System

Abstract

A system is provided.SOLUTION: A system comprising: user interface means for a receiver to input and change a desired delivery time; communication means for transmitting the desired delivery time input through the user interface means to a server; data management means for receiving the desired delivery time transmitted by the communication means and storing the desired delivery time in a database; route generation means for generating an optimal delivery route based on the desired delivery time stored in the data management means; and notification means for transmitting information on the delivery route generated by the route generation means to a terminal of a deliverer.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In the delivery industry, it is difficult to reflect the recipient's desired delivery time in real time, which can lead to redelivery and delivery delays. This also increases the burden on the deliverer, making efficient routing difficult. For these reasons, there is a need to build a system that allows real-time communication between the recipient and the deliverer. [Means for solving the problem]

[0005] The present invention provides a user interface means for the recipient to input and change a desired delivery time, and includes a communication means for transmitting the input desired delivery time to a server. The server has a data management means for storing the received desired delivery time in a database, and a route generation means for generating an optimal delivery route based on the stored information. It also has a notification means for sending information about the generated delivery route to the sender's terminal. This configuration allows changes on the recipient's side to be reflected in real time, providing an efficient delivery route, thereby reducing redelivery and delivery delays.

[0006] The "user interface means" is a means for providing an interface for the recipient to input and change the desired delivery time.

[0007] The "communication means" is a means for transmitting the desired delivery time input via the user interface means to the server.

[0008] The "data management means" is a means for receiving the desired delivery time transmitted by the communication means and storing it in a database.

[0009] The "route generation means" is a means for generating an optimal delivery route based on the desired delivery time stored in the data management means.

[0010] The "notification means" is a means for transmitting information about the delivery route generated by the route generation means to the terminal of the deliverer.

[0011] "Recipient" refers to the person who receives the delivery and has the right to input and change the desired delivery time through the user interface means.

[0012] The term "deliverer" refers to a person who delivers a delivery to a recipient, and who performs the work based on the delivery route information transmitted by the notification means.

[0013] The "server" is a computer system that receives desired delivery times via communication means and manages and generates delivery routes through data management means and route generation means.

[0014] "Delivery route" refers to the optimal route calculated by the route generation means in order to efficiently deliver the delivery item. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

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

[0025] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0032] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] The present invention relates to a system that provides a user interface for the recipient to input and change a desired delivery time and includes a communication means for transmitting the input desired delivery time to a server. The system has a data management means for storing the desired delivery time received by the server in a database, and a route generation means for generating an optimal delivery route based on the stored information. It also has a notification means for transmitting information about the generated delivery route to the sender's terminal. This configuration allows changes made by the recipient to be reflected in real time, providing an efficient delivery route, thereby reducing redelivery and delivery delays.

[0037] (Example of specific program processing)

[0038] 1. The user changes the desired delivery time

[0039] Processing Description

[0040] Users can change the pickup time through the "Rakuhai" app. For example, a user can select "I want to change the delivery time to between 3:00 PM and 5:00 PM today."

[0041] Examples:

[0042] If User A wishes to change the current delivery time from "18:00-20:00" to "15:00-17:00", he or she uses the user interface means to select a new delivery time from the settings screen of the app and presses the "Confirm" button.

[0043] 2. The device sends the desired delivery time

[0044] Processing Description

[0045] After the user presses the confirm button, the terminal transmits the new desired delivery time to the server.

[0046] Examples:

[0047] User A's smartphone generates the information "Change to 15:00-17:00" in JSON format and sends it to the "Rakuhai" system server.

[0048] 3. The server updates the recipient's desired delivery time.

[0049] Processing Description

[0050] The server saves the received desired delivery time in the database, and updates the existing delivery information at the same time.

[0051] Examples:

[0052] The server updates User A's delivery schedule in the database from "18:00-20:00" to "15:00-17:00."

[0053] 4. The server generates an efficient delivery route

[0054] Processing Description

[0055] The server generates a new, optimized delivery route based on the latest desired delivery time using a generative AI model that also takes into account the deliverer's current location and traffic information.

[0056] Examples:

[0057] The server recalculates the optimal delivery route using the route generation AI, taking into account all other delivery information and User A's new time.

[0058] 5. The device retrieves the latest delivery route.

