedback from nutrition experts. As input, it receives feedback data entered by nutrition experts through a dedicated interface. As data processing, the server takes in the feedback data, compares it with an existing nutrition database, and generates a new nutritionally balanced menu. As output, the new recommended menu is registered in the database.

[0976] Step 2:

[0977] The terminal collects information provided by food ingredient suppliers and sends it to the server. The input includes food ingredient information provided by producers. As a data calculation, the terminal sends the information to the server, and the server uses this information to conclude a contract with the producer and registers the contract information in the management system. As an output, information on food ingredients that have been safety and quality controlled is stored on the server.

[0978] Step 3:

[0979] The server applies the latest refrigeration technology to maintain the freshness of the received ingredients. The input includes data indicating the freshness status of the ingredients. For data processing, the terminal periodically monitors the freshness and sends the information to the server. The server uses this information to optimize the settings of the refrigeration equipment and adjust it to maintain the best possible freshness. The output holds information about ingredients whose freshness has been guaranteed.

[0980] Step 4:

[0981] The server works in conjunction with an existing delivery system to calculate the optimal delivery route. The input includes delivery data obtained from the existing delivery system. As a data calculation, the server analyzes this data and calculates the optimal delivery route. As an output, the optimal delivery route and schedule are created and sent to the terminal.

[0982] Step 5:

[0983] The terminal uses GPS to track the location information of the food being delivered. The input includes the current location information of the food being delivered. The data is processed by sending the location information to the server in real time. The output is the real-time tracking information of the food being delivered, which is stored on the server.

[0984] Step 6:

[0985] Users provide feedback through QR codes. The input includes the feedback information provided by users by scanning the QR code. As a data calculation, the server collects this feedback, evaluates it, and extracts improvements. As an output, the results are reflected in the next menu improvement.

[0986] This series of steps makes it possible to efficiently provide nutritionally balanced and healthy meals and increase customer satisfaction.

[0987] 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.

[0988] The present invention is an integrated system that includes menu development based on feedback from nutrition experts, provision of safe, high-quality meals using local, seasonal ingredients, preservation of freshness of ingredients using the latest refrigeration technology, optimization of logistics by linking with existing bento delivery systems, collection of customer feedback using QR codes, and a process of recognizing user emotions and improving products using an emotion engine.

[0989] Program processing explanation

[0990] Menu development with nutrition experts

[0991] 1. Gathering feedback

[0992] The server provides an interface for registering feedback from nutrition experts in a database, and the experts input their feedback through their terminals.

[0993] 2. Comparison with nutritional data

[0994] The server compares the nutritional database and generates menu recommendations based on expert feedback.

[0995] Ingredient contracts and management

[0996] 1. Collecting producer information

[0997] The terminal collects information from the producer and sends it to the server.

[0998] 2. Contract conclusion and management

[0999] The server enters into a contract with the producer and registers and manages that information in a database.

[1000] Preserving freshness with refrigeration technology

[1001] 1. Receiving and checking ingredients

[1002] The user (producer) sends ingredients to the distribution center.

[1003] 2. Application of refrigeration technology

[1004] The server uses refrigeration technology to set up the food to keep it fresh.

[1005] 3. Freshness monitoring

[1006] The terminal monitors the freshness of the food being kept refrigerated and sends the data to the server.

[1007] Logistics Optimization

[1008] 1. Calculating delivery routes

[1009] The server calculates the optimal delivery route based on data from the existing delivery system.

[1010] 2. Executing and tracking deliveries

[1011] The terminal receives a delivery schedule based on the calculation results and carries out the delivery.

[1012] Collecting customer feedback

[1013] 1. Distribution of the questionnaire

[1014] The server generates a QR code and prints the questionnaire on the lunch box packaging.

[1015] 2. Gathering Feedback

[1016] The user scans the QR code to answer the survey.

[1017] Emotion recognition by emotion engine

[1018] 1. Sentiment analysis of feedback

[1019] The feedback data collected by the server is analyzed by an emotion engine to recognize the user's emotions.

[1020] 2. Identifying areas for improvement

[1021] The server extracts areas for improvement in menus and services based on the results of sentiment analysis.

[1022] 3. Implementation of improvements

[1023] Based on the identified areas for improvement, the server plans and implements the next menu and service improvements.

[1024] Specific examples

[1025] Menu development with nutrition experts

[1026] Step 1:

[1027] The server registers the feedback of "high protein, low fat" from nutrition experts in a database. The experts input their feedback using a terminal, and the server stores it in the database.

[1028] Step 2:

[1029] The server compares the registered feedback with the company's nutritional database to search for matching ingredients and menu items.

[1030] Step 3:

[1031] The server generates a new recommended menu item, "High-protein, low-fat salad," based on the matching results and stores it in the database.

[1032] Ingredient contracts and management

[1033] Step 1:

[1034] The terminal collects information sent by the producer (for example, whether fresh tomatoes are available in summer) and transmits it to the server.

[1035] Step 2:

[1036] The server concludes a contract with the producer and registers this contract information in the management system.

[1037] Preserving freshness with refrigeration technology

[1038] Step 1:

[1039] A user (producer) sends fresh strawberries to a distribution center. The strawberries are scanned by a terminal and the information is sent to the server.

[1040] Step 2:

[1041] The server sets the optimum temperature and humidity based on the condition of the strawberries and sends this setting information to the cooling device.

[1042] Step 3:

[1043] The terminal periodically monitors the freshness of the strawberries and sends the information to the server, which then adjusts the cooling device to maintain the optimum environment.

[1044] Logistics Optimization

[1045] Step 1:

[1046] The server retrieves information from the existing delivery system, including past delivery data and current delivery status.

[1047] Step 2:

[1048] The server calculates the optimal delivery route based on past and current data and sends the results to the terminal.

[1049] Step 3:

[1050] The terminal receives delivery schedules and provides drivers with the optimal route in real time.

[1051] Collecting and analyzing customer feedback

[1052] Step 1:

[1053] The server generates a QR code and prints the questionnaire on the lunch box packaging.

[1054] Step 2:

[1055] Users scan the QR code and answer a questionnaire on their smartphone or PC, which includes a rating of their diet and suggestions for improvement.

[1056] Step 3:

[1057] The server stores the user feedback in a database for later analysis.

[1058] Emotion recognition and improvement with emotion engine

[1059] Step 1:

[1060] The server inputs the collected feedback data into an emotion engine and analyzes the user's emotions. For example, it recognizes the emotion of "dissatisfaction" from feedback such as "the flavor is bland."

[1061] Step 2:

[1062] The server extracts specific areas for improvement (e.g., "The seasoning needs to be improved") based on the results of sentiment analysis.

[1063] Step 3:

[1064] Based on the identified improvements, the server creates a plan to improve the next menu or service. This plan is shared with relevant experts and staff and reflected in actual improvements.

[1065] This system can efficiently provide nutritionally balanced, safe, and fresh meals and quickly reflect user feedback based on their emotions.

[1066] The processing flow will be explained below.

[1067] Menu development with nutrition experts

[1068] Step 1:

[1069] The server provides an interface for registering feedback from nutrition experts in the database, who input nutritional information and food recommendations via their terminals.

[1070] Step 2:

[1071] The device receives input from experts and sends it to a server, where feedback includes recommendations for specific nutritious ingredients and healthy recipes.

[1072] Step 3:

[1073] The server stores the received feedback in a database, which is used in subsequent processes.

[1074] Step 4:

[1075] The server then consults the nutrition database and matches it with expert feedback, specifically searching for data that matches the recommended ingredients and recipes.

[1076] Step 5:

[1077] The server generates new menu recommendations based on the matching results and stores them in the database. For example, a new menu item might be "high-protein, low-fat salad."

[1078] Ingredient contracts and management

[1079] Step 1:

[1080] The terminal collects information provided by producers (e.g., available ingredients, supply period) and transmits it to the server.

[1081] Step 2:

[1082] The server stores the received producer information in a database, including the types of ingredients each producer offers and the seasons in which they are available.

[1083] Step 3:

[1084] The server enters into a contract with a producer and registers the contract information in a database. For example, a contract may be made to supply fresh tomatoes in the summer.

[1085] Step 4:

[1086] The server monitors the status of contract fulfillment and manages whether ingredients are being supplied appropriately according to the supply schedule.

[1087] Preserving freshness with refrigeration technology

[1088] Step 1:

[1089] A user (producer) sends fresh produce (e.g., strawberries) to a distribution center. The produce is scanned at a terminal dedicated to receiving the produce.

[1090] Step 2:

[1091] The terminal scans the condition of the received ingredients (e.g., temperature, humidity) and sends the data to the server.

[1092] Step 3:

[1093] The server uses the scan data to determine optimal cooling settings, such as calculating the ideal temperature and humidity for storing strawberries.

[1094] Step 4:

[1095] The terminal receives instructions from the server and sets the refrigeration device, thereby keeping the food optimally fresh.

[1096] Step 5:

[1097] The terminal periodically monitors the freshness of the food in the refrigerator and sends the data to the server. If an abnormality is detected, an alert is sent immediately.

[1098] Logistics Optimization

[1099] Step 1:

[1100] The server receives data from existing delivery systems and delivery partners, including delivery times and past delivery routes.

[1101] Step 2:

[1102] The server calculates the optimal delivery route based on the received data, including real-time traffic information.

[1103] Step 3:

[1104] The server creates a delivery schedule based on the calculation results and sends it to the terminal. The delivery schedule includes detailed routes for each delivery.

[1105] Step 4:

[1106] The terminal receives delivery schedules and provides the optimal delivery route to the driver, who receives real-time instructions using the terminal.

[1107] Step 5:

[1108] The device uses GPS to track the location of the bento during delivery and sends this information in real time to a server, which continuously updates the delivery status.

[1109] Collecting and analyzing customer feedback

[1110] Step 1:

[1111] The server generates a QR code for the survey and prints it on the lunch box packaging, which contains a specific survey link.

[1112] Step 2:

[1113] Users scan the QR code and access the survey using their smartphone or PC, which includes fields for rating their diet and providing suggestions for improvement.

[1114] Step 3:

[1115] The server receives the survey data from users and stores it in a database, where the feedback is later analyzed by the emotion engine.

[1116] Emotion recognition and improvement with emotion engine

[1117] Step 1:

[1118] The server inputs the collected feedback data into an emotion engine and analyzes the user's emotions. For example, it recognizes the emotion of "dissatisfaction" from feedback such as "the flavor is bland."

[1119] Step 2:

[1120] The server extracts specific improvements based on the results of sentiment analysis, for example, determining that "the flavor needs to be improved."

[1121] Step 3:

[1122] Based on the identified improvements, the server creates an improvement plan for the next menu or service. The improvement plan is shared with relevant experts and staff and is reflected in actual improvements.

[1123] In this way, it is possible to efficiently provide nutritionally balanced, safe and fresh meals through each processing step, and to quickly reflect the user's emotional feedback.

[1124] Example 2

[1125] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1126] Modern eating habits demand the provision of nutritionally balanced, safe, and fresh meals. However, conventional systems have difficulty effectively incorporating feedback from nutrition experts into menus, and have issues with contract management of ingredients, maintaining freshness, efficient logistics, and insufficient collection and analysis of customer feedback. Furthermore, they lack a mechanism for improving products that reflect user sentiment. As a result, improvements in customer satisfaction and continuous product improvement have not been fully achieved.

[1127] 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.

[1128] In this invention, the server includes means for receiving feedback from nutrition experts and registering it in a database, means for comparing the expert feedback with the nutrition database to create recommended menus, means for contracting for ingredients provided by ingredient suppliers and managing the contract information, means for applying refrigeration technology to maintain the freshness of received ingredients, means for monitoring the status of ingredients while maintaining freshness using refrigeration technology and sending the data to the server, means for calculating the optimal delivery route in cooperation with an existing delivery system and executing and tracking delivery, means for collecting customer feedback via QR codes and analyzing the data to utilize for product improvement, and means for analyzing the collected feedback using an emotion engine, recognizing user emotions, and extracting areas for improvement. This enables the efficient provision of nutritionally balanced, safe, and fresh meals and rapid product improvement.

[1129] A "nutrition expert" refers to a person who has specialized knowledge about nutrition and whose job is to evaluate and provide guidance on the nutritional balance of meals.

[1130] "Feedback" refers to opinions and evaluations provided by users, experts, etc.

[1131] A "database" refers to a system that stores data and enables it to be efficiently managed and searched.

[1132] "Verification" refers to the act of comparing different information or data and checking whether they match.

[1133] "Recommended Menu" refers to meal suggestions made based on specific criteria or conditions.

[1134] "Food supplier" refers to a professional company that produces and supplies fresh food ingredients.

[1135] "Agreement" means any legally recognized document or process of agreement.

[1136] "Cold storage technology" refers to the technology and equipment used to maintain a low temperature environment.

[1137] "Monitoring" refers to the act of continuously watching over and checking the status.

[1138] A "delivery system" refers to a system or network for efficiently transporting goods.

[1139] "Delivery route" refers to the optimal route connecting delivery destinations.

[1140] A "QR code" is a type of two-dimensional barcode that allows information to be easily read.

[1141] "Customer feedback" refers to opinions and evaluations provided by customers regarding products and services.

[1142] "Data analysis" refers to the process of analyzing collected data and finding meaning and patterns.

[1143] "Product improvement" refers to improving the quality of products and services in order to increase customer satisfaction.

[1144] An "emotion engine" refers to a system that uses natural language processing technology to analyze emotions from text data.

[1145] "User emotions" refers to the impressions and feelings that users have about a product or service.

[1146] "Improvements" refers to changes or corrections that are needed to improve the current situation.

[1147] The present invention is an integrated system that efficiently provides nutritionally balanced meals and can quickly reflect customer feedback in improving products. This system is mainly composed of a server, terminals, and users.

