System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving order information; means for storing the received order information in a database; means comprising a AI engine for optimizing cooking and catering procedures based on the order information; means for transmitting the optimized cooking and catering procedures to display terminals; and terminals for displaying the optimized cooking and catering procedures.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] The restaurant industry is facing issues such as labor shortages and increasingly complicated operations. Dispensing operations, in particular, rely heavily on experience and intuition, and vary from store to store, making efficient operations difficult. This reduces table turnover and hinders sales growth. To address these issues, it is necessary to standardize and streamline dispensing operations, increase table turnover, and boost sales. [Means for solving the problem]

[0005] The present invention provides a system including a means for receiving order information, a means for storing the received order information in a database, a means having an AI engine for optimizing cooking procedures and serving procedures based on the order information, a means for transmitting the optimized cooking procedures and serving procedures to a display terminal, and a terminal for displaying the optimized cooking procedures and serving procedures. Furthermore, by combining this system with a means for collecting sales data and inventory data and a means having a business intelligence tool for analyzing the collected data, it is possible to support business efficiency and strategic decision-making, thereby increasing table turnover and boosting sales.

[0006] "Order information" refers to information related to ordering at a restaurant, such as the customer's order details and table number.

[0007] A "database" refers to a system that systematically stores and manages information such as order information, sales data, and inventory data.

[0008] An "AI engine" is a program that uses artificial intelligence to analyze data and calculate optimal cooking and serving procedures.

[0009] "Display terminal" refers to a device, such as a tablet or smartphone, used by kitchen and serving staff to display optimized procedures.

[0010] "Sales data" refers to information relating to the revenue generated by a store, including, for example, the number of items sold and the sales amount.

[0011] "Inventory data" refers to information about the quantity of goods or materials held by a store.

[0012] "Business intelligence tools" refers to software that analyzes collected sales and inventory data to support business improvement and strategic decision-making.

[0013] "Cooking instructions" refers to the specific steps and procedures for preparing each dish.

[0014] "Serving procedure" refers to the specific order and steps for delivering the finished food to the customer's table.

[0015] "Dessert work" refers to the work of checking the quality of cooked food and giving instructions for its proper serving. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] This invention is a system that uses AI to optimize cooking and serving procedures based on order information in restaurants, thereby improving table turnover. This system aims to improve business efficiency by inputting and managing order information, and having AI calculate and display the optimal cooking and serving procedures.

[0038] System Configuration

[0039] The system includes the following elements:

[0040] 1. Means of receiving order information

[0041] 2. A means of storing received order information in a database

[0042] 3. An AI engine to optimize cooking and serving procedures based on order information

[0043] 4. Means for transmitting optimized cooking and serving instructions to the display device

[0044] 5. A device that displays optimized cooking and serving procedures

[0045] 6. Means of collecting sales and inventory data

[0046] 7. Business intelligence tools to analyze the collected data

[0047] Operation flow

[0048] 1. Receiving and storing order information

[0049] The user (staff member) uses the POS system to input order information from customers. For example, an order for "hamburger steak, salad, and drink" is received from table 1. The terminal sends the input order information to the server in real time. The server stores the received order information in a database.

[0050] 2. Optimizing cooking and serving procedures

[0051] The server sends the saved order information to the AI ​​engine. The server (AI engine) calculates the optimal cooking and serving procedures based on the order information. For example, it suggests "cook the hamburger first, prepare the salad, serve the salad, serve the drink, and serve the hamburger." The calculation results are saved in a database and sent to a display device such as a tablet.

[0052] 3. Display of cooking and serving instructions

[0053] The terminal (tablet) displays the cooking and serving instructions sent from the server in real time. The user (cook) starts cooking according to the instructions on the tablet and then serves the food. For example, the user might cook hamburgers, then prepare salads, then serve salads and drinks, and finally serve the hamburgers.

[0054] 4. Analysis of sales and inventory data

[0055] The server sends daily sales and inventory data to the business intelligence tool for analysis. The user (administrator) uses the business intelligence tool to check the analysis results and plan the next strategy. For example, if the analysis results show that hamburger steak orders are concentrated during a specific time period, the system adjusts staff deployment and inventory to suit that time period.

[0056] Specific examples

[0057] For example, the process when an order for "hamburger steak, salad, and drink" is placed from table 1 will be explained.

[0058] The user (staff member) inputs order information using the POS system, and the terminal sends it to the server in real time. The server saves the order information in a database and sends it to the AI ​​engine. The server (AI engine) calculates the optimal cooking and serving procedures based on the order information, saves the results in the database, and sends them to the display terminal.

[0059] The terminal (tablet) displays the steps: "Start cooking hamburger steak, prepare salad, serve salad, serve drinks, serve hamburger steak," and the user (cooking staff) cooks and serves the food according to the instructions.

[0060] In addition, daily sales and inventory data is collected by the server and analyzed using business intelligence tools. Based on the analysis results, users (administrators) can, for example, allocate staff to serve popular menu items during specific times or adjust inventory.

[0061] In this way, the entire system can operate efficiently through a series of processes, improving table turnover.

[0062] The processing flow will be explained below.

[0063] Step 1:

[0064] A user (staff member) uses the POS system to input order information from a customer. For example, an order for "hamburger steak, salad, and drink" is received from table 1.

[0065] Step 2:

[0066] The terminal sends the input order information to the server in real time. Specifically, data is sent from the POS system to the server via API.

[0067] Step 3:

[0068] The server saves the received order information in the database. At this time, the table number and order details are recorded as new order data.

[0069] Step 4:

[0070] The server sends the order information stored in the database to the AI ​​engine, which then sends the data to optimize cooking and serving procedures based on the order information.

[0071] Step 5:

[0072] The server (AI engine) analyzes the order information and calculates the optimal cooking and serving procedures. For example, it determines a specific procedure such as "prepare the hamburger first, prepare the salad, serve the salad, serve the drink, and serve the hamburger."

[0073] Step 6:

[0074] The server stores the AI ​​engine's calculation results in a database and sends optimized cooking and serving instructions to each display device, allowing each cook and server to receive instructions.

[0075] Step 7:

[0076] The device (tablet) displays optimized cooking and serving procedures in real time, showing specific work instructions such as "Step 1: Start cooking the hamburger steak, Step 2: Prepare the salad."

[0077] Step 8:

[0078] The user (cook) starts cooking according to the instructions on the terminal. For example, he / she cooks a hamburger steak as instructed, and then prepares a salad.

[0079] Step 9:

[0080] The user (the waiter) serves the food according to instructions on the terminal. For example, the salad is served as soon as it is ready, followed by the drinks, and finally the hamburger steak.

[0081] Step 10:

[0082] The server collects daily sales and inventory data, which are automatically recorded in a database.

[0083] Step 11:

[0084] The server sends the collected sales and inventory data to a business intelligence tool for analysis, specifically to determine which menu items are popular during specific times and how inventory is consumed.

[0085] Step 12:

[0086] The user (administrator) uses the business intelligence tool to check the analysis results and plan the next strategy, such as adjusting staff allocation or inventory to suit specific time periods.

[0087] The above is a series of processing steps of the system, which will improve business efficiency and increase sales.

[0088] Example 1

[0089] 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."

[0090] Restaurants are required to streamline the workflow from ordering to cooking and serving, and to improve table turnover. However, when each staff member cooks and serves food at their own discretion, inefficiencies are likely to occur, which can lead to lower customer satisfaction. Furthermore, when sales and inventory data are analyzed manually, there is a problem that the results of the analysis are not reflected in timely business improvements.

[0091] 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.

[0092] In this invention, the server includes means for receiving order information, means for saving the received order information in a database, means for sending the saved order information to an AI engine and optimizing cooking procedures and serving procedures, means for saving the optimized cooking procedures and serving procedures in a database and sending them to a display terminal, means for collecting sales data and inventory data and sending them to a business analysis tool, and means for improving operations and formulating strategies based on the analysis results. This enables optimization of cooking procedures and serving procedures, efficient business execution, timely data analysis, and business improvement.

[0093] "Order information" is data about the food and drinks that customers order at restaurants.

[0094] A "database" is a set of structures for efficiently storing, managing, retrieving, and updating information.

[0095] An "AI engine" is a software component that uses artificial intelligence technology to analyze data and generate optimal results and recommendations.

[0096] A "display terminal" is a digital device that allows a user to visually check information.

[0097] "Sales data" is data that records information about product sales.

[0098] "Inventory data" refers to data that records information about the quantity and condition of stored products.

[0099] A "business analysis tool" is software that analyzes business data and provides the information necessary for business improvement and strategy planning.

[0100] An "optimized cooking procedure" is a procedure in which the steps are optimally arranged to provide food efficiently and quickly.

[0101] An "optimized food serving procedure" is a procedure in which the steps are optimally arranged to efficiently and quickly serve food to customers.

[0102] "Business improvement" is a series of activities undertaken to improve the efficiency and effectiveness of business operations.

[0103] Strategic planning is the process of developing plans to achieve organizational goals from a long-term perspective.

[0104] This invention is a system that optimizes cooking and serving procedures based on order information in restaurants, improving table turnover. This system aims to improve operational efficiency by inputting and managing order information, and using AI to calculate and display the optimal cooking and serving procedures.

[0105] System Configuration

[0106] The system includes the following elements:

[0107] 1. Means of receiving order information

[0108] The user (staff member) uses the POS system to input customer order information. For example, "Table 1 orders a hamburger steak, salad, and drink."

[0109] 2. A way to store order information in a database

[0110] The terminal transmits the input order information to the server in real time. The terminal transmits the order information to the server as an HTTP request via network communication.

[0111] The server stores the received order information in a database, which uses SQL queries to store the order information efficiently.

[0112] 3. A means to send saved order information to an AI engine to optimize cooking and serving procedures

[0113] The server sends the saved order information to an AI engine, which is implemented using frameworks such as TensorFlow and PyTorch.

[0114] The server (AI engine) calculates the optimal cooking and serving sequence based on the order information. For example, it calculates a sequence such as "prepare the hamburger first, prepare the salad, serve the salad, serve the drink, and serve the hamburger."

[0115] 4. A means for storing optimized cooking and serving procedures in a database and transmitting them to a display terminal.

[0116] The server stores the calculation results in a database and sends them to the display terminal. The server then uses network communication to return the result data to the terminal as an HTTP response.

[0117] 5. A device that displays optimized cooking and serving procedures

[0118] The terminal (tablet) displays the cooking and serving instructions sent from the server in real time. The terminal provides a visually easy-to-understand GUI, allowing users to carry out the instructions efficiently.

[0119] 6. A means of collecting sales and inventory data and transmitting it to business analytics tools

[0120] The server collects daily sales and inventory data and sends it to a business analytics tool, such as Tableau or Power BI.

[0121] The user (administrator) uses the tool to check the analysis results and plan the next strategy. For example, if it is found that hamburger steak orders are concentrated during a specific time period, the system will adjust staff allocation and inventory to suit that time period.

[0122] Specific examples

[0123] For example, if table 1 orders a hamburger steak, salad, and drink, the flow is as follows:

[0124] 1. The user (staff member) inputs "hamburger steak, salad, drink" into the POS system, and the terminal sends this information to the server in real time.

[0125] 2. The server saves the order information in the database and simultaneously sends it to the AI ​​engine.

[0126] 3. The server (AI engine) calculates "cook hamburger first, prepare salad, serve salad, serve drink, serve hamburger", saves the results in a database, and sends them to the display terminal.

[0127] 4. The terminal (tablet) displays the calculated procedure to the user, and the user (cooking staff) cooks and serves the food according to the instructions.

[0128] 5. The server sends daily sales and inventory data to a business analysis tool, and the user (administrator) uses the tool to plan the next strategy.

[0129] This ensures efficient operation of the entire system and optimizes the process from ordering to cooking and serving, resulting in improved table turnover and customer satisfaction.

[0130] Prompt Sentence Examples

[0131] Examples of prompts to input to a generative AI model include:

[0132] "Please explain the functions and operation of an AI system that optimizes cooking and serving procedures based on restaurant order information."

[0133] By using this prompt, the AI ​​model can provide appropriate information about the specific processes and functions of the system.

[0134] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0135] Step 1:

[0136] A user (staff member) uses the POS system to input order information from a customer. For example, "Table 1 orders a hamburger steak, salad, and drink." The input order information is formatted based on the POS system's interface.

[0137] Step 2:

[0138] The terminal sends the entered order information to the server in real time. The terminal wraps the order information in a packet as an HTTP request and sends it to the server over the network. The input is the order information entered by the user, and the output is a data packet sent to the server. The data is sent according to the network transmission and protocol.

[0139] Step 3:

[0140] The server stores the received order information in a database. The server parses the order information and generates SQL queries to insert it into the database in the appropriate format. The database has a structure that allows information to be managed efficiently and accessed quickly. The input is the order information received by the server, and the output is the information stored in the database.

[0141] Step 4:

[0142] The server sends the saved order information to an AI engine, which is implemented using frameworks such as TensorFlow and PyTorch. The input is the order information, and the output is optimized cooking and serving procedures. The AI ​​engine analyzes the data in real time and calculates the optimal procedure based on the order information.

[0143] Step 5:

[0144] The server (AI engine) calculates optimized cooking and serving procedures and stores the results in a database. The calculation results are adjusted based on specific algorithms to maximize data and work efficiency. The input is the data analyzed by the AI ​​engine, and the output is the optimized procedures stored in the database.

[0145] Step 6:

[0146] The server sends the optimized cooking and serving instructions to the display terminal. Here too, network communication occurs, and the resulting data is returned to the display terminal as an HTTP response. The input is the optimized instructions stored in the database, and the output is the data sent to the display terminal.

[0147] Step 7:

[0148] The terminal (tablet) displays the cooking and serving procedures sent from the server in real time. The terminal provides a visual GUI so that the user can efficiently check the instructions. The input is the optimization procedure data sent from the server, and the output is the information displayed on the tablet.

[0149] Step 8:

[0150] The user (cook) starts cooking according to the instructions on the tablet. For example, first cook the hamburger steak and then prepare the salad. The input is the optimization procedure displayed on the tablet, and the output is the cooked dish.

[0151] Step 9:

[0152] The user (cook) serves the food according to the displayed procedure. For example, they serve salad and drinks, and then serve the hamburger steak last. The input is the serving procedure displayed on the tablet, and the output is the food served to the customer.

[0153] Step 10:

[0154] The server sends daily sales and inventory data to a business analysis tool for analysis. The business analysis tool uses tools such as Tableau or Power BI. The input is store sales and inventory data, and the output is analysis results and reports.

[0155] Step 11:

[0156] The user (administrator) uses the tool to check the analysis results and plan the next strategy. For example, if it is found that hamburger steak orders are concentrated during a specific time period, the user can adjust staff deployment and inventory to suit that time period. The input is the analysis results obtained from the business analysis tool, and the output is an improved business strategy.

[0157] (Application example 1)

[0158] 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."

[0159] For restaurants and food delivery services, efficiently optimizing the entire process, from order receipt to cooking, serving, and even delivery, is essential to improving operational efficiency and customer satisfaction. Collecting and analyzing related data is also essential for strategic operational improvements and inventory management. However, conventional systems do not adequately provide the means to comprehensively and efficiently optimize these processes, and many aspects rely on manual work, resulting in inefficiencies. Therefore, there is a need for a system that not only optimizes cooking and serving procedures based on order information, but also improves the efficiency of delivery operations.

[0160] 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.

[0161] In this invention, the server includes means for receiving order information, means for storing the received order information in a database, means having an artificial intelligence engine for optimizing cooking procedures and serving procedures based on the order information, means for transmitting the optimized cooking procedures and serving procedures to a display terminal, a terminal for displaying the optimized cooking procedures and serving procedures, means for optimizing cooking procedures and packaging procedures based on the order information, and means for calculating a delivery route. This enables restaurants and delivery services to improve operational efficiency and provide customers with fast and accurate service.

[0162] "Order information" is data including the details of an order from a customer.

[0163] "Means for receiving" refers to a device or method for receiving data or information from an external source.

[0164] A "database" is an information management system designed to organize and store digital information so that it can be efficiently searched and retrieved.

[0165] "Storage means" means a device or method for recording and storing received data in a secure and reliable manner.

[0166] An "artificial intelligence engine" is software or hardware that uses machine learning and data analysis techniques to solve specific problems.

[0167] An "optimization method" is a method of calculation or adjustment to perform a series of tasks or procedures efficiently and effectively.

[0168] A "display terminal" is a device for visually displaying digital information.

[0169] A "transmission means" is a device or method for moving data or information from one place to another.

[0170] A "display terminal" is a device that visually displays received information to a user.

[0171] "Packaging procedures" are specific procedures for properly packing a food or product into a container or packaging.

[0172] A "delivery route" is the most efficient route for delivering goods.

[0173] "Sales data" is information relating to sales performance during a specific period.

[0174] "Inventory data" is information about the quantity of goods or raw materials currently in stock.

[0175] "Business intelligence tools" are software and methods used to collect, integrate, and analyze corporate data to support decision-making.

[0176] "Business improvement" refers to reviewing the means and methods for making current business processes more efficient and effective.

[0177] "Strategic planning" is the process of formulating policies and plans for a company or organization to achieve its goals.

[0178] The present invention is a system that optimizes cooking procedures, serving procedures, packaging procedures, and delivery routes based on order information, and is intended to improve operational efficiency in food delivery services in particular. Specific embodiments of the system are described below.

[0179] System Configuration

[0180] The system of the present invention includes the following elements:

[0181] 1. Means of receiving order information

[0182] Use a smartphone application to receive order information from customers.

[0183] Software used: Real-time database (e.g. Firebase Firestore)

[0184] 2. A means of storing received order information in a database

[0185] The received order information is stored in a cloud database.

[0186] Software used: Firebase, Amazon DynamoDB

[0187] 3. An artificial intelligence engine to optimize cooking and serving procedures based on order information

[0188] We will implement an AI model that calculates the optimal cooking and serving procedures based on order information.

[0189] Software used: TensorFlow, Python

[0190] 4. Means for transmitting optimized cooking and serving instructions to the display device

[0191] Optimized procedures are sent to the display devices of cooking and serving staff.

[0192] Software used: Node.js, Real-time Database

[0193] 5. A device that displays optimized cooking and serving procedures

[0194] Tablet and smartphone applications used by kitchen and serving staff.

[0195] Software used: React Native

[0196] 6. A means to optimize cooking and packaging procedures based on order information

[0197] AI optimizes cooking and packaging procedures and provides instructions to kitchen staff.

[0198] Software used: TensorFlow, Python

[0199] 7. A way to calculate delivery routes

[0200] It has the ability to calculate routes to complete deliveries in the shortest time possible.

[0201] Software used: Google Maps API, GraphHopper

[0202] Explanation of program processing

[0203] The server receives order information via a smartphone app or POS system. This information is stored in a real-time database, and the cooking and serving procedures are calculated by an artificial intelligence engine. The AI ​​engine uses machine learning with TensorFlow and Python to derive the optimal procedure. The calculation results are sent to the display device via the server.

[0204] On the display device, a smartphone or tablet app using React Native displays real-time instructions to the kitchen and serving staff, and uses Node.js and a real-time database to synchronize data with the server.

[0205] In addition, the server uses Google Maps API and GraphHopper to calculate the optimal delivery route and contact the delivery staff, thereby improving delivery efficiency.

[0206] Specific examples

[0207] For example, when a customer orders a hamburger and fries, the smartphone app first receives the order information and stores it in Firebase Firestore. The AI ​​engine uses that information to calculate the optimal cooking and packaging procedures and sends the results to the display device. The chef cooks the food while checking the tablet and packages it in the optimal order. The delivery staff then quickly delivers the food by following the optimized route provided by the Google Maps API.

[0208] Prompt Sentence Examples

[0209] "Food delivery optimization application: How do you design an AI model to optimize the process when a user places an order? For example, what algorithm uses order data to optimize the cooking order and calculate the delivery route?"

[0210] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0211] Step 1:

[0212] The server receives order information from users (customers) via a smartphone app. The input is the order details entered by the customer into the app, and the output is the received order information. Specifically, the smartphone app enters the order information, which is then sent to Firebase Firestore, where it is received by the server and stored in the database.

[0213] Step 2:

[0214] The server saves the received order information in a database (Firebase Firestore). The input is the order information, and the output is the order information saved in the database. Specifically, the received data is saved in the cloud database in real time.

[0215] Step 3:

[0216] The server uses an artificial intelligence engine to calculate the optimal cooking and serving procedures based on the stored order information. The input is the order information stored in the database, and the output is the optimized cooking and serving procedures. Specifically, machine learning is performed using TensorFlow to derive the optimal procedures.

[0217] Step 4:

[0218] The server sends the optimized cooking and serving instructions to the display terminal. The input is the optimized cooking and serving instructions, and the output is the optimization information sent to the display terminal. Specifically, it uses Node.js to connect to a real-time database and transmits the calculation results to a tablet or smartphone.

[0219] Step 5:

[0220] The terminal displays the optimized cooking and serving instructions. The input is the optimization information sent from the server, and the output is the cooking and serving instructions displayed on the terminal. In concrete terms, a user interface is built using React Native, and instructions are displayed on the display terminal in real time.

[0221] Step 6:

[0222] The server optimizes cooking and packaging procedures based on order information. The input is the order information stored in the database, and the output is the optimized cooking and packaging procedures. Specifically, a machine learning model using TensorFlow calculates the optimal procedure, including packaging.

[0223] Step 7:

[0224] The server calculates the delivery route. The input is the delivery destination information and the current location information, and the output is the optimized delivery route. Specifically, it calculates the shortest route using the Google Maps API and GraphHopper and notifies the delivery staff.

[0225] Step 8:

[0226] The terminal cooks, packages, serves, and delivers food according to the optimized procedure displayed on the display terminal. The input is the displayed optimized procedure and route information, and the output is the status of the actual cooking, packaging, serving, and delivery. In concrete terms, the cooking staff cooks and packages food according to the instructions on the tablet, and the delivery staff delivers food according to the displayed route.