[0059] Processing Description

[0060] The deliverer's terminal receives the notification from the server and acquires the new route information, allowing the deliverer to deliver efficiently based on the latest delivery route.

[0061] Examples:

[0062] Delivery person B uses the "Rakuhai" app to check the latest delivery route notified by the server. This route reflects User A's new delivery time.

[0063] With the above configuration, the present invention provides a system that reflects changes in recipient preferences in real time and supports efficient delivery routing. This system reduces redelivery and delivery delays and improves the work efficiency of deliverers.

[0064] The processing flow will be explained below.

[0065] Specific explanation of program processing

[0066] (Step 1: User changes desired delivery time)

[0067] 1. The user launches the "Rakuhai" app.

[0068] 2. The user accesses their My Page or Order Details page and displays delivery details.

[0069] 3. The user selects the desired delivery time section and selects a new preferred time slot.

[0070] 4. The user confirms the changes and presses the "Confirm" button.

[0071] (Step 2: The device sends the desired delivery time)

[0072] 1. Obtain the data of the desired delivery time changed through the user interface means.

[0073] 2. The desired delivery time obtained by the device is converted into JSON format.

[0074] 3. The device sends a request to change the desired delivery time to the backend API endpoint.

[0075] 4. The device waits for a response from the server.

[0076] (Step 3: The server updates the recipient's desired delivery time)

[0077] 1. The server analyzes the request to change the desired delivery time received from the terminal.

[0078] 2. The server extracts the delivery ID and new desired delivery time from the request data.

[0079] 3. The server generates a database query based on the delivery ID to update the desired delivery time for the corresponding record to the new value.

[0080] 4. The server executes the generated database query.

[0081] 5. The server verifies that the database update completed successfully.

[0082] 6. The server sends a response to the terminal indicating that the desired delivery time has been successfully updated.

[0083] (Step 4: The server generates an efficient delivery route)

[0084] 1. The server re-fetches all delivery schedule information from the database.

[0085] 2. The server prepares to input all the delivery schedule information it has obtained into the generative AI model.

[0086] 3. The server also obtains the current location data of the deliverer and real-time traffic information.

[0087] 4. The server inputs all necessary data into the generated AI model and has it calculate the optimal delivery route.

[0088] 5. The server saves the generated optimal delivery route in the delivery route table in the database.

[0089] 6. The server sends a notification containing the new delivery route information to the deliverer's terminal.

[0090] (Step 5: The device retrieves the latest delivery route)

[0091] 1. The device receives a push notification from the server.

[0092] 2. The device analyzes the contents of the push notification and prepares a request to obtain a new delivery route.

[0093] 3. The device sends a request to the server's API endpoint to obtain the latest delivery route information.

[0094] 4. The terminal receives the response from the server and obtains the new delivery route data.

[0095] 5. The new delivery route data acquired by the device is displayed in the app's UI.

[0096] 6. The terminal notifies the user of the latest delivery route information and allows them to confirm it.

[0097] These are the program processing steps of the "Rakuhai" app. Through this specific processing, it is possible to reflect the recipient's desired delivery time in real time and generate and manage efficient delivery routes.

[0098] Example 1

[0099] 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."

[0100] In modern logistics systems, desired delivery times often change on the recipient's side, and there is a need to reflect these changes in real time and optimize delivery routes. Conventional systems have difficulty responding to sudden changes in desired delivery times or traffic information, which can lead to redelivery and delivery delays. Therefore, there is a need for a system that can quickly and efficiently reflect changes in desired delivery times on the recipient's side and generate optimal delivery routes.

[0101] 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.

[0102] In this invention, the server includes input means for the recipient to input or change the desired delivery time, transmission means for transmitting the desired delivery time input via the input means to the server, storage means for receiving the desired delivery time transmitted by the transmission means and storing it in a database, route generation means for generating an optimal delivery route based on the desired delivery time stored in the storage means, notification means for transmitting information on the delivery route generated by the route generation means to the deliverer's terminal, and supply and demand optimization means for optimizing the delivery route based on the deliverer's current situation and traffic information using a generative AI model. This allows changes in the recipient's request to be reflected in real time, reducing redelivery and delivery delays and enabling the generation of efficient delivery routes.

[0103] The "input means" is an interface device that allows the recipient to input or change the desired delivery time.