[1148] The server performs the following functions: It provides an interface for nutrition experts to input their feedback into the database. Experts use a browser to input their feedback, which is then sent to the server and stored in the database. It also compares the feedback with the existing nutrition database to generate recommended menus. These menus are then stored in the database along with a list of ingredients and their nutritional information.

[1149] The server then concludes contracts with producers based on information provided by food suppliers and registers the contract information in the management system. After receiving the ingredients, it uses refrigeration technology to set the appropriate temperature and humidity, adjusting the environment to maintain freshness. It also optimizes logistics and calculates the optimal delivery route based on past and current delivery data.

[1150] Meanwhile, the terminal is responsible for collecting information from producers and sending it to the server. For example, if a producer can supply fresh tomatoes, the information is entered into the terminal and sent to the server. When receiving ingredients, the terminal is used to scan the ingredients and the information is sent to the server. When applying refrigeration technology, the terminal also monitors the freshness of the ingredients and continuously sends this data to the server. This allows the refrigeration device to maintain an optimal environment.

[1151] Users scan the QR code using their smartphone and answer the questionnaire. The feedback is sent to the server and stored in a database. The server inputs this feedback data into an emotion engine and uses natural language processing technology to analyze the user's emotions. For example, feedback such as "the flavor is bland" can be recognized as an emotion of "dissatisfaction." Based on the analysis results, specific areas for improvement are extracted and reflected in the next menu or service.

[1152] Specific examples

[1153] Menu development with nutrition experts

[1154] The server registers the feedback of "high protein, low fat" from nutrition experts in a database. The experts input their feedback using a terminal, and the server stores it in the database.

[1155] The server compares the registered feedback with the company's nutritional database to search for matching ingredients and menu items.

[1156] The server generates a new recommended menu item, "High-protein, low-fat salad," based on the matching results and stores it in the database.

[1157] Ingredient contracts and management

[1158] The terminal collects information sent by the producer (for example, whether fresh tomatoes are available in summer) and transmits it to the server.

[1159] The server concludes a contract with the producer and registers this contract information in the management system.

[1160] Preserving freshness with refrigeration technology

[1161] A user (producer) sends fresh strawberries to a distribution center. The strawberries are scanned by a terminal and the information is sent to the server.

[1162] The server sets the optimum temperature and humidity based on the condition of the strawberries and sends this setting information to the cooling device.

[1163] The terminal periodically monitors the freshness of the strawberries and sends the information to the server, which then adjusts the cooling device to maintain the optimal environment.

[1164] Logistics Optimization

[1165] The server retrieves information from the existing delivery system, including past delivery data and current delivery status.

[1166] The server calculates the optimal delivery route based on past and current data and sends the results to the terminal.

[1167] The terminal receives delivery schedules and provides drivers with the optimal route in real time.

[1168] Collecting and analyzing customer feedback

[1169] The server generates a QR code and prints the questionnaire on the lunch box packaging.

[1170] Users scan the QR code and answer a questionnaire on their smartphone or PC, which includes a rating of their diet and suggestions for improvement.

[1171] The server stores the user feedback in a database for later analysis.

[1172] Emotion recognition and improvement with emotion engine

[1173] The server inputs the collected feedback data into an emotion engine and analyzes the user's emotions. For example, it recognizes the emotion of "dissatisfaction" from feedback such as "the flavor is bland."

[1174] The server extracts specific areas for improvement (e.g., "The seasoning needs to be improved") based on the results of sentiment analysis.

[1175] Based on the identified improvements, the server creates a plan to improve the next menu or service. This plan is shared with relevant experts and staff and reflected in actual improvements.

[1176] This system can efficiently provide nutritionally balanced, safe, and fresh meals and quickly reflect user feedback based on their emotions.

[1177] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1178] Menu development with nutrition experts

[1179] Step 1:

[1180] The server collects feedback from nutrition experts, who input feedback such as "high-protein, low-fat menus are recommended" using a terminal, which is then sent to the server's database.

[1181] Input: Expert feedback

[1182] Output: Feedback data stored in a database

[1183] Step 2:

[1184] The server compares the feedback stored in the database with a nutrition database using a pre-defined algorithm.

[1185] Input: Expert feedback, nutrition database

[1186] Output: Matching result

[1187] Step 3:

[1188] The server generates new menu recommendations based on the match, including specific ingredient lists and nutritional information.

[1189] Input: Matching result

[1190] Output: Menu recommendations, new cooking recipes

[1191] Ingredient contracts and management

[1192] Step 1:

[1193] The terminal collects information from producers and sends it to the server, for example, by inputting detailed information about available ingredients and when they will be available.

[1194] Input: Supply information from producers

[1195] Output: The feed sent to the server

[1196] Step 2:

[1197] The server generates a contract based on the collected producer information and concludes the contract using an electronic signature system. The contract details are then registered in the management system.

[1198] Input: Supply information from producers

[1199] Output: Registered contract information

[1200] Preserving freshness with refrigeration technology

[1201] Step 1:

[1202] The user (producer) sends fresh ingredients to the distribution center. The received ingredients are scanned by a terminal and the information is sent to the server.

[1203] Input: Ingredients sent

[1204] Output: Scanned food data

[1205] Step 2:

[1206] The server calculates the optimal cooling settings based on the scanned food data and sends the setting information to the cooling device.

[1207] Input: scanned food data

[1208] Output: Cooling setting information

[1209] Step 3:

[1210] The terminal periodically collects data from the refrigerator to monitor the freshness of the ingredients. This data is then sent to a server, which then appropriately manages the environment to maintain freshness.

[1211] Input: Data from refrigeration equipment

[1212] Output: Monitoring data

[1213] Logistics Optimization

[1214] Step 1:

[1215] The server acquires existing delivery system data and calculates the optimal delivery route based on past and current delivery status.

[1216] Input: Existing delivery system data

[1217] Output: Optimal delivery route information

[1218] Step 2:

[1219] The terminal provides the driver with optimal delivery route information and real-time route instructions, while simultaneously transmitting delivery status information to the server.

[1220] Input: Optimal delivery route information

[1221] Output: Real-time delivery instructions, location data

[1222] Collecting and analyzing customer feedback

[1223] Step 1:

[1224] The server generates a QR code and prints it on the lunch box package, which contains a link to the survey form.

[1225] Input: QR code generation information

[1226] Output: QR code printed on the bento package

[1227] Step 2:

[1228] Users scan the QR code with their smartphone to access the survey form and submit their answers.

[1229] Input: Customer feedback

[1230] Output: Survey data saved on the server

[1231] Emotion recognition and improvement with emotion engine

[1232] Step 1:

[1233] The server inputs the collected feedback data into an emotion engine, which then analyzes the user's emotions using natural language processing technology.

[1234] Input: Customer feedback data

[1235] Output: Emotion analysis results

[1236] Step 2:

[1237] The server extracts specific areas for improvement based on the results of sentiment analysis. For example, from feedback that the food tastes bland, it identifies the need to improve the seasoning.

[1238] Input: Sentiment analysis results

[1239] Output: Extracted improvements

[1240] Step 3:

[1241] The server will then create a plan to improve the next menu or service based on the identified improvements, and share this plan with experts and staff. This plan will be reflected in future product offerings.

[1242] Input: Improvements

[1243] Output: Improvement plan

[1244] In this way, the system can quickly reflect user feedback and efficiently provide nutritionally balanced, safe, and fresh meals.

[1245] (Application example 2)

[1246] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1247] In recent years, consumers have become increasingly health-conscious, leading to an increased demand for nutritionally balanced meals and fresh ingredients. However, previous systems made it difficult to effectively incorporate feedback from nutrition experts, and were inadequate in maintaining the freshness of ingredients and in quickly collecting and analyzing customer feedback. Furthermore, there was a lack of efficient methods for optimizing logistics and managing the freshness of ingredients. This made it difficult to provide high-quality meals that met the needs of individual customers. Furthermore, there was a lack of sufficient efforts to improve service based on customer sentiment. As a result, there were problems with reduced satisfaction and lost opportunities.

[1248] 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 means for receiving feedback from nutrition experts and creating menus, means for contracting for seasonal ingredients from ingredient suppliers and managing their safety and quality, means for applying the latest refrigeration technology to maintain the freshness of received ingredients, means for optimizing delivery routes in cooperation with existing home delivery systems, means for collecting customer feedback via QR codes and reflecting it in product improvements, means for collecting customer feedback using QR codes, analyzing it with a sentiment analysis engine, and reflecting it in service improvements, and means for optimizing logistics and monitoring freshness using smart devices. This not only enables efficient and high-quality meal provision, but also enables rapid service improvements based on customer sentiment, thereby improving customer satisfaction.

[1249] A "nutrition expert" is a professional with knowledge and experience regarding the nutritional balance and health of meals, who provides feedback on menu creation and ingredient selection.

[1250] "Feedback" refers to opinions, evaluations, and suggestions for improvement provided by users and experts regarding systems and services, and is information that is used to improve quality and efficiency.

[1251] A "menu" is a list of meals that take into account a specific purpose and nutritional balance, and is a meal plan created with feedback from nutrition experts.

[1252] A "food supplier" is a business that produces or sells food ingredients and provides seasonal ingredients through contracts, and is required to manage safety and quality.

[1253] "Contract" means an agreement between a food supplier and a service provider under which food is promised to be provided for a specified period and under specified conditions.

[1254] "Cold storage technology" is a technique used to maintain the freshness of received ingredients for a long period of time, and includes temperature control and humidity control.

[1255] "Existing delivery system" refers to a logistics system that is already in operation to efficiently deliver ingredients and products to customers.

[1256] A "delivery route" is the route a product takes from its departure point to its destination, and optimizing it improves delivery efficiency and reduces time and costs.

[1257] A QR code is a type of two-dimensional barcode that can be scanned to access information or collect feedback.

[1258] An "emotion analysis engine" is a computer system that analyzes collected feedback data and automatically recognizes users' emotions and satisfaction levels.

[1259] A "smart device" is an electronic device that has Internet connectivity and can send, receive, and process various types of information, including smartphones and tablets.

[1260] "Logistics optimization" is the process of optimizing delivery routes, times, and resources for the efficient transportation of goods.

[1261] "Freshness monitoring" is the process of using refrigeration technology to monitor the freshness of ingredients in real time and collect freshness information.

[1262] "Service improvement" refers to ongoing activities to improve the quality and efficiency of the services we provide based on collected feedback and analytical results.

[1263] This invention is a system that integrates menu development based on feedback from nutrition experts, seasonal ingredient contracts, safety and quality control, preserving the freshness of ingredients using the latest refrigeration technology, optimizing delivery routes by linking with existing delivery systems, collecting customer feedback using QR codes, and improving services using a sentiment analysis engine.

[1264] Menu development with nutrition experts

[1265] The server receives feedback from nutrition experts and registers the feedback in a database. The server then compares it with the company's nutrition database and generates recommended menu items based on the expert's feedback. For example, if the server receives feedback such as "high protein, low fat," it can generate a recommended menu item: "high protein, low fat salad."

[1266] Ingredient contracts and management

[1267] The terminal collects information provided by producers and sends it to the server. The server then uses this information to conclude contracts with food suppliers and registers the contract information in a system that manages such information. For example, the server may collect information from a producer that "fresh tomatoes are available" and conclude a supply contract based on this information.

[1268] Preserving freshness with refrigeration technology

[1269] Food suppliers use the latest refrigeration technology to maintain freshness. The server sets the optimal temperature and humidity based on the condition of the food and sends this setting information to the refrigeration device. The terminal periodically monitors the freshness of the food and sends the information to the server. For example, to maintain the freshness of fresh strawberries, the refrigeration device can be set to the optimal environment.

[1270] Logistics Optimization

[1271] The server acquires information from existing delivery systems and calculates the optimal delivery route based on past delivery data and current delivery status. The terminal receives the delivery schedule based on the calculation results and provides the driver with the optimal route in real time. For example, the most efficient delivery route can be calculated based on past delivery data.

[1272] Customer feedback collection and sentiment analysis

[1273] The server generates a QR code and prints a questionnaire on the lunch box packaging. The user scans this QR code with their smartphone and answers the questionnaire. The server then analyzes the collected feedback using a sentiment analysis engine to recognize the user's emotions. Based on this, the server identifies areas for improvement in the service and creates plans to improve the next menu or service. For example, in response to feedback that the flavor is "bland," the server can identify specific areas for improvement such as "the seasoning needs to be improved."

[1274] Examples of concrete examples and prompts

[1275] Specific examples include developing a "high-protein, low-fat salad" menu, signing a contract to supply fresh tomatoes, setting up an optimal refrigeration environment, calculating delivery routes, collecting feedback using QR codes, and analyzing emotions such as "the taste is bland" to "dissatisfied."

[1276] An example prompt might be, "Please provide the code that will help us analyze user feedback, analyze it with our sentiment engine, and improve our menu next time."

[1277] The above-mentioned system not only enables efficient and high-quality food service, but also allows for quick service improvements based on customer sentiment, thereby increasing customer satisfaction.

[1278] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1279] Step 1:

[1280] The server receives feedback from nutrition experts and registers it in a database. First, the server provides a feedback input interface to the experts, who then use their terminals to input specific feedback such as "high protein, low fat." This input is sent to the server and stored in the database.

[1281] Input: Expert feedback (e.g., "high protein, low fat")

[1282] Data processing / calculation: Feedback content is registered in the database

[1283] Output: Feedback is saved in a database

[1284] Step 2:

[1285] The server compares the feedback with the company's nutrition database and creates menu recommendations based on the feedback. For example, based on the feedback "high protein, low fat," the server searches for matching ingredients and cooking methods, generating a new menu item such as "high protein, low fat salad."

[1286] Input: Nutrition expert feedback data

[1287] Data processing / calculation: Matching feedback with nutritional database, generating new menu items

[1288] Output: Recommended menu (e.g. "High protein, low fat salad")

[1289] Step 3:

[1290] The terminal collects information about ingredients provided by producers and sends it to the server. For example, a producer inputs into the terminal that they can supply fresh tomatoes, and the information is sent to the server.