[0227] 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.

[0228] This invention is a system that uses AI to optimize cooking and serving procedures based on order information in restaurants, and also recognizes user emotions to adjust operations. This system not only inputs and manages order information, and the AI ​​calculates and displays the optimal cooking and serving procedures, but also recognizes the user's emotional state and makes adjustments based on that, improving the quality of service.

[0229] System Configuration

[0230] The system includes the following elements:

[0231] 1. Means of receiving order information

[0232] 2. A means of storing received order information in a database

[0233] 3. An AI engine to optimize cooking and serving procedures based on order information

[0234] 4. Means for transmitting optimized cooking and serving instructions to the display device

[0235] 5. A device that displays optimized cooking and serving procedures

[0236] 6. Means of collecting sales and inventory data

[0237] 7. Business intelligence tools to analyze the collected data

[0238] 8. Emotion engine that recognizes user emotions

[0239] 9. A means to store data obtained from the emotion engine in a database and adjust cooking and serving procedures as needed.

[0240] Operation flow

[0241] 1. Receiving and storing order information

[0242] A user (staff member) uses the POS system to input order information from a customer. For example, an order for "hamburger steak, salad, and drink" is received from table 1. The terminal sends the input order information to the server in real time. The server then stores the received order information in a database.

[0243] 2. Optimizing cooking and serving procedures

[0244] The server sends the order information stored in the database to the AI ​​engine. The server (AI engine) analyzes the order information and calculates the optimal cooking and serving procedures. For example, it suggests "cook the hamburger first, prepare the salad, serve the salad, serve the drink, and serve the hamburger." The calculation results are stored in the database and sent to a display device such as a tablet.

[0245] 3. Emotion recognition and adjustment using an emotion engine

[0246] The device (tablet) and sensors capture the customer's facial expressions and tone of voice and send this data to the server. The server (emotion engine) analyzes the data and recognizes the user's emotional state. For example, it identifies whether the customer is satisfied or dissatisfied. The server stores the data obtained from the emotion engine in a database.

[0247] 4. Display and adjust cooking and serving instructions

[0248] The device (tablet) displays optimized cooking and serving procedures in real time. The user (cook) begins cooking by following the instructions on the tablet. For example, they cook a hamburger steak as instructed, and then prepare a salad.

[0249] The server takes into account the data from the emotion engine and adjusts cooking and serving procedures as needed, for example, changing the instructions to prioritize serving procedures if a customer is unhappy.

[0250] 5. Analysis of sales and inventory data

[0251] The server sends daily sales and inventory data to the business intelligence tool for analysis. The user (administrator) uses the business intelligence tool to check the analysis results and plan the next strategy. For example, if the analysis results show that hamburger steak orders are concentrated during a specific time period, the administrator can adjust staff deployment and inventory to suit that time period.

[0252] Specific examples

[0253] For example, the process when an order for "hamburger steak, salad, and drink" is placed from table 1 will be explained.

[0254] The user (staff member) enters order information using the POS system, and the terminal sends it to the server in real time. The server saves the order information in a database and sends it to the AI ​​engine. The server (AI engine) calculates the optimal cooking and serving procedures based on the order information, saves the results in the database, and sends them to the display terminal.

[0255] The terminal (tablet) displays the procedure: "Start cooking hamburger steak, prepare salad, serve salad, serve drinks, serve hamburger steak," and the user (cooking staff) cooks and serves the steak according to the instructions.

[0256] The device (tablet) and sensors capture the customer's facial expressions and tone of voice and send the data to the server (emotion engine). The server (emotion engine) analyzes the data and, if it determines that the customer is dissatisfied, for example, changes the server's instructions to prioritize the serving procedure.

[0257] The server collects daily sales and inventory data and analyzes it using business intelligence tools. Based on the analysis results, users (administrators) can allocate staff and adjust inventory to match popular menu items during specific times.

[0258] In this way, incorporating emotion recognition functionality can increase customer satisfaction, improve business efficiency, and increase sales.

[0259] The processing flow will be explained below.

[0260] Step 1:

[0261] A user (staff member) uses the POS system to input order information from a customer. For example, an order for "hamburger steak, salad, and drink" is received from table 1.

[0262] Step 2:

[0263] The terminal sends the input order information to the server in real time. Specifically, data is sent from the POS system to the server via API.

[0264] Step 3:

[0265] The server saves the received order information in the database. At this time, the table number and order details are recorded as new order data.

[0266] Step 4:

[0267] The server sends the order information stored in the database to the AI ​​engine, which then sends the data to optimize cooking and serving procedures based on the order information.

[0268] Step 5:

[0269] The server (AI engine) analyzes the order information and calculates the optimal cooking and serving procedures. For example, it determines a specific procedure such as "prepare the hamburger first, prepare the salad, serve the salad, serve the drink, and serve the hamburger."

[0270] Step 6:

[0271] The server stores the AI ​​engine's calculation results in a database and sends optimized cooking and serving instructions to each display device, allowing each cook and server to receive instructions.

[0272] Step 7:

[0273] The device (tablet) displays optimized cooking and serving procedures in real time, showing specific work instructions such as "Step 1: Start cooking the hamburger steak, Step 2: Prepare the salad."

[0274] Step 8:

[0275] The user (cook) starts cooking according to the instructions on the terminal. For example, he / she cooks a hamburger steak as instructed, and then prepares a salad.

[0276] Step 9:

[0277] The user (the waiter) serves the food according to instructions on the terminal. For example, the salad is served as soon as it is ready, followed by the drinks, and finally the hamburger steak.

[0278] Step 10:

[0279] The device (tablet) and sensors capture the customer's facial expressions and tone of voice and send this data to the server. Specifically, a camera and microphone are used.

[0280] Step 11:

[0281] The server (emotion engine) analyzes the transmitted emotion data and recognizes the user's emotional state, for example, identifying whether the customer is satisfied or dissatisfied.

[0282] Step 12:

[0283] The server stores the emotion engine's recognition results in a database, and the emotion data is used to track customer satisfaction in real time.

[0284] Step 13:

[0285] The server adjusts cooking and serving procedures based on emotion recognition data. For example, if a customer expresses dissatisfaction, it changes instructions to prioritize serving procedures.

[0286] Step 14:

[0287] The server collects daily sales and inventory data, which are automatically recorded in a database.

[0288] Step 15:

[0289] The server sends the collected sales and inventory data to a business intelligence tool for analysis, specifically to determine which menu items are popular during specific times and how inventory is consumed.

[0290] Step 16:

[0291] The user (administrator) uses the business intelligence tool to check the analysis results and plan the next strategy, such as adjusting staff allocation or inventory to suit specific time periods.

[0292] The above is a series of processing steps in a system incorporating an emotion engine, which can increase customer satisfaction, improve business efficiency, and increase sales.

[0293] Example 2

[0294] 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."

[0295] Efficient operations and improved customer satisfaction are key challenges for modern restaurants. However, managing order information and optimizing cooking and serving procedures requires a lot of effort, and flexible responses based on customer sentiment are required. As a result, current systems have limitations, making it difficult to provide efficient and highly satisfying service.

[0296] 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.

[0297] In this invention, the server includes means for receiving order information, means for saving the received order information in a database, means having an artificial intelligence engine for optimizing cooking procedures and serving procedures based on the order information, means for sending the optimized cooking procedures and serving procedures to a display terminal, a display device for displaying the optimized cooking procedures and serving procedures, means having an emotion engine for recognizing the user's emotions and saving emotion data in a database, and means for adjusting the cooking procedures and serving procedures based on the emotion data. This enables efficient management of order information, optimization of cooking procedures and serving procedures using AI, and flexible operation according to customer emotions.

[0298] "Order information" is data that indicates the details of an order from a customer at a restaurant.

[0299] "Means for receiving" refers to the devices and technologies used to acquire order information and input it into the system.

[0300] "Database" refers to an information system for storing and managing received order information and emotion data.

[0301] An "artificial intelligence engine" refers to software and algorithms that calculate and analyze optimal cooking and serving procedures based on order information.

[0302] "Display terminal" refers to a device for visually displaying calculated cooking and serving instructions to a user.

[0303] "Display device" refers to a screen or device for displaying optimized cooking and serving instructions.

[0304] "User emotions" refers to the emotional state of customers, such as satisfaction or dissatisfaction.

[0305] An "emotion engine" refers to software or algorithms that analyze users' emotions and generate emotional data.

[0306] "Emotion data" refers to data that indicates the emotional state of a customer analyzed by the emotion engine.

[0307] "Adjustment means" refers to techniques and methods for changing cooking and serving procedures based on emotional data to provide optimal service.

[0308] "Sales data" refers to data that indicates information about daily sales.

[0309] "Inventory Data" refers to data that indicates information about inventory items and their quantities.

[0310] "Business intelligence tools" refers to the technology and software used to analyze collected data and derive business insights and strategies.

[0311] "Business improvement" refers to improvement activities aimed at improving business efficiency and quality.

[0312] "Strategic planning" refers to the activity of determining specific plans and policies to achieve business objectives.

[0313] MODE FOR CARRYING OUT THE INVENTION

[0314] This invention is a system that uses AI to optimize cooking and serving procedures based on order information in restaurants, and also recognizes user emotions to adjust operations. This system not only inputs and manages order information, and the AI ​​calculates and displays the optimal cooking and serving procedures, but also recognizes the user's emotional state and makes adjustments based on that, improving the quality of service.

[0315] System Configuration

[0316] The system includes the following elements:

[0317] 1. Means for receiving order information: Using an input device such as a POS system.

[0318] 2. Means for storing received order information in a database: A database server is used to manage order information.

[0319] 3. Means having an artificial intelligence engine for optimizing cooking procedures and serving procedures based on order information: an AI engine that implements a machine learning algorithm.

[0320] 4. Means for transmitting optimized cooking procedures and serving procedures to a display terminal: Information is transmitted to a display device such as a tablet via network communication.

[0321] 5. Display devices that show optimized cooking and serving procedures: tablets and projectors are used.

[0322] 6. Means having an emotion engine for recognizing the user's emotions and storing the emotion data in a database: data is acquired using a camera or microphone, and software implementing an emotion recognition algorithm is used.

[0323] 7. A means for adjusting cooking and serving procedures based on emotional data: A software module that works in conjunction with the AI ​​engine to make adjustments.

[0324] 8. Means of collecting sales and inventory data: Software that connects to a database and collects sales and inventory information.

[0325] 9. Business intelligence means to analyze collected data: Using analytical tools (e.g., business intelligence software).

[0326] Operation flow

[0327] For example, the process when an order for "hamburger steak, salad, and drink" is placed from table 1 will be explained.

[0328] The user (staff member) enters order information using the POS system, and the terminal sends it to the server in real time. The server saves the order information in a database and sends it to the AI ​​engine. The server (AI engine) calculates the optimal cooking and serving procedures based on the order information, saves the results in the database, and sends them to the display terminal.

[0329] The terminal (tablet) displays the procedure: "Start cooking hamburger steak, prepare salad, serve salad, serve drinks, serve hamburger steak," and the user (cooking staff) cooks and serves the steak according to the instructions.

[0330] The device (tablet) and sensors capture the customer's facial expressions and tone of voice and send the data to the server (emotion engine). The server (emotion engine) analyzes the data and, if it determines that the customer is dissatisfied, for example, changes the server's instructions to prioritize the serving procedure.

[0331] The server collects daily sales and inventory data and analyzes it using business intelligence tools. Based on the analysis results, users (administrators) can allocate staff and adjust inventory to match popular menu items during specific times.

[0332] Prompt Sentence Examples

[0333] "Could you explain a system in which AI calculates the optimal cooking and serving procedures based on order information in a restaurant, and also recognizes customer emotions and adjusts operations accordingly?"

[0334] In this way, incorporating emotion recognition functionality can increase customer satisfaction, improve business efficiency, and increase sales.

[0335] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0336] The flow of this system's program processing

[0337] Step 1: Receiving and storing order information

[0338] A user (staff member) uses the POS system to input order information from a customer. For example, "Table 1 orders a hamburger steak, salad, and drink."

[0339] Input: Customer order information

[0340] The terminal sends the entered order information to the server in real time. When an order is entered, the terminal immediately sends the information to the server.

[0341] Output: Order information data

[0342] The server stores the received order information in a database, and this captured data is used in subsequent processing steps.

[0343] Step 2: Optimize cooking and serving procedures

[0344] The server sends the order information stored in the database to the AI ​​engine, which then sends the order details to the AI ​​engine, which then begins the next analysis phase.

[0345] Input: Saved order information data

[0346] The server (AI engine) analyzes the received order information and calculates the optimal cooking and serving sequence, such as "cook the hamburger steak first, prepare the salad, serve the salad, serve the drink, and then serve the hamburger steak last."

[0347] Output: Optimized cooking and serving procedures

[0348] The server stores the calculated results in a database and sends the information to a display device such as a tablet.

[0349] Step 3: Emotion recognition and regulation by the emotion engine

[0350] The device (tablet) and sensors capture the customer's facial expressions and tone of voice and send this data to the server. For example, the tablet's built-in camera and microphone capture the customer's reactions.

[0351] Input: Customer's facial expression data and voice data

[0352] The server (emotion engine) analyzes the transmitted data and recognizes the user's emotional state. If the customer is smiling, it is determined to be satisfied, and if they have a stern expression, it is determined to be dissatisfied.

[0353] Output: Emotion data

[0354] The server stores the data obtained from the emotion engine in a database, which is later used to coordinate operations.

[0355] Step 4: View and adjust cooking and serving instructions

[0356] The device (tablet) displays optimized cooking and serving procedures in real time, such as "Start cooking hamburger steak, prepare salad, serve salad, serve drink, serve hamburger steak."

[0357] Input: Optimized cooking and serving procedures

[0358] The user (cook) starts cooking by following the instructions on the tablet. After cooking the hamburger steak as instructed, the user prepares the salad and then serves the food.

[0359] Output: Execute cooking and serving

[0360] The server takes into account the data from the emotion engine and adjusts cooking and serving procedures as needed, for example, changing instructions to prioritize serving procedures if a customer is unhappy.

[0361] Step 5: Analyze sales and inventory data

[0362] The server sends daily sales and inventory data to the business intelligence tool for analysis, allowing users to understand sales trends and inventory status.

[0363] Input: Sales data and inventory data

[0364] The user (administrator) uses a business intelligence tool to check the analysis results and plan the next strategy. For example, if it turns out that hamburger steak orders are concentrated during lunchtime, they can adjust staff allocation and inventory to suit that time period.

[0365] Output: Business improvement plans and strategies

[0366] (Application example 2)

[0367] 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."

[0368] While conventional food delivery systems can manage order information and optimize cooking and serving procedures, they are unable to grasp customers' emotional states in real time and adjust services accordingly. This makes it difficult to increase customer satisfaction and limits the efficiency of operations and sales. Therefore, there is a need for a system that can recognize customers' emotions and respond flexibly based on them.

[0369] 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 order information, means for saving the received order information in a database, means having an AI engine for optimizing cooking procedures and serving procedures based on the order information, means for transmitting the optimized cooking procedures and serving procedures to the display terminal, an emotion recognition engine for recognizing the emotional state of the customer, means for saving data obtained from the emotion recognition engine in a database and adjusting the cooking procedures and serving procedures, means for collecting sales data and inventory data, and means having a business intelligence tool for analyzing the collected data. This makes it possible to grasp the emotional state of customers in real time and improve the quality of service.

[0370] "Order information" is data indicating the details of an order from a customer.

[0371] A "database" is a system for electronically storing and managing information.

[0372] An "AI engine" is a component that uses artificial intelligence to analyze data and optimize specific tasks.

[0373] A "display terminal" is a device for displaying digital information, including tablets and smartphones.

[0374] The "emotion recognition engine" is a component that analyzes the customer's facial expressions and tone of voice to recognize their emotional state.

[0375] A "business intelligence tool" is software that collects and analyzes corporate data and supports decision-making.

[0376] "Sales data" is information relating to revenues earned from the sale of products.

[0377] "Inventory data" is information about the quantity and condition of goods and materials in a store.

[0378] "Cooking procedures" are the specific steps and methods for preparing a dish.

[0379] "Serving procedure" refers to the process or method for serving the finished food to the customer.

[0380] System Configuration

[0381] This invention is an AI system that receives order information from customers and optimizes cooking and serving procedures based on that information. It can also improve service quality by recognizing customer emotions and making adjustments based on those emotions. The system includes the following components:

[0382] 1. Means of receiving order information

[0383] 2. A means of storing received order information in a database

[0384] 3. An AI engine to optimize cooking and serving procedures based on order information

[0385] 4. Means for transmitting optimized cooking and serving instructions to the display device

[0386] 5. A device that displays optimized cooking and serving procedures

[0387] 6. Means of collecting sales and inventory data

[0388] 7. Business intelligence tools to analyze the collected data

[0389] 8. Emotion engine that recognizes customer emotions

[0390] 9. A means to store data obtained from the emotion engine in a database and adjust cooking and serving procedures as needed.

[0391] Hardware and software used

[0392] The system implementation uses the following hardware and software:

[0393] Smartphone (iOS / Android compatible)

[0394] Delivery robot (if needed)

[0395] Cloud server (AWS or Google Cloud)

[0396] AI engine (TensorFlow or PyTorch)

[0397] Emotion Engine (OpenCV and NLTK)

[0398] Database (MySQL or MongoDB)

[0399] Business intelligence tools (Tableau, Power BI)

[0400] Program processing explanation

[0401] 1. Receiving order information

[0402] Users input order information from customers using a smartphone app, and the smartphone then transmits the input order information to a cloud server in real time.

[0403] The server stores the received order information in a database.

[0404] 2. Optimizing cooking and serving procedures

[0405] The server sends the order information stored in the database to the AI ​​engine.

[0406] The server (AI engine) analyzes the order information and calculates the optimal cooking and serving procedures.

[0407] The server stores the calculation results in a database and sends them to the display terminal.

[0408] 3. Emotion recognition

[0409] The devices (smartphones and delivery robots) capture the customer's facial expressions and tone of voice and send this data to a cloud server.

[0410] The server (emotion engine) analyzes the transmitted data and recognizes the customer's emotional state.

[0411] The server stores the data obtained from the emotion engine in a database and adjusts cooking and serving procedures as needed.

[0412] 4. Collection and analysis of sales and inventory data

[0413] The server sends daily sales and inventory data to a business intelligence tool for analysis.

[0414] The user (administrator) uses a business intelligence tool to check the analysis results and plan the next strategy.

[0415] Specific examples

[0416] For example, if a customer uses a smartphone app to order "pizza, salad, and juice," the following process takes place:

[0417] The user enters order information into their smartphone and sends it to the cloud server.

[0418] The order information received by the server is stored in a database and analyzed by an AI engine.

[0419] The server (AI engine) calculates the optimal procedure, such as "prepare the pizza first, prepare the salad, serve the juice, serve the salad, and serve the pizza," and sends it to the display terminal.

[0420] The terminal captures the customer's emotional state and analyzes it on the server (emotion engine).

[0421] If the server determines that the customer is dissatisfied, the server changes the instructions to prioritize the serving procedure.

[0422] Example prompts for generative AI models

[0423] "Generate an AI model that uses this data to calculate optimal cooking and serving procedures, analyzes customer sentiment, and suggests procedures to provide the most satisfying service."

[0424] In this way, by incorporating a customer emotion recognition function, this system can increase customer satisfaction, improve business efficiency, and increase sales.

[0425] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0426] Step 1:

[0427] The user uses a smartphone app to input order information. The input order information includes specific menu items such as "pizza, salad, and juice." The device (smartphone) sends this information to the cloud server in real time. The input data is in text format, and each piece of order information is saved as a field. The operation in this step is to send the input order information to the cloud server.

[0428] Step 2:

[0429] The order information received by the server is saved in a database (MySQL). Specifically, the server analyzes the order information and stores each field (menu items, etc.) in a database table. The input data is the order information, and the saved data is the output. Data processing here involves converting the text-format order information into a database table using SQL statements.

[0430] Step 3:

[0431] The server sends the order information stored in the database to an AI engine (TensorFlow). The AI ​​engine analyzes the order information and calculates the optimal cooking and serving procedures. The input data is the order information extracted from the database, and the output is the calculated cooking and serving procedures. The data calculation here involves the AI ​​engine calculating the cooking and serving procedures based on a predictive model.

[0432] Step 4:

[0433] The server stores the calculation results in a database and sends them to the display device (smartphone or tablet). Specifically, the server stores the optimized cooking and serving instructions received from the AI ​​engine in the database using SQL statements. The input data is the output from the AI ​​engine, and the data stored in the database is the output.

[0434] Step 5:

[0435] The device (smartphone or tablet) captures the customer's facial expression and tone of voice. Specifically, the device's built-in camera and microphone collect facial expression and voice data. The input data is the customer's facial expression and tone of voice, and the captured data is the output.

[0436] Step 6:

[0437] The device sends the captured data to a cloud server. Here, data collected by the camera and microphone is sent to the server in real time. The input data is the captured facial expression and tone of voice data, and the output is the data sent to the server.

[0438] Step 7:

[0439] The server (emotion engine) analyzes the transmitted data and recognizes the customer's emotional state. Specifically, the server uses OpenCV and NLTK to perform facial expression recognition and voice analysis. The input data is facial expression and tone of voice data transmitted from the device, and the output is the recognized emotional state. The data calculation here is emotion analysis based on a machine learning model.

[0440] Step 8:

[0441] The server stores the data obtained from the emotion engine in a database and adjusts the cooking and serving instructions as needed. The input data is the output from the emotion engine, and the output is the adjusted cooking and serving instructions. Data processing here involves calculating and saving new instructions that take the emotion data into account.

[0442] Step 9:

[0443] The server collects daily sales and inventory data, sends it to a business intelligence tool (Tableau), and analyzes it. Specifically, the server collects sales and inventory data from each store and sends it to the analysis tool. The input data is sales and inventory data, and the output is the analysis results from the business intelligence tool.

[0444] 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.

[0445] 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.