[0104] The "transmission means" is a device for transmitting the desired delivery time input via the input means to the server via the network.

[0105] The "storage means" is a device that receives the desired delivery time sent by the transmission means and stores it in a database.

[0106] The "route generation means" is a device for generating an optimal delivery route based on the desired delivery time stored in the storage means.

[0107] The "notification means" is a device for transmitting information about the delivery route generated by the route generation means to the terminal of the deliverer.

[0108] The "supply and demand optimization means" is a device that uses a generative AI model to calculate and generate the optimal delivery route based on the delivery person's current location and traffic information.

[0109] A "generative AI model" is an artificial intelligence model that uses machine learning algorithms to derive optimal delivery routes from input data.

[0110] A "prompt statement" is an instruction statement that causes a generative AI model to perform specific data processing or calculations.

[0111] The present invention is configured to provide an efficient delivery system, which allows recipients to input and change their desired delivery time, and this information is reflected in delivery management in real time.

[0112] First, the user operates the delivery app using a device such as a smartphone or PC. This delivery app has an input means and provides an interface that allows the user to select or change the desired delivery time. For example, the user can select "15:00-17:00" and press the "Confirm" button to enter the new desired delivery time.

[0113] Next, the terminal uses the transmission means to transmit this new desired delivery time to the server. The transmitted data can be in a general data format such as JSON format.

[0114] The server receives the desired delivery time data sent from the sending means and saves the information in the database using the saving means. Specifically, the server analyzes the received JSON data and stores the information in the database as an SQL query. At this time, the existing delivery information is also updated.

[0115] Based on the desired delivery time stored in the storage means, the server uses the route generation means to generate the optimal delivery route. A generative AI model is used here, which generates a route that takes into account the user's new desired delivery time, the delivery person's current location, traffic information, etc. The following prompt sentences are used in this process:

[0116] Prompt Sentence Examples

[0117] "Please generate the optimal delivery route taking into account the next delivery information, the current location of the delivery person, and traffic information. The new desired delivery time is 3:00 PM to 5:00 PM."

[0118] The generated optimal delivery route is sent to the deliverer's terminal using a notification means. This notification allows the deliverer to check the latest delivery route on their own terminal and deliver efficiently accordingly.

[0119] For example, if a delivery person has a dedicated delivery device, they will receive a real-time notification on that device saying, "A new delivery route has been set." This notification prompts the delivery person to open the "delivery app," check the new route information, and begin delivery.

[0120] A key feature of this invention is that if a user changes their desired delivery time, the change is reflected in real time. This reduces redelivery and delivery delays, resulting in more efficient delivery. Furthermore, by using a generative AI model, the system takes into account the current location of the deliverer and real-time traffic information, allowing for the generation of optimal delivery routes.

[0121] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0122] Divide the processing flow of this system's program into processing steps

[0123] Step 1: User enters or changes desired delivery time

[0124] Step 2: The device sends the desired delivery time to the server

[0125] Step 3: Store the requested delivery time received by the server in a database

[0126] Step 4: The server generates an efficient delivery route

[0127] Step 5: The delivery person's device receives the latest delivery route

[0128] Detailed description of each processing step

[0129] Step 1: User enters or changes desired delivery time

[0130] Input: A user launches a delivery app and selects a delivery time.

[0131] Output: A delivery time change request is generated.

[0132] Specific actions

[0133] The user opens the delivery app, selects the desired time slot from the displayed time slots, and presses the "Confirm" button. For example, if the user wants to change the time slot to "15:00-17:00," select that time slot and press the "Confirm" button.

[0134] Step 2: The device sends the desired delivery time to the server

[0135] Input: User selected delivery time information.

[0136] Output: Sends a request to change the desired delivery time to the server.

[0137] Specific actions

[0138] The user's device converts the selected desired delivery time into JSON format and sends it to the server as an HTTP POST request. For example, the user's device generates JSON data including the time information "15:00~17:00" and sends it to the server.

[0139] Step 3: Store the requested delivery time received by the server in a database

[0140] Input: JSON data of the desired delivery time sent to the server.

[0141] Output: The requested delivery time information updated in the database.

[0142] Specific actions

[0143] The server parses the received JSON data and saves the user's delivery information in the database. For example, if the server receives data for "15:00~17:00", it parses it, generates an SQL query, and updates the delivery information in the database.