[1291] Input: Ingredient information from producers (e.g., "Fresh tomatoes available")

[1292] Data processing / calculation: Sending ingredient information to the server

[1293] Output: Ingredient information is saved on the server

[1294] Step 4:

[1295] The server concludes contracts with food suppliers and registers the contract information in the management system. For example, the server digitizes contracts with producers and registers them in the management system.

[1296] Input: Contract information with food suppliers

[1297] Data processing / calculation: Digitization and registration of contract information

[1298] Output: Contract information is saved in the management system

[1299] Step 5:

[1300] The server sets the optimal temperature and humidity based on the condition of the ingredients and sends this setting information to the refrigeration device. For example, to maintain the freshness of produced strawberries, the server calculates the optimal refrigeration environment (temperature and humidity) and sets it in the device.

[1301] Input: Freshness of ingredients

[1302] Data processing / calculation: Calculation of cooling settings based on freshness status

[1303] Output: Configuration information sent to the refrigerator

[1304] Step 6:

[1305] The device periodically monitors the freshness of the ingredients and sends the information to the server. For example, a sensor in the refrigerator collects freshness data, and the device then forwards the data to the server.

[1306] Input: Freshness data from the refrigerator sensor

[1307] Data processing / calculation: Monitoring and transferring freshness data

[1308] Output: Freshness information sent to the server

[1309] Step 7:

[1310] The server obtains information from existing delivery systems and optimizes delivery routes. Based on past delivery data and current delivery status, the server calculates the optimal delivery route and sends the results to the terminal.

[1311] Input: Data from existing delivery system

[1312] Data processing / calculation: Calculating the optimal delivery route

[1313] Output: The optimal route information is sent to the device.

[1314] Step 8:

[1315] The device generates a QR code and prints the questionnaire on the lunch box package. The user scans the QR code with their smartphone and answers the questionnaire.

[1316] Input: QR code generation request

[1317] Data processing / calculation: QR code generation

[1318] Output: Survey with QR code printed

[1319] Step 9:

[1320] The server analyzes the collected feedback using a sentiment analysis engine to recognize the user's emotions. Feedback such as "the flavor is bland" is recognized as "dissatisfied," and the server identifies areas for improvement in the next menu or service.

[1321] Input: Feedback data

[1322] Data processing / calculation: Sentiment analysis, extraction of areas for improvement

[1323] Output: Next menu or service with improvements reflected

[1324] The above processing steps enable a smooth process of collecting feedback provided by users in real time and using the emotion engine to reflect it in improving the next menu or service.

[1325] 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.

[1326] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1327] 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.

[1328] [Third embodiment]

[1329] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1330] 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.

[1331] 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).

[1332] 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.

[1333] 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.

[1334] 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).

[1335] 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. 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.

[1336] 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.

[1337] 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.

[1338] 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.

[1339] 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.

[1340] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1341] The present invention is a system that includes menu development based on feedback from nutrition experts, safety and quality control of ingredients based on contracts with producers, freshness maintenance using the latest refrigeration technology, logistics optimization through integration with existing bento delivery systems, and a process for collecting customer feedback and improving products using QR codes.

[1342] Program processing explanation

[1343] Menu development with nutrition experts

[1344] 1. Gathering feedback

[1345] The server stores the feedback from the nutrition experts in a database.

[1346] The terminal inputs feedback through the nutrition expert interface and transmits it to the server.

[1347] 2. Comparison with nutritional data

[1348] The server compares the stored feedback with an in-house nutrition database.

[1349] The server searches for matching ingredients and menu items.

[1350] 3. Creating a recommended menu

[1351] The server creates and stores new recommended menus based on the results of comparison with the nutrition database.

[1352] Ingredient contracts and management

[1353] 1. Collecting producer information

[1354] The terminal collects information from the producer and transmits it to the server.

[1355] 2. Contract conclusion and management

[1356] The server concludes a contract with the producer and registers the contract information in the management system.

[1357] Preserving freshness with refrigeration technology

[1358] 1. Receiving and checking ingredients

[1359] The user (producer) sends ingredients to the distribution center.

[1360] The terminal checks the freshness of the received ingredients and sends the information to the server.

[1361] 2. Application of refrigeration technology

[1362] The server connects the food ingredient data to the refrigeration equipment and applies the optimal refrigeration technology.

[1363] 3. Freshness monitoring

[1364] The terminal periodically monitors the freshness of the food items being kept refrigerated and sends this information to the server.

[1365] Logistics Optimization

[1366] 1. Calculating delivery routes

[1367] The server calculates the optimal delivery route based on data from the existing delivery system.

[1368] 2. Create a delivery schedule

[1369] The server creates a delivery schedule based on the calculated delivery route and transmits it to the terminal.

[1370] 3. Track your delivery

[1371] The device uses GPS to track the current location of the lunch box during delivery and transmits that information to the server in real time.

[1372] Collecting and analyzing customer feedback

[1373] 1. Distribution of the questionnaire

[1374] The server generates a QR code for the survey and prints it on the lunch box packaging.

[1375] 2. Gathering Feedback

[1376] Users scan the QR code to answer the survey.

[1377] The server stores the user's feedback in a database.

[1378] 3. Analyzing feedback and identifying areas for improvement

[1379] The server analyzes the collected feedback and extracts low-rated items and areas for improvement.

[1380] Specific examples

[1381] As a specific example, the following series of processes can be considered.

[1382] 1. Nutrition experts propose new menu items based on the theme of "high protein, low fat." The server registers this feedback in a database and compares it with the nutrition database to create recommended menu items.

[1383] 2. A local farmer signs a contract to provide fresh tomatoes during the summer season. The terminal sends this contract information to the server and registers it in the management system.

[1384] 3. Strawberries received at the distribution center are stored in the latest refrigeration equipment and temperature controlled to maintain freshness. The terminal monitors the freshness of the strawberries and periodically reports this to the server.

[1385] 4. The server uses an optimization algorithm to calculate the fastest delivery route and create a delivery schedule. The device tracks the location of the bento box in real time during delivery and sends it to the server.

[1386] 5. The user scans the QR code and sends feedback that the food tastes bland. The server analyzes this feedback and reflects it in improving the menu for the next time.

[1387] This system makes it possible to efficiently provide nutritionally balanced, safe, and fresh meals.

[1388] The processing flow will be explained below.

[1389] Menu development with nutrition experts

[1390] Step 1:

[1391] The server provides an interface for storing feedback from nutrition experts in a database, and the experts input their feedback through terminals.

[1392] Step 2:

[1393] The device receives expert feedback and sends it to a server, which includes specific nutritional information and areas for improvement.

[1394] Step 3:

[1395] The server registers the expert's feedback in a database, which is used to match the feedback with the nutrition database.

[1396] Step 4:

[1397] The server will refer to the nutrition database and compare it with the registered feedback, searching for matching ingredients and menu items.

[1398] Step 5:

[1399] The server generates a new recommended menu based on the matching results and stores it in a database.

[1400] Ingredient contracts and management

[1401] Step 1:

[1402] The terminal collects information from producers (for example, information on available ingredients and seasonal information) and sends it to the server.

[1403] Step 2:

[1404] The server registers the information sent from the producers in a database, including the type of food and the supply period.

[1405] Step 3:

[1406] The server performs the procedure to conclude a contract with the producer, confirms the contract details, and saves them in the database.

[1407] Step 4:

[1408] The server monitors the status of contract fulfillment and displays the seasonal food supply status on the management system.

[1409] Preserving freshness with refrigeration technology

[1410] Step 1:

[1411] The user (producer) sends ingredients to the distribution center, where they are scanned at a receiving terminal.

[1412] Step 2:

[1413] The terminal scans the received ingredients to determine their condition (e.g., temperature, humidity) and sends the data to the server.

[1414] Step 3:

[1415] The server receives the food ingredient data and starts communicating with the refrigeration equipment, determining the optimal refrigeration technology (temperature and humidity settings).

[1416] Step 4:

[1417] The terminal receives instructions from the server and sets the cooling device appropriately, creating an environment that keeps food fresh.

[1418] Step 5:

[1419] The terminal periodically monitors the freshness of the food in the refrigerator and sends the status to the server, issuing an alert if there is an abnormality.

[1420] Logistics Optimization

[1421] Step 1:

[1422] The server receives data from existing delivery systems and delivery partners, including current delivery status and past delivery data.

[1423] Step 2:

[1424] Based on the data received by the server, an optimization algorithm is used to calculate the optimal delivery route.

[1425] Step 3:

[1426] The server creates a delivery schedule based on the calculation results and sends it to the terminal.

[1427] Step 4:

[1428] The terminal receives delivery schedules and assists in executing deliveries, while the driver uses the terminal to check route information in real time.

[1429] Step 5:

[1430] The device uses GPS to track the current location of the bento and ingredients being delivered and sends that data to a server, which updates the delivery status in real time.

[1431] Collecting and analyzing customer feedback

[1432] Step 1:

[1433] The server generates a QR code for the survey and prints it on the lunch box packaging, which contains a specific survey link.

[1434] Step 2:

[1435] Users scan the QR code to access the survey on their smartphone or PC, which includes a field to rate the diet and provide suggestions for improvement.

[1436] Step 3:

[1437] The server receives the survey data from users and stores it in a database, where the feedback is later analyzed.

[1438] Step 4:

[1439] The server analyzes the collected feedback data and extracts low-rated items and specific areas for improvement.

[1440] Step 5:

[1441] Based on the identified improvements, the server creates a plan to improve the next menu or service. The plan is shared with experts and staff.

[1442] In this way, a system is realized that efficiently provides nutritionally balanced, safe, and fresh meals through each processing step.

[1443] Example 1

[1444] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1445] In recent years, growing health consciousness has led to an increasing demand for systems that efficiently provide nutritionally balanced meals. However, conventional systems have not been able to fully incorporate feedback from nutrition experts, resulting in insufficient optimization of ingredient freshness management and logistics. Furthermore, there is a lack of means to efficiently collect and incorporate customer feedback. Furthermore, automating contract management with ingredient suppliers and freshness monitoring has also been an issue. There is a need to solve these issues.

[1446] 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.

[1447] In this invention, the server includes a means for receiving feedback from nutrition experts and creating menus, a means for comparing the feedback with a nutrition database, and a means for applying the latest refrigeration technology to maintain the freshness of the received ingredients, thereby enabling the proposal of nutritionally balanced menus, the management of the freshness of ingredients, the optimization of logistics, and the collection and analysis of customer feedback.

[1448] A "nutritionist" is a professional with specialized knowledge of nutrition who optimizes the nutritional balance of meals and designs menus tailored to specific health goals.

[1449] "Feedback" refers to opinions and evaluation information provided by nutrition experts and customers, based on which the system and menus are improved.

[1450] "Menu" refers to a list of meals or dishes, including ingredients and cooking methods, organized around a particular theme or with nutritional balance in mind.

[1451] "Food suppliers" refers to producers and businesses that provide seasonal food ingredients and are subject to safety and quality control.

[1452] "Contract" means a formal agreement between a food supplier and a system operator that provides for the supply of food of a specified quality and quantity within a specified period of time.

[1453] "Cold storage technology" is a technique for maintaining a low temperature environment and is a means used to keep food ingredients fresh for a long period of time.

[1454] "Delivery system" refers to the infrastructure and procedures for delivering goods, and is the existing delivery network used to streamline logistics.

[1455] A "QR code" is a type of two-dimensional barcode that can be read with a camera on a smartphone or other device to quickly access information.

[1456] "Customer feedback" refers to the opinions and evaluations that customers submit about services and products, and is valuable data for product improvement.

[1457] A "nutrition database" is a database that stores detailed information on the nutritional components contained in various ingredients and dishes, and is used to optimize nutritional balance.

[1458] "Freshness monitoring" refers to the process of regularly monitoring the quality status of food ingredients (e.g., color, temperature, humidity, etc.) and sending that information to a server for analysis.

[1459] "Delivery route" refers to the route along which goods are transported to their destination, and is optimized for efficient delivery.

[1460] "Smartphone" is an abbreviation for smartphone, a type of mobile phone equipped with GPS functionality and internet connectivity.

[1461] "Real-time tracking" refers to the ability to check the current location of an object in real time, especially for goods being delivered.

[1462] The present invention is a system that includes menu development based on feedback from nutrition experts, safety and quality control of ingredients based on contracts with producers, freshness maintenance using the latest refrigeration technology, logistics optimization through integration with existing home delivery systems, and a process for collecting customer feedback and improving products using QR codes.

[1463] Menu development with nutrition experts

[1464] The server stores the feedback from nutrition experts in a database. Feedback is provided as a URL, document file, or XML feed, and the server automatically analyzes and registers it in the database. The terminal provides an administration screen for nutrition experts, where they can enter their feedback using text boxes and check boxes. The entered information is sent to the server via an HTTP request.

[1465] The server then matches the feedback stored in the database with a nutrition database (e.g., MySQL) and uses a keyword search algorithm to find matching ingredients and menu items. The matched data is statistically analyzed using Python or R to generate new menu recommendations. This menu is then stored again in the database and formatted for screen output.

[1466] A specific example includes a process in which a nutritionist submits feedback on the theme "high protein, low fat" via an administration screen, and the server generates a recommended menu item, "chicken breast salad," based on this information.

[1467] Ingredient contracts and management

[1468] The terminal provides a dedicated web form for collecting information from producers. This form is an interface for entering information such as the farmer's name, location, and list of ingredients they can provide. This information is sent from the terminal to the server via an HTTP request and automatically registered in a database.

[1469] The server registers contract information with producers (contract start date, end date, supply volume, etc.) in the management system. The contract is saved as a PDF, and various conditions are stored in the database in JSON format.

[1470] A specific example involves a process in which a local farmer enters a contract to "provide fresh tomatoes during the summer season" through a web form, and the server registers the information in a database.