[0446] 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.

[0447] [Second embodiment]

[0448] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0449] 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.

[0450] 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).

[0451] 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.

[0452] 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.

[0453] 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).

[0454] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0455] 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.

[0456] 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.

[0457] 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.

[0458] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0459] 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."

[0460] This invention is a system that uses AI to optimize cooking and serving procedures based on order information in restaurants, thereby improving table turnover. This system aims to improve business efficiency by inputting and managing order information, and having AI calculate and display the optimal cooking and serving procedures.

[0461] System Configuration

[0462] The system includes the following elements:

[0463] 1. Means of receiving order information

[0464] 2. A means of storing received order information in a database

[0465] 3. An AI engine to optimize cooking and serving procedures based on order information

[0466] 4. Means for transmitting optimized cooking and serving instructions to the display device

[0467] 5. A device that displays optimized cooking and serving procedures

[0468] 6. Means of collecting sales and inventory data

[0469] 7. Business intelligence tools to analyze the collected data

[0470] Operation flow

[0471] 1. Receiving and storing order information

[0472] The user (staff member) uses the POS system to input order information from customers. For example, an order for "hamburger steak, salad, and drink" is received from table 1. The terminal sends the input order information to the server in real time. The server stores the received order information in a database.

[0473] 2. Optimizing cooking and serving procedures

[0474] The server sends the saved order information to the AI ​​engine. The server (AI engine) calculates the optimal cooking and serving procedures based on the order information. For example, it suggests "cook the hamburger first, prepare the salad, serve the salad, serve the drink, and serve the hamburger." The calculation results are saved in a database and sent to a display device such as a tablet.

[0475] 3. Display of cooking and serving instructions

[0476] The terminal (tablet) displays the cooking and serving instructions sent from the server in real time. The user (cook) starts cooking according to the instructions on the tablet and then serves the food. For example, the user might cook hamburgers, then prepare salads, then serve salads and drinks, and finally serve the hamburgers.

[0477] 4. Analysis of sales and inventory data

[0478] The server sends daily sales and inventory data to the business intelligence tool for analysis. The user (administrator) uses the business intelligence tool to check the analysis results and plan the next strategy. For example, if the analysis results show that hamburger steak orders are concentrated during a specific time period, the system adjusts staff deployment and inventory to suit that time period.

[0479] Specific examples

[0480] For example, the process when an order for "hamburger steak, salad, and drink" is placed from table 1 will be explained.

[0481] The user (staff member) inputs order information using the POS system, and the terminal sends it to the server in real time. The server saves the order information in a database and sends it to the AI ​​engine. The server (AI engine) calculates the optimal cooking and serving procedures based on the order information, saves the results in the database, and sends them to the display terminal.

[0482] The terminal (tablet) displays the steps: "Start cooking hamburger steak, prepare salad, serve salad, serve drinks, serve hamburger steak," and the user (cooking staff) cooks and serves the food according to the instructions.

[0483] In addition, daily sales and inventory data is collected by the server and analyzed using business intelligence tools. Based on the analysis results, users (administrators) can, for example, allocate staff to serve popular menu items during specific times or adjust inventory.

[0484] In this way, the entire system can operate efficiently through a series of processes, improving table turnover.

[0485] The processing flow will be explained below.

[0486] Step 1:

[0487] A user (staff member) uses the POS system to input order information from a customer. For example, an order for "hamburger steak, salad, and drink" is received from table 1.

[0488] Step 2:

[0489] The terminal sends the input order information to the server in real time. Specifically, data is sent from the POS system to the server via API.

[0490] Step 3:

[0491] The server saves the received order information in the database. At this time, the table number and order details are recorded as new order data.

[0492] Step 4:

[0493] The server sends the order information stored in the database to the AI ​​engine, which then sends the data to optimize cooking and serving procedures based on the order information.

[0494] Step 5:

[0495] The server (AI engine) analyzes the order information and calculates the optimal cooking and serving procedures. For example, it determines a specific procedure such as "prepare the hamburger first, prepare the salad, serve the salad, serve the drink, and serve the hamburger."

[0496] Step 6:

[0497] The server stores the AI ​​engine's calculation results in a database and sends optimized cooking and serving instructions to each display device, allowing each cook and server to receive instructions.

[0498] Step 7:

[0499] The device (tablet) displays optimized cooking and serving procedures in real time, showing specific work instructions such as "Step 1: Start cooking the hamburger steak, Step 2: Prepare the salad."

[0500] Step 8:

[0501] The user (cook) starts cooking according to the instructions on the terminal. For example, he / she cooks a hamburger steak as instructed, and then prepares a salad.

[0502] Step 9:

[0503] The user (the waiter) serves the food according to instructions on the terminal. For example, the salad is served as soon as it is ready, followed by the drinks, and finally the hamburger steak.

[0504] Step 10:

[0505] The server collects daily sales and inventory data, which are automatically recorded in a database.

[0506] Step 11:

[0507] The server sends the collected sales and inventory data to a business intelligence tool for analysis, specifically to determine which menu items are popular during specific times and how inventory is consumed.

[0508] Step 12:

[0509] The user (administrator) uses the business intelligence tool to check the analysis results and plan the next strategy, such as adjusting staff allocation or inventory to suit specific time periods.

[0510] The above is a series of processing steps of the system, which will improve business efficiency and increase sales.

[0511] Example 1

[0512] 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."

[0513] Restaurants are required to streamline the workflow from ordering to cooking and serving, and to improve table turnover. However, when each staff member cooks and serves food at their own discretion, inefficiencies are likely to occur, which can lead to lower customer satisfaction. Furthermore, when sales and inventory data are analyzed manually, there is a problem that the results of the analysis are not reflected in timely business improvements.

[0514] 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.

[0515] In this invention, the server includes means for receiving order information, means for saving the received order information in a database, means for sending the saved order information to an AI engine and optimizing cooking procedures and serving procedures, means for saving the optimized cooking procedures and serving procedures in a database and sending them to a display terminal, means for collecting sales data and inventory data and sending them to a business analysis tool, and means for improving operations and formulating strategies based on the analysis results. This enables optimization of cooking procedures and serving procedures, efficient business execution, timely data analysis, and business improvement.

[0516] "Order information" is data about the food and drinks that customers order at restaurants.

[0517] A "database" is a set of structures for efficiently storing, managing, retrieving, and updating information.

[0518] An "AI engine" is a software component that uses artificial intelligence technology to analyze data and generate optimal results and recommendations.

[0519] A "display terminal" is a digital device that allows a user to visually check information.

[0520] "Sales data" is data that records information about product sales.

[0521] "Inventory data" refers to data that records information about the quantity and condition of stored products.

[0522] A "business analysis tool" is software that analyzes business data and provides the information necessary for business improvement and strategy planning.

[0523] An "optimized cooking procedure" is a procedure in which the steps are optimally arranged to provide food efficiently and quickly.

[0524] An "optimized food serving procedure" is a procedure in which the steps are optimally arranged to efficiently and quickly serve food to customers.

[0525] "Business improvement" is a series of activities undertaken to improve the efficiency and effectiveness of business operations.

[0526] Strategic planning is the process of developing plans to achieve organizational goals from a long-term perspective.

[0527] This invention is a system that optimizes cooking and serving procedures based on order information in restaurants, improving table turnover. This system aims to improve operational efficiency by inputting and managing order information, and using AI to calculate and display the optimal cooking and serving procedures.

[0528] System Configuration

[0529] The system includes the following elements:

[0530] 1. Means of receiving order information

[0531] The user (staff member) uses the POS system to input customer order information. For example, "Table 1 orders a hamburger steak, salad, and drink."

[0532] 2. A way to store order information in a database

[0533] The terminal transmits the input order information to the server in real time. The terminal transmits the order information to the server as an HTTP request via network communication.

[0534] The server stores the received order information in a database, which uses SQL queries to store the order information efficiently.

[0535] 3. A means to send saved order information to an AI engine to optimize cooking and serving procedures

[0536] The server sends the saved order information to an AI engine, which is implemented using frameworks such as TensorFlow and PyTorch.

[0537] The server (AI engine) calculates the optimal cooking and serving sequence based on the order information. For example, it calculates a sequence such as "prepare the hamburger first, prepare the salad, serve the salad, serve the drink, and serve the hamburger."

[0538] 4. A means for storing optimized cooking and serving procedures in a database and transmitting them to a display terminal.

[0539] The server stores the calculation results in a database and sends them to the display terminal. The server then uses network communication to return the result data to the terminal as an HTTP response.

[0540] 5. A device that displays optimized cooking and serving procedures

[0541] The terminal (tablet) displays the cooking and serving instructions sent from the server in real time. The terminal provides a visually easy-to-understand GUI, allowing users to carry out the instructions efficiently.

[0542] 6. A means of collecting sales and inventory data and transmitting it to business analytics tools

[0543] The server collects daily sales and inventory data and sends it to a business analytics tool, such as Tableau or Power BI.

[0544] The user (administrator) uses the tool to check the analysis results and plan the next strategy. For example, if it is found that hamburger steak orders are concentrated during a specific time period, the system will adjust staff allocation and inventory to suit that time period.

[0545] Specific examples

[0546] For example, if table 1 orders a hamburger steak, salad, and drink, the flow is as follows:

[0547] 1. The user (staff member) inputs "hamburger steak, salad, drink" into the POS system, and the terminal sends this information to the server in real time.

[0548] 2. The server saves the order information in the database and simultaneously sends it to the AI ​​engine.

[0549] 3. The server (AI engine) calculates "cook hamburger first, prepare salad, serve salad, serve drink, serve hamburger", saves the results in a database, and sends them to the display terminal.

[0550] 4. The terminal (tablet) displays the calculated procedure to the user, and the user (cooking staff) cooks and serves the food according to the instructions.

[0551] 5. The server sends daily sales and inventory data to a business analysis tool, and the user (administrator) uses the tool to plan the next strategy.

[0552] This ensures efficient operation of the entire system and optimizes the process from ordering to cooking and serving, resulting in improved table turnover and customer satisfaction.

[0553] Prompt Sentence Examples

[0554] Examples of prompts to input to a generative AI model include:

[0555] "Please explain the functions and operation of an AI system that optimizes cooking and serving procedures based on restaurant order information."

[0556] By using this prompt, the AI ​​model can provide appropriate information about the specific processes and functions of the system.

[0557] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0558] Step 1:

[0559] A user (staff member) uses the POS system to input order information from a customer. For example, "Table 1 orders a hamburger steak, salad, and drink." The input order information is formatted based on the POS system's interface.

[0560] Step 2:

[0561] The terminal sends the entered order information to the server in real time. The terminal wraps the order information in a packet as an HTTP request and sends it to the server over the network. The input is the order information entered by the user, and the output is a data packet sent to the server. The data is sent according to the network transmission and protocol.

[0562] Step 3:

[0563] The server stores the received order information in a database. The server parses the order information and generates SQL queries to insert it into the database in the appropriate format. The database has a structure that allows information to be managed efficiently and accessed quickly. The input is the order information received by the server, and the output is the information stored in the database.

[0564] Step 4:

[0565] The server sends the saved order information to an AI engine, which is implemented using frameworks such as TensorFlow and PyTorch. The input is the order information, and the output is optimized cooking and serving procedures. The AI ​​engine analyzes the data in real time and calculates the optimal procedure based on the order information.

[0566] Step 5:

[0567] The server (AI engine) calculates optimized cooking and serving procedures and stores the results in a database. The calculation results are adjusted based on specific algorithms to maximize data and work efficiency. The input is the data analyzed by the AI ​​engine, and the output is the optimized procedures stored in the database.

[0568] Step 6:

[0569] The server sends the optimized cooking and serving instructions to the display terminal. Here too, network communication occurs, and the resulting data is returned to the display terminal as an HTTP response. The input is the optimized instructions stored in the database, and the output is the data sent to the display terminal.

[0570] Step 7:

[0571] The terminal (tablet) displays the cooking and serving procedures sent from the server in real time. The terminal provides a visual GUI so that the user can efficiently check the instructions. The input is the optimization procedure data sent from the server, and the output is the information displayed on the tablet.

[0572] Step 8:

[0573] The user (cook) starts cooking according to the instructions on the tablet. For example, first cook the hamburger steak and then prepare the salad. The input is the optimization procedure displayed on the tablet, and the output is the cooked dish.

[0574] Step 9:

[0575] The user (cook) serves the food according to the displayed procedure. For example, they serve salad and drinks, and then serve the hamburger steak last. The input is the serving procedure displayed on the tablet, and the output is the food served to the customer.

[0576] Step 10:

[0577] The server sends daily sales and inventory data to a business analysis tool for analysis. The business analysis tool uses tools such as Tableau or Power BI. The input is store sales and inventory data, and the output is analysis results and reports.

[0578] Step 11:

[0579] The user (administrator) uses the tool to check the analysis results and plan the next strategy. For example, if it is found that hamburger steak orders are concentrated during a specific time period, the user can adjust staff deployment and inventory to suit that time period. The input is the analysis results obtained from the business analysis tool, and the output is an improved business strategy.

[0580] (Application example 1)

[0581] 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."

[0582] For restaurants and food delivery services, efficiently optimizing the entire process, from order receipt to cooking, serving, and even delivery, is essential to improving operational efficiency and customer satisfaction. Collecting and analyzing related data is also essential for strategic operational improvements and inventory management. However, conventional systems do not adequately provide the means to comprehensively and efficiently optimize these processes, and many aspects rely on manual work, resulting in inefficiencies. Therefore, there is a need for a system that not only optimizes cooking and serving procedures based on order information, but also improves the efficiency of delivery operations.

[0583] 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.

[0584] In this invention, the server includes means for receiving order information, means for storing the received order information in a database, means having an artificial intelligence engine for optimizing cooking procedures and serving procedures based on the order information, means for transmitting the optimized cooking procedures and serving procedures to a display terminal, a terminal for displaying the optimized cooking procedures and serving procedures, means for optimizing cooking procedures and packaging procedures based on the order information, and means for calculating a delivery route. This enables restaurants and delivery services to improve operational efficiency and provide customers with fast and accurate service.

[0585] "Order information" is data including the details of an order from a customer.

[0586] "Means for receiving" refers to a device or method for receiving data or information from an external source.

[0587] A "database" is an information management system designed to organize and store digital information so that it can be efficiently searched and retrieved.

[0588] "Storage means" means a device or method for recording and storing received data in a secure and reliable manner.

[0589] An "artificial intelligence engine" is software or hardware that uses machine learning and data analysis techniques to solve specific problems.

[0590] An "optimization method" is a method of calculation or adjustment to perform a series of tasks or procedures efficiently and effectively.

[0591] A "display terminal" is a device for visually displaying digital information.

[0592] A "transmission means" is a device or method for moving data or information from one place to another.

[0593] A "display terminal" is a device that visually displays received information to a user.

[0594] "Packaging procedures" are specific procedures for properly packing a food or product into a container or packaging.

[0595] A "delivery route" is the most efficient route for delivering goods.

[0596] "Sales data" is information relating to sales performance during a specific period.

[0597] "Inventory data" is information about the quantity of goods or raw materials currently in stock.

[0598] "Business intelligence tools" are software and methods used to collect, integrate, and analyze corporate data to support decision-making.

[0599] "Business improvement" refers to reviewing the means and methods for making current business processes more efficient and effective.

[0600] "Strategic planning" is the process of formulating policies and plans for a company or organization to achieve its goals.

[0601] The present invention is a system that optimizes cooking procedures, serving procedures, packaging procedures, and delivery routes based on order information, and is intended to improve operational efficiency in food delivery services in particular. Specific embodiments of the system are described below.

[0602] System Configuration

[0603] The system of the present invention includes the following elements:

[0604] 1. Means of receiving order information

[0605] Use a smartphone application to receive order information from customers.

[0606] Software used: Real-time database (e.g. Firebase Firestore)

[0607] 2. A means of storing received order information in a database

[0608] The received order information is stored in a cloud database.

[0609] Software used: Firebase, Amazon DynamoDB

[0610] 3. An artificial intelligence engine to optimize cooking and serving procedures based on order information

[0611] We will implement an AI model that calculates the optimal cooking and serving procedures based on order information.

[0612] Software used: TensorFlow, Python

[0613] 4. Means for transmitting optimized cooking and serving instructions to the display device

[0614] Optimized procedures are sent to the display devices of cooking and serving staff.

[0615] Software used: Node.js, Real-time Database

[0616] 5. A device that displays optimized cooking and serving procedures

[0617] Tablet and smartphone applications used by kitchen and serving staff.

[0618] Software used: React Native

[0619] 6. A means to optimize cooking and packaging procedures based on order information

[0620] AI optimizes cooking and packaging procedures and provides instructions to kitchen staff.

[0621] Software used: TensorFlow, Python

[0622] 7. A way to calculate delivery routes

[0623] It has the ability to calculate routes to complete deliveries in the shortest time possible.

[0624] Software used: Google Maps API, GraphHopper

[0625] Explanation of program processing

[0626] The server receives order information via a smartphone app or POS system. This information is stored in a real-time database, and the cooking and serving procedures are calculated by an artificial intelligence engine. The AI ​​engine uses machine learning with TensorFlow and Python to derive the optimal procedure. The calculation results are sent to the display device via the server.

[0627] On the display device, a smartphone or tablet app using React Native displays real-time instructions to the kitchen and serving staff, and uses Node.js and a real-time database to synchronize data with the server.

[0628] In addition, the server uses Google Maps API and GraphHopper to calculate the optimal delivery route and contact the delivery staff, thereby improving delivery efficiency.

[0629] Specific examples

[0630] For example, when a customer orders a hamburger and fries, the smartphone app first receives the order information and stores it in Firebase Firestore. The AI ​​engine uses that information to calculate the optimal cooking and packaging procedures and sends the results to the display device. The chef cooks the food while checking the tablet and packages it in the optimal order. The delivery staff then quickly delivers the food by following the optimized route provided by the Google Maps API.

[0631] Prompt Sentence Examples

[0632] "Food delivery optimization application: How do you design an AI model to optimize the process when a user places an order? For example, what algorithm uses order data to optimize the cooking order and calculate the delivery route?"

[0633] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0634] Step 1:

[0635] The server receives order information from users (customers) via a smartphone app. The input is the order details entered by the customer into the app, and the output is the received order information. Specifically, the smartphone app enters the order information, which is then sent to Firebase Firestore, where it is received by the server and stored in the database.

[0636] Step 2:

[0637] The server saves the received order information in a database (Firebase Firestore). The input is the order information, and the output is the order information saved in the database. Specifically, the received data is saved in the cloud database in real time.

[0638] Step 3:

[0639] The server uses an artificial intelligence engine to calculate the optimal cooking and serving procedures based on the stored order information. The input is the order information stored in the database, and the output is the optimized cooking and serving procedures. Specifically, machine learning is performed using TensorFlow to derive the optimal procedures.

[0640] Step 4:

[0641] The server sends the optimized cooking and serving instructions to the display terminal. The input is the optimized cooking and serving instructions, and the output is the optimization information sent to the display terminal. Specifically, it uses Node.js to connect to a real-time database and transmits the calculation results to a tablet or smartphone.

[0642] Step 5:

[0643] The terminal displays the optimized cooking and serving instructions. The input is the optimization information sent from the server, and the output is the cooking and serving instructions displayed on the terminal. In concrete terms, a user interface is built using React Native, and instructions are displayed on the display terminal in real time.

[0644] Step 6:

[0645] The server optimizes cooking and packaging procedures based on order information. The input is the order information stored in the database, and the output is the optimized cooking and packaging procedures. Specifically, a machine learning model using TensorFlow calculates the optimal procedure, including packaging.

[0646] Step 7:

[0647] The server calculates the delivery route. The input is the delivery destination information and the current location information, and the output is the optimized delivery route. Specifically, it calculates the shortest route using the Google Maps API and GraphHopper and notifies the delivery staff.

[0648] Step 8:

[0649] The terminal cooks, packages, serves, and delivers food according to the optimized procedure displayed on the display terminal. The input is the displayed optimized procedure and route information, and the output is the status of the actual cooking, packaging, serving, and delivery. In concrete terms, the cooking staff cooks and packages food according to the instructions on the tablet, and the delivery staff delivers food according to the displayed route.

[0650] 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.

[0651] This invention is a system that uses AI to optimize cooking and serving procedures based on order information in restaurants, and also recognizes user emotions to adjust operations. This system not only inputs and manages order information, and the AI ​​calculates and displays the optimal cooking and serving procedures, but also recognizes the user's emotional state and makes adjustments based on that, improving the quality of service.

[0652] System Configuration

[0653] The system includes the following elements:

[0654] 1. Means of receiving order information

[0655] 2. A means of storing received order information in a database

[0656] 3. An AI engine to optimize cooking and serving procedures based on order information

[0657] 4. Means for transmitting optimized cooking and serving instructions to the display device

[0658] 5. A device that displays optimized cooking and serving procedures

[0659] 6. Means of collecting sales and inventory data

[0660] 7. Business intelligence tools to analyze the collected data

[0661] 8. Emotion engine that recognizes user emotions

[0662] 9. A means to store data obtained from the emotion engine in a database and adjust cooking and serving procedures as needed.

[0663] Operation flow

[0664] 1. Receiving and storing order information

[0665] A user (staff member) uses the POS system to input order information from a customer. For example, an order for "hamburger steak, salad, and drink" is received from table 1. The terminal sends the input order information to the server in real time. The server then stores the received order information in a database.

[0666] 2. Optimizing cooking and serving procedures

[0667] The server sends the order information stored in the database to the AI ​​engine. The server (AI engine) analyzes the order information and calculates the optimal cooking and serving procedures. For example, it suggests "cook the hamburger first, prepare the salad, serve the salad, serve the drink, and serve the hamburger." The calculation results are stored in the database and sent to a display device such as a tablet.

[0668] 3. Emotion recognition and adjustment using an emotion engine

[0669] The device (tablet) and sensors capture the customer's facial expressions and tone of voice and send this data to the server. The server (emotion engine) analyzes the data and recognizes the user's emotional state. For example, it identifies whether the customer is satisfied or dissatisfied. The server stores the data obtained from the emotion engine in a database.