[0144] Step 4: The server generates an efficient delivery route

[0145] Input: Latest desired delivery time information stored in the database, current location information of the delivery person, and traffic information.

[0146] Output: The generated optimal delivery route.

[0147] Specific actions

[0148] The server uses the generative AI model to generate the optimal delivery route based on the latest desired delivery time, the delivery person's current location, and traffic information. At this point, the server sends the following prompt to the generative AI model:

[0149] Example prompt: "Generate the optimal delivery route taking into account the following delivery information, the delivery person's current location, and traffic information. The new desired delivery time is between 3:00 PM and 5:00 PM."

[0150] The server receives the optimal delivery route generated by the generative AI model and stores that information.

[0151] Step 5: The delivery person's device receives the latest delivery route

[0152] Input: Optimal delivery route information sent from the server.

[0153] Output: The updated delivery route displayed on the delivery person's terminal.

[0154] Specific actions

[0155] The server notifies the delivery person's device of the new delivery route information, and the device receives this information. For example, the delivery person's device receives a notification that "a new delivery route has been set," and can check the latest delivery route within the app.

[0156] Through the above steps, even if the user changes the desired delivery time, the change is reflected in real time, an optimal delivery route is generated, and delivery is carried out efficiently.

[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] In food delivery, when a user changes their desired delivery time, the delivery person's route becomes inefficient, resulting in redelivery and delays. When this happens, user satisfaction decreases and delivery efficiency drops significantly. To solve this, a system is needed that can reflect changes in the desired delivery time in real time and generate the optimal delivery route.

[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 a display device for the recipient to input and change the desired delivery time, a data transmission device for transmitting the desired delivery time input via the display device to the server, a data storage device for receiving the desired delivery time transmitted by the data transmission device and storing it in a database, a route generation device for generating an optimal delivery route based on the desired delivery time stored in the data storage device, a notification device for transmitting the delivery route generated by the route generation device to the carrier's terminal, and a processing device using artificial intelligence to optimize the delivery route generated by the route generation device. This allows the optimal delivery route to be generated in real time even when the user changes the delivery time, thereby improving delivery efficiency and reducing delays.

[0162] The "display device" is a device that provides an interactive operation screen for the recipient to input and change the desired delivery time.

[0163] The "data transmission means" is a means having a communication function for transmitting the desired delivery time input via the display means to the server.

[0164] The "data storage means" is a means for receiving the desired delivery time transmitted by the data transmission means and storing it in a database.

[0165] The "route generation means" is a means for generating an optimal delivery route based on the desired delivery time stored in the data storage means.

[0166] The "notification means" is a means for transmitting information about the delivery route generated by the route generation means to the carrier's terminal.

[0167] The "processing means" is a means that uses artificial intelligence to optimize the delivery route generated by the route generation means.

[0168] The "server" is a central processing unit that receives the desired delivery time, stores the data, generates routes, and sends notifications.

[0169] "Transporter's terminal" refers to an information processing device carried by the transporter to receive and display delivery route information notified from the server.

[0170] "Real-time" means that the moment a user changes their desired delivery time, the change is immediately reflected throughout the entire delivery system.

[0171] "Generative artificial intelligence" refers to machine learning algorithms and AI models that generate and optimize optimal delivery routes based on large amounts of data.

[0172] The present invention provides a system that allows recipients to change their desired delivery time in real time in order to significantly improve the efficiency of food delivery. Specific embodiments of this system are described below.

[0173] System Overview

[0174] This system consists of the following main elements:

[0175] 1. Display device means

[0176] 2. Data transmission method

[0177] 3. Data storage method

[0178] 4. Route Generation Method

[0179] 5. Means of notification

[0180] 6. Processing Means

[0181] Hardware and Software Use

[0182] Hardware: Smartphones, servers, carrier terminals

[0183] Software: Food delivery app (compatible with iOS / Android), database system (MySQL, PostgreSQL, etc.), route generation AI model (TensorFlow, PyTorch, etc.)

[0184] display means

[0185] The recipient can input and change the desired delivery time through the smartphone app. The display device means provides an interactive operation screen and is designed to allow the user to easily select the desired delivery time.