[1471] Preserving freshness with refrigeration technology

[1472] The user (producer) sends the harvested ingredients to the distribution center. The terminal provides a smartphone app to check the freshness of the ingredients received at the distribution center. The app checks color, aroma, temperature, etc., and sends the results digitally to the server.

[1473] The server can determine the optimal refrigeration method (temperature, humidity, etc.) based on the received food information and issue instructions to the refrigeration device. The terminal also periodically monitors the freshness of the food using cameras and sensors in the refrigeration device and sends this data to the server.

[1474] A specific example is a process that measures the color and temperature of strawberries received at a distribution center and allows the server to set the optimal refrigeration temperature. Sensors in the refrigeration equipment monitor freshness and periodically send data to the server.

[1475] Logistics Optimization

[1476] The server acquires data from existing delivery systems and calculates optimal delivery routes using the Google Maps API and a proprietary optimization algorithm. It automatically generates a delivery schedule based on the route information and sends the results to the device. The delivery schedule includes estimated delivery times and orders.

[1477] The device uses the GPS function installed on the delivery driver's smartphone to track the current location of the bento boxes being delivered in real time and transmits this information to a server at regular intervals.

[1478] For example, the server uses the Google Maps API to calculate the optimal route, generate a delivery schedule, and send it to the driver's smartphone. The device periodically uploads GPS information to the server, allowing the driver to check the delivery status in real time.

[1479] Collecting and analyzing customer feedback

[1480] The server generates a QR code for customer feedback and prints it on the lunch box package label. Users scan the QR code with their smartphone to access the survey form and enter their opinions. The server saves the entered feedback data in a database in real time.

[1481] The server analyzes the collected feedback data using machine learning algorithms in Python and R to identify low-rated items and areas for improvement. The analysis results are visualized on a management screen and reflected in menu development and logistics management.

[1482] A specific example includes a process where a user scans a QR code and sends feedback such as "the flavor is bland," which the server analyzes and reflects in the next menu revision, adjusting the "optimal amount of seasoning."

[1483] Example prompt sentence:

[1484] "I would like to create a new, nutritionally balanced menu. Please suggest recipes that use high-protein, low-fat ingredients."

[1485] Thus, the system of the present invention comprehensively covers all the steps required to efficiently provide nutritionally balanced, safe and fresh meals.

[1486] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1487] Program processing flow

[1488] Step 1: Gather expert feedback

[1489] explanation:

[1490] The device provides a dedicated management screen for receiving feedback from nutrition experts. The management screen has text boxes and check boxes where experts can enter their opinions and suggestions. The entered data is sent to the server via an HTTP request. The server stores the received data in a database.

[1491] input:

[1492] Nutrition expert feedback (text and multiple choice answers)

[1493] output:

[1494] Feedback information stored in a database

[1495] Specific behavior:

[1496] When an expert enters feedback such as "high protein, low fat" into the management screen and presses the send button, the data is sent to the server.

[1497] Step 2: Check against nutritional data

[1498] explanation:

[1499] The server retrieves the feedback stored in the database and compares it with the company's internal nutrition database. Specifically, it performs text analysis of the feedback and searches for related ingredients and menu items using keyword searches. The search results are temporarily stored.

[1500] input:

[1501] Feedback information stored in a database

[1502] output:

[1503] Matched ingredients and menu list

[1504] Specific behavior:

[1505] Based on the keywords "high protein, low fat," the server checks a nutritional database to extract information on ingredients such as "chicken breast" and "lean fish."

[1506] Step 3: Create a recommended menu

[1507] explanation:

[1508] The server generates new recommended menus based on the matching results. Using Python and R, the menus are constructed to meet nutritional balance and calorie constraints. The generated menus are saved in a database and can be viewed on the management screen.

[1509] input:

[1510] Matched ingredients and menu list

[1511] output:

[1512] Recommendations stored in a database

[1513] Specific behavior:

[1514] The server generates a menu list including "chicken breast salad" and stores it in a database.

[1515] Step 4: Collecting producer information and managing contracts

[1516] explanation:

[1517] The terminal provides an interface where producers can enter information through a dedicated web form, including, for example, the farmer's name, location, and available ingredients list. The entered information is sent via an HTTP request to the server, which then registers it in a database.

[1518] input:

[1519] Information from producer (name, location, list of ingredients)

[1520] output:

[1521] Producer information and contract information registered in the database

[1522] Specific behavior:

[1523] Producers enter information such as "providing fresh tomatoes during the summer season" into a web form, and the server registers the information in a database.

[1524] Step 5: Receive ingredients and check freshness

[1525] explanation:

[1526] The user (producer) sends the harvested ingredients to the distribution center. The terminal provides an interface for checking the freshness of the ingredients that arrive at the center using a smartphone app. Check items include color, aroma, temperature, etc. The terminal then digitally transmits the results to the server.

[1527] input:

[1528] Freshness information for ingredients received at the distribution center

[1529] output:

[1530] Freshness data sent to the server

[1531] Specific behavior:

[1532] At the distribution center, users measure the color and temperature of strawberries using a smartphone app and send the data to the server.

[1533] Step 6: Applying cooling technology

[1534] explanation:

[1535] The server determines the optimal refrigeration method based on the received food information, sets temperature and humidity conditions, and issues instructions to the refrigeration device. It also monitors sensors to maintain freshness under the set environment, and continuously sends this data to the server.

[1536] input:

[1537] Freshness data and ingredient information

[1538] output:

[1539] Setting data that gives instructions to the cooling device

[1540] Specific behavior:

[1541] The server sets the temperature and humidity conditions for the strawberries and instructs the refrigeration device to "store them at the preset temperature."

[1542] Step 7: Optimize delivery routes

[1543] explanation:

[1544] The server acquires data from existing delivery systems and calculates optimal delivery routes using the Google Maps API and proprietary algorithms. Based on the results of the calculations, it automatically generates a delivery schedule and sends the results to the device.

[1545] input:

[1546] Delivery system data and customer delivery information

[1547] output:

[1548] Optimal delivery routes and schedules

[1549] Specific behavior:

[1550] The server uses the Google Maps API to calculate the "fastest route," generate a schedule, and send it to the driver's smartphone.

[1551] Step 8: Track your shipment

[1552] explanation:

[1553] The device uses the GPS function installed on the delivery driver's smartphone to periodically track the current location of the lunch box during delivery. The location information is sent to a server at regular intervals and displayed in real time on the management screen.

[1554] input:

[1555] GPS location information from the driver's smartphone

[1556] output:

[1557] Real-time location tracking data

[1558] Specific behavior:

[1559] The device acquires the location information of the lunch box being delivered and periodically uploads it to the server, allowing delivery status to be checked in real time.

[1560] Step 9: Collect and analyze customer feedback

[1561] explanation:

[1562] The server generates a QR code for customer feedback and prints it on the lunch box package label. The customer scans the QR code with their smartphone, accesses the survey form, and enters their feedback. The entered data is saved on the server in real time.

[1563] input:

[1564] Customer feedback (survey responses)

[1565] output:

[1566] Feedback data stored on the server

[1567] Specific behavior:

[1568] The user scans the QR code printed on the bento box and sends feedback such as "the taste is bland," which the server then stores in a database.

[1569] Step 10: Analyze feedback and identify areas for improvement

[1570] explanation:

[1571] The server analyzes the collected feedback data using machine learning algorithms in Python and R to identify low-rated items and areas for improvement. The analysis results are visualized on a management screen and reflected in the next menu development and logistics management.

[1572] input:

[1573] Collected customer feedback data

[1574] output:

[1575] Analysis results and list of improvements

[1576] Specific behavior:

[1577] The server will analyze the feedback that the food is "bland" and implement a process to reflect the "optimal amount of seasoning" in the next menu.

[1578] In this way, each step works together to create a system that efficiently provides nutritionally balanced, safe, and fresh meals.

[1579] (Application example 1)

[1580] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1581] Providing nutritionally balanced meals and delivering them efficiently is an important issue in modern society. However, currently, menu development that appropriately reflects expert feedback, managing the safety and quality of ingredients, applying refrigeration technology to ensure fast delivery and freshness, and even collecting customer feedback and improving products are all fragmented at each stage, resulting in insufficient coordination as a comprehensive system. Furthermore, achieving efficient food delivery using smartphones and other devices remains a challenge.

[1582] 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.

[1583] In this invention, the server includes means for receiving feedback from nutrition experts and creating menus, means for contracting seasonal ingredients from ingredient suppliers and managing their safety and quality, means for applying the latest refrigeration technology to maintain the freshness of received ingredients, means for optimizing delivery routes in cooperation with existing home delivery systems, means for collecting customer feedback via QR codes and reflecting it in product improvements, and means for installing a food delivery application on smartphones to provide nutritionally balanced, health-conscious meals, thereby enabling the efficient provision of nutritionally balanced, healthy meals and increasing customer satisfaction.

[1584] "Nutrition experts" are people with specialized knowledge about the nutritional value and health benefits of foods.

[1585] "Feedback" refers to an evaluation or opinion provided based on specific information or experience.

[1586] A "menu" is a list of specific meals or dishes, specifying the food offerings.

[1587] "Food supplier" refers to a company or individual that produces and supplies food to restaurants and consumers.

[1588] "Seasonal ingredients" refer to ingredients that are harvested in a particular season due to natural conditions.

[1589] A "contract" is a formal agreement between two parties.

[1590] "Safety" refers to the quality of food that does not adversely affect people's health.

[1591] "Quality" evaluates the superior characteristics of food, such as taste, freshness, and nutritional value.

[1592] "Freshness" refers to the degree of freshness of food between the time it is harvested and the time it is consumed.

[1593] "Cold storage technology" refers to the technology of maintaining food at low temperatures by cooling or freezing, thereby preserving its freshness.

[1594] "Delivery system" refers to a logistics system for delivering goods to a designated location.

[1595] "Delivery route" refers to the route or path planned for efficient delivery of goods.

[1596] "Optimization" refers to adjusting or improving something to achieve the best results for a particular purpose.

[1597] A "QR code" is a type of two-dimensional barcode that allows information to be read quickly.

[1598] "Customer feedback" refers to the means of collecting customer ratings and opinions about products and services.

[1599] "Product improvement" refers to the process of improving a product or service based on collected feedback.

[1600] A "food delivery application" is mobile software that allows you to order food online and have it delivered.

[1601] A "smartphone" refers to a portable information device with advanced computing power and connectivity.

[1602] The system for implementing this invention includes a server that receives feedback from nutrition experts and creates menus, terminals and servers equipped with means for contracting seasonal ingredients provided by food suppliers and managing their safety and quality, equipment that applies the latest refrigeration technology to maintain the freshness of received ingredients, means for optimizing delivery routes in cooperation with existing home delivery systems, and a mechanism for collecting customer feedback via QR codes and reflecting it in product improvements.

[1603] 1. Collaboration with nutrition experts

[1604] The server creates menus based on feedback from nutrition experts. Nutrition experts enter their feedback through a dedicated interface, which is then sent to the server. The server receives this feedback, compares it with its internal nutrition database, and generates new, nutritionally balanced menus. This information is also stored in a database for future reference.

[1605] 2. Ingredient contracts and management

[1606] The terminal collects information about ingredients provided by producers and sends it to a server. The server uses this information to conclude contracts with producers and registers the contract information in a management system. This management system constantly monitors the safety and quality of ingredients and provides feedback as needed.

[1607] 3. Cooling technology to maintain freshness

[1608] The received ingredients are stored in a device that uses the latest refrigeration technology to maintain freshness. The terminal regularly monitors the freshness of the ingredients and sends the information to the server. The server uses this information to optimize the settings of the refrigeration device and adjust it to maintain the maximum freshness of the ingredients.

[1609] 4. Logistics optimization

[1610] The server works with existing delivery systems to calculate optimal delivery routes and create delivery schedules. This schedule is sent to the terminals to improve delivery efficiency. The terminals use GPS to track the location of food during delivery and send it to the server in real time.

[1611] 5. Collecting and incorporating customer feedback

[1612] The server also generates a QR code and prints it on the bento packaging. Users can scan the QR code and provide feedback through the application. The server analyzes this feedback, identifies poorly rated items, and uses them to improve the next menu.

[1613] Specific examples

[1614] Specifically, when a nutrition expert suggests a "low-calorie, high-nutrition" menu, the server registers this feedback in a database and compares it to create new recommended menus. The server also sends contract information for fresh tomatoes provided by local farmers in the summer to the server and registers it in the management system. The received tomatoes are stored in a state-of-the-art refrigeration system, and their freshness is regularly monitored via terminals. The server calculates the fastest delivery route and provides the schedule to the terminals, ensuring efficient delivery. When a user scans a QR code and provides feedback that the flavor is "a little bland," the server analyzes the opinion and uses it to improve the next menu.

[1615] Prompt Sentence Examples

[1616] 1. Nutrition experts, please suggest new menu items based on the theme of "high protein, low fat."

[1617] 2. Send the Fresh Tomato contract information to the server and register it in the management system.

[1618] 3. Monitor the freshness of tomatoes and report it to the server.

[1619] 4. Calculate the fastest delivery route and generate a delivery schedule.

[1620] 5. Scan the QR code and give your feedback on the taste of the dish.

[1621] This approach makes it possible to efficiently provide nutritionally balanced and healthy meals and increase customer satisfaction.

[1622] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1623] Step 1:

[1624] The server receives feedback from nutrition experts. As input, it receives feedback data entered by nutrition experts through a dedicated interface. As data processing, the server takes in the feedback data, compares it with an existing nutrition database, and generates a new nutritionally balanced menu. As output, the new recommended menu is registered in the database.

[1625] Step 2:

[1626] The terminal collects information provided by food ingredient suppliers and sends it to the server. The input includes food ingredient information provided by producers. As a data calculation, the terminal sends the information to the server, and the server uses this information to conclude a contract with the producer and registers the contract information in the management system. As an output, information on food ingredients that have been safety and quality controlled is stored on the server.