[0670] 4. Display and adjust cooking and serving instructions

[0671] The device (tablet) displays optimized cooking and serving procedures in real time. The user (cook) begins cooking by following the instructions on the tablet. For example, they cook a hamburger steak as instructed, and then prepare a salad.

[0672] The server takes into account the data from the emotion engine and adjusts cooking and serving procedures as needed, for example, changing the instructions to prioritize serving procedures if a customer is unhappy.

[0673] 5. Analysis of sales and inventory data

[0674] The server sends daily sales and inventory data to the business intelligence tool for analysis. The user (administrator) uses the business intelligence tool to check the analysis results and plan the next strategy. For example, if the analysis results show that hamburger steak orders are concentrated during a specific time period, the administrator can adjust staff deployment and inventory to suit that time period.

[0675] Specific examples

[0676] For example, the process when an order for "hamburger steak, salad, and drink" is placed from table 1 will be explained.

[0677] The user (staff member) enters order information using the POS system, and the terminal sends it to the server in real time. The server saves the order information in a database and sends it to the AI ​​engine. The server (AI engine) calculates the optimal cooking and serving procedures based on the order information, saves the results in the database, and sends them to the display terminal.

[0678] The terminal (tablet) displays the procedure: "Start cooking hamburger steak, prepare salad, serve salad, serve drinks, serve hamburger steak," and the user (cooking staff) cooks and serves the steak according to the instructions.

[0679] The device (tablet) and sensors capture the customer's facial expressions and tone of voice and send the data to the server (emotion engine). The server (emotion engine) analyzes the data and, if it determines that the customer is dissatisfied, for example, changes the server's instructions to prioritize the serving procedure.

[0680] The server collects daily sales and inventory data and analyzes it using business intelligence tools. Based on the analysis results, users (administrators) can allocate staff and adjust inventory to match popular menu items during specific times.

[0681] In this way, incorporating emotion recognition functionality can increase customer satisfaction, improve business efficiency, and increase sales.

[0682] The processing flow will be explained below.

[0683] Step 1:

[0684] A user (staff member) uses the POS system to input order information from a customer. For example, an order for "hamburger steak, salad, and drink" is received from table 1.

[0685] Step 2:

[0686] The terminal sends the input order information to the server in real time. Specifically, data is sent from the POS system to the server via API.

[0687] Step 3:

[0688] The server saves the received order information in the database. At this time, the table number and order details are recorded as new order data.

[0689] Step 4:

[0690] The server sends the order information stored in the database to the AI ​​engine, which then sends the data to optimize cooking and serving procedures based on the order information.

[0691] Step 5:

[0692] The server (AI engine) analyzes the order information and calculates the optimal cooking and serving procedures. For example, it determines a specific procedure such as "prepare the hamburger first, prepare the salad, serve the salad, serve the drink, and serve the hamburger."

[0693] Step 6:

[0694] The server stores the AI ​​engine's calculation results in a database and sends optimized cooking and serving instructions to each display device, allowing each cook and server to receive instructions.

[0695] Step 7:

[0696] The device (tablet) displays optimized cooking and serving procedures in real time, showing specific work instructions such as "Step 1: Start cooking the hamburger steak, Step 2: Prepare the salad."

[0697] Step 8:

[0698] The user (cook) starts cooking according to the instructions on the terminal. For example, he / she cooks a hamburger steak as instructed, and then prepares a salad.

[0699] Step 9:

[0700] The user (the waiter) serves the food according to instructions on the terminal. For example, the salad is served as soon as it is ready, followed by the drinks, and finally the hamburger steak.

[0701] Step 10:

[0702] The device (tablet) and sensors capture the customer's facial expressions and tone of voice and send this data to the server. Specifically, a camera and microphone are used.

[0703] Step 11:

[0704] The server (emotion engine) analyzes the transmitted emotion data and recognizes the user's emotional state, for example, identifying whether the customer is satisfied or dissatisfied.

[0705] Step 12:

[0706] The server stores the emotion engine's recognition results in a database, and the emotion data is used to track customer satisfaction in real time.

[0707] Step 13:

[0708] The server adjusts cooking and serving procedures based on emotion recognition data. For example, if a customer expresses dissatisfaction, it changes instructions to prioritize serving procedures.

[0709] Step 14:

[0710] The server collects daily sales and inventory data, which are automatically recorded in a database.

[0711] Step 15:

[0712] The server sends the collected sales and inventory data to a business intelligence tool for analysis, specifically to determine which menu items are popular during specific times and how inventory is consumed.

[0713] Step 16:

[0714] The user (administrator) uses the business intelligence tool to check the analysis results and plan the next strategy, such as adjusting staff allocation or inventory to suit specific time periods.

[0715] The above is a series of processing steps in a system incorporating an emotion engine, which can increase customer satisfaction, improve business efficiency, and increase sales.

[0716] Example 2

[0717] 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."

[0718] Efficient operations and improved customer satisfaction are key challenges for modern restaurants. However, managing order information and optimizing cooking and serving procedures requires a lot of effort, and flexible responses based on customer sentiment are required. As a result, current systems have limitations, making it difficult to provide efficient and highly satisfying service.

[0719] 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.

[0720] In this invention, the server includes means for receiving order information, means for saving the received order information in a database, means having an artificial intelligence engine for optimizing cooking procedures and serving procedures based on the order information, means for sending the optimized cooking procedures and serving procedures to a display terminal, a display device for displaying the optimized cooking procedures and serving procedures, means having an emotion engine for recognizing the user's emotions and saving emotion data in a database, and means for adjusting the cooking procedures and serving procedures based on the emotion data. This enables efficient management of order information, optimization of cooking procedures and serving procedures using AI, and flexible operation according to customer emotions.

[0721] "Order information" is data that indicates the details of an order from a customer at a restaurant.

[0722] "Means for receiving" refers to the devices and technologies used to acquire order information and input it into the system.

[0723] "Database" refers to an information system for storing and managing received order information and emotion data.

[0724] An "artificial intelligence engine" refers to software and algorithms that calculate and analyze optimal cooking and serving procedures based on order information.

[0725] "Display terminal" refers to a device for visually displaying calculated cooking and serving instructions to a user.

[0726] "Display device" refers to a screen or device for displaying optimized cooking and serving instructions.

[0727] "User emotions" refers to the emotional state of customers, such as satisfaction or dissatisfaction.

[0728] An "emotion engine" refers to software or algorithms that analyze users' emotions and generate emotional data.

[0729] "Emotion data" refers to data that indicates the emotional state of a customer analyzed by the emotion engine.

[0730] "Adjustment means" refers to techniques and methods for changing cooking and serving procedures based on emotional data to provide optimal service.

[0731] "Sales data" refers to data that indicates information about daily sales.

[0732] "Inventory Data" refers to data that indicates information about inventory items and their quantities.

[0733] "Business intelligence tools" refers to the technology and software used to analyze collected data and derive business insights and strategies.

[0734] "Business improvement" refers to improvement activities aimed at improving business efficiency and quality.

[0735] "Strategic planning" refers to the activity of determining specific plans and policies to achieve business objectives.

[0736] MODE FOR CARRYING OUT THE INVENTION

[0737] This invention is a system that uses AI to optimize cooking and serving procedures based on order information in restaurants, and also recognizes user emotions to adjust operations. This system not only inputs and manages order information, and the AI ​​calculates and displays the optimal cooking and serving procedures, but also recognizes the user's emotional state and makes adjustments based on that, improving the quality of service.

[0738] System Configuration

[0739] The system includes the following elements:

[0740] 1. Means for receiving order information: Using an input device such as a POS system.

[0741] 2. Means for storing received order information in a database: A database server is used to manage order information.

[0742] 3. Means having an artificial intelligence engine for optimizing cooking procedures and serving procedures based on order information: an AI engine that implements a machine learning algorithm.

[0743] 4. Means for transmitting optimized cooking procedures and serving procedures to a display terminal: Information is transmitted to a display device such as a tablet via network communication.

[0744] 5. Display devices that show optimized cooking and serving procedures: tablets and projectors are used.

[0745] 6. Means having an emotion engine for recognizing the user's emotions and storing the emotion data in a database: data is acquired using a camera or microphone, and software implementing an emotion recognition algorithm is used.

[0746] 7. A means for adjusting cooking and serving procedures based on emotional data: A software module that works in conjunction with the AI ​​engine to make adjustments.

[0747] 8. Means of collecting sales and inventory data: Software that connects to a database and collects sales and inventory information.

[0748] 9. Business intelligence means to analyze collected data: Using analytical tools (e.g., business intelligence software).

[0749] Operation flow

[0750] For example, the process when an order for "hamburger steak, salad, and drink" is placed from table 1 will be explained.

[0751] The user (staff member) enters order information using the POS system, and the terminal sends it to the server in real time. The server saves the order information in a database and sends it to the AI ​​engine. The server (AI engine) calculates the optimal cooking and serving procedures based on the order information, saves the results in the database, and sends them to the display terminal.

[0752] The terminal (tablet) displays the procedure: "Start cooking hamburger steak, prepare salad, serve salad, serve drinks, serve hamburger steak," and the user (cooking staff) cooks and serves the steak according to the instructions.

[0753] The device (tablet) and sensors capture the customer's facial expressions and tone of voice and send the data to the server (emotion engine). The server (emotion engine) analyzes the data and, if it determines that the customer is dissatisfied, for example, changes the server's instructions to prioritize the serving procedure.

[0754] The server collects daily sales and inventory data and analyzes it using business intelligence tools. Based on the analysis results, users (administrators) can allocate staff and adjust inventory to match popular menu items during specific times.

[0755] Prompt Sentence Examples

[0756] "Could you explain a system in which AI calculates the optimal cooking and serving procedures based on order information in a restaurant, and also recognizes customer emotions and adjusts operations accordingly?"

[0757] In this way, incorporating emotion recognition functionality can increase customer satisfaction, improve business efficiency, and increase sales.

[0758] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0759] The flow of this system's program processing

[0760] Step 1: Receiving and storing order information

[0761] A user (staff member) uses the POS system to input order information from a customer. For example, "Table 1 orders a hamburger steak, salad, and drink."

[0762] Input: Customer order information

[0763] The terminal sends the entered order information to the server in real time. When an order is entered, the terminal immediately sends the information to the server.

[0764] Output: Order information data

[0765] The server stores the received order information in a database, and this captured data is used in subsequent processing steps.

[0766] Step 2: Optimize cooking and serving procedures

[0767] The server sends the order information stored in the database to the AI ​​engine, which then sends the order details to the AI ​​engine, which then begins the next analysis phase.

[0768] Input: Saved order information data

[0769] The server (AI engine) analyzes the received order information and calculates the optimal cooking and serving sequence, such as "cook the hamburger steak first, prepare the salad, serve the salad, serve the drink, and then serve the hamburger steak last."

[0770] Output: Optimized cooking and serving procedures

[0771] The server stores the calculated results in a database and sends the information to a display device such as a tablet.

[0772] Step 3: Emotion recognition and regulation by the emotion engine

[0773] The device (tablet) and sensors capture the customer's facial expressions and tone of voice and send this data to the server. For example, the tablet's built-in camera and microphone capture the customer's reactions.

[0774] Input: Customer's facial expression data and voice data

[0775] The server (emotion engine) analyzes the transmitted data and recognizes the user's emotional state. If the customer is smiling, it is determined to be satisfied, and if they have a stern expression, it is determined to be dissatisfied.

[0776] Output: Emotion data

[0777] The server stores the data obtained from the emotion engine in a database, which is later used to coordinate operations.

[0778] Step 4: View and adjust cooking and serving instructions

[0779] The device (tablet) displays optimized cooking and serving procedures in real time, such as "Start cooking hamburger steak, prepare salad, serve salad, serve drink, serve hamburger steak."

[0780] Input: Optimized cooking and serving procedures

[0781] The user (cook) starts cooking by following the instructions on the tablet. After cooking the hamburger steak as instructed, the user prepares the salad and then serves the food.

[0782] Output: Execute cooking and serving

[0783] The server takes into account the data from the emotion engine and adjusts cooking and serving procedures as needed, for example, changing instructions to prioritize serving procedures if a customer is unhappy.

[0784] Step 5: Analyze sales and inventory data

[0785] The server sends daily sales and inventory data to the business intelligence tool for analysis, allowing users to understand sales trends and inventory status.

[0786] Input: Sales data and inventory data

[0787] The user (administrator) uses a business intelligence tool to check the analysis results and plan the next strategy. For example, if it turns out that hamburger steak orders are concentrated during lunchtime, they can adjust staff allocation and inventory to suit that time period.

[0788] Output: Business improvement plans and strategies

[0789] (Application example 2)

[0790] 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."

[0791] While conventional food delivery systems can manage order information and optimize cooking and serving procedures, they are unable to grasp customers' emotional states in real time and adjust services accordingly. This makes it difficult to increase customer satisfaction and limits the efficiency of operations and sales. Therefore, there is a need for a system that can recognize customers' emotions and respond flexibly based on them.

[0792] 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 order information, means for saving the received order information in a database, means having an AI engine for optimizing cooking procedures and serving procedures based on the order information, means for transmitting the optimized cooking procedures and serving procedures to the display terminal, an emotion recognition engine for recognizing the emotional state of the customer, means for saving data obtained from the emotion recognition engine in a database and adjusting the cooking procedures and serving procedures, means for collecting sales data and inventory data, and means having a business intelligence tool for analyzing the collected data. This makes it possible to grasp the emotional state of customers in real time and improve the quality of service.

[0793] "Order information" is data indicating the details of an order from a customer.

[0794] A "database" is a system for electronically storing and managing information.

[0795] An "AI engine" is a component that uses artificial intelligence to analyze data and optimize specific tasks.

[0796] A "display terminal" is a device for displaying digital information, including tablets and smartphones.

[0797] The "emotion recognition engine" is a component that analyzes the customer's facial expressions and tone of voice to recognize their emotional state.

[0798] A "business intelligence tool" is software that collects and analyzes corporate data and supports decision-making.

[0799] "Sales data" is information relating to revenues earned from the sale of products.

[0800] "Inventory data" is information about the quantity and condition of goods and materials in a store.

[0801] "Cooking procedures" are the specific steps and methods for preparing a dish.

[0802] "Serving procedure" refers to the process or method for serving the finished food to the customer.

[0803] System Configuration

[0804] This invention is an AI system that receives order information from customers and optimizes cooking and serving procedures based on that information. It can also improve service quality by recognizing customer emotions and making adjustments based on those emotions. The system includes the following components:

[0805] 1. Means of receiving order information

[0806] 2. A means of storing received order information in a database

[0807] 3. An AI engine to optimize cooking and serving procedures based on order information

[0808] 4. Means for transmitting optimized cooking and serving instructions to the display device

[0809] 5. A device that displays optimized cooking and serving procedures

[0810] 6. Means of collecting sales and inventory data

[0811] 7. Business intelligence tools to analyze the collected data

[0812] 8. Emotion engine that recognizes customer emotions

[0813] 9. A means to store data obtained from the emotion engine in a database and adjust cooking and serving procedures as needed.

[0814] Hardware and software used

[0815] The system implementation uses the following hardware and software:

[0816] Smartphone (iOS / Android compatible)

[0817] Delivery robot (if needed)

[0818] Cloud server (AWS or Google Cloud)

[0819] AI engine (TensorFlow or PyTorch)

[0820] Emotion Engine (OpenCV and NLTK)

[0821] Database (MySQL or MongoDB)

[0822] Business intelligence tools (Tableau, Power BI)

[0823] Program processing explanation

[0824] 1. Receiving order information

[0825] Users input order information from customers using a smartphone app, and the smartphone then transmits the input order information to a cloud server in real time.

[0826] The server stores the received order information in a database.

[0827] 2. Optimizing cooking and serving procedures

[0828] The server sends the order information stored in the database to the AI ​​engine.

[0829] The server (AI engine) analyzes the order information and calculates the optimal cooking and serving procedures.

[0830] The server stores the calculation results in a database and sends them to the display terminal.

[0831] 3. Emotion recognition

[0832] The devices (smartphones and delivery robots) capture the customer's facial expressions and tone of voice and send this data to a cloud server.

[0833] The server (emotion engine) analyzes the transmitted data and recognizes the customer's emotional state.

[0834] The server stores the data obtained from the emotion engine in a database and adjusts cooking and serving procedures as needed.

[0835] 4. Collection and analysis of sales and inventory data

[0836] The server sends daily sales and inventory data to a business intelligence tool for analysis.

[0837] The user (administrator) uses a business intelligence tool to check the analysis results and plan the next strategy.

[0838] Specific examples

[0839] For example, if a customer uses a smartphone app to order "pizza, salad, and juice," the following process takes place:

[0840] The user enters order information into their smartphone and sends it to the cloud server.

[0841] The order information received by the server is stored in a database and analyzed by an AI engine.

[0842] The server (AI engine) calculates the optimal procedure, such as "prepare the pizza first, prepare the salad, serve the juice, serve the salad, and serve the pizza," and sends it to the display terminal.

[0843] The terminal captures the customer's emotional state and analyzes it on the server (emotion engine).

[0844] If the server determines that the customer is dissatisfied, the server changes the instructions to prioritize the serving procedure.

[0845] Example prompts for generative AI models

[0846] "Generate an AI model that uses this data to calculate optimal cooking and serving procedures, analyzes customer sentiment, and suggests procedures to provide the most satisfying service."

[0847] In this way, by incorporating a customer emotion recognition function, this system can increase customer satisfaction, improve business efficiency, and increase sales.

[0848] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0849] Step 1:

[0850] The user uses a smartphone app to input order information. The input order information includes specific menu items such as "pizza, salad, and juice." The device (smartphone) sends this information to the cloud server in real time. The input data is in text format, and each piece of order information is saved as a field. The operation in this step is to send the input order information to the cloud server.

[0851] Step 2:

[0852] The order information received by the server is saved in a database (MySQL). Specifically, the server analyzes the order information and stores each field (menu items, etc.) in a database table. The input data is the order information, and the saved data is the output. Data processing here involves converting the text-format order information into a database table using SQL statements.

[0853] Step 3:

[0854] The server sends the order information stored in the database to an AI engine (TensorFlow). The AI ​​engine analyzes the order information and calculates the optimal cooking and serving procedures. The input data is the order information extracted from the database, and the output is the calculated cooking and serving procedures. The data calculation here involves the AI ​​engine calculating the cooking and serving procedures based on a predictive model.

[0855] Step 4:

[0856] The server stores the calculation results in a database and sends them to the display device (smartphone or tablet). Specifically, the server stores the optimized cooking and serving instructions received from the AI ​​engine in the database using SQL statements. The input data is the output from the AI ​​engine, and the data stored in the database is the output.

[0857] Step 5:

[0858] The device (smartphone or tablet) captures the customer's facial expression and tone of voice. Specifically, the device's built-in camera and microphone collect facial expression and voice data. The input data is the customer's facial expression and tone of voice, and the captured data is the output.

[0859] Step 6:

[0860] The device sends the captured data to a cloud server. Here, data collected by the camera and microphone is sent to the server in real time. The input data is the captured facial expression and tone of voice data, and the output is the data sent to the server.

[0861] Step 7:

[0862] The server (emotion engine) analyzes the transmitted data and recognizes the customer's emotional state. Specifically, the server uses OpenCV and NLTK to perform facial expression recognition and voice analysis. The input data is facial expression and tone of voice data transmitted from the device, and the output is the recognized emotional state. The data calculation here is emotion analysis based on a machine learning model.

[0863] Step 8:

[0864] The server stores the data obtained from the emotion engine in a database and adjusts the cooking and serving instructions as needed. The input data is the output from the emotion engine, and the output is the adjusted cooking and serving instructions. Data processing here involves calculating and saving new instructions that take the emotion data into account.

[0865] Step 9:

[0866] The server collects daily sales and inventory data, sends it to a business intelligence tool (Tableau), and analyzes it. Specifically, the server collects sales and inventory data from each store and sends it to the analysis tool. The input data is sales and inventory data, and the output is the analysis results from the business intelligence tool.

[0867] 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.

[0868] 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.

[0869] 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.

[0870] [Third embodiment]

[0871] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0872] 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.

[0873] 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).

[0874] 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.

[0875] 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.

[0876] 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).

[0877] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0878] 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.

[0879] 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.

[0880] 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.

[0881] 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.

[0882] 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."

[0883] This invention is a system that uses AI to optimize cooking and serving procedures based on order information in restaurants, thereby improving table turnover. This system aims to improve business efficiency by inputting and managing order information, and having AI calculate and display the optimal cooking and serving procedures.

[0884] System Configuration

[0885] The system includes the following elements:

[0886] 1. Means of receiving order information

[0887] 2. A means of storing received order information in a database

[0888] 3. An AI engine to optimize cooking and serving procedures based on order information

[0889] 4. Means for transmitting optimized cooking and serving instructions to the display device

[0890] 5. A device that displays optimized cooking and serving procedures

[0891] 6. Means of collecting sales and inventory data

[0892] 7. Business intelligence tools to analyze the collected data

[0893] Operation flow

[0894] 1. Receiving and storing order information

[0895] The user (staff member) uses the POS system to input order information from customers. For example, an order for "hamburger steak, salad, and drink" is received from table 1. The terminal sends the input order information to the server in real time. The server stores the received order information in a database.

[0896] 2. Optimizing cooking and serving procedures

[0897] The server sends the saved order information to the AI ​​engine. The server (AI engine) calculates the optimal cooking and serving procedures based on the order information. For example, it suggests "cook the hamburger first, prepare the salad, serve the salad, serve the drink, and serve the hamburger." The calculation results are saved in a database and sent to a display device such as a tablet.

[0898] 3. Display of cooking and serving instructions

[0899] The terminal (tablet) displays the cooking and serving instructions sent from the server in real time. The user (cook) starts cooking according to the instructions on the tablet and then serves the food. For example, the user might cook hamburgers, then prepare salads, then serve salads and drinks, and finally serve the hamburgers.