[0186] Examples:

[0187] If a user opens a food delivery app and wants to change their current desired delivery time from "18:00-20:00" to "15:00-17:00," they select a new time on the app screen and press the "Confirm" button.

[0188] Data transmission method

[0189] After a user changes their desired delivery time, their smartphone generates the new desired time as JSON data and sends it to the server via an HTTPS request, ensuring that the information reaches the server securely and quickly.

[0190] Data storage means

[0191] The server stores the received desired delivery time in a database. The stored data reflects the updated desired delivery time, and existing delivery information is updated appropriately.

[0192] Route Generation Method

[0193] Based on the latest desired delivery times stored in the database, the server generates the optimal delivery route using a generative AI model, taking into account the carrier's current location and traffic information.

[0194] Examples:

[0195] The server takes into account all delivery information and the user's new desired time and uses route generation AI to recalculate the optimal delivery route.

[0196] Notification means

[0197] The generated new delivery route is notified to the carrier's terminal, allowing the carrier to act efficiently based on the latest delivery route.

[0198] Examples:

[0199] The carrier uses the app to check the updated delivery route provided by the server, which now reflects the user's new delivery time.

[0200] Processing means

[0201] Processing methods using generative artificial intelligence generate and optimize optimal delivery routes based on large amounts of data, thereby improving delivery efficiency and minimizing delays.

[0202] Prompt Sentence Examples

[0203] If the desired delivery time changes, generate the optimal delivery route based on the new desired time. Take the following data into consideration:

[0204] Current location of the deliverer

[0205] Traffic information

[0206] Other delivery schedules

[0207] In this way, the system reflects changes in desired delivery times in real time and provides the optimal delivery route, thereby improving the efficiency of food delivery.

[0208] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0209] Step 1:

[0210] The user uses the display device to input and change the desired delivery time.

[0211] Input: Current desired delivery time and new desired delivery time

[0212] Output: Confirmation of new desired time

[0213] Specific action: The user selects a new desired delivery time on the settings screen of a food delivery app and presses the "Confirm" button.

[0214] Step 2:

[0215] The terminal generates a new desired delivery time as data in JSON format and transmits it to the server via the data transmission means.

[0216] Input: New desired delivery time selected and confirmed by the user

[0217] Output: HTTPS request to the server

[0218] What happens: The smartphone generates JSON data containing the new desired delivery time and sends it to the server via an HTTPS request.

[0219] Step 3:

[0220] The server receives the data and stores the new desired delivery time in a database using the data storage means.

[0221] Input: JSON data of the new desired delivery time sent from the device

[0222] Output: Desired delivery time updated in the database

[0223] What happens: The server analyzes the received data and updates the existing delivery information with the new desired delivery time.

[0224] Step 4:

[0225] The server uses the route generation means to generate an optimal delivery route based on the new desired delivery time.

[0226] Input: Updated desired delivery time, current delivery information, carrier's current location, traffic information

[0227] Output: Optimized delivery route

[0228] How it works: Using generative artificial intelligence, it recalculates the optimal delivery route based on all input data.

[0229] Step 5:

[0230] The server transmits the newly generated delivery route information to the carrier's terminal via the notification means.

[0231] Input: Optimized delivery route information

[0232] Output: Notification to carrier terminal and route information update

[0233] Specific operation: The server generates new delivery route data and sends it to the carrier's device via push notification.

[0234] Step 6:

[0235] The carrier's terminal displays the new delivery route information received from the server and delivers the goods according to it.

[0236] Input: New delivery route information sent from the server

[0237] Output: Efficient delivery by carriers

[0238] Specific operation: The carrier's terminal displays the latest delivery route information, and the carrier makes the delivery based on that information.

[0239] This process allows the system to generate the optimal delivery route in real time, even if the user changes the desired delivery time, preventing delays and redelivery.

[0240] 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.

[0241] The present invention relates to a system that provides a user interface for a recipient to input and change a desired delivery time and includes a communication means for transmitting the input desired delivery time to a server. The system has a data management means for storing the desired delivery time received by the server in a database, and a route generation means for generating an optimal delivery route based on the stored information. The system also has a notification means for transmitting information about the generated delivery route to the deliverer's terminal. The system also includes an emotion engine for recognizing the recipient's emotions, and is able to propose a desired delivery time and optimize the delivery route by taking into account the emotion information obtained from the emotion engine.