[1627] Step 3:

[1628] The server applies the latest refrigeration technology to maintain the freshness of the received ingredients. The input includes data indicating the freshness status of the ingredients. For data processing, the terminal periodically monitors the freshness and sends the information to the server. The server uses this information to optimize the settings of the refrigeration equipment and adjust it to maintain the best possible freshness. The output holds information about ingredients whose freshness has been guaranteed.

[1629] Step 4:

[1630] The server works in conjunction with an existing delivery system to calculate the optimal delivery route. The input includes delivery data obtained from the existing delivery system. As a data calculation, the server analyzes this data and calculates the optimal delivery route. As an output, the optimal delivery route and schedule are created and sent to the terminal.

[1631] Step 5:

[1632] The terminal uses GPS to track the location information of the food being delivered. The input includes the current location information of the food being delivered. The data is processed by sending the location information to the server in real time. The output is the real-time tracking information of the food being delivered, which is stored on the server.

[1633] Step 6:

[1634] Users provide feedback through QR codes. The input includes the feedback information provided by users by scanning the QR code. As a data calculation, the server collects this feedback, evaluates it, and extracts improvements. As an output, the results are reflected in the next menu improvement.

[1635] This series of steps makes it possible to efficiently provide nutritionally balanced and healthy meals and increase customer satisfaction.

[1636] 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.

[1637] The present invention is an integrated system that includes menu development based on feedback from nutrition experts, provision of safe, high-quality meals using local, seasonal ingredients, preservation of freshness of ingredients using the latest refrigeration technology, optimization of logistics by linking with existing bento delivery systems, collection of customer feedback using QR codes, and a process of recognizing user emotions and improving products using an emotion engine.

[1638] Program processing explanation

[1639] Menu development with nutrition experts

[1640] 1. Gathering feedback

[1641] The server provides an interface for registering feedback from nutrition experts in a database, and the experts input their feedback through their terminals.

[1642] 2. Comparison with nutritional data

[1643] The server compares the nutritional database and generates menu recommendations based on expert feedback.

[1644] Ingredient contracts and management

[1645] 1. Collecting producer information

[1646] The terminal collects information from the producer and sends it to the server.

[1647] 2. Contract conclusion and management

[1648] The server enters into a contract with the producer and registers and manages that information in a database.

[1649] Preserving freshness with refrigeration technology

[1650] 1. Receiving and checking ingredients

[1651] The user (producer) sends ingredients to the distribution center.

[1652] 2. Application of refrigeration technology

[1653] The server uses refrigeration technology to set up the food to keep it fresh.

[1654] 3. Freshness monitoring

[1655] The terminal monitors the freshness of the food being kept refrigerated and sends the data to the server.

[1656] Logistics Optimization

[1657] 1. Calculating delivery routes

[1658] The server calculates the optimal delivery route based on data from the existing delivery system.

[1659] 2. Executing and tracking deliveries

[1660] The terminal receives a delivery schedule based on the calculation results and carries out the delivery.

[1661] Collecting customer feedback

[1662] 1. Distribution of the questionnaire

[1663] The server generates a QR code and prints the questionnaire on the lunch box packaging.

[1664] 2. Gathering Feedback

[1665] The user scans the QR code to answer the survey.

[1666] Emotion recognition by emotion engine

[1667] 1. Sentiment analysis of feedback

[1668] The feedback data collected by the server is analyzed by an emotion engine to recognize the user's emotions.

[1669] 2. Identifying areas for improvement

[1670] The server extracts areas for improvement in menus and services based on the results of sentiment analysis.

[1671] 3. Implementation of improvements

[1672] Based on the identified areas for improvement, the server plans and implements the next menu and service improvements.

[1673] Specific examples

[1674] Menu development with nutrition experts

[1675] Step 1:

[1676] The server registers the feedback of "high protein, low fat" from nutrition experts in a database. The experts input their feedback using a terminal, and the server stores it in the database.

[1677] Step 2:

[1678] The server compares the registered feedback with the company's nutritional database to search for matching ingredients and menu items.

[1679] Step 3:

[1680] The server generates a new recommended menu item, "High-protein, low-fat salad," based on the matching results and stores it in the database.

[1681] Ingredient contracts and management

[1682] Step 1:

[1683] The terminal collects information sent by the producer (for example, whether fresh tomatoes are available in summer) and transmits it to the server.

[1684] Step 2:

[1685] The server concludes a contract with the producer and registers this contract information in the management system.

[1686] Preserving freshness with refrigeration technology

[1687] Step 1:

[1688] A user (producer) sends fresh strawberries to a distribution center. The strawberries are scanned by a terminal and the information is sent to the server.

[1689] Step 2:

[1690] The server sets the optimum temperature and humidity based on the condition of the strawberries and sends this setting information to the cooling device.

[1691] Step 3:

[1692] The terminal periodically monitors the freshness of the strawberries and sends the information to the server, which then adjusts the cooling device to maintain the optimum environment.

[1693] Logistics Optimization

[1694] Step 1:

[1695] The server retrieves information from the existing delivery system, including past delivery data and current delivery status.

[1696] Step 2:

[1697] The server calculates the optimal delivery route based on past and current data and sends the results to the terminal.

[1698] Step 3:

[1699] The terminal receives delivery schedules and provides drivers with the optimal route in real time.

[1700] Collecting and analyzing customer feedback

[1701] Step 1:

[1702] The server generates a QR code and prints the questionnaire on the lunch box packaging.

[1703] Step 2:

[1704] Users scan the QR code and answer a questionnaire on their smartphone or PC, which includes a rating of their diet and suggestions for improvement.

[1705] Step 3:

[1706] The server stores the user feedback in a database for later analysis.

[1707] Emotion recognition and improvement with emotion engine

[1708] Step 1:

[1709] The server inputs the collected feedback data into an emotion engine and analyzes the user's emotions. For example, it recognizes the emotion of "dissatisfaction" from feedback such as "the flavor is bland."

[1710] Step 2:

[1711] The server extracts specific areas for improvement (e.g., "The seasoning needs to be improved") based on the results of sentiment analysis.

[1712] Step 3:

[1713] Based on the identified improvements, the server creates a plan to improve the next menu or service. This plan is shared with relevant experts and staff and reflected in actual improvements.

[1714] This system can efficiently provide nutritionally balanced, safe, and fresh meals and quickly reflect user feedback based on their emotions.

[1715] The processing flow will be explained below.

[1716] Menu development with nutrition experts

[1717] Step 1:

[1718] The server provides an interface for registering feedback from nutrition experts in the database, who input nutritional information and food recommendations via their terminals.

[1719] Step 2:

[1720] The device receives input from experts and sends it to a server, where feedback includes recommendations for specific nutritious ingredients and healthy recipes.

[1721] Step 3:

[1722] The server stores the received feedback in a database, which is used in subsequent processes.

[1723] Step 4:

[1724] The server then consults the nutrition database and matches it with expert feedback, specifically searching for data that matches the recommended ingredients and recipes.

[1725] Step 5:

[1726] The server generates new menu recommendations based on the matching results and stores them in the database. For example, a new menu item might be "high-protein, low-fat salad."

[1727] Ingredient contracts and management

[1728] Step 1:

[1729] The terminal collects information provided by producers (e.g., available ingredients, supply period) and transmits it to the server.

[1730] Step 2:

[1731] The server stores the received producer information in a database, including the types of ingredients each producer offers and the seasons in which they are available.

[1732] Step 3:

[1733] The server enters into a contract with a producer and registers the contract information in a database. For example, a contract may be made to supply fresh tomatoes in the summer.

[1734] Step 4:

[1735] The server monitors the status of contract fulfillment and manages whether ingredients are being supplied appropriately according to the supply schedule.

[1736] Preserving freshness with refrigeration technology

[1737] Step 1:

[1738] A user (producer) sends fresh produce (e.g., strawberries) to a distribution center. The produce is scanned at a terminal dedicated to receiving the produce.

[1739] Step 2:

[1740] The terminal scans the condition of the received ingredients (e.g., temperature, humidity) and sends the data to the server.

[1741] Step 3:

[1742] The server uses the scan data to determine optimal cooling settings, such as calculating the ideal temperature and humidity for storing strawberries.

[1743] Step 4:

[1744] The terminal receives instructions from the server and sets the refrigeration device, thereby keeping the food optimally fresh.

[1745] Step 5:

[1746] The terminal periodically monitors the freshness of the food in the refrigerator and sends the data to the server. If an abnormality is detected, an alert is sent immediately.

[1747] Logistics Optimization

[1748] Step 1:

[1749] The server receives data from existing delivery systems and delivery partners, including delivery times and past delivery routes.

[1750] Step 2:

[1751] The server calculates the optimal delivery route based on the received data, including real-time traffic information.

[1752] Step 3:

[1753] The server creates a delivery schedule based on the calculation results and sends it to the terminal. The delivery schedule includes detailed routes for each delivery.

[1754] Step 4:

[1755] The terminal receives delivery schedules and provides the optimal delivery route to the driver, who receives real-time instructions using the terminal.

[1756] Step 5:

[1757] The device uses GPS to track the location of the bento during delivery and sends this information in real time to a server, which continuously updates the delivery status.

[1758] Collecting and analyzing customer feedback

[1759] Step 1:

[1760] The server generates a QR code for the survey and prints it on the lunch box packaging, which contains a specific survey link.

[1761] Step 2:

[1762] Users scan the QR code and access the survey using their smartphone or PC, which includes fields for rating their diet and providing suggestions for improvement.

[1763] Step 3:

[1764] The server receives the survey data from users and stores it in a database, where the feedback is later analyzed by the emotion engine.

[1765] Emotion recognition and improvement with emotion engine

[1766] Step 1:

[1767] The server inputs the collected feedback data into an emotion engine and analyzes the user's emotions. For example, it recognizes the emotion of "dissatisfaction" from feedback such as "the flavor is bland."

[1768] Step 2:

[1769] The server extracts specific improvements based on the results of sentiment analysis, for example, determining that "the flavor needs to be improved."

[1770] Step 3:

[1771] Based on the identified improvements, the server creates an improvement plan for the next menu or service. The improvement plan is shared with relevant experts and staff and is reflected in actual improvements.

[1772] In this way, it is possible to efficiently provide nutritionally balanced, safe and fresh meals through each processing step, and to quickly reflect the user's emotional feedback.

[1773] Example 2

[1774] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1775] Modern eating habits demand the provision of nutritionally balanced, safe, and fresh meals. However, conventional systems have difficulty effectively incorporating feedback from nutrition experts into menus, and have issues with contract management of ingredients, maintaining freshness, efficient logistics, and insufficient collection and analysis of customer feedback. Furthermore, they lack a mechanism for improving products that reflect user sentiment. As a result, improvements in customer satisfaction and continuous product improvement have not been fully achieved.

[1776] 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.

[1777] In this invention, the server includes means for receiving feedback from nutrition experts and registering it in a database, means for comparing the expert feedback with the nutrition database to create recommended menus, means for contracting for ingredients provided by ingredient suppliers and managing the contract information, means for applying refrigeration technology to maintain the freshness of received ingredients, means for monitoring the status of ingredients while maintaining freshness using refrigeration technology and sending the data to the server, means for calculating the optimal delivery route in cooperation with an existing delivery system and executing and tracking delivery, means for collecting customer feedback via QR codes and analyzing the data to utilize for product improvement, and means for analyzing the collected feedback using an emotion engine, recognizing user emotions, and extracting areas for improvement. This enables the efficient provision of nutritionally balanced, safe, and fresh meals and rapid product improvement.

[1778] A "nutrition expert" refers to a person who has specialized knowledge about nutrition and whose job is to evaluate and provide guidance on the nutritional balance of meals.

[1779] "Feedback" refers to opinions and evaluations provided by users, experts, etc.

[1780] A "database" refers to a system that stores data and enables it to be efficiently managed and searched.

[1781] "Verification" refers to the act of comparing different information or data and checking whether they match.

[1782] "Recommended Menu" refers to meal suggestions made based on specific criteria or conditions.

[1783] "Food supplier" refers to a professional company that produces and supplies fresh food ingredients.

[1784] "Agreement" means any legally recognized document or process of agreement.

[1785] "Cold storage technology" refers to the technology and equipment used to maintain a low temperature environment.

[1786] "Monitoring" refers to the act of continuously watching over and checking the status.

[1787] A "delivery system" refers to a system or network for efficiently transporting goods.

[1788] "Delivery route" refers to the optimal route connecting delivery destinations.

[1789] A "QR code" is a type of two-dimensional barcode that allows information to be easily read.

[1790] "Customer feedback" refers to opinions and evaluations provided by customers regarding products and services.

[1791] "Data analysis" refers to the process of analyzing collected data and finding meaning and patterns.

[1792] "Product improvement" refers to improving the quality of products and services in order to increase customer satisfaction.

[1793] An "emotion engine" refers to a system that uses natural language processing technology to analyze emotions from text data.

[1794] "User emotions" refers to the impressions and feelings that users have about a product or service.

[1795] "Improvements" refers to changes or corrections that are needed to improve the current situation.

[1796] The present invention is an integrated system that efficiently provides nutritionally balanced meals and can quickly reflect customer feedback in improving products. This system is mainly composed of a server, terminals, and users.

[1797] The server performs the following functions: It provides an interface for nutrition experts to input their feedback into the database. Experts use a browser to input their feedback, which is then sent to the server and stored in the database. It also compares the feedback with the existing nutrition database to generate recommended menus. These menus are then stored in the database along with a list of ingredients and their nutritional information.

[1798] The server then concludes contracts with producers based on information provided by food suppliers and registers the contract information in the management system. After receiving the ingredients, it uses refrigeration technology to set the appropriate temperature and humidity, adjusting the environment to maintain freshness. It also optimizes logistics and calculates the optimal delivery route based on past and current delivery data.