[0900] 4. Analysis of sales and inventory data

[0901] The server sends daily sales and inventory data to the business intelligence tool for analysis. The user (administrator) uses the business intelligence tool to check the analysis results and plan the next strategy. For example, if the analysis results show that hamburger steak orders are concentrated during a specific time period, the system adjusts staff deployment and inventory to suit that time period.

[0902] Specific examples

[0903] For example, the process when an order for "hamburger steak, salad, and drink" is placed from table 1 will be explained.

[0904] The user (staff member) inputs order information using the POS system, and the terminal sends it to the server in real time. The server saves the order information in a database and sends it to the AI ​​engine. The server (AI engine) calculates the optimal cooking and serving procedures based on the order information, saves the results in the database, and sends them to the display terminal.

[0905] The terminal (tablet) displays the steps: "Start cooking hamburger steak, prepare salad, serve salad, serve drinks, serve hamburger steak," and the user (cooking staff) cooks and serves the food according to the instructions.

[0906] In addition, daily sales and inventory data is collected by the server and analyzed using business intelligence tools. Based on the analysis results, users (administrators) can, for example, allocate staff to serve popular menu items during specific times or adjust inventory.

[0907] In this way, the entire system can operate efficiently through a series of processes, improving table turnover.

[0908] The processing flow will be explained below.

[0909] Step 1:

[0910] A user (staff member) uses the POS system to input order information from a customer. For example, an order for "hamburger steak, salad, and drink" is received from table 1.

[0911] Step 2:

[0912] The terminal sends the input order information to the server in real time. Specifically, data is sent from the POS system to the server via API.

[0913] Step 3:

[0914] The server saves the received order information in the database. At this time, the table number and order details are recorded as new order data.

[0915] Step 4:

[0916] The server sends the order information stored in the database to the AI ​​engine, which then sends the data to optimize cooking and serving procedures based on the order information.

[0917] Step 5:

[0918] The server (AI engine) analyzes the order information and calculates the optimal cooking and serving procedures. For example, it determines a specific procedure such as "prepare the hamburger first, prepare the salad, serve the salad, serve the drink, and serve the hamburger."

[0919] Step 6:

[0920] The server stores the AI ​​engine's calculation results in a database and sends optimized cooking and serving instructions to each display device, allowing each cook and server to receive instructions.

[0921] Step 7:

[0922] The device (tablet) displays optimized cooking and serving procedures in real time, showing specific work instructions such as "Step 1: Start cooking the hamburger steak, Step 2: Prepare the salad."

[0923] Step 8:

[0924] The user (cook) starts cooking according to the instructions on the terminal. For example, he / she cooks a hamburger steak as instructed, and then prepares a salad.

[0925] Step 9:

[0926] The user (the waiter) serves the food according to instructions on the terminal. For example, the salad is served as soon as it is ready, followed by the drinks, and finally the hamburger steak.

[0927] Step 10:

[0928] The server collects daily sales and inventory data, which are automatically recorded in a database.

[0929] Step 11:

[0930] The server sends the collected sales and inventory data to a business intelligence tool for analysis, specifically to determine which menu items are popular during specific times and how inventory is consumed.

[0931] Step 12:

[0932] The user (administrator) uses the business intelligence tool to check the analysis results and plan the next strategy, such as adjusting staff allocation or inventory to suit specific time periods.

[0933] The above is a series of processing steps of the system, which will improve business efficiency and increase sales.

[0934] Example 1

[0935] 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."

[0936] Restaurants are required to streamline the workflow from ordering to cooking and serving, and to improve table turnover. However, when each staff member cooks and serves food at their own discretion, inefficiencies are likely to occur, which can lead to lower customer satisfaction. Furthermore, when sales and inventory data are analyzed manually, there is a problem that the results of the analysis are not reflected in timely business improvements.

[0937] 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.

[0938] In this invention, the server includes means for receiving order information, means for saving the received order information in a database, means for sending the saved order information to an AI engine and optimizing cooking procedures and serving procedures, means for saving the optimized cooking procedures and serving procedures in a database and sending them to a display terminal, means for collecting sales data and inventory data and sending them to a business analysis tool, and means for improving operations and formulating strategies based on the analysis results. This enables optimization of cooking procedures and serving procedures, efficient business execution, timely data analysis, and business improvement.

[0939] "Order information" is data about the food and drinks that customers order at restaurants.

[0940] A "database" is a set of structures for efficiently storing, managing, retrieving, and updating information.

[0941] An "AI engine" is a software component that uses artificial intelligence technology to analyze data and generate optimal results and recommendations.

[0942] A "display terminal" is a digital device that allows a user to visually check information.

[0943] "Sales data" is data that records information about product sales.

[0944] "Inventory data" refers to data that records information about the quantity and condition of stored products.

[0945] A "business analysis tool" is software that analyzes business data and provides the information necessary for business improvement and strategy planning.

[0946] An "optimized cooking procedure" is a procedure in which the steps are optimally arranged to provide food efficiently and quickly.

[0947] An "optimized food serving procedure" is a procedure in which the steps are optimally arranged to efficiently and quickly serve food to customers.

[0948] "Business improvement" is a series of activities undertaken to improve the efficiency and effectiveness of business operations.

[0949] Strategic planning is the process of developing plans to achieve organizational goals from a long-term perspective.

[0950] This invention is a system that optimizes cooking and serving procedures based on order information in restaurants, improving table turnover. This system aims to improve operational efficiency by inputting and managing order information, and using AI to calculate and display the optimal cooking and serving procedures.

[0951] System Configuration

[0952] The system includes the following elements:

[0953] 1. Means of receiving order information

[0954] The user (staff member) uses the POS system to input customer order information. For example, "Table 1 orders a hamburger steak, salad, and drink."

[0955] 2. A way to store order information in a database

[0956] The terminal transmits the input order information to the server in real time. The terminal transmits the order information to the server as an HTTP request via network communication.

[0957] The server stores the received order information in a database, which uses SQL queries to store the order information efficiently.

[0958] 3. A means to send saved order information to an AI engine to optimize cooking and serving procedures

[0959] The server sends the saved order information to an AI engine, which is implemented using frameworks such as TensorFlow and PyTorch.

[0960] The server (AI engine) calculates the optimal cooking and serving sequence based on the order information. For example, it calculates a sequence such as "prepare the hamburger first, prepare the salad, serve the salad, serve the drink, and serve the hamburger."

[0961] 4. A means for storing optimized cooking and serving procedures in a database and transmitting them to a display terminal.

[0962] The server stores the calculation results in a database and sends them to the display terminal. The server then uses network communication to return the result data to the terminal as an HTTP response.

[0963] 5. A device that displays optimized cooking and serving procedures

[0964] The terminal (tablet) displays the cooking and serving instructions sent from the server in real time. The terminal provides a visually easy-to-understand GUI, allowing users to carry out the instructions efficiently.

[0965] 6. A means of collecting sales and inventory data and transmitting it to business analytics tools

[0966] The server collects daily sales and inventory data and sends it to a business analytics tool, such as Tableau or Power BI.

[0967] The user (administrator) uses the tool to check the analysis results and plan the next strategy. For example, if it is found that hamburger steak orders are concentrated during a specific time period, the system will adjust staff allocation and inventory to suit that time period.

[0968] Specific examples

[0969] For example, if table 1 orders a hamburger steak, salad, and drink, the flow is as follows:

[0970] 1. The user (staff member) inputs "hamburger steak, salad, drink" into the POS system, and the terminal sends this information to the server in real time.

[0971] 2. The server saves the order information in the database and simultaneously sends it to the AI ​​engine.

[0972] 3. The server (AI engine) calculates "cook hamburger first, prepare salad, serve salad, serve drink, serve hamburger", saves the results in a database, and sends them to the display terminal.

[0973] 4. The terminal (tablet) displays the calculated procedure to the user, and the user (cooking staff) cooks and serves the food according to the instructions.

[0974] 5. The server sends daily sales and inventory data to a business analysis tool, and the user (administrator) uses the tool to plan the next strategy.

[0975] This ensures efficient operation of the entire system and optimizes the process from ordering to cooking and serving, resulting in improved table turnover and customer satisfaction.

[0976] Prompt Sentence Examples

[0977] Examples of prompts to input to a generative AI model include:

[0978] "Please explain the functions and operation of an AI system that optimizes cooking and serving procedures based on restaurant order information."

[0979] By using this prompt, the AI ​​model can provide appropriate information about the specific processes and functions of the system.

[0980] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0981] Step 1:

[0982] A user (staff member) uses the POS system to input order information from a customer. For example, "Table 1 orders a hamburger steak, salad, and drink." The input order information is formatted based on the POS system's interface.

[0983] Step 2:

[0984] The terminal sends the entered order information to the server in real time. The terminal wraps the order information in a packet as an HTTP request and sends it to the server over the network. The input is the order information entered by the user, and the output is a data packet sent to the server. The data is sent according to the network transmission and protocol.

[0985] Step 3:

[0986] The server stores the received order information in a database. The server parses the order information and generates SQL queries to insert it into the database in the appropriate format. The database has a structure that allows information to be managed efficiently and accessed quickly. The input is the order information received by the server, and the output is the information stored in the database.

[0987] Step 4:

[0988] The server sends the saved order information to an AI engine, which is implemented using frameworks such as TensorFlow and PyTorch. The input is the order information, and the output is optimized cooking and serving procedures. The AI ​​engine analyzes the data in real time and calculates the optimal procedure based on the order information.

[0989] Step 5:

[0990] The server (AI engine) calculates optimized cooking and serving procedures and stores the results in a database. The calculation results are adjusted based on specific algorithms to maximize data and work efficiency. The input is the data analyzed by the AI ​​engine, and the output is the optimized procedures stored in the database.

[0991] Step 6:

[0992] The server sends the optimized cooking and serving instructions to the display terminal. Here too, network communication occurs, and the resulting data is returned to the display terminal as an HTTP response. The input is the optimized instructions stored in the database, and the output is the data sent to the display terminal.

[0993] Step 7:

[0994] The terminal (tablet) displays the cooking and serving procedures sent from the server in real time. The terminal provides a visual GUI so that the user can efficiently check the instructions. The input is the optimization procedure data sent from the server, and the output is the information displayed on the tablet.

[0995] Step 8:

[0996] The user (cook) starts cooking according to the instructions on the tablet. For example, first cook the hamburger steak and then prepare the salad. The input is the optimization procedure displayed on the tablet, and the output is the cooked dish.

[0997] Step 9:

[0998] The user (cook) serves the food according to the displayed procedure. For example, they serve salad and drinks, and then serve the hamburger steak last. The input is the serving procedure displayed on the tablet, and the output is the food served to the customer.

[0999] Step 10:

[1000] The server sends daily sales and inventory data to a business analysis tool for analysis. The business analysis tool uses tools such as Tableau or Power BI. The input is store sales and inventory data, and the output is analysis results and reports.

[1001] Step 11:

[1002] The user (administrator) uses the tool to check the analysis results and plan the next strategy. For example, if it is found that hamburger steak orders are concentrated during a specific time period, the user can adjust staff deployment and inventory to suit that time period. The input is the analysis results obtained from the business analysis tool, and the output is an improved business strategy.

[1003] (Application example 1)

[1004] 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."

[1005] For restaurants and food delivery services, efficiently optimizing the entire process, from order receipt to cooking, serving, and even delivery, is essential to improving operational efficiency and customer satisfaction. Collecting and analyzing related data is also essential for strategic operational improvements and inventory management. However, conventional systems do not adequately provide the means to comprehensively and efficiently optimize these processes, and many aspects rely on manual work, resulting in inefficiencies. Therefore, there is a need for a system that not only optimizes cooking and serving procedures based on order information, but also improves the efficiency of delivery operations.

[1006] 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.

[1007] In this invention, the server includes means for receiving order information, means for storing the received order information in a database, means having an artificial intelligence engine for optimizing cooking procedures and serving procedures based on the order information, means for transmitting the optimized cooking procedures and serving procedures to a display terminal, a terminal for displaying the optimized cooking procedures and serving procedures, means for optimizing cooking procedures and packaging procedures based on the order information, and means for calculating a delivery route. This enables restaurants and delivery services to improve operational efficiency and provide customers with fast and accurate service.

[1008] "Order information" is data including the details of an order from a customer.

[1009] "Means for receiving" refers to a device or method for receiving data or information from an external source.

[1010] A "database" is an information management system designed to organize and store digital information so that it can be efficiently searched and retrieved.

[1011] "Storage means" means a device or method for recording and storing received data in a secure and reliable manner.

[1012] An "artificial intelligence engine" is software or hardware that uses machine learning and data analysis techniques to solve specific problems.

[1013] An "optimization method" is a method of calculation or adjustment to perform a series of tasks or procedures efficiently and effectively.

[1014] A "display terminal" is a device for visually displaying digital information.

[1015] A "transmission means" is a device or method for moving data or information from one place to another.

[1016] A "display terminal" is a device that visually displays received information to a user.

[1017] "Packaging procedures" are specific procedures for properly packing a food or product into a container or packaging.

[1018] A "delivery route" is the most efficient route for delivering goods.

[1019] "Sales data" is information relating to sales performance during a specific period.

[1020] "Inventory data" is information about the quantity of goods or raw materials currently in stock.

[1021] "Business intelligence tools" are software and methods used to collect, integrate, and analyze corporate data to support decision-making.

[1022] "Business improvement" refers to reviewing the means and methods for making current business processes more efficient and effective.

[1023] "Strategic planning" is the process of formulating policies and plans for a company or organization to achieve its goals.

[1024] The present invention is a system that optimizes cooking procedures, serving procedures, packaging procedures, and delivery routes based on order information, and is intended to improve operational efficiency in food delivery services in particular. Specific embodiments of the system are described below.

[1025] System Configuration

[1026] The system of the present invention includes the following elements:

[1027] 1. Means of receiving order information

[1028] Use a smartphone application to receive order information from customers.

[1029] Software used: Real-time database (e.g. Firebase Firestore)

[1030] 2. A means of storing received order information in a database

[1031] The received order information is stored in a cloud database.

[1032] Software used: Firebase, Amazon DynamoDB

[1033] 3. An artificial intelligence engine to optimize cooking and serving procedures based on order information

[1034] We will implement an AI model that calculates the optimal cooking and serving procedures based on order information.

[1035] Software used: TensorFlow, Python

[1036] 4. Means for transmitting optimized cooking and serving instructions to the display device

[1037] Optimized procedures are sent to the display devices of cooking and serving staff.

[1038] Software used: Node.js, Real-time Database

[1039] 5. A device that displays optimized cooking and serving procedures

[1040] Tablet and smartphone applications used by kitchen and serving staff.

[1041] Software used: React Native

[1042] 6. A means to optimize cooking and packaging procedures based on order information

[1043] AI optimizes cooking and packaging procedures and provides instructions to kitchen staff.

[1044] Software used: TensorFlow, Python

[1045] 7. A way to calculate delivery routes

[1046] It has the ability to calculate routes to complete deliveries in the shortest time possible.

[1047] Software used: Google Maps API, GraphHopper

[1048] Explanation of program processing

[1049] The server receives order information via a smartphone app or POS system. This information is stored in a real-time database, and the cooking and serving procedures are calculated by an artificial intelligence engine. The AI ​​engine uses machine learning with TensorFlow and Python to derive the optimal procedure. The calculation results are sent to the display device via the server.

[1050] On the display device, a smartphone or tablet app using React Native displays real-time instructions to the kitchen and serving staff, and uses Node.js and a real-time database to synchronize data with the server.

[1051] In addition, the server uses Google Maps API and GraphHopper to calculate the optimal delivery route and contact the delivery staff, thereby improving delivery efficiency.

[1052] Specific examples

[1053] For example, when a customer orders a hamburger and fries, the smartphone app first receives the order information and stores it in Firebase Firestore. The AI ​​engine uses that information to calculate the optimal cooking and packaging procedures and sends the results to the display device. The chef cooks the food while checking the tablet and packages it in the optimal order. The delivery staff then quickly delivers the food by following the optimized route provided by the Google Maps API.

[1054] Prompt Sentence Examples

[1055] "Food delivery optimization application: How do you design an AI model to optimize the process when a user places an order? For example, what algorithm uses order data to optimize the cooking order and calculate the delivery route?"

[1056] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1057] Step 1:

[1058] The server receives order information from users (customers) via a smartphone app. The input is the order details entered by the customer into the app, and the output is the received order information. Specifically, the smartphone app enters the order information, which is then sent to Firebase Firestore, where it is received by the server and stored in the database.

[1059] Step 2:

[1060] The server saves the received order information in a database (Firebase Firestore). The input is the order information, and the output is the order information saved in the database. Specifically, the received data is saved in the cloud database in real time.

[1061] Step 3:

[1062] The server uses an artificial intelligence engine to calculate the optimal cooking and serving procedures based on the stored order information. The input is the order information stored in the database, and the output is the optimized cooking and serving procedures. Specifically, machine learning is performed using TensorFlow to derive the optimal procedures.

[1063] Step 4:

[1064] The server sends the optimized cooking and serving instructions to the display terminal. The input is the optimized cooking and serving instructions, and the output is the optimization information sent to the display terminal. Specifically, it uses Node.js to connect to a real-time database and transmits the calculation results to a tablet or smartphone.

[1065] Step 5:

[1066] The terminal displays the optimized cooking and serving instructions. The input is the optimization information sent from the server, and the output is the cooking and serving instructions displayed on the terminal. In concrete terms, a user interface is built using React Native, and instructions are displayed on the display terminal in real time.

[1067] Step 6:

[1068] The server optimizes cooking and packaging procedures based on order information. The input is the order information stored in the database, and the output is the optimized cooking and packaging procedures. Specifically, a machine learning model using TensorFlow calculates the optimal procedure, including packaging.

[1069] Step 7:

[1070] The server calculates the delivery route. The input is the delivery destination information and the current location information, and the output is the optimized delivery route. Specifically, it calculates the shortest route using the Google Maps API and GraphHopper and notifies the delivery staff.

[1071] Step 8:

[1072] The terminal cooks, packages, serves, and delivers food according to the optimized procedure displayed on the display terminal. The input is the displayed optimized procedure and route information, and the output is the status of the actual cooking, packaging, serving, and delivery. In concrete terms, the cooking staff cooks and packages food according to the instructions on the tablet, and the delivery staff delivers food according to the displayed route.

[1073] 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.

[1074] This invention is a system that uses AI to optimize cooking and serving procedures based on order information in restaurants, and also recognizes user emotions to adjust operations. This system not only inputs and manages order information, and the AI ​​calculates and displays the optimal cooking and serving procedures, but also recognizes the user's emotional state and makes adjustments based on that, improving the quality of service.

[1075] System Configuration

[1076] The system includes the following elements:

[1077] 1. Means of receiving order information

[1078] 2. A means of storing received order information in a database

[1079] 3. An AI engine to optimize cooking and serving procedures based on order information

[1080] 4. Means for transmitting optimized cooking and serving instructions to the display device

[1081] 5. A device that displays optimized cooking and serving procedures

[1082] 6. Means of collecting sales and inventory data

[1083] 7. Business intelligence tools to analyze the collected data

[1084] 8. Emotion engine that recognizes user emotions

[1085] 9. A means to store data obtained from the emotion engine in a database and adjust cooking and serving procedures as needed.

[1086] Operation flow

[1087] 1. Receiving and storing order information

[1088] A user (staff member) uses the POS system to input order information from a customer. For example, an order for "hamburger steak, salad, and drink" is received from table 1. The terminal sends the input order information to the server in real time. The server then stores the received order information in a database.

[1089] 2. Optimizing cooking and serving procedures

[1090] The server sends the order information stored in the database to the AI ​​engine. The server (AI engine) analyzes the order information and calculates the optimal cooking and serving procedures. For example, it suggests "cook the hamburger first, prepare the salad, serve the salad, serve the drink, and serve the hamburger." The calculation results are stored in the database and sent to a display device such as a tablet.

[1091] 3. Emotion recognition and adjustment using an emotion engine

[1092] The device (tablet) and sensors capture the customer's facial expressions and tone of voice and send this data to the server. The server (emotion engine) analyzes the data and recognizes the user's emotional state. For example, it identifies whether the customer is satisfied or dissatisfied. The server stores the data obtained from the emotion engine in a database.

[1093] 4. Display and adjust cooking and serving instructions

[1094] The device (tablet) displays optimized cooking and serving procedures in real time. The user (cook) begins cooking by following the instructions on the tablet. For example, they cook a hamburger steak as instructed, and then prepare a salad.

[1095] The server takes into account the data from the emotion engine and adjusts cooking and serving procedures as needed, for example, changing the instructions to prioritize serving procedures if a customer is unhappy.

[1096] 5. Analysis of sales and inventory data

[1097] The server sends daily sales and inventory data to the business intelligence tool for analysis. The user (administrator) uses the business intelligence tool to check the analysis results and plan the next strategy. For example, if the analysis results show that hamburger steak orders are concentrated during a specific time period, the administrator can adjust staff deployment and inventory to suit that time period.

[1098] Specific examples

[1099] For example, the process when an order for "hamburger steak, salad, and drink" is placed from table 1 will be explained.

[1100] The user (staff member) enters order information using the POS system, and the terminal sends it to the server in real time. The server saves the order information in a database and sends it to the AI ​​engine. The server (AI engine) calculates the optimal cooking and serving procedures based on the order information, saves the results in the database, and sends them to the display terminal.

[1101] The terminal (tablet) displays the procedure: "Start cooking hamburger steak, prepare salad, serve salad, serve drinks, serve hamburger steak," and the user (cooking staff) cooks and serves the steak according to the instructions.

[1102] The device (tablet) and sensors capture the customer's facial expressions and tone of voice and send the data to the server (emotion engine). The server (emotion engine) analyzes the data and, if it determines that the customer is dissatisfied, for example, changes the server's instructions to prioritize the serving procedure.