[0242] (Example of specific program processing)

[0243] 1. The user changes the desired delivery time

[0244] Processing Description

[0245] Users can change or input the pickup time through the "Rakuhai" app. For example, a user can select "I want to change the delivery time to between 3:00 PM and 5:00 PM today." At this time, the emotion engine recognizes the user's emotion and acquires emotion data.

[0246] Examples:

[0247] If User A wishes to change the current delivery time from "18:00-20:00" to "15:00-17:00," he or she selects a new delivery time from the app's settings screen using the user interface means and presses the "Confirm" button. At this time, the emotion engine detects that User A is feeling stressed and suggests an earlier time slot.

[0248] 2. The device sends the desired delivery time

[0249] Processing Description

[0250] When the user confirms the desired delivery time, the terminal transmits the new desired delivery time and emotion data to the server.

[0251] Examples:

[0252] User A's smartphone generates the information "change to 15:00-17:00" and emotion data in JSON format and sends it to the server.

[0253] 3. The server updates the recipient's desired delivery time.

[0254] Processing Description

[0255] The server stores the received desired delivery time and emotion data in a database, and updates the existing delivery information.

[0256] Examples:

[0257] The server updates User A's delivery schedule in the database from "18:00-20:00" to "15:00-17:00" and also saves the emotion data.

[0258] 4. The server generates an efficient delivery route

[0259] Processing Description

[0260] The server generates a new, optimized delivery route based on the latest desired delivery time and emotion data, using a generative AI model that also takes into account the deliverer's current location and traffic information.

[0261] Examples:

[0262] The server recalculates the optimal delivery route using the route generation AI, taking into account all other delivery information and User A's new time and emotion data.

[0263] 5. The device retrieves the latest delivery route.

[0264] Processing Description

[0265] The deliverer's terminal receives the notification from the server and acquires the new route information, allowing the deliverer to deliver efficiently based on the latest delivery route.

[0266] Examples:

[0267] Delivery person B uses the "Rakuhai" app to check the latest delivery route notified by the server. This route reflects User A's new delivery time and has been prioritized based on the emotion data.

[0268] With the above configuration, the present invention provides a system that supports more efficient delivery routing with higher user satisfaction by reflecting changes in recipient preferences and emotional information in real time. This system reduces redelivery and delivery delays, improves the work efficiency of deliverers, and increases convenience and satisfaction for recipients.

[0269] The processing flow will be explained below.

[0270] (Example of specific program processing)

[0271] 1. The user changes the desired delivery time

[0272] Step 1:

[0273] The user launches the "Rakuhai" app.

[0274] Step 2:

[0275] The user accesses their My Page or Order Details page and displays delivery details.

[0276] Step 3:

[0277] The user selects the desired delivery time section and selects a new desired time slot. At this time, the emotion engine recognizes the user's emotions from facial expressions, voice, etc. and captures them as data.

[0278] Step 4:

[0279] The user confirms the changes and presses the "Confirm" button.

[0280] 2. The device sends the desired delivery time and emotion data

[0281] Step 1:

[0282] The terminal collects the desired delivery time data and emotion data acquired through the user interface means.

[0283] Step 2:

[0284] The device converts this data into JSON format.

[0285] Step 3:

[0286] The device sends a request to the backend API endpoint to change the desired delivery time and emotion data.

[0287] Step 4:

[0288] The terminal waits for a response from the server.

[0289] 3. The server updates the recipient's desired delivery time and emotion data.

[0290] Step 1:

[0291] The server analyzes the request for change of desired delivery time and emotion data received from the terminal.

[0292] Step 2:

[0293] The server extracts the delivery ID, new desired delivery time, and emotion data from the request data.

[0294] Step 3:

[0295] Based on the delivery ID, the server generates a database query to update the desired delivery time and emotion data of the corresponding record to new values.

[0296] Step 4:

[0297] The server executes the generated database query.

[0298] Step 5:

[0299] The server verifies that the database update completed successfully.

[0300] Step 6:

[0301] The server sends a response to the terminal indicating that the desired delivery time and emotion data have been successfully updated.

[0302] 4. The server generates an efficient delivery route

[0303] Step 1:

[0304] The server retrieves all delivery schedule information and emotion data from the database.