[1799] Meanwhile, the terminal is responsible for collecting information from producers and sending it to the server. For example, if a producer can supply fresh tomatoes, the information is entered into the terminal and sent to the server. When receiving ingredients, the terminal is used to scan the ingredients and the information is sent to the server. When applying refrigeration technology, the terminal also monitors the freshness of the ingredients and continuously sends this data to the server. This allows the refrigeration device to maintain an optimal environment.

[1800] Users scan the QR code using their smartphone and answer the questionnaire. The feedback is sent to the server and stored in a database. The server inputs this feedback data into an emotion engine and uses natural language processing technology to analyze the user's emotions. For example, feedback such as "the flavor is bland" can be recognized as an emotion of "dissatisfaction." Based on the analysis results, specific areas for improvement are extracted and reflected in the next menu or service.

[1801] Specific examples

[1802] Menu development with nutrition experts

[1803] The server registers the feedback of "high protein, low fat" from nutrition experts in a database. The experts input their feedback using a terminal, and the server stores it in the database.

[1804] The server compares the registered feedback with the company's nutritional database to search for matching ingredients and menu items.

[1805] The server generates a new recommended menu item, "High-protein, low-fat salad," based on the matching results and stores it in the database.

[1806] Ingredient contracts and management

[1807] The terminal collects information sent by the producer (for example, whether fresh tomatoes are available in summer) and transmits it to the server.

[1808] The server concludes a contract with the producer and registers this contract information in the management system.

[1809] Preserving freshness with refrigeration technology

[1810] A user (producer) sends fresh strawberries to a distribution center. The strawberries are scanned by a terminal and the information is sent to the server.

[1811] The server sets the optimum temperature and humidity based on the condition of the strawberries and sends this setting information to the cooling device.

[1812] The terminal periodically monitors the freshness of the strawberries and sends the information to the server, which then adjusts the cooling device to maintain the optimal environment.

[1813] Logistics Optimization

[1814] The server retrieves information from the existing delivery system, including past delivery data and current delivery status.

[1815] The server calculates the optimal delivery route based on past and current data and sends the results to the terminal.

[1816] The terminal receives delivery schedules and provides drivers with the optimal route in real time.

[1817] Collecting and analyzing customer feedback

[1818] The server generates a QR code and prints the questionnaire on the lunch box packaging.

[1819] Users scan the QR code and answer a questionnaire on their smartphone or PC, which includes a rating of their diet and suggestions for improvement.

[1820] The server stores the user feedback in a database for later analysis.

[1821] Emotion recognition and improvement with emotion engine

[1822] The server inputs the collected feedback data into an emotion engine and analyzes the user's emotions. For example, it recognizes the emotion of "dissatisfaction" from feedback such as "the flavor is bland."

[1823] The server extracts specific areas for improvement (e.g., "The seasoning needs to be improved") based on the results of sentiment analysis.

[1824] Based on the identified improvements, the server creates a plan to improve the next menu or service. This plan is shared with relevant experts and staff and reflected in actual improvements.

[1825] This system can efficiently provide nutritionally balanced, safe, and fresh meals and quickly reflect user feedback based on their emotions.

[1826] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1827] Menu development with nutrition experts

[1828] Step 1:

[1829] The server collects feedback from nutrition experts, who input feedback such as "high-protein, low-fat menus are recommended" using a terminal, which is then sent to the server's database.

[1830] Input: Expert feedback

[1831] Output: Feedback data stored in a database

[1832] Step 2:

[1833] The server compares the feedback stored in the database with a nutrition database using a pre-defined algorithm.

[1834] Input: Expert feedback, nutrition database

[1835] Output: Matching result

[1836] Step 3:

[1837] The server generates new menu recommendations based on the match, including specific ingredient lists and nutritional information.

[1838] Input: Matching result

[1839] Output: Menu recommendations, new cooking recipes

[1840] Ingredient contracts and management

[1841] Step 1:

[1842] The terminal collects information from producers and sends it to the server, for example, by inputting detailed information about available ingredients and when they will be available.

[1843] Input: Supply information from producers

[1844] Output: The feed sent to the server

[1845] Step 2:

[1846] The server generates a contract based on the collected producer information and concludes the contract using an electronic signature system. The contract details are then registered in the management system.

[1847] Input: Supply information from producers

[1848] Output: Registered contract information

[1849] Preserving freshness with refrigeration technology

[1850] Step 1:

[1851] The user (producer) sends fresh ingredients to the distribution center. The received ingredients are scanned by a terminal and the information is sent to the server.

[1852] Input: Ingredients sent

[1853] Output: Scanned food data

[1854] Step 2:

[1855] The server calculates the optimal cooling settings based on the scanned food data and sends the setting information to the cooling device.

[1856] Input: scanned food data

[1857] Output: Cooling setting information

[1858] Step 3:

[1859] The terminal periodically collects data from the refrigerator to monitor the freshness of the ingredients. This data is then sent to a server, which then appropriately manages the environment to maintain freshness.

[1860] Input: Data from refrigeration equipment

[1861] Output: Monitoring data

[1862] Logistics Optimization

[1863] Step 1:

[1864] The server acquires existing delivery system data and calculates the optimal delivery route based on past and current delivery status.

[1865] Input: Existing delivery system data

[1866] Output: Optimal delivery route information

[1867] Step 2:

[1868] The terminal provides the driver with optimal delivery route information and real-time route instructions, while simultaneously transmitting delivery status information to the server.

[1869] Input: Optimal delivery route information

[1870] Output: Real-time delivery instructions, location data

[1871] Collecting and analyzing customer feedback

[1872] Step 1:

[1873] The server generates a QR code and prints it on the lunch box package, which contains a link to the survey form.

[1874] Input: QR code generation information

[1875] Output: QR code printed on the bento package

[1876] Step 2:

[1877] Users scan the QR code with their smartphone to access the survey form and submit their answers.

[1878] Input: Customer feedback

[1879] Output: Survey data saved on the server

[1880] Emotion recognition and improvement with emotion engine

[1881] Step 1:

[1882] The server inputs the collected feedback data into an emotion engine, which then analyzes the user's emotions using natural language processing technology.

[1883] Input: Customer feedback data

[1884] Output: Emotion analysis results

[1885] Step 2:

[1886] The server extracts specific areas for improvement based on the results of sentiment analysis. For example, from feedback that the food tastes bland, it identifies the need to improve the seasoning.

[1887] Input: Sentiment analysis results

[1888] Output: Extracted improvements

[1889] Step 3:

[1890] The server will then create a plan to improve the next menu or service based on the identified improvements, and share this plan with experts and staff. This plan will be reflected in future product offerings.

[1891] Input: Improvements

[1892] Output: Improvement plan

[1893] In this way, the system can quickly reflect user feedback and efficiently provide nutritionally balanced, safe, and fresh meals.

[1894] (Application example 2)

[1895] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1896] In recent years, consumers have become increasingly health-conscious, leading to an increased demand for nutritionally balanced meals and fresh ingredients. However, previous systems made it difficult to effectively incorporate feedback from nutrition experts, and were inadequate in maintaining the freshness of ingredients and in quickly collecting and analyzing customer feedback. Furthermore, there was a lack of efficient methods for optimizing logistics and managing the freshness of ingredients. This made it difficult to provide high-quality meals that met the needs of individual customers. Furthermore, there was a lack of sufficient efforts to improve service based on customer sentiment. As a result, there were problems with reduced satisfaction and lost opportunities.

[1897] 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 means for receiving feedback from nutrition experts and creating menus, means for contracting for seasonal ingredients from ingredient suppliers and managing their safety and quality, means for applying the latest refrigeration technology to maintain the freshness of received ingredients, means for optimizing delivery routes in cooperation with existing home delivery systems, means for collecting customer feedback via QR codes and reflecting it in product improvements, means for collecting customer feedback using QR codes, analyzing it with a sentiment analysis engine, and reflecting it in service improvements, and means for optimizing logistics and monitoring freshness using smart devices. This not only enables efficient and high-quality meal provision, but also enables rapid service improvements based on customer sentiment, thereby improving customer satisfaction.

[1898] A "nutrition expert" is a professional with knowledge and experience regarding the nutritional balance and health of meals, who provides feedback on menu creation and ingredient selection.

[1899] "Feedback" refers to opinions, evaluations, and suggestions for improvement provided by users and experts regarding systems and services, and is information that is used to improve quality and efficiency.

[1900] A "menu" is a list of meals that take into account a specific purpose and nutritional balance, and is a meal plan created with feedback from nutrition experts.

[1901] A "food supplier" is a business that produces or sells food ingredients and provides seasonal ingredients through contracts, and is required to manage safety and quality.

[1902] "Contract" means an agreement between a food supplier and a service provider under which food is promised to be provided for a specified period and under specified conditions.

[1903] "Cold storage technology" is a technique used to maintain the freshness of received ingredients for a long period of time, and includes temperature control and humidity control.

[1904] "Existing delivery system" refers to a logistics system that is already in operation to efficiently deliver ingredients and products to customers.

[1905] A "delivery route" is the route a product takes from its departure point to its destination, and optimizing it improves delivery efficiency and reduces time and costs.

[1906] A QR code is a type of two-dimensional barcode that can be scanned to access information or collect feedback.

[1907] An "emotion analysis engine" is a computer system that analyzes collected feedback data and automatically recognizes users' emotions and satisfaction levels.

[1908] A "smart device" is an electronic device that has Internet connectivity and can send, receive, and process various types of information, including smartphones and tablets.

[1909] "Logistics optimization" is the process of optimizing delivery routes, times, and resources for the efficient transportation of goods.

[1910] "Freshness monitoring" is the process of using refrigeration technology to monitor the freshness of ingredients in real time and collect freshness information.

[1911] "Service improvement" refers to ongoing activities to improve the quality and efficiency of the services we provide based on collected feedback and analytical results.

[1912] This invention is a system that integrates menu development based on feedback from nutrition experts, seasonal ingredient contracts, safety and quality control, preserving the freshness of ingredients using the latest refrigeration technology, optimizing delivery routes by linking with existing delivery systems, collecting customer feedback using QR codes, and improving services using a sentiment analysis engine.

[1913] Menu development with nutrition experts

[1914] The server receives feedback from nutrition experts and registers the feedback in a database. The server then compares it with the company's nutrition database and generates recommended menu items based on the expert's feedback. For example, if the server receives feedback such as "high protein, low fat," it can generate a recommended menu item: "high protein, low fat salad."

[1915] Ingredient contracts and management

[1916] The terminal collects information provided by producers and sends it to the server. The server then uses this information to conclude contracts with food suppliers and registers the contract information in a system that manages such information. For example, the server may collect information from a producer that "fresh tomatoes are available" and conclude a supply contract based on this information.

[1917] Preserving freshness with refrigeration technology

[1918] Food suppliers use the latest refrigeration technology to maintain freshness. The server sets the optimal temperature and humidity based on the condition of the food and sends this setting information to the refrigeration device. The terminal periodically monitors the freshness of the food and sends the information to the server. For example, to maintain the freshness of fresh strawberries, the refrigeration device can be set to the optimal environment.

[1919] Logistics Optimization

[1920] The server acquires information from existing delivery systems and calculates the optimal delivery route based on past delivery data and current delivery status. The terminal receives the delivery schedule based on the calculation results and provides the driver with the optimal route in real time. For example, the most efficient delivery route can be calculated based on past delivery data.

[1921] Customer feedback collection and sentiment analysis

[1922] The server generates a QR code and prints a questionnaire on the lunch box packaging. The user scans this QR code with their smartphone and answers the questionnaire. The server then analyzes the collected feedback using a sentiment analysis engine to recognize the user's emotions. Based on this, the server identifies areas for improvement in the service and creates plans to improve the next menu or service. For example, in response to feedback that the flavor is "bland," the server can identify specific areas for improvement such as "the seasoning needs to be improved."

[1923] Examples of concrete examples and prompts

[1924] Specific examples include developing a "high-protein, low-fat salad" menu, signing a contract to supply fresh tomatoes, setting up an optimal refrigeration environment, calculating delivery routes, collecting feedback using QR codes, and analyzing emotions such as "the taste is bland" to "dissatisfied."

[1925] An example prompt might be, "Please provide the code that will help us analyze user feedback, analyze it with our sentiment engine, and improve our menu next time."

[1926] The above-mentioned system not only enables efficient and high-quality food service, but also allows for quick service improvements based on customer sentiment, thereby increasing customer satisfaction.

[1927] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1928] Step 1:

[1929] The server receives feedback from nutrition experts and registers it in a database. First, the server provides a feedback input interface to the experts, who then use their terminals to input specific feedback such as "high protein, low fat." This input is sent to the server and stored in the database.

[1930] Input: Expert feedback (e.g., "high protein, low fat")

[1931] Data processing / calculation: Feedback content is registered in the database

[1932] Output: Feedback is saved in a database

[1933] Step 2:

[1934] The server compares the feedback with the company's nutrition database and creates menu recommendations based on the feedback. For example, based on the feedback "high protein, low fat," the server searches for matching ingredients and cooking methods, generating a new menu item such as "high protein, low fat salad."

[1935] Input: Nutrition expert feedback data

[1936] Data processing / calculation: Matching feedback with nutritional database, generating new menu items

[1937] Output: Recommended menu (e.g. "High protein, low fat salad")

[1938] Step 3:

[1939] The terminal collects information about ingredients provided by producers and sends it to the server. For example, a producer inputs into the terminal that they can supply fresh tomatoes, and the information is sent to the server.

[1940] Input: Ingredient information from producers (e.g., "Fresh tomatoes available")

[1941] Data processing / calculation: Sending ingredient information to the server

[1942] Output: Ingredient information is saved on the server

[1943] Step 4:

[1944] The server concludes contracts with food suppliers and registers the contract information in the management system. For example, the server digitizes contracts with producers and registers them in the management system.