[1103] The server collects daily sales and inventory data and analyzes it using business intelligence tools. Based on the analysis results, users (administrators) can allocate staff and adjust inventory to match popular menu items during specific times.

[1104] In this way, incorporating emotion recognition functionality can increase customer satisfaction, improve business efficiency, and increase sales.

[1105] The processing flow will be explained below.

[1106] Step 1:

[1107] A user (staff member) uses the POS system to input order information from a customer. For example, an order for "hamburger steak, salad, and drink" is received from table 1.

[1108] Step 2:

[1109] The terminal sends the input order information to the server in real time. Specifically, data is sent from the POS system to the server via API.

[1110] Step 3:

[1111] The server saves the received order information in the database. At this time, the table number and order details are recorded as new order data.

[1112] Step 4:

[1113] The server sends the order information stored in the database to the AI ​​engine, which then sends the data to optimize cooking and serving procedures based on the order information.

[1114] Step 5:

[1115] The server (AI engine) analyzes the order information and calculates the optimal cooking and serving procedures. For example, it determines a specific procedure such as "prepare the hamburger first, prepare the salad, serve the salad, serve the drink, and serve the hamburger."

[1116] Step 6:

[1117] The server stores the AI ​​engine's calculation results in a database and sends optimized cooking and serving instructions to each display device, allowing each cook and server to receive instructions.

[1118] Step 7:

[1119] The device (tablet) displays optimized cooking and serving procedures in real time, showing specific work instructions such as "Step 1: Start cooking the hamburger steak, Step 2: Prepare the salad."

[1120] Step 8:

[1121] The user (cook) starts cooking according to the instructions on the terminal. For example, he / she cooks a hamburger steak as instructed, and then prepares a salad.

[1122] Step 9:

[1123] The user (the waiter) serves the food according to instructions on the terminal. For example, the salad is served as soon as it is ready, followed by the drinks, and finally the hamburger steak.

[1124] Step 10:

[1125] The device (tablet) and sensors capture the customer's facial expressions and tone of voice and send this data to the server. Specifically, a camera and microphone are used.

[1126] Step 11:

[1127] The server (emotion engine) analyzes the transmitted emotion data and recognizes the user's emotional state, for example, identifying whether the customer is satisfied or dissatisfied.

[1128] Step 12:

[1129] The server stores the emotion engine's recognition results in a database, and the emotion data is used to track customer satisfaction in real time.

[1130] Step 13:

[1131] The server adjusts cooking and serving procedures based on emotion recognition data. For example, if a customer expresses dissatisfaction, it changes instructions to prioritize serving procedures.

[1132] Step 14:

[1133] The server collects daily sales and inventory data, which are automatically recorded in a database.

[1134] Step 15:

[1135] The server sends the collected sales and inventory data to a business intelligence tool for analysis, specifically to determine which menu items are popular during specific times and how inventory is consumed.

[1136] Step 16:

[1137] The user (administrator) uses the business intelligence tool to check the analysis results and plan the next strategy, such as adjusting staff allocation or inventory to suit specific time periods.

[1138] The above is a series of processing steps in a system incorporating an emotion engine, which can increase customer satisfaction, improve business efficiency, and increase sales.

[1139] Example 2

[1140] 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."

[1141] Efficient operations and improved customer satisfaction are key challenges for modern restaurants. However, managing order information and optimizing cooking and serving procedures requires a lot of effort, and flexible responses based on customer sentiment are required. As a result, current systems have limitations, making it difficult to provide efficient and highly satisfying service.

[1142] 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.

[1143] In this invention, the server includes means for receiving order information, means for saving the received order information in a database, means having an artificial intelligence engine for optimizing cooking procedures and serving procedures based on the order information, means for sending the optimized cooking procedures and serving procedures to a display terminal, a display device for displaying the optimized cooking procedures and serving procedures, means having an emotion engine for recognizing the user's emotions and saving emotion data in a database, and means for adjusting the cooking procedures and serving procedures based on the emotion data. This enables efficient management of order information, optimization of cooking procedures and serving procedures using AI, and flexible operation according to customer emotions.

[1144] "Order information" is data that indicates the details of an order from a customer at a restaurant.

[1145] "Means for receiving" refers to the devices and technologies used to acquire order information and input it into the system.

[1146] "Database" refers to an information system for storing and managing received order information and emotion data.

[1147] An "artificial intelligence engine" refers to software and algorithms that calculate and analyze optimal cooking and serving procedures based on order information.

[1148] "Display terminal" refers to a device for visually displaying calculated cooking and serving instructions to a user.

[1149] "Display device" refers to a screen or device for displaying optimized cooking and serving instructions.

[1150] "User emotions" refers to the emotional state of customers, such as satisfaction or dissatisfaction.

[1151] An "emotion engine" refers to software or algorithms that analyze users' emotions and generate emotional data.

[1152] "Emotion data" refers to data that indicates the emotional state of a customer analyzed by the emotion engine.

[1153] "Adjustment means" refers to techniques and methods for changing cooking and serving procedures based on emotional data to provide optimal service.

[1154] "Sales data" refers to data that indicates information about daily sales.

[1155] "Inventory Data" refers to data that indicates information about inventory items and their quantities.

[1156] "Business intelligence tools" refers to the technology and software used to analyze collected data and derive business insights and strategies.

[1157] "Business improvement" refers to improvement activities aimed at improving business efficiency and quality.

[1158] "Strategic planning" refers to the activity of determining specific plans and policies to achieve business objectives.

[1159] MODE FOR CARRYING OUT THE INVENTION

[1160] This invention is a system that uses AI to optimize cooking and serving procedures based on order information in restaurants, and also recognizes user emotions to adjust operations. This system not only inputs and manages order information, and the AI ​​calculates and displays the optimal cooking and serving procedures, but also recognizes the user's emotional state and makes adjustments based on that, improving the quality of service.

[1161] System Configuration

[1162] The system includes the following elements:

[1163] 1. Means for receiving order information: Using an input device such as a POS system.

[1164] 2. Means for storing received order information in a database: A database server is used to manage order information.

[1165] 3. Means having an artificial intelligence engine for optimizing cooking procedures and serving procedures based on order information: an AI engine that implements a machine learning algorithm.

[1166] 4. Means for transmitting optimized cooking procedures and serving procedures to a display terminal: Information is transmitted to a display device such as a tablet via network communication.

[1167] 5. Display devices that show optimized cooking and serving procedures: tablets and projectors are used.

[1168] 6. Means having an emotion engine for recognizing the user's emotions and storing the emotion data in a database: data is acquired using a camera or microphone, and software implementing an emotion recognition algorithm is used.

[1169] 7. A means for adjusting cooking and serving procedures based on emotional data: A software module that works in conjunction with the AI ​​engine to make adjustments.

[1170] 8. Means of collecting sales and inventory data: Software that connects to a database and collects sales and inventory information.

[1171] 9. Business intelligence means to analyze collected data: Using analytical tools (e.g., business intelligence software).

[1172] Operation flow

[1173] For example, the process when an order for "hamburger steak, salad, and drink" is placed from table 1 will be explained.

[1174] The user (staff member) enters order information using the POS system, and the terminal sends it to the server in real time. The server saves the order information in a database and sends it to the AI ​​engine. The server (AI engine) calculates the optimal cooking and serving procedures based on the order information, saves the results in the database, and sends them to the display terminal.

[1175] The terminal (tablet) displays the procedure: "Start cooking hamburger steak, prepare salad, serve salad, serve drinks, serve hamburger steak," and the user (cooking staff) cooks and serves the steak according to the instructions.

[1176] The device (tablet) and sensors capture the customer's facial expressions and tone of voice and send the data to the server (emotion engine). The server (emotion engine) analyzes the data and, if it determines that the customer is dissatisfied, for example, changes the server's instructions to prioritize the serving procedure.

[1177] The server collects daily sales and inventory data and analyzes it using business intelligence tools. Based on the analysis results, users (administrators) can allocate staff and adjust inventory to match popular menu items during specific times.

[1178] Prompt Sentence Examples

[1179] "Could you explain a system in which AI calculates the optimal cooking and serving procedures based on order information in a restaurant, and also recognizes customer emotions and adjusts operations accordingly?"

[1180] In this way, incorporating emotion recognition functionality can increase customer satisfaction, improve business efficiency, and increase sales.

[1181] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1182] The flow of this system's program processing

[1183] Step 1: Receiving and storing order information

[1184] A user (staff member) uses the POS system to input order information from a customer. For example, "Table 1 orders a hamburger steak, salad, and drink."

[1185] Input: Customer order information

[1186] The terminal sends the entered order information to the server in real time. When an order is entered, the terminal immediately sends the information to the server.

[1187] Output: Order information data

[1188] The server stores the received order information in a database, and this captured data is used in subsequent processing steps.

[1189] Step 2: Optimize cooking and serving procedures

[1190] The server sends the order information stored in the database to the AI ​​engine, which then sends the order details to the AI ​​engine, which then begins the next analysis phase.

[1191] Input: Saved order information data

[1192] The server (AI engine) analyzes the received order information and calculates the optimal cooking and serving sequence, such as "cook the hamburger steak first, prepare the salad, serve the salad, serve the drink, and then serve the hamburger steak last."

[1193] Output: Optimized cooking and serving procedures

[1194] The server stores the calculated results in a database and sends the information to a display device such as a tablet.

[1195] Step 3: Emotion recognition and regulation by the emotion engine

[1196] The device (tablet) and sensors capture the customer's facial expressions and tone of voice and send this data to the server. For example, the tablet's built-in camera and microphone capture the customer's reactions.

[1197] Input: Customer's facial expression data and voice data

[1198] The server (emotion engine) analyzes the transmitted data and recognizes the user's emotional state. If the customer is smiling, it is determined to be satisfied, and if they have a stern expression, it is determined to be dissatisfied.

[1199] Output: Emotion data

[1200] The server stores the data obtained from the emotion engine in a database, which is later used to coordinate operations.

[1201] Step 4: View and adjust cooking and serving instructions

[1202] The device (tablet) displays optimized cooking and serving procedures in real time, such as "Start cooking hamburger steak, prepare salad, serve salad, serve drink, serve hamburger steak."

[1203] Input: Optimized cooking and serving procedures

[1204] The user (cook) starts cooking by following the instructions on the tablet. After cooking the hamburger steak as instructed, the user prepares the salad and then serves the food.

[1205] Output: Execute cooking and serving

[1206] The server takes into account the data from the emotion engine and adjusts cooking and serving procedures as needed, for example, changing instructions to prioritize serving procedures if a customer is unhappy.

[1207] Step 5: Analyze sales and inventory data

[1208] The server sends daily sales and inventory data to the business intelligence tool for analysis, allowing users to understand sales trends and inventory status.

[1209] Input: Sales data and inventory data

[1210] The user (administrator) uses a business intelligence tool to check the analysis results and plan the next strategy. For example, if it turns out that hamburger steak orders are concentrated during lunchtime, they can adjust staff allocation and inventory to suit that time period.

[1211] Output: Business improvement plans and strategies

[1212] (Application example 2)

[1213] 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."

[1214] While conventional food delivery systems can manage order information and optimize cooking and serving procedures, they are unable to grasp customers' emotional states in real time and adjust services accordingly. This makes it difficult to increase customer satisfaction and limits the efficiency of operations and sales. Therefore, there is a need for a system that can recognize customers' emotions and respond flexibly based on them.

[1215] 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 order information, means for saving the received order information in a database, means having an AI engine for optimizing cooking procedures and serving procedures based on the order information, means for transmitting the optimized cooking procedures and serving procedures to the display terminal, an emotion recognition engine for recognizing the emotional state of the customer, means for saving data obtained from the emotion recognition engine in a database and adjusting the cooking procedures and serving procedures, means for collecting sales data and inventory data, and means having a business intelligence tool for analyzing the collected data. This makes it possible to grasp the emotional state of customers in real time and improve the quality of service.

[1216] "Order information" is data indicating the details of an order from a customer.

[1217] A "database" is a system for electronically storing and managing information.

[1218] An "AI engine" is a component that uses artificial intelligence to analyze data and optimize specific tasks.

[1219] A "display terminal" is a device for displaying digital information, including tablets and smartphones.

[1220] The "emotion recognition engine" is a component that analyzes the customer's facial expressions and tone of voice to recognize their emotional state.

[1221] A "business intelligence tool" is software that collects and analyzes corporate data and supports decision-making.

[1222] "Sales data" is information relating to revenues earned from the sale of products.

[1223] "Inventory data" is information about the quantity and condition of goods and materials in a store.

[1224] "Cooking procedures" are the specific steps and methods for preparing a dish.

[1225] "Serving procedure" refers to the process or method for serving the finished food to the customer.

[1226] System Configuration

[1227] This invention is an AI system that receives order information from customers and optimizes cooking and serving procedures based on that information. It can also improve service quality by recognizing customer emotions and making adjustments based on those emotions. The system includes the following components:

[1228] 1. Means of receiving order information

[1229] 2. A means of storing received order information in a database

[1230] 3. An AI engine to optimize cooking and serving procedures based on order information

[1231] 4. Means for transmitting optimized cooking and serving instructions to the display device

[1232] 5. A device that displays optimized cooking and serving procedures

[1233] 6. Means of collecting sales and inventory data

[1234] 7. Business intelligence tools to analyze the collected data

[1235] 8. Emotion engine that recognizes customer emotions

[1236] 9. A means to store data obtained from the emotion engine in a database and adjust cooking and serving procedures as needed.

[1237] Hardware and software used

[1238] The system implementation uses the following hardware and software:

[1239] Smartphone (iOS / Android compatible)

[1240] Delivery robot (if needed)

[1241] Cloud server (AWS or Google Cloud)

[1242] AI engine (TensorFlow or PyTorch)

[1243] Emotion Engine (OpenCV and NLTK)

[1244] Database (MySQL or MongoDB)

[1245] Business intelligence tools (Tableau, Power BI)

[1246] Program processing explanation

[1247] 1. Receiving order information

[1248] Users input order information from customers using a smartphone app, and the smartphone then transmits the input order information to a cloud server in real time.

[1249] The server stores the received order information in a database.

[1250] 2. Optimizing cooking and serving procedures

[1251] The server sends the order information stored in the database to the AI ​​engine.

[1252] The server (AI engine) analyzes the order information and calculates the optimal cooking and serving procedures.

[1253] The server stores the calculation results in a database and sends them to the display terminal.

[1254] 3. Emotion recognition

[1255] The devices (smartphones and delivery robots) capture the customer's facial expressions and tone of voice and send this data to a cloud server.

[1256] The server (emotion engine) analyzes the transmitted data and recognizes the customer's emotional state.

[1257] The server stores the data obtained from the emotion engine in a database and adjusts cooking and serving procedures as needed.

[1258] 4. Collection and analysis of sales and inventory data

[1259] The server sends daily sales and inventory data to a business intelligence tool for analysis.

[1260] The user (administrator) uses a business intelligence tool to check the analysis results and plan the next strategy.

[1261] Specific examples

[1262] For example, if a customer uses a smartphone app to order "pizza, salad, and juice," the following process takes place:

[1263] The user enters order information into their smartphone and sends it to the cloud server.

[1264] The order information received by the server is stored in a database and analyzed by an AI engine.

[1265] The server (AI engine) calculates the optimal procedure, such as "prepare the pizza first, prepare the salad, serve the juice, serve the salad, and serve the pizza," and sends it to the display terminal.

[1266] The terminal captures the customer's emotional state and analyzes it on the server (emotion engine).

[1267] If the server determines that the customer is dissatisfied, the server changes the instructions to prioritize the serving procedure.

[1268] Example prompts for generative AI models

[1269] "Generate an AI model that uses this data to calculate optimal cooking and serving procedures, analyzes customer sentiment, and suggests procedures to provide the most satisfying service."

[1270] In this way, by incorporating a customer emotion recognition function, this system can increase customer satisfaction, improve business efficiency, and increase sales.

[1271] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1272] Step 1:

[1273] The user uses a smartphone app to input order information. The input order information includes specific menu items such as "pizza, salad, and juice." The device (smartphone) sends this information to the cloud server in real time. The input data is in text format, and each piece of order information is saved as a field. The operation in this step is to send the input order information to the cloud server.

[1274] Step 2:

[1275] The order information received by the server is saved in a database (MySQL). Specifically, the server analyzes the order information and stores each field (menu items, etc.) in a database table. The input data is the order information, and the saved data is the output. Data processing here involves converting the text-format order information into a database table using SQL statements.

[1276] Step 3:

[1277] The server sends the order information stored in the database to an AI engine (TensorFlow). The AI ​​engine analyzes the order information and calculates the optimal cooking and serving procedures. The input data is the order information extracted from the database, and the output is the calculated cooking and serving procedures. The data calculation here involves the AI ​​engine calculating the cooking and serving procedures based on a predictive model.

[1278] Step 4:

[1279] The server stores the calculation results in a database and sends them to the display device (smartphone or tablet). Specifically, the server stores the optimized cooking and serving instructions received from the AI ​​engine in the database using SQL statements. The input data is the output from the AI ​​engine, and the data stored in the database is the output.

[1280] Step 5:

[1281] The device (smartphone or tablet) captures the customer's facial expression and tone of voice. Specifically, the device's built-in camera and microphone collect facial expression and voice data. The input data is the customer's facial expression and tone of voice, and the captured data is the output.

[1282] Step 6:

[1283] The device sends the captured data to a cloud server. Here, data collected by the camera and microphone is sent to the server in real time. The input data is the captured facial expression and tone of voice data, and the output is the data sent to the server.

[1284] Step 7:

[1285] The server (emotion engine) analyzes the transmitted data and recognizes the customer's emotional state. Specifically, the server uses OpenCV and NLTK to perform facial expression recognition and voice analysis. The input data is facial expression and tone of voice data transmitted from the device, and the output is the recognized emotional state. The data calculation here is emotion analysis based on a machine learning model.

[1286] Step 8:

[1287] The server stores the data obtained from the emotion engine in a database and adjusts the cooking and serving instructions as needed. The input data is the output from the emotion engine, and the output is the adjusted cooking and serving instructions. Data processing here involves calculating and saving new instructions that take the emotion data into account.

[1288] Step 9:

[1289] The server collects daily sales and inventory data, sends it to a business intelligence tool (Tableau), and analyzes it. Specifically, the server collects sales and inventory data from each store and sends it to the analysis tool. The input data is sales and inventory data, and the output is the analysis results from the business intelligence tool.

[1290] 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.

[1291] 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.

[1292] 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.

[1293] [Fourth embodiment]

[1294] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1295] 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.

[1296] 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).

[1297] 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.

[1298] 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.

[1299] 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).

[1300] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1301] 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.

[1302] 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.

[1303] 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.

[1304] 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.

[1305] 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.

[1306] 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."

[1307] This invention is a system that uses AI to optimize cooking and serving procedures based on order information in restaurants, thereby improving table turnover. This system aims to improve business efficiency by inputting and managing order information, and having AI calculate and display the optimal cooking and serving procedures.

[1308] System Configuration

[1309] The system includes the following elements:

[1310] 1. Means of receiving order information

[1311] 2. A means of storing received order information in a database

[1312] 3. An AI engine to optimize cooking and serving procedures based on order information

[1313] 4. Means for transmitting optimized cooking and serving instructions to the display device

[1314] 5. A device that displays optimized cooking and serving procedures

[1315] 6. Means of collecting sales and inventory data

[1316] 7. Business intelligence tools to analyze the collected data

[1317] Operation flow

[1318] 1. Receiving and storing order information

[1319] The user (staff member) uses the POS system to input order information from customers. For example, an order for "hamburger steak, salad, and drink" is received from table 1. The terminal sends the input order information to the server in real time. The server stores the received order information in a database.

[1320] 2. Optimizing cooking and serving procedures

[1321] The server sends the saved order information to the AI ​​engine. The server (AI engine) calculates the optimal cooking and serving procedures based on the order information. For example, it suggests "cook the hamburger first, prepare the salad, serve the salad, serve the drink, and serve the hamburger." The calculation results are saved in a database and sent to a display device such as a tablet.

[1322] 3. Display of cooking and serving instructions

[1323] The terminal (tablet) displays the cooking and serving instructions sent from the server in real time. The user (cook) starts cooking according to the instructions on the tablet and then serves the food. For example, the user might cook hamburgers, then prepare salads, then serve salads and drinks, and finally serve the hamburgers.

[1324] 4. Analysis of sales and inventory data

[1325] The server sends daily sales and inventory data to the business intelligence tool for analysis. The user (administrator) uses the business intelligence tool to check the analysis results and plan the next strategy. For example, if the analysis results show that hamburger steak orders are concentrated during a specific time period, the system adjusts staff deployment and inventory to suit that time period.

[1326] Specific examples

[1327] For example, the process when an order for "hamburger steak, salad, and drink" is placed from table 1 will be explained.

[1328] The user (staff member) inputs order information using the POS system, and the terminal sends it to the server in real time. The server saves the order information in a database and sends it to the AI ​​engine. The server (AI engine) calculates the optimal cooking and serving procedures based on the order information, saves the results in the database, and sends them to the display terminal.

[1329] The terminal (tablet) displays the steps: "Start cooking hamburger steak, prepare salad, serve salad, serve drinks, serve hamburger steak," and the user (cooking staff) cooks and serves the food according to the instructions.

[1330] In addition, daily sales and inventory data is collected by the server and analyzed using business intelligence tools. Based on the analysis results, users (administrators) can, for example, allocate staff to serve popular menu items during specific times or adjust inventory.

[1331] In this way, the entire system can operate efficiently through a series of processes, improving table turnover.

[1332] The processing flow will be explained below.

[1333] Step 1:

[1334] A user (staff member) uses the POS system to input order information from a customer. For example, an order for "hamburger steak, salad, and drink" is received from table 1.

[1335] Step 2:

[1336] The terminal sends the input order information to the server in real time. Specifically, data is sent from the POS system to the server via API.

[1337] Step 3:

[1338] The server saves the received order information in the database. At this time, the table number and order details are recorded as new order data.