[0305] Step 2:

[0306] The server prepares to input all the delivery schedule information it has obtained into the generative AI model.

[0307] Step 3:

[0308] The server also obtains the current location data of the deliverer and real-time traffic information.

[0309] Step 4:

[0310] The server inputs all necessary data into the generated AI model, which calculates the optimal delivery route, adjusting the urgency and priority based on emotional data.

[0311] Step 5:

[0312] The server stores the generated optimal delivery route in a delivery route table in the database.

[0313] Step 6:

[0314] The server sends a notification containing new delivery route information to the deliverer's terminal.

[0315] 5. The device retrieves the latest delivery route.

[0316] Step 1:

[0317] The device receives a push notification from the server.

[0318] Step 2:

[0319] The device analyzes the contents of the push notification and prepares a request to obtain a new delivery route.

[0320] Step 3:

[0321] The terminal sends a request to the server's API endpoint to obtain the latest delivery route information.

[0322] Step 4:

[0323] The terminal receives the response from the server and acquires new delivery route data.

[0324] Step 5:

[0325] The new delivery route data acquired by the device is displayed in the app's UI.

[0326] Step 6:

[0327] The terminal notifies the user of the latest delivery route information and allows the user to confirm it.

[0328] Example 2

[0329] 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."

[0330] In conventional delivery systems, changes to desired delivery times are not reflected in real time, and delivery routes are determined without taking into account the feelings of the recipient, resulting in frequent redelivery and reduced delivery efficiency and user satisfaction. Furthermore, efficient delivery is difficult because routes are generated without sufficient consideration of the deliverer's current location or traffic information.

[0331] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a user interface means for the recipient to input and change the desired delivery time, a communication means for transmitting the desired delivery time input via the user interface means to the server, a data management means for receiving the desired delivery time and emotion data transmitted by the communication means and storing them in a database, a route generation means for generating an optimal delivery route based on the desired delivery time and emotion data stored in the data management means, and a notification means for transmitting information about the delivery route generated by the route generation means to the deliverer's terminal. This allows changes to the desired delivery time to be reflected in real time, enabling the generation of an efficient delivery route that takes emotion information into account. It also enables the generation of an optimal route that takes the deliverer's current location and traffic information into account.

[0332] "User interface means" refers to an interface that allows the recipient to input and change the desired delivery time.

[0333] The "communication means" refers to a means for transmitting the desired delivery time input via the user interface means to the server.

[0334] "Data management means" refers to a means for receiving the desired delivery time and emotion data sent by the communication means and storing them in a database.

[0335] The "route generation means" refers to a means for generating an optimal delivery route based on the desired delivery time and emotion data stored in the data management means.

[0336] The "notification means" refers to a means for transmitting information about the delivery route generated by the route generation means to the terminal of the deliverer.

[0337] A "generative AI model" refers to an artificial intelligence model that generates optimal delivery routes using data such as desired delivery time, emotional data, the delivery person's current location, and traffic information.

[0338] "Emotional data" refers to data obtained by analyzing the user's emotions, and refers to information that can affect changes to the desired delivery time or route generation.

[0339] This invention describes a system that provides a user interface means for the recipient to input and change the desired delivery time, a communication means for transmitting the input desired delivery time to a server, and a system that uses this data to generate the optimal delivery route.

[0340] In this system, the user first launches the "Rakuhai" app on a device such as a smartphone or tablet. The user then selects the option to change the delivery time within the app and enters the new desired delivery time. At this time, the emotion engine analyzes the user's emotions and acquires emotional data. As a specific example, if a user wants to change the current delivery time from "18:00-20:00" to "15:00-17:00," they select a new delivery time from the app's settings screen and press the "Confirm" button. At this time, the emotion engine detects that the user is feeling stressed and suggests an earlier time slot.

[0341] When the user confirms the desired delivery time, the device generates the new desired delivery time and emotion data in JSON format and sends it to the server. For example, User A's smartphone generates the information "changed to 15:00-17:00" and emotion data and sends it to the server.

[0342] The server parses the received desired delivery time and emotion data and saves it in the database. At this time, the existing delivery information is also updated. Specifically, the server updates User A's delivery schedule in the database from "18:00-20:00" to "15:00-17:00" and saves the emotion data at the same time.