[1945] Input: Contract information with food suppliers

[1946] Data processing / calculation: Digitization and registration of contract information

[1947] Output: Contract information is saved in the management system

[1948] Step 5:

[1949] The server sets the optimal temperature and humidity based on the condition of the ingredients and sends this setting information to the refrigeration device. For example, to maintain the freshness of produced strawberries, the server calculates the optimal refrigeration environment (temperature and humidity) and sets it in the device.

[1950] Input: Freshness of ingredients

[1951] Data processing / calculation: Calculation of cooling settings based on freshness status

[1952] Output: Configuration information sent to the refrigerator

[1953] Step 6:

[1954] The device periodically monitors the freshness of the ingredients and sends the information to the server. For example, a sensor in the refrigerator collects freshness data, and the device then forwards the data to the server.

[1955] Input: Freshness data from the refrigerator sensor

[1956] Data processing / calculation: Monitoring and transferring freshness data

[1957] Output: Freshness information sent to the server

[1958] Step 7:

[1959] The server obtains information from existing delivery systems and optimizes delivery routes. Based on past delivery data and current delivery status, the server calculates the optimal delivery route and sends the results to the terminal.

[1960] Input: Data from existing delivery system

[1961] Data processing / calculation: Calculating the optimal delivery route

[1962] Output: The optimal route information is sent to the device.

[1963] Step 8:

[1964] The device generates a QR code and prints the questionnaire on the lunch box package. The user scans the QR code with their smartphone and answers the questionnaire.

[1965] Input: QR code generation request

[1966] Data processing / calculation: QR code generation

[1967] Output: Survey with QR code printed

[1968] Step 9:

[1969] The server analyzes the collected feedback using a sentiment analysis engine to recognize the user's emotions. Feedback such as "the flavor is bland" is recognized as "dissatisfied," and the server identifies areas for improvement in the next menu or service.

[1970] Input: Feedback data

[1971] Data processing / calculation: Sentiment analysis, extraction of areas for improvement

[1972] Output: Next menu or service with improvements reflected

[1973] The above processing steps enable a smooth process of collecting feedback provided by users in real time and using the emotion engine to reflect it in improving the next menu or service.

[1974] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1975] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1976] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1977] [Fourth embodiment]

[1978] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1979] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1980] 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).

[1981] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1982] 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.

[1983] 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).

[1984] 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. 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.

[1985] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1986] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1987] 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.

[1988] 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.

[1989] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1990] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1991] The present invention is a system that includes menu development based on feedback from nutrition experts, safety and quality control of ingredients based on contracts with producers, freshness maintenance using the latest refrigeration technology, logistics optimization through integration with existing bento delivery systems, and a process for collecting customer feedback and improving products using QR codes.

[1992] Program processing explanation

[1993] Menu development with nutrition experts

[1994] 1. Gathering feedback

[1995] The server stores the feedback from the nutrition experts in a database.

[1996] The terminal inputs feedback through the nutrition expert interface and transmits it to the server.

[1997] 2. Comparison with nutritional data

[1998] The server compares the stored feedback with an in-house nutrition database.

[1999] The server searches for matching ingredients and menu items.

[2000] 3. Creating a recommended menu

[2001] The server creates and stores new recommended menus based on the results of comparison with the nutrition database.

[2002] Ingredient contracts and management

[2003] 1. Collecting producer information

[2004] The terminal collects information from the producer and transmits it to the server.

[2005] 2. Contract conclusion and management

[2006] The server concludes a contract with the producer and registers the contract information in the management system.

[2007] Preserving freshness with refrigeration technology

[2008] 1. Receiving and checking ingredients

[2009] The user (producer) sends ingredients to the distribution center.

[2010] The terminal checks the freshness of the received ingredients and sends the information to the server.

[2011] 2. Application of refrigeration technology

[2012] The server connects the food ingredient data to the refrigeration equipment and applies the optimal refrigeration technology.

[2013] 3. Freshness monitoring

[2014] The terminal periodically monitors the freshness of the food items being kept refrigerated and sends this information to the server.

[2015] Logistics Optimization

[2016] 1. Calculating delivery routes

[2017] The server calculates the optimal delivery route based on data from the existing delivery system.

[2018] 2. Create a delivery schedule

[2019] The server creates a delivery schedule based on the calculated delivery route and transmits it to the terminal.

[2020] 3. Track your delivery

[2021] The device uses GPS to track the current location of the lunch box during delivery and transmits that information to the server in real time.

[2022] Collecting and analyzing customer feedback

[2023] 1. Distribution of the questionnaire

[2024] The server generates a QR code for the survey and prints it on the lunch box packaging.

[2025] 2. Gathering Feedback

[2026] Users scan the QR code to answer the survey.

[2027] The server stores the user's feedback in a database.

[2028] 3. Analyzing feedback and identifying areas for improvement

[2029] The server analyzes the collected feedback and extracts low-rated items and areas for improvement.

[2030] Specific examples

[2031] As a specific example, the following series of processes can be considered.

[2032] 1. Nutrition experts propose new menu items based on the theme of "high protein, low fat." The server registers this feedback in a database and compares it with the nutrition database to create recommended menu items.

[2033] 2. A local farmer signs a contract to provide fresh tomatoes during the summer season. The terminal sends this contract information to the server and registers it in the management system.

[2034] 3. Strawberries received at the distribution center are stored in the latest refrigeration equipment and temperature controlled to maintain freshness. The terminal monitors the freshness of the strawberries and periodically reports this to the server.

[2035] 4. The server uses an optimization algorithm to calculate the fastest delivery route and create a delivery schedule. The device tracks the location of the bento box in real time during delivery and sends it to the server.

[2036] 5. The user scans the QR code and sends feedback that the food tastes bland. The server analyzes this feedback and reflects it in improving the menu for the next time.

[2037] This system makes it possible to efficiently provide nutritionally balanced, safe, and fresh meals.

[2038] The processing flow will be explained below.

[2039] Menu development with nutrition experts

[2040] Step 1:

[2041] The server provides an interface for storing feedback from nutrition experts in a database, and the experts input their feedback through terminals.

[2042] Step 2:

[2043] The device receives expert feedback and sends it to a server, which includes specific nutritional information and areas for improvement.

[2044] Step 3:

[2045] The server registers the expert's feedback in a database, which is used to match the feedback with the nutrition database.

[2046] Step 4:

[2047] The server will refer to the nutrition database and compare it with the registered feedback, searching for matching ingredients and menu items.

[2048] Step 5:

[2049] The server generates a new recommended menu based on the matching results and stores it in a database.

[2050] Ingredient contracts and management

[2051] Step 1:

[2052] The terminal collects information from producers (for example, information on available ingredients and seasonal information) and sends it to the server.

[2053] Step 2:

[2054] The server registers the information sent from the producers in a database, including the type of food and the supply period.

[2055] Step 3:

[2056] The server performs the procedure to conclude a contract with the producer, confirms the contract details, and saves them in the database.

[2057] Step 4:

[2058] The server monitors the status of contract fulfillment and displays the seasonal food supply status on the management system.

[2059] Preserving freshness with refrigeration technology

[2060] Step 1:

[2061] The user (producer) sends ingredients to the distribution center, where they are scanned at a receiving terminal.

[2062] Step 2:

[2063] The terminal scans the received ingredients to determine their condition (e.g., temperature, humidity) and sends the data to the server.

[2064] Step 3:

[2065] The server receives the food ingredient data and starts communicating with the refrigeration equipment, determining the optimal refrigeration technology (temperature and humidity settings).

[2066] Step 4:

[2067] The terminal receives instructions from the server and sets the cooling device appropriately, creating an environment that keeps food fresh.

[2068] Step 5:

[2069] The terminal periodically monitors the freshness of the food in the refrigerator and sends the status to the server, issuing an alert if there is an abnormality.

[2070] Logistics Optimization

[2071] Step 1:

[2072] The server receives data from existing delivery systems and delivery partners, including current delivery status and past delivery data.

[2073] Step 2:

[2074] Based on the data received by the server, an optimization algorithm is used to calculate the optimal delivery route.

[2075] Step 3:

[2076] The server creates a delivery schedule based on the calculation results and sends it to the terminal.

[2077] Step 4:

[2078] The terminal receives delivery schedules and assists in executing deliveries, while the driver uses the terminal to check route information in real time.

[2079] Step 5:

[2080] The device uses GPS to track the current location of the bento and ingredients being delivered and sends that data to a server, which updates the delivery status in real time.

[2081] Collecting and analyzing customer feedback

[2082] Step 1:

[2083] The server generates a QR code for the survey and prints it on the lunch box packaging, which contains a specific survey link.

[2084] Step 2:

[2085] Users scan the QR code to access the survey on their smartphone or PC, which includes a field to rate the diet and provide suggestions for improvement.

[2086] Step 3:

[2087] The server receives the survey data from users and stores it in a database, where the feedback is later analyzed.

[2088] Step 4:

[2089] The server analyzes the collected feedback data and extracts low-rated items and specific areas for improvement.

[2090] Step 5:

[2091] Based on the identified improvements, the server creates a plan to improve the next menu or service. The plan is shared with experts and staff.

[2092] In this way, a system is realized that efficiently provides nutritionally balanced, safe, and fresh meals through each processing step.

[2093] Example 1

[2094] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2095] In recent years, growing health consciousness has led to an increasing demand for systems that efficiently provide nutritionally balanced meals. However, conventional systems have not been able to fully incorporate feedback from nutrition experts, resulting in insufficient optimization of ingredient freshness management and logistics. Furthermore, there is a lack of means to efficiently collect and incorporate customer feedback. Furthermore, automating contract management with ingredient suppliers and freshness monitoring has also been an issue. There is a need to solve these issues.

[2096] 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.

[2097] In this invention, the server includes a means for receiving feedback from nutrition experts and creating menus, a means for comparing the feedback with a nutrition database, and a means for applying the latest refrigeration technology to maintain the freshness of the received ingredients, thereby enabling the proposal of nutritionally balanced menus, the management of the freshness of ingredients, the optimization of logistics, and the collection and analysis of customer feedback.

[2098] A "nutritionist" is a professional with specialized knowledge of nutrition who optimizes the nutritional balance of meals and designs menus tailored to specific health goals.

[2099] "Feedback" refers to opinions and evaluation information provided by nutrition experts and customers, based on which the system and menus are improved.

[2100] "Menu" refers to a list of meals or dishes, including ingredients and cooking methods, organized around a particular theme or with nutritional balance in mind.

[2101] "Food suppliers" refers to producers and businesses that provide seasonal food ingredients and are subject to safety and quality control.

[2102] "Contract" means a formal agreement between a food supplier and a system operator that provides for the supply of food of a specified quality and quantity within a specified period of time.

[2103] "Cold storage technology" is a technique for maintaining a low temperature environment and is a means used to keep food ingredients fresh for a long period of time.

[2104] "Delivery system" refers to the infrastructure and procedures for delivering goods, and is the existing delivery network used to streamline logistics.

[2105] A "QR code" is a type of two-dimensional barcode that can be read with a camera on a smartphone or other device to quickly access information.

[2106] "Customer feedback" refers to the opinions and evaluations that customers submit about services and products, and is valuable data for product improvement.

[2107] A "nutrition database" is a database that stores detailed information on the nutritional components contained in various ingredients and dishes, and is used to optimize nutritional balance.

[2108] "Freshness monitoring" refers to the process of regularly monitoring the quality status of food ingredients (e.g., color, temperature, humidity, etc.) and sending that information to a server for analysis.

[2109] "Delivery route" refers to the route along which goods are transported to their destination, and is optimized for efficient delivery.

[2110] "Smartphone" is an abbreviation for smartphone, a type of mobile phone equipped with GPS functionality and internet connectivity.

[2111] "Real-time tracking" refers to the ability to check the current location of an object in real time, especially for goods being delivered.

[2112] The present invention is a system that includes menu development based on feedback from nutrition experts, safety and quality control of ingredients based on contracts with producers, freshness maintenance using the latest refrigeration technology, logistics optimization through integration with existing home delivery systems, and a process for collecting customer feedback and improving products using QR codes.

[2113] Menu development with nutrition experts

[2114] The server stores the feedback from nutrition experts in a database. Feedback is provided as a URL, document file, or XML feed, and the server automatically analyzes and registers it in the database. The terminal provides an administration screen for nutrition experts, where they can enter their feedback using text boxes and check boxes. The entered information is sent to the server via an HTTP request.

[2115] The server then matches the feedback stored in the database with a nutrition database (e.g., MySQL) and uses a keyword search algorithm to find matching ingredients and menu items. The matched data is statistically analyzed using Python or R to generate new menu recommendations. This menu is then stored again in the database and formatted for screen output.

[2116] A specific example includes a process in which a nutritionist submits feedback on the theme "high protein, low fat" via an administration screen, and the server generates a recommended menu item, "chicken breast salad," based on this information.

[2117] Ingredient contracts and management

[2118] The terminal provides a dedicated web form for collecting information from producers. This form is an interface for entering information such as the farmer's name, location, and list of ingredients they can provide. This information is sent from the terminal to the server via an HTTP request and automatically registered in a database.

[2119] The server registers contract information with producers (contract start date, end date, supply volume, etc.) in the management system. The contract is saved as a PDF, and various conditions are stored in the database in JSON format.

[2120] A specific example involves a process in which a local farmer enters a contract to "provide fresh tomatoes during the summer season" through a web form, and the server registers the information in a database.

[2121] Preserving freshness with refrigeration technology

[2122] The user (producer) sends the harvested ingredients to the distribution center. The terminal provides a smartphone app to check the freshness of the ingredients received at the distribution center. The app checks color, aroma, temperature, etc., and sends the results digitally to the server.

[2123] The server can determine the optimal refrigeration method (temperature, humidity, etc.) based on the received food information and issue instructions to the refrigeration device. The terminal also periodically monitors the freshness of the food using cameras and sensors in the refrigeration device and sends this data to the server.

[2124] A specific example is a process that measures the color and temperature of strawberries received at a distribution center and allows the server to set the optimal refrigeration temperature. Sensors in the refrigeration equipment monitor freshness and periodically send data to the server.