[1339] Step 4:

[1340] The server sends the order information stored in the database to the AI ​​engine, which then sends the data to optimize cooking and serving procedures based on the order information.

[1341] Step 5:

[1342] The server (AI engine) analyzes the order information and calculates the optimal cooking and serving procedures. For example, it determines a specific procedure such as "prepare the hamburger first, prepare the salad, serve the salad, serve the drink, and serve the hamburger."

[1343] Step 6:

[1344] The server stores the AI ​​engine's calculation results in a database and sends optimized cooking and serving instructions to each display device, allowing each cook and server to receive instructions.

[1345] Step 7:

[1346] The device (tablet) displays optimized cooking and serving procedures in real time, showing specific work instructions such as "Step 1: Start cooking the hamburger steak, Step 2: Prepare the salad."

[1347] Step 8:

[1348] The user (cook) starts cooking according to the instructions on the terminal. For example, he / she cooks a hamburger steak as instructed, and then prepares a salad.

[1349] Step 9:

[1350] The user (the waiter) serves the food according to instructions on the terminal. For example, the salad is served as soon as it is ready, followed by the drinks, and finally the hamburger steak.

[1351] Step 10:

[1352] The server collects daily sales and inventory data, which are automatically recorded in a database.

[1353] Step 11:

[1354] The server sends the collected sales and inventory data to a business intelligence tool for analysis, specifically to determine which menu items are popular during specific times and how inventory is consumed.

[1355] Step 12:

[1356] The user (administrator) uses the business intelligence tool to check the analysis results and plan the next strategy, such as adjusting staff allocation or inventory to suit specific time periods.

[1357] The above is a series of processing steps of the system, which will improve business efficiency and increase sales.

[1358] Example 1

[1359] 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."

[1360] Restaurants are required to streamline the workflow from ordering to cooking and serving, and to improve table turnover. However, when each staff member cooks and serves food at their own discretion, inefficiencies are likely to occur, which can lead to lower customer satisfaction. Furthermore, when sales and inventory data are analyzed manually, there is a problem that the results of the analysis are not reflected in timely business improvements.

[1361] 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.

[1362] In this invention, the server includes means for receiving order information, means for saving the received order information in a database, means for sending the saved order information to an AI engine and optimizing cooking procedures and serving procedures, means for saving the optimized cooking procedures and serving procedures in a database and sending them to a display terminal, means for collecting sales data and inventory data and sending them to a business analysis tool, and means for improving operations and formulating strategies based on the analysis results. This enables optimization of cooking procedures and serving procedures, efficient business execution, timely data analysis, and business improvement.

[1363] "Order information" is data about the food and drinks that customers order at restaurants.

[1364] A "database" is a set of structures for efficiently storing, managing, retrieving, and updating information.

[1365] An "AI engine" is a software component that uses artificial intelligence technology to analyze data and generate optimal results and recommendations.

[1366] A "display terminal" is a digital device that allows a user to visually check information.

[1367] "Sales data" is data that records information about product sales.

[1368] "Inventory data" refers to data that records information about the quantity and condition of stored products.

[1369] A "business analysis tool" is software that analyzes business data and provides the information necessary for business improvement and strategy planning.

[1370] An "optimized cooking procedure" is a procedure in which the steps are optimally arranged to provide food efficiently and quickly.

[1371] An "optimized food serving procedure" is a procedure in which the steps are optimally arranged to efficiently and quickly serve food to customers.

[1372] "Business improvement" is a series of activities undertaken to improve the efficiency and effectiveness of business operations.

[1373] Strategic planning is the process of developing plans to achieve organizational goals from a long-term perspective.

[1374] This invention is a system that optimizes cooking and serving procedures based on order information in restaurants, improving table turnover. This system aims to improve operational efficiency by inputting and managing order information, and using AI to calculate and display the optimal cooking and serving procedures.

[1375] System Configuration

[1376] The system includes the following elements:

[1377] 1. Means of receiving order information

[1378] The user (staff member) uses the POS system to input customer order information. For example, "Table 1 orders a hamburger steak, salad, and drink."

[1379] 2. A way to store order information in a database

[1380] The terminal transmits the input order information to the server in real time. The terminal transmits the order information to the server as an HTTP request via network communication.

[1381] The server stores the received order information in a database, which uses SQL queries to store the order information efficiently.

[1382] 3. A means to send saved order information to an AI engine to optimize cooking and serving procedures

[1383] The server sends the saved order information to an AI engine, which is implemented using frameworks such as TensorFlow and PyTorch.

[1384] The server (AI engine) calculates the optimal cooking and serving sequence based on the order information. For example, it calculates a sequence such as "prepare the hamburger first, prepare the salad, serve the salad, serve the drink, and serve the hamburger."

[1385] 4. A means for storing optimized cooking and serving procedures in a database and transmitting them to a display terminal.

[1386] The server stores the calculation results in a database and sends them to the display terminal. The server then uses network communication to return the result data to the terminal as an HTTP response.

[1387] 5. A device that displays optimized cooking and serving procedures

[1388] The terminal (tablet) displays the cooking and serving instructions sent from the server in real time. The terminal provides a visually easy-to-understand GUI, allowing users to carry out the instructions efficiently.

[1389] 6. A means of collecting sales and inventory data and transmitting it to business analytics tools

[1390] The server collects daily sales and inventory data and sends it to a business analytics tool, such as Tableau or Power BI.

[1391] The user (administrator) uses the tool to check the analysis results and plan the next strategy. For example, if it is found that hamburger steak orders are concentrated during a specific time period, the system will adjust staff allocation and inventory to suit that time period.

[1392] Specific examples

[1393] For example, if table 1 orders a hamburger steak, salad, and drink, the flow is as follows:

[1394] 1. The user (staff member) inputs "hamburger steak, salad, drink" into the POS system, and the terminal sends this information to the server in real time.

[1395] 2. The server saves the order information in the database and simultaneously sends it to the AI ​​engine.

[1396] 3. The server (AI engine) calculates "cook hamburger first, prepare salad, serve salad, serve drink, serve hamburger", saves the results in a database, and sends them to the display terminal.

[1397] 4. The terminal (tablet) displays the calculated procedure to the user, and the user (cooking staff) cooks and serves the food according to the instructions.

[1398] 5. The server sends daily sales and inventory data to a business analysis tool, and the user (administrator) uses the tool to plan the next strategy.

[1399] This ensures efficient operation of the entire system and optimizes the process from ordering to cooking and serving, resulting in improved table turnover and customer satisfaction.

[1400] Prompt Sentence Examples

[1401] Examples of prompts to input to a generative AI model include:

[1402] "Please explain the functions and operation of an AI system that optimizes cooking and serving procedures based on restaurant order information."

[1403] By using this prompt, the AI ​​model can provide appropriate information about the specific processes and functions of the system.

[1404] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1405] Step 1:

[1406] A user (staff member) uses the POS system to input order information from a customer. For example, "Table 1 orders a hamburger steak, salad, and drink." The input order information is formatted based on the POS system's interface.

[1407] Step 2:

[1408] The terminal sends the entered order information to the server in real time. The terminal wraps the order information in a packet as an HTTP request and sends it to the server over the network. The input is the order information entered by the user, and the output is a data packet sent to the server. The data is sent according to the network transmission and protocol.

[1409] Step 3:

[1410] The server stores the received order information in a database. The server parses the order information and generates SQL queries to insert it into the database in the appropriate format. The database has a structure that allows information to be managed efficiently and accessed quickly. The input is the order information received by the server, and the output is the information stored in the database.

[1411] Step 4:

[1412] The server sends the saved order information to an AI engine, which is implemented using frameworks such as TensorFlow and PyTorch. The input is the order information, and the output is optimized cooking and serving procedures. The AI ​​engine analyzes the data in real time and calculates the optimal procedure based on the order information.

[1413] Step 5:

[1414] The server (AI engine) calculates optimized cooking and serving procedures and stores the results in a database. The calculation results are adjusted based on specific algorithms to maximize data and work efficiency. The input is the data analyzed by the AI ​​engine, and the output is the optimized procedures stored in the database.

[1415] Step 6:

[1416] The server sends the optimized cooking and serving instructions to the display terminal. Here too, network communication occurs, and the resulting data is returned to the display terminal as an HTTP response. The input is the optimized instructions stored in the database, and the output is the data sent to the display terminal.

[1417] Step 7:

[1418] The terminal (tablet) displays the cooking and serving procedures sent from the server in real time. The terminal provides a visual GUI so that the user can efficiently check the instructions. The input is the optimization procedure data sent from the server, and the output is the information displayed on the tablet.

[1419] Step 8:

[1420] The user (cook) starts cooking according to the instructions on the tablet. For example, first cook the hamburger steak and then prepare the salad. The input is the optimization procedure displayed on the tablet, and the output is the cooked dish.

[1421] Step 9:

[1422] The user (cook) serves the food according to the displayed procedure. For example, they serve salad and drinks, and then serve the hamburger steak last. The input is the serving procedure displayed on the tablet, and the output is the food served to the customer.

[1423] Step 10:

[1424] The server sends daily sales and inventory data to a business analysis tool for analysis. The business analysis tool uses tools such as Tableau or Power BI. The input is store sales and inventory data, and the output is analysis results and reports.

[1425] Step 11:

[1426] The user (administrator) uses the tool to check the analysis results and plan the next strategy. For example, if it is found that hamburger steak orders are concentrated during a specific time period, the user can adjust staff deployment and inventory to suit that time period. The input is the analysis results obtained from the business analysis tool, and the output is an improved business strategy.

[1427] (Application example 1)

[1428] 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."

[1429] For restaurants and food delivery services, efficiently optimizing the entire process, from order receipt to cooking, serving, and even delivery, is essential to improving operational efficiency and customer satisfaction. Collecting and analyzing related data is also essential for strategic operational improvements and inventory management. However, conventional systems do not adequately provide the means to comprehensively and efficiently optimize these processes, and many aspects rely on manual work, resulting in inefficiencies. Therefore, there is a need for a system that not only optimizes cooking and serving procedures based on order information, but also improves the efficiency of delivery operations.

[1430] 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.

[1431] In this invention, the server includes means for receiving order information, means for storing the received order information in a database, means having an artificial intelligence engine for optimizing cooking procedures and serving procedures based on the order information, means for transmitting the optimized cooking procedures and serving procedures to a display terminal, a terminal for displaying the optimized cooking procedures and serving procedures, means for optimizing cooking procedures and packaging procedures based on the order information, and means for calculating a delivery route. This enables restaurants and delivery services to improve operational efficiency and provide customers with fast and accurate service.

[1432] "Order information" is data including the details of an order from a customer.

[1433] "Means for receiving" refers to a device or method for receiving data or information from an external source.

[1434] A "database" is an information management system designed to organize and store digital information so that it can be efficiently searched and retrieved.

[1435] "Storage means" means a device or method for recording and storing received data in a secure and reliable manner.

[1436] An "artificial intelligence engine" is software or hardware that uses machine learning and data analysis techniques to solve specific problems.

[1437] An "optimization method" is a method of calculation or adjustment to perform a series of tasks or procedures efficiently and effectively.

[1438] A "display terminal" is a device for visually displaying digital information.

[1439] A "transmission means" is a device or method for moving data or information from one place to another.

[1440] A "display terminal" is a device that visually displays received information to a user.

[1441] "Packaging procedures" are specific procedures for properly packing a food or product into a container or packaging.

[1442] A "delivery route" is the most efficient route for delivering goods.

[1443] "Sales data" is information relating to sales performance during a specific period.

[1444] "Inventory data" is information about the quantity of goods or raw materials currently in stock.

[1445] "Business intelligence tools" are software and methods used to collect, integrate, and analyze corporate data to support decision-making.

[1446] "Business improvement" refers to reviewing the means and methods for making current business processes more efficient and effective.

[1447] "Strategic planning" is the process of formulating policies and plans for a company or organization to achieve its goals.

[1448] The present invention is a system that optimizes cooking procedures, serving procedures, packaging procedures, and delivery routes based on order information, and is intended to improve operational efficiency in food delivery services in particular. Specific embodiments of the system are described below.

[1449] System Configuration

[1450] The system of the present invention includes the following elements:

[1451] 1. Means of receiving order information

[1452] Use a smartphone application to receive order information from customers.

[1453] Software used: Real-time database (e.g. Firebase Firestore)

[1454] 2. A means of storing received order information in a database

[1455] The received order information is stored in a cloud database.

[1456] Software used: Firebase, Amazon DynamoDB

[1457] 3. An artificial intelligence engine to optimize cooking and serving procedures based on order information

[1458] We will implement an AI model that calculates the optimal cooking and serving procedures based on order information.

[1459] Software used: TensorFlow, Python

[1460] 4. Means for transmitting optimized cooking and serving instructions to the display device

[1461] Optimized procedures are sent to the display devices of cooking and serving staff.

[1462] Software used: Node.js, Real-time Database

[1463] 5. A device that displays optimized cooking and serving procedures

[1464] Tablet and smartphone applications used by kitchen and serving staff.

[1465] Software used: React Native

[1466] 6. A means to optimize cooking and packaging procedures based on order information

[1467] AI optimizes cooking and packaging procedures and provides instructions to kitchen staff.

[1468] Software used: TensorFlow, Python

[1469] 7. A way to calculate delivery routes

[1470] It has the ability to calculate routes to complete deliveries in the shortest time possible.

[1471] Software used: Google Maps API, GraphHopper

[1472] Explanation of program processing

[1473] The server receives order information via a smartphone app or POS system. This information is stored in a real-time database, and the cooking and serving procedures are calculated by an artificial intelligence engine. The AI ​​engine uses machine learning with TensorFlow and Python to derive the optimal procedure. The calculation results are sent to the display device via the server.

[1474] On the display device, a smartphone or tablet app using React Native displays real-time instructions to the kitchen and serving staff, and uses Node.js and a real-time database to synchronize data with the server.

[1475] In addition, the server uses Google Maps API and GraphHopper to calculate the optimal delivery route and contact the delivery staff, thereby improving delivery efficiency.

[1476] Specific examples

[1477] For example, when a customer orders a hamburger and fries, the smartphone app first receives the order information and stores it in Firebase Firestore. The AI ​​engine uses that information to calculate the optimal cooking and packaging procedures and sends the results to the display device. The chef cooks the food while checking the tablet and packages it in the optimal order. The delivery staff then quickly delivers the food by following the optimized route provided by the Google Maps API.

[1478] Prompt Sentence Examples

[1479] "Food delivery optimization application: How do you design an AI model to optimize the process when a user places an order? For example, what algorithm uses order data to optimize the cooking order and calculate the delivery route?"

[1480] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1481] Step 1:

[1482] The server receives order information from users (customers) via a smartphone app. The input is the order details entered by the customer into the app, and the output is the received order information. Specifically, the smartphone app enters the order information, which is then sent to Firebase Firestore, where it is received by the server and stored in the database.

[1483] Step 2:

[1484] The server saves the received order information in a database (Firebase Firestore). The input is the order information, and the output is the order information saved in the database. Specifically, the received data is saved in the cloud database in real time.

[1485] Step 3:

[1486] The server uses an artificial intelligence engine to calculate the optimal cooking and serving procedures based on the stored order information. The input is the order information stored in the database, and the output is the optimized cooking and serving procedures. Specifically, machine learning is performed using TensorFlow to derive the optimal procedures.

[1487] Step 4:

[1488] The server sends the optimized cooking and serving instructions to the display terminal. The input is the optimized cooking and serving instructions, and the output is the optimization information sent to the display terminal. Specifically, it uses Node.js to connect to a real-time database and transmits the calculation results to a tablet or smartphone.

[1489] Step 5:

[1490] The terminal displays the optimized cooking and serving instructions. The input is the optimization information sent from the server, and the output is the cooking and serving instructions displayed on the terminal. In concrete terms, a user interface is built using React Native, and instructions are displayed on the display terminal in real time.

[1491] Step 6:

[1492] The server optimizes cooking and packaging procedures based on order information. The input is the order information stored in the database, and the output is the optimized cooking and packaging procedures. Specifically, a machine learning model using TensorFlow calculates the optimal procedure, including packaging.

[1493] Step 7:

[1494] The server calculates the delivery route. The input is the delivery destination information and the current location information, and the output is the optimized delivery route. Specifically, it calculates the shortest route using the Google Maps API and GraphHopper and notifies the delivery staff.

[1495] Step 8:

[1496] The terminal cooks, packages, serves, and delivers food according to the optimized procedure displayed on the display terminal. The input is the displayed optimized procedure and route information, and the output is the status of the actual cooking, packaging, serving, and delivery. In concrete terms, the cooking staff cooks and packages food according to the instructions on the tablet, and the delivery staff delivers food according to the displayed route.

[1497] 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.

[1498] This invention is a system that uses AI to optimize cooking and serving procedures based on order information in restaurants, and also recognizes user emotions to adjust operations. This system not only inputs and manages order information, and the AI ​​calculates and displays the optimal cooking and serving procedures, but also recognizes the user's emotional state and makes adjustments based on that, improving the quality of service.

[1499] System Configuration

[1500] The system includes the following elements:

[1501] 1. Means of receiving order information

[1502] 2. A means of storing received order information in a database

[1503] 3. An AI engine to optimize cooking and serving procedures based on order information

[1504] 4. Means for transmitting optimized cooking and serving instructions to the display device

[1505] 5. A device that displays optimized cooking and serving procedures

[1506] 6. Means of collecting sales and inventory data

[1507] 7. Business intelligence tools to analyze the collected data

[1508] 8. Emotion engine that recognizes user emotions

[1509] 9. A means to store data obtained from the emotion engine in a database and adjust cooking and serving procedures as needed.

[1510] Operation flow

[1511] 1. Receiving and storing order information

[1512] A user (staff member) uses the POS system to input order information from a customer. For example, an order for "hamburger steak, salad, and drink" is received from table 1. The terminal sends the input order information to the server in real time. The server then stores the received order information in a database.

[1513] 2. Optimizing cooking and serving procedures

[1514] The server sends the order information stored in the database to the AI ​​engine. The server (AI engine) analyzes the order information and calculates the optimal cooking and serving procedures. For example, it suggests "cook the hamburger first, prepare the salad, serve the salad, serve the drink, and serve the hamburger." The calculation results are stored in the database and sent to a display device such as a tablet.

[1515] 3. Emotion recognition and adjustment using an emotion engine

[1516] The device (tablet) and sensors capture the customer's facial expressions and tone of voice and send this data to the server. The server (emotion engine) analyzes the data and recognizes the user's emotional state. For example, it identifies whether the customer is satisfied or dissatisfied. The server stores the data obtained from the emotion engine in a database.

[1517] 4. Display and adjust cooking and serving instructions

[1518] The device (tablet) displays optimized cooking and serving procedures in real time. The user (cook) begins cooking by following the instructions on the tablet. For example, they cook a hamburger steak as instructed, and then prepare a salad.

[1519] The server takes into account the data from the emotion engine and adjusts cooking and serving procedures as needed, for example, changing the instructions to prioritize serving procedures if a customer is unhappy.

[1520] 5. Analysis of sales and inventory data

[1521] The server sends daily sales and inventory data to the business intelligence tool for analysis. The user (administrator) uses the business intelligence tool to check the analysis results and plan the next strategy. For example, if the analysis results show that hamburger steak orders are concentrated during a specific time period, the administrator can adjust staff deployment and inventory to suit that time period.

[1522] Specific examples

[1523] For example, the process when an order for "hamburger steak, salad, and drink" is placed from table 1 will be explained.

[1524] The user (staff member) enters order information using the POS system, and the terminal sends it to the server in real time. The server saves the order information in a database and sends it to the AI ​​engine. The server (AI engine) calculates the optimal cooking and serving procedures based on the order information, saves the results in the database, and sends them to the display terminal.

[1525] The terminal (tablet) displays the procedure: "Start cooking hamburger steak, prepare salad, serve salad, serve drinks, serve hamburger steak," and the user (cooking staff) cooks and serves the steak according to the instructions.

[1526] The device (tablet) and sensors capture the customer's facial expressions and tone of voice and send the data to the server (emotion engine). The server (emotion engine) analyzes the data and, if it determines that the customer is dissatisfied, for example, changes the server's instructions to prioritize the serving procedure.

[1527] The server collects daily sales and inventory data and analyzes it using business intelligence tools. Based on the analysis results, users (administrators) can allocate staff and adjust inventory to match popular menu items during specific times.

[1528] In this way, incorporating emotion recognition functionality can increase customer satisfaction, improve business efficiency, and increase sales.

[1529] The processing flow will be explained below.

[1530] Step 1:

[1531] A user (staff member) uses the POS system to input order information from a customer. For example, an order for "hamburger steak, salad, and drink" is received from table 1.

[1532] Step 2:

[1533] The terminal sends the input order information to the server in real time. Specifically, data is sent from the POS system to the server via API.

[1534] Step 3:

[1535] The server saves the received order information in the database. At this time, the table number and order details are recorded as new order data.

[1536] Step 4:

[1537] The server sends the order information stored in the database to the AI ​​engine, which then sends the data to optimize cooking and serving procedures based on the order information.

[1538] Step 5:

[1539] The server (AI engine) analyzes the order information and calculates the optimal cooking and serving procedures. For example, it determines a specific procedure such as "prepare the hamburger first, prepare the salad, serve the salad, serve the drink, and serve the hamburger."

[1540] Step 6:

[1541] The server stores the AI ​​engine's calculation results in a database and sends optimized cooking and serving instructions to each display device, allowing each cook and server to receive instructions.

[1542] Step 7:

[1543] The device (tablet) displays optimized cooking and serving procedures in real time, showing specific work instructions such as "Step 1: Start cooking the hamburger steak, Step 2: Prepare the salad."

[1544] Step 8:

[1545] The user (cook) starts cooking according to the instructions on the terminal. For example, he / she cooks a hamburger steak as instructed, and then prepares a salad.

[1546] Step 9:

[1547] The user (the waiter) serves the food according to instructions on the terminal. For example, the salad is served as soon as it is ready, followed by the drinks, and finally the hamburger steak.