[0343] Next, the server retrieves the latest desired delivery time and emotion data from the database and uses the generative AI model to calculate the optimal delivery route. At this time, the server also takes into account the current location of the delivery person and traffic information. For example, the server recalculates the optimal delivery route using the route generation AI based on all other delivery information and User A's new time and emotion data. An example of a prompt sentence is, "Do you want to generate a new delivery route? The information taken into account includes emotion data."

[0344] Finally, the server notifies the delivery person's device of the latest delivery route information. The delivery person's device receives the notification from the server and displays the new route information. As a concrete example, the delivery person uses the "Rakuhai" app to check the latest delivery route notified by the server. This route reflects User A's new delivery time and has been given a higher priority based on emotion data.

[0345] With the above configuration, the present invention allows changes to desired delivery times to be reflected in real time, enabling the creation of efficient delivery routes that take emotional information into account. It also allows the creation of optimal routes that take into account the deliverer's current location and traffic information, reducing redelivery and delays, and improving the work efficiency of the deliverer and the convenience and satisfaction of the recipient.

[0346] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0347] Step 1:

[0348] The user launches the "Rakuhai" app.

[0349] Specific operation: The user taps the "Rakuhai" app from the smartphone's home screen to launch it.

[0350] Input: User action (app launch).

[0351] Output: Home screen displayed after launching the app.

[0352] Step 2:

[0353] The user selects the change delivery time option.

[0354] What happens: The user taps the menu icon in the app and selects the option to change delivery time.

[0355] Input: User action (option selection).

[0356] Output: Display of delivery time change screen.

[0357] Step 3:

[0358] The user inputs a new desired delivery time.

[0359] What happens: The user selects a new desired delivery time from the drop-down menu or calendar and fills out the form. For example, "15:00-17:00."

[0360] Input: User input data (new desired delivery time).

[0361] Output: The desired delivery time entered ("15:00~17:00").

[0362] Step 4:

[0363] The device activates an emotion engine and analyzes the user's emotions.

[0364] Specific operation: Uses the device's camera and microphone to analyze facial expressions and tone of voice to collect emotional data.

[0365] Input: User facial and voice data.

[0366] Output: Emotion data (e.g., "I feel stressed").

[0367] Step 5:

[0368] The user presses the "Confirm" button to confirm the time change.

[0369] Specific behavior: After the user enters a new desired delivery time in the input form, they tap the "Confirm" button.

[0370] Input: User action (tapping the confirm button).

[0371] Output: Confirmed desired delivery time data and emotion data.

[0372] Step 6:

[0373] The device generates new desired delivery time and emotion data in JSON format.

[0374] Specific operation: Convert the input desired delivery time and emotion data into JSON format.

[0375] Input: Desired delivery time data ("15:00~17:00") and emotion data.

[0376] Output: JSON format data (desired delivery time and emotion data).

[0377] Step 7:

[0378] The device sends the generated JSON format data to the server.

[0379] Specific operation: The device creates an HTTP request and sends the new desired delivery time and emotion data to the server.

[0380] Input: Desired delivery time data and emotion data in JSON format.

[0381] Output: Sending data to the server.

[0382] Step 8:

[0383] The server parses the desired delivery time and emotion data received.

[0384] Specific operation: The server parses the received JSON data and converts it into structured data.

[0385] Input: JSON data received from the terminal.

[0386] Output: Parsed desired delivery time data and sentiment data.

[0387] Step 9:

[0388] The server stores the parsed data in a database.

[0389] Specific operation: The server executes an SQL query to insert or update the desired delivery time and emotion data into the database.

[0390] Input: Parsed desired delivery time data and sentiment data.

[0391] Output: Records of data stored in a database.

[0392] Step 10:

[0393] The server retrieves the latest desired delivery time and emotion data from the database.

[0394] What happens: The server uses an SQL query to retrieve the required data from the database.

[0395] Input: None (Trigger in server).

[0396] Output: The latest desired delivery time data and sentiment data.

[0397] Step 11:

[0398] The server uses the generative AI model to calculate the optimal delivery route.

[0399] How it works: The server inputs data into the generative AI model to generate the optimal route, taking into account the delivery person's current location and traffic information.

[0400] Input: Desired delivery time data, emotion data, and delivery person's location and traffic information.

[0401] Output: Optimal delivery route data.

[0402] Step 