[2125] Logistics Optimization

[2126] The server acquires data from existing delivery systems and calculates optimal delivery routes using the Google Maps API and a proprietary optimization algorithm. It automatically generates a delivery schedule based on the route information and sends the results to the device. The delivery schedule includes estimated delivery times and orders.

[2127] The device uses the GPS function installed on the delivery driver's smartphone to track the current location of the bento boxes being delivered in real time and transmits this information to a server at regular intervals.

[2128] For example, the server uses the Google Maps API to calculate the optimal route, generate a delivery schedule, and send it to the driver's smartphone. The device periodically uploads GPS information to the server, allowing the driver to check the delivery status in real time.

[2129] Collecting and analyzing customer feedback

[2130] The server generates a QR code for customer feedback and prints it on the lunch box package label. Users scan the QR code with their smartphone to access the survey form and enter their opinions. The server saves the entered feedback data in a database in real time.

[2131] The server analyzes the collected feedback data using machine learning algorithms in Python and R to identify low-rated items and areas for improvement. The analysis results are visualized on a management screen and reflected in menu development and logistics management.

[2132] A specific example includes a process where a user scans a QR code and sends feedback such as "the flavor is bland," which the server analyzes and reflects in the next menu revision, adjusting the "optimal amount of seasoning."

[2133] Example prompt sentence:

[2134] "I would like to create a new, nutritionally balanced menu. Please suggest recipes that use high-protein, low-fat ingredients."

[2135] Thus, the system of the present invention comprehensively covers all the steps required to efficiently provide nutritionally balanced, safe and fresh meals.

[2136] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2137] Program processing flow

[2138] Step 1: Gather expert feedback

[2139] explanation:

[2140] The device provides a dedicated management screen for receiving feedback from nutrition experts. The management screen has text boxes and check boxes where experts can enter their opinions and suggestions. The entered data is sent to the server via an HTTP request. The server stores the received data in a database.

[2141] input:

[2142] Nutrition expert feedback (text and multiple choice answers)

[2143] output:

[2144] Feedback information stored in a database

[2145] Specific behavior:

[2146] When an expert enters feedback such as "high protein, low fat" into the management screen and presses the send button, the data is sent to the server.

[2147] Step 2: Check against nutritional data

[2148] explanation:

[2149] The server retrieves the feedback stored in the database and compares it with the company's internal nutrition database. Specifically, it performs text analysis of the feedback and searches for related ingredients and menu items using keyword searches. The search results are temporarily stored.

[2150] input:

[2151] Feedback information stored in a database

[2152] output:

[2153] Matched ingredients and menu list

[2154] Specific behavior:

[2155] Based on the keywords "high protein, low fat," the server checks a nutritional database to extract information on ingredients such as "chicken breast" and "lean fish."

[2156] Step 3: Create a recommended menu

[2157] explanation:

[2158] The server generates new recommended menus based on the matching results. Using Python and R, the menus are constructed to meet nutritional balance and calorie constraints. The generated menus are saved in a database and can be viewed on the management screen.

[2159] input:

[2160] Matched ingredients and menu list

[2161] output:

[2162] Recommendations stored in a database

[2163] Specific behavior:

[2164] The server generates a menu list including "chicken breast salad" and stores it in a database.

[2165] Step 4: Collecting producer information and managing contracts

[2166] explanation:

[2167] The terminal provides an interface where producers can enter information through a dedicated web form, including, for example, the farmer's name, location, and available ingredients list. The entered information is sent via an HTTP request to the server, which then registers it in a database.

[2168] input:

[2169] Information from producer (name, location, list of ingredients)

[2170] output:

[2171] Producer information and contract information registered in the database

[2172] Specific behavior:

[2173] Producers enter information such as "providing fresh tomatoes during the summer season" into a web form, and the server registers the information in a database.

[2174] Step 5: Receive ingredients and check freshness

[2175] explanation:

[2176] The user (producer) sends the harvested ingredients to the distribution center. The terminal provides an interface for checking the freshness of the ingredients that arrive at the center using a smartphone app. Check items include color, aroma, temperature, etc. The terminal then digitally transmits the results to the server.

[2177] input:

[2178] Freshness information for ingredients received at the distribution center

[2179] output:

[2180] Freshness data sent to the server

[2181] Specific behavior:

[2182] At the distribution center, users measure the color and temperature of strawberries using a smartphone app and send the data to the server.

[2183] Step 6: Applying cooling technology

[2184] explanation:

[2185] The server determines the optimal refrigeration method based on the received food information, sets temperature and humidity conditions, and issues instructions to the refrigeration device. It also monitors sensors to maintain freshness under the set environment, and continuously sends this data to the server.

[2186] input:

[2187] Freshness data and ingredient information

[2188] output:

[2189] Setting data that gives instructions to the cooling device

[2190] Specific behavior:

[2191] The server sets the temperature and humidity conditions for the strawberries and instructs the refrigeration device to "store them at the preset temperature."

[2192] Step 7: Optimize delivery routes

[2193] explanation:

[2194] The server acquires data from existing delivery systems and calculates optimal delivery routes using the Google Maps API and proprietary algorithms. Based on the results of the calculations, it automatically generates a delivery schedule and sends the results to the device.

[2195] input:

[2196] Delivery system data and customer delivery information

[2197] output:

[2198] Optimal delivery routes and schedules

[2199] Specific behavior:

[2200] The server uses the Google Maps API to calculate the "fastest route," generate a schedule, and send it to the driver's smartphone.

[2201] Step 8: Track your shipment

[2202] explanation:

[2203] The device uses the GPS function installed on the delivery driver's smartphone to periodically track the current location of the lunch box during delivery. The location information is sent to a server at regular intervals and displayed in real time on the management screen.

[2204] input:

[2205] GPS location information from the driver's smartphone

[2206] output:

[2207] Real-time location tracking data

[2208] Specific behavior:

[2209] The device acquires the location information of the lunch box being delivered and periodically uploads it to the server, allowing delivery status to be checked in real time.

[2210] Step 9: Collect and analyze customer feedback

[2211] explanation:

[2212] The server generates a QR code for customer feedback and prints it on the lunch box package label. The customer scans the QR code with their smartphone, accesses the survey form, and enters their feedback. The entered data is saved on the server in real time.

[2213] input:

[2214] Customer feedback (survey responses)

[2215] output:

[2216] Feedback data stored on the server

[2217] Specific behavior:

[2218] The user scans the QR code printed on the bento box and sends feedback such as "the taste is bland," which the server then stores in a database.

[2219] Step 10: Analyze feedback and identify areas for improvement

[2220] explanation:

[2221] The server analyzes the collected feedback data using machine learning algorithms in Python and R to identify low-rated items and areas for improvement. The analysis results are visualized on a management screen and reflected in the next menu development and logistics management.

[2222] input:

[2223] Collected customer feedback data

[2224] output:

[2225] Analysis results and list of improvements

[2226] Specific behavior:

[2227] The server will analyze the feedback that the food is "bland" and implement a process to reflect the "optimal amount of seasoning" in the next menu.

[2228] In this way, each step works together to create a system that efficiently provides nutritionally balanced, safe, and fresh meals.

[2229] (Application example 1)

[2230] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2231] Providing nutritionally balanced meals and delivering them efficiently is an important issue in modern society. However, currently, menu development that appropriately reflects expert feedback, managing the safety and quality of ingredients, applying refrigeration technology to ensure fast delivery and freshness, and even collecting customer feedback and improving products are all fragmented at each stage, resulting in insufficient coordination as a comprehensive system. Furthermore, achieving efficient food delivery using smartphones and other devices remains a challenge.

[2232] 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.

[2233] In this invention, the server includes means for receiving feedback from nutrition experts and creating menus, means for contracting seasonal ingredients from ingredient suppliers and managing their safety and quality, means for applying the latest refrigeration technology to maintain the freshness of received ingredients, means for optimizing delivery routes in cooperation with existing home delivery systems, means for collecting customer feedback via QR codes and reflecting it in product improvements, and means for installing a food delivery application on smartphones to provide nutritionally balanced, health-conscious meals, thereby enabling the efficient provision of nutritionally balanced, healthy meals and increasing customer satisfaction.

[2234] "Nutrition experts" are people with specialized knowledge about the nutritional value and health benefits of foods.

[2235] "Feedback" refers to an evaluation or opinion provided based on specific information or experience.

[2236] A "menu" is a list of specific meals or dishes, specifying the food offerings.

[2237] "Food supplier" refers to a company or individual that produces and supplies food to restaurants and consumers.

[2238] "Seasonal ingredients" refer to ingredients that are harvested in a particular season due to natural conditions.

[2239] A "contract" is a formal agreement between two parties.

[2240] "Safety" refers to the quality of food that does not adversely affect people's health.

[2241] "Quality" evaluates the superior characteristics of food, such as taste, freshness, and nutritional value.

[2242] "Freshness" refers to the degree of freshness of food between the time it is harvested and the time it is consumed.

[2243] "Cold storage technology" refers to the technology of maintaining food at low temperatures by cooling or freezing, thereby preserving its freshness.

[2244] "Delivery system" refers to a logistics system for delivering goods to a designated location.

[2245] "Delivery route" refers to the route or path planned for efficient delivery of goods.

[2246] "Optimization" refers to adjusting or improving something to achieve the best results for a particular purpose.

[2247] A "QR code" is a type of two-dimensional barcode that allows information to be read quickly.

[2248] "Customer feedback" refers to the means of collecting customer ratings and opinions about products and services.

[2249] "Product improvement" refers to the process of improving a product or service based on collected feedback.

[2250] A "food delivery application" is mobile software that allows you to order food online and have it delivered.

[2251] A "smartphone" refers to a portable information device with advanced computing power and connectivity.

[2252] The system for implementing this invention includes a server that receives feedback from nutrition experts and creates menus, terminals and servers equipped with means for contracting seasonal ingredients provided by food suppliers and managing their safety and quality, equipment that applies the latest refrigeration technology to maintain the freshness of received ingredients, means for optimizing delivery routes in cooperation with existing home delivery systems, and a mechanism for collecting customer feedback via QR codes and reflecting it in product improvements.

[2253] 1. Collaboration with nutrition experts

[2254] The server creates menus based on feedback from nutrition experts. Nutrition experts enter their feedback through a dedicated interface, which is then sent to the server. The server receives this feedback, compares it with its internal nutrition database, and generates new, nutritionally balanced menus. This information is also stored in a database for future reference.

[2255] 2. Ingredient contracts and management

[2256] The terminal collects information about ingredients provided by producers and sends it to a server. The server uses this information to conclude contracts with producers and registers the contract information in a management system. This management system constantly monitors the safety and quality of ingredients and provides feedback as needed.

[2257] 3. Cooling technology to maintain freshness

[2258] The received ingredients are stored in a device that uses the latest refrigeration technology to maintain freshness. The terminal regularly monitors the freshness of the ingredients and sends the information to the server. The server uses this information to optimize the settings of the refrigeration device and adjust it to maintain the maximum freshness of the ingredients.

[2259] 4. Logistics optimization

[2260] The server works with existing delivery systems to calculate optimal delivery routes and create delivery schedules. This schedule is sent to the terminals to improve delivery efficiency. The terminals use GPS to track the location of food during delivery and send it to the server in real time.

[2261] 5. Collecting and incorporating customer feedback

[2262] The server also generates a QR code and prints it on the bento packaging. Users can scan the QR code and provide feedback through the application. The server analyzes this feedback, identifies poorly rated items, and uses them to improve the next menu.

[2263] Specific examples

[2264] Specifically, when a nutrition expert suggests a "low-calorie, high-nutrition" menu, the server registers this feedback in a database and compares it to create new recommended menus. The server also sends contract information for fresh tomatoes provided by local farmers in the summer to the server and registers it in the management system. The received tomatoes are stored in a state-of-the-art refrigeration system, and their freshness is regularly monitored via terminals. The server calculates the fastest delivery route and provides the schedule to the terminals, ensuring efficient delivery. When a user scans a QR code and provides feedback that the flavor is "a little bland," the server analyzes the opinion and uses it to improve the next menu.

[2265] Prompt Sentence Examples

[2266] 1. Nutrition experts, please suggest new menu items based on the theme of "high protein, low fat."

[2267] 2. Send the Fresh Tomato contract information to the server and register it in the management system.

[2268] 3. Monitor the freshness of tomatoes and report it to the server.

[2269] 4. Calculate the fastest delivery route and generate a delivery schedule.

[2270] 5. Scan the QR code and give your feedback on the taste of the dish.

[2271] This approach makes it possible to efficiently provide nutritionally balanced and healthy meals and increase customer satisfaction.

[2272] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2273] Step 1:

[2274] The server receives feedback from nutrition experts. As input, it receives feedback data entered by nutrition experts through a dedicated interface. As data processing, the server takes in the feedback data, compares it with an existing nutrition database, and generates a new nutritionally balanced menu. As output, the new recommended menu is registered in the database.

[2275] Step 2:

[2276] The terminal collects information provided by food ingredient suppliers and sends it to the server. The input includes food ingredient information provided by producers. As a data calculation, the terminal sends the information to the server, and the server uses this information to conclude a contract with the producer and registers the contract information in the management system. As...

Claims

1. A means to receive feedback from nutrition experts and create menus; A means of contracting seasonal ingredients from food suppliers and controlling their safety and quality; The means to apply the latest refrigeration technology to maintain the freshness of received ingredients; A means to optimize delivery routes by linking with existing delivery systems, A means of collecting customer feedback through QR codes and reflecting it in product improvements, A system including:

2. 10. The system of claim 1, further comprising means for cross-checking expert feedback with a nutrition database to generate menu recommendations.

3. 2. The system according to claim 1, further comprising means for monitoring the state of the food material in the means for maintaining the freshness of the food material using refrigeration technology and transmitting the information to the server.

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