[1548] Step 10:

[1549] The device (tablet) and sensors capture the customer's facial expressions and tone of voice and send this data to the server. Specifically, a camera and microphone are used.

[1550] Step 11:

[1551] The server (emotion engine) analyzes the transmitted emotion data and recognizes the user's emotional state, for example, identifying whether the customer is satisfied or dissatisfied.

[1552] Step 12:

[1553] The server stores the emotion engine's recognition results in a database, and the emotion data is used to track customer satisfaction in real time.

[1554] Step 13:

[1555] The server adjusts cooking and serving procedures based on emotion recognition data. For example, if a customer expresses dissatisfaction, it changes instructions to prioritize serving procedures.

[1556] Step 14:

[1557] The server collects daily sales and inventory data, which are automatically recorded in a database.

[1558] Step 15:

[1559] The server sends the collected sales and inventory data to a business intelligence tool for analysis, specifically to determine which menu items are popular during specific times and how inventory is consumed.

[1560] Step 16:

[1561] The user (administrator) uses the business intelligence tool to check the analysis results and plan the next strategy, such as adjusting staff allocation or inventory to suit specific time periods.

[1562] The above is a series of processing steps in a system incorporating an emotion engine, which can increase customer satisfaction, improve business efficiency, and increase sales.

[1563] Example 2

[1564] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1565] Efficient operations and improved customer satisfaction are key challenges for modern restaurants. However, managing order information and optimizing cooking and serving procedures requires a lot of effort, and flexible responses based on customer sentiment are required. As a result, current systems have limitations, making it difficult to provide efficient and highly satisfying service.

[1566] 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.

[1567] In this invention, the server includes means for receiving order information, means for saving the received order information in a database, means having an artificial intelligence engine for optimizing cooking procedures and serving procedures based on the order information, means for sending the optimized cooking procedures and serving procedures to a display terminal, a display device for displaying the optimized cooking procedures and serving procedures, means having an emotion engine for recognizing the user's emotions and saving emotion data in a database, and means for adjusting the cooking procedures and serving procedures based on the emotion data. This enables efficient management of order information, optimization of cooking procedures and serving procedures using AI, and flexible operation according to customer emotions.

[1568] "Order information" is data that indicates the details of an order from a customer at a restaurant.

[1569] "Means for receiving" refers to the devices and technologies used to acquire order information and input it into the system.

[1570] "Database" refers to an information system for storing and managing received order information and emotion data.

[1571] An "artificial intelligence engine" refers to software and algorithms that calculate and analyze optimal cooking and serving procedures based on order information.

[1572] "Display terminal" refers to a device for visually displaying calculated cooking and serving instructions to a user.

[1573] "Display device" refers to a screen or device for displaying optimized cooking and serving instructions.

[1574] "User emotions" refers to the emotional state of customers, such as satisfaction or dissatisfaction.

[1575] An "emotion engine" refers to software or algorithms that analyze users' emotions and generate emotional data.

[1576] "Emotion data" refers to data that indicates the emotional state of a customer analyzed by the emotion engine.

[1577] "Adjustment means" refers to techniques and methods for changing cooking and serving procedures based on emotional data to provide optimal service.

[1578] "Sales data" refers to data that indicates information about daily sales.

[1579] "Inventory Data" refers to data that indicates information about inventory items and their quantities.

[1580] "Business intelligence tools" refers to the technology and software used to analyze collected data and derive business insights and strategies.

[1581] "Business improvement" refers to improvement activities aimed at improving business efficiency and quality.

[1582] "Strategic planning" refers to the activity of determining specific plans and policies to achieve business objectives.

[1583] MODE FOR CARRYING OUT THE INVENTION

[1584] This invention is a system that uses AI to optimize cooking and serving procedures based on order information in restaurants, and also recognizes user emotions to adjust operations. This system not only inputs and manages order information, and the AI ​​calculates and displays the optimal cooking and serving procedures, but also recognizes the user's emotional state and makes adjustments based on that, improving the quality of service.

[1585] System Configuration

[1586] The system includes the following elements:

[1587] 1. Means for receiving order information: Using an input device such as a POS system.

[1588] 2. Means for storing received order information in a database: A database server is used to manage order information.

[1589] 3. Means having an artificial intelligence engine for optimizing cooking procedures and serving procedures based on order information: an AI engine that implements a machine learning algorithm.

[1590] 4. Means for transmitting optimized cooking procedures and serving procedures to a display terminal: Information is transmitted to a display device such as a tablet via network communication.

[1591] 5. Display devices that show optimized cooking and serving procedures: tablets and projectors are used.

[1592] 6. Means having an emotion engine for recognizing the user's emotions and storing the emotion data in a database: data is acquired using a camera or microphone, and software implementing an emotion recognition algorithm is used.

[1593] 7. A means for adjusting cooking and serving procedures based on emotional data: A software module that works in conjunction with the AI ​​engine to make adjustments.

[1594] 8. Means of collecting sales and inventory data: Software that connects to a database and collects sales and inventory information.

[1595] 9. Business intelligence means to analyze collected data: Using analytical tools (e.g., business intelligence software).

[1596] Operation flow

[1597] For example, the process when an order for "hamburger steak, salad, and drink" is placed from table 1 will be explained.

[1598] The user (staff member) enters order information using the POS system, and the terminal sends it to the server in real time. The server saves the order information in a database and sends it to the AI ​​engine. The server (AI engine) calculates the optimal cooking and serving procedures based on the order information, saves the results in the database, and sends them to the display terminal.

[1599] The terminal (tablet) displays the procedure: "Start cooking hamburger steak, prepare salad, serve salad, serve drinks, serve hamburger steak," and the user (cooking staff) cooks and serves the steak according to the instructions.

[1600] The device (tablet) and sensors capture the customer's facial expressions and tone of voice and send the data to the server (emotion engine). The server (emotion engine) analyzes the data and, if it determines that the customer is dissatisfied, for example, changes the server's instructions to prioritize the serving procedure.

[1601] The server collects daily sales and inventory data and analyzes it using business intelligence tools. Based on the analysis results, users (administrators) can allocate staff and adjust inventory to match popular menu items during specific times.

[1602] Prompt Sentence Examples

[1603] "Could you explain a system in which AI calculates the optimal cooking and serving procedures based on order information in a restaurant, and also recognizes customer emotions and adjusts operations accordingly?"

[1604] In this way, incorporating emotion recognition functionality can increase customer satisfaction, improve business efficiency, and increase sales.

[1605] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1606] The flow of this system's program processing

[1607] Step 1: Receiving and storing order information

[1608] A user (staff member) uses the POS system to input order information from a customer. For example, "Table 1 orders a hamburger steak, salad, and drink."

[1609] Input: Customer order information

[1610] The terminal sends the entered order information to the server in real time. When an order is entered, the terminal immediately sends the information to the server.

[1611] Output: Order information data

[1612] The server stores the received order information in a database, and this captured data is used in subsequent processing steps.

[1613] Step 2: Optimize cooking and serving procedures

[1614] The server sends the order information stored in the database to the AI ​​engine, which then sends the order details to the AI ​​engine, which then begins the next analysis phase.

[1615] Input: Saved order information data

[1616] The server (AI engine) analyzes the received order information and calculates the optimal cooking and serving sequence, such as "cook the hamburger steak first, prepare the salad, serve the salad, serve the drink, and then serve the hamburger steak last."

[1617] Output: Optimized cooking and serving procedures

[1618] The server stores the calculated results in a database and sends the information to a display device such as a tablet.

[1619] Step 3: Emotion recognition and regulation by the emotion engine

[1620] The device (tablet) and sensors capture the customer's facial expressions and tone of voice and send this data to the server. For example, the tablet's built-in camera and microphone capture the customer's reactions.

[1621] Input: Customer's facial expression data and voice data

[1622] The server (emotion engine) analyzes the transmitted data and recognizes the user's emotional state. If the customer is smiling, it is determined to be satisfied, and if they have a stern expression, it is determined to be dissatisfied.

[1623] Output: Emotion data

[1624] The server stores the data obtained from the emotion engine in a database, which is later used to coordinate operations.

[1625] Step 4: View and adjust cooking and serving instructions

[1626] The device (tablet) displays optimized cooking and serving procedures in real time, such as "Start cooking hamburger steak, prepare salad, serve salad, serve drink, serve hamburger steak."

[1627] Input: Optimized cooking and serving procedures

[1628] The user (cook) starts cooking by following the instructions on the tablet. After cooking the hamburger steak as instructed, the user prepares the salad and then serves the food.

[1629] Output: Execute cooking and serving

[1630] The server takes into account the data from the emotion engine and adjusts cooking and serving procedures as needed, for example, changing instructions to prioritize serving procedures if a customer is unhappy.

[1631] Step 5: Analyze sales and inventory data

[1632] The server sends daily sales and inventory data to the business intelligence tool for analysis, allowing users to understand sales trends and inventory status.

[1633] Input: Sales data and inventory data

[1634] The user (administrator) uses a business intelligence tool to check the analysis results and plan the next strategy. For example, if it turns out that hamburger steak orders are concentrated during lunchtime, they can adjust staff allocation and inventory to suit that time period.

[1635] Output: Business improvement plans and strategies

[1636] (Application example 2)

[1637] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1638] While conventional food delivery systems can manage order information and optimize cooking and serving procedures, they are unable to grasp customers' emotional states in real time and adjust services accordingly. This makes it difficult to increase customer satisfaction and limits the efficiency of operations and sales. Therefore, there is a need for a system that can recognize customers' emotions and respond flexibly based on them.

[1639] 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 order information, means for saving the received order information in a database, means having an AI engine for optimizing cooking procedures and serving procedures based on the order information, means for transmitting the optimized cooking procedures and serving procedures to the display terminal, an emotion recognition engine for recognizing the emotional state of the customer, means for saving data obtained from the emotion recognition engine in a database and adjusting the cooking procedures and serving procedures, means for collecting sales data and inventory data, and means having a business intelligence tool for analyzing the collected data. This makes it possible to grasp the emotional state of customers in real time and improve the quality of service.

[1640] "Order information" is data indicating the details of an order from a customer.

[1641] A "database" is a system for electronically storing and managing information.

[1642] An "AI engine" is a component that uses artificial intelligence to analyze data and optimize specific tasks.

[1643] A "display terminal" is a device for displaying digital information, including tablets and smartphones.

[1644] The "emotion recognition engine" is a component that analyzes the customer's facial expressions and tone of voice to recognize their emotional state.

[1645] A "business intelligence tool" is software that collects and analyzes corporate data and supports decision-making.

[1646] "Sales data" is information relating to revenues earned from the sale of products.

[1647] "Inventory data" is information about the quantity and condition of goods and materials in a store.

[1648] "Cooking procedures" are the specific steps and methods for preparing a dish.

[1649] "Serving procedure" refers to the process or method for serving the finished food to the customer.

[1650] System Configuration

[1651] This invention is an AI system that receives order information from customers and optimizes cooking and serving procedures based on that information. It can also improve service quality by recognizing customer emotions and making adjustments based on those emotions. The system includes the following components:

[1652] 1. Means of receiving order information

[1653] 2. A means of storing received order information in a database

[1654] 3. An AI engine to optimize cooking and serving procedures based on order information

[1655] 4. Means for transmitting optimized cooking and serving instructions to the display device

[1656] 5. A device that displays optimized cooking and serving procedures

[1657] 6. Means of collecting sales and inventory data

[1658] 7. Business intelligence tools to analyze the collected data

[1659] 8. Emotion engine that recognizes customer emotions

[1660] 9. A means to store data obtained from the emotion engine in a database and adjust cooking and serving procedures as needed.

[1661] Hardware and software used

[1662] The system implementation uses the following hardware and software:

[1663] Smartphone (iOS / Android compatible)

[1664] Delivery robot (if needed)

[1665] Cloud server (AWS or Google Cloud)

[1666] AI engine (TensorFlow or PyTorch)

[1667] Emotion Engine (OpenCV and NLTK)

[1668] Database (MySQL or MongoDB)

[1669] Business intelligence tools (Tableau, Power BI)

[1670] Program processing explanation

[1671] 1. Receiving order information

[1672] Users input order information from customers using a smartphone app, and the smartphone then transmits the input order information to a cloud server in real time.

[1673] The server stores the received order information in a database.

[1674] 2. Optimizing cooking and serving procedures

[1675] The server sends the order information stored in the database to the AI ​​engine.

[1676] The server (AI engine) analyzes the order information and calculates the optimal cooking and serving procedures.

[1677] The server stores the calculation results in a database and sends them to the display terminal.

[1678] 3. Emotion recognition

[1679] The devices (smartphones and delivery robots) capture the customer's facial expressions and tone of voice and send this data to a cloud server.

[1680] The server (emotion engine) analyzes the transmitted data and recognizes the customer's emotional state.

[1681] The server stores the data obtained from the emotion engine in a database and adjusts cooking and serving procedures as needed.

[1682] 4. Collection and analysis of sales and inventory data

[1683] The server sends daily sales and inventory data to a business intelligence tool for analysis.

[1684] The user (administrator) uses a business intelligence tool to check the analysis results and plan the next strategy.

[1685] Specific examples

[1686] For example, if a customer uses a smartphone app to order "pizza, salad, and juice," the following process takes place:

[1687] The user enters order information into their smartphone and sends it to the cloud server.

[1688] The order information received by the server is stored in a database and analyzed by an AI engine.

[1689] The server (AI engine) calculates the optimal procedure, such as "prepare the pizza first, prepare the salad, serve the juice, serve the salad, and serve the pizza," and sends it to the display terminal.

[1690] The terminal captures the customer's emotional state and analyzes it on the server (emotion engine).

[1691] If the server determines that the customer is dissatisfied, the server changes the instructions to prioritize the serving procedure.

[1692] Example prompts for generative AI models

[1693] "Generate an AI model that uses this data to calculate optimal cooking and serving procedures, analyzes customer sentiment, and suggests procedures to provide the most satisfying service."

[1694] In this way, by incorporating a customer emotion recognition function, this system can increase customer satisfaction, improve business efficiency, and increase sales.

[1695] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1696] Step 1:

[1697] The user uses a smartphone app to input order information. The input order information includes specific menu items such as "pizza, salad, and juice." The device (smartphone) sends this information to the cloud server in real time. The input data is in text format, and each piece of order information is saved as a field. The operation in this step is to send the input order information to the cloud server.

[1698] Step 2:

[1699] The order information received by the server is saved in a database (MySQL). Specifically, the server analyzes the order information and stores each field (menu items, etc.) in a database table. The input data is the order information, and the saved data is the output. Data processing here involves converting the text-format order information into a database table using SQL statements.

[1700] Step 3:

[1701] The server sends the order information stored in the database to an AI engine (TensorFlow). The AI ​​engine analyzes the order information and calculates the optimal cooking and serving procedures. The input data is the order information extracted from the database, and the output is the calculated cooking and serving procedures. The data calculation here involves the AI ​​engine calculating the cooking and serving procedures based on a predictive model.

[1702] Step 4:

[1703] The server stores the calculation results in a database and sends them to the display device (smartphone or tablet). Specifically, the server stores the optimized cooking and serving instructions received from the AI ​​engine in the database using SQL statements. The input data is the output from the AI ​​engine, and the data stored in the database is the output.

[1704] Step 5:

[1705] The device (smartphone or tablet) captures the customer's facial expression and tone of voice. Specifically, the device's built-in camera and microphone collect facial expression and voice data. The input data is the customer's facial expression and tone of voice, and the captured data is the output.

[1706] Step 6:

[1707] The device sends the captured data to a cloud server. Here, data collected by the camera and microphone is sent to the server in real time. The input data is the captured facial expression and tone of voice data, and the output is the data sent to the server.

[1708] Step 7:

[1709] The server (emotion engine) analyzes the transmitted data and recognizes the customer's emotional state. Specifically, the server uses OpenCV and NLTK to perform facial expression recognition and voice analysis. The input data is facial expression and tone of voice data transmitted from the device, and the output is the recognized emotional state. The data calculation here is emotion analysis based on a machine learning model.

[1710] Step 8:

[1711] The server stores the data obtained from the emotion engine in a database and adjusts the cooking and serving instructions as needed. The input data is the output from the emotion engine, and the output is the adjusted cooking and serving instructions. Data processing here involves calculating and saving new instructions that take the emotion data into account.

[1712] Step 9:

[1713] The server collects daily sales and inventory data, sends it to a business intelligence tool (Tableau), and analyzes it. Specifically, the server collects sales and inventory data from each store and sends it to the analysis tool. The input data is sales and inventory data, and the output is the analysis results from the business intelligence tool.

[1714] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1715] 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.

[1716] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1717] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1718] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1719] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1720] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1721] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1722] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1723] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1724] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1725] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1726] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1727] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1728] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1729] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1730] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1731] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1732] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1733] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1734] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1735] The following is further disclosed regarding the above embodiment.

[1736] (Claim 1)

[1737] means for receiving order information;

[1738] means for storing the received order information in a database;

[1739] A means having an AI engine for optimizing cooking procedures and serving procedures based on order information;

[1740] means for transmitting the optimized cooking and serving instructions to a display terminal;

[1741] a terminal that displays optimized cooking and serving procedures;

[1742] A system including:

[1743] (Claim 2)

[1744] a means of collecting sales and inventory data;

[1745] means for analyzing the collected data and a business intelligence tool for analyzing the collected data;

[1746] 10. The system of claim 1.

[1747] (Claim 3)

[1748] means for cooking and serving food in accordance with the optimized cooking procedure and serving procedure in the display terminal;

[1749] A means of improving business operations and formulating strategies based on the analysis results,

[1750] 10. The system of claim 1.

[1751]

[1752] "Example 1"

[1753] (Claim 1)

[1754] means for receiving order information;

[1755] means for storing the received order information in a database;

[1756] A means of sending stored order information to an AI engine to optimize cooking and serving procedures;

[1757] means for storing the optimized cooking and serving procedures in a database and transmitting the same to a display terminal;

[1758] a terminal that displays optimized cooking and serving procedures;

[1759] A system including:

[1760] (Claim 2)

[1761] a means for collecting and transmitting sales and inventory data to a business analytics tool;

[1762] A means of improving business operations and formulating strategies based on the analysis results,

[1763] 10. The system of claim 1.

[1764] (Claim 3)

[1765] means for cooking and serving food in accordance with the optimized cooking procedure and serving procedure in the display terminal;

[1766] 10. The system of claim 1.

[1767] "Application Example 1"

[1768] (Claim 1)

[1769] means for receiving order information;

[1770] means for storing the received order information in a database;

[1771] means having an artificial intelligence engine for optimizing cooking and serving procedures based on order information;

[1772] means for transmitting the optimized cooking and serving instructions to a display terminal;

[1773] a terminal that displays optimized cooking and serving procedures;

[1774] means for optimizing cooking and packaging procedures based on order information;

[1775] a means for calculating a delivery route;

[1776] A system including:

[1777] (Claim 2)

[1778] a means of collecting sales and inventory data;

[1779] means for analyzing the collected data and a business intelligence tool for analyzing the collected data;

[1780] 10. The system of claim 1.

[1781] (Claim 3)

[1782] means for cooking, packaging and serving food in accordance with the optimized cooking procedure, serving procedure and delivery route in the display terminal;

[1783] A means of improving business operations and formulating strategies based on the analysis results,

[1784] 10. The system of claim 1.

[1785] "Example 2: Combining Emotion Engines"

[1786] (Claim 1)

[1787] means for receiving order information;

[1788] means for storing the received order information in a database;

[1789] means having an artificial intelligence engine for optimizing cooking and serving procedures based on order information;

[1790] means for transmitting the optimized cooking and serving instructions to a display terminal;

[1791] a display device that displays the optimized cooking and serving procedures;

[1792] means having an emotion engine for recognizing user emotions and storing emotion data in a database;

[1793] means for adjusting cooking and serving procedures based on the emotion data;

[1794] A system including:

[1795] (Claim 2)

[1796] a means of collecting sales and inventory data;

[1797] Business intelligence measures to analyze the collected data;

[1798] 10. The system of claim 1.

[1799] (Claim 3)

[1800] means for cooking and serving food in accordance with the optimized cooking and serving procedures in the display device;

[1801] means for adjusting cooking and serving procedures based on the emotion data;

[1802] A means of improving business operations and formulating strategies based on the analysis results,

[1803] 10. The system of claim 1.

[1804] "Application example 2 when combining emotion engines"

[1805] (Claim 1)

[1806] means for receiving order information;

[1807] means for storing the received order information in a database;

[1808] A means having an AI engine for optimizing cooking procedures and serving procedures based on order information;

[1809] means for transmitting the optimized cooking and serving instructions to a display terminal;

[1810] a terminal that displays optimized cooking and serving procedures;

[1811] an emotion recognition engine that recognizes the emotional state of the customer;

[1812] means for storing data obtained from the emotion recognition engine in a database and adjusting cooking and serving procedures;

[1813] A system including:

[1814] (Claim 2)

[1815] a means of collecting sales and inventory data;

[1816] means for analyzing the collected data and a business intelligence tool for analyzing the collected data;

[1817] 10. The system of claim 1.

[1818] (Claim 3)

[1819] means for cooking and serving food in accordance with the optimized cooking procedure and serving procedure in the display terminal;

[1820] a means for adjusting cooking and serving procedures based on the emotional state of the customer;

[1821] A means of improving business operations and formulating strategies based on the analysis results,

[1822] 10. The system of claim 1. [Explanation of symbols]

[1823] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving order information; means for storing the received order information in a database; A means having an AI engine for optimizing cooking procedures and serving procedures based on order information; means for transmitting the optimized cooking and serving instructions to a display terminal; a terminal that displays optimized cooking and serving procedures; A system including:

2. a means of collecting sales and inventory data; means for analyzing the collected data and a business intelligence tool for analyzing the collected data; The system of claim 1 .

3. means for cooking and serving food in accordance with the optimized cooking procedure and serving procedure in the display terminal; A means of improving business operations and formulating strategies based on the analysis results, The system of claim 1 .

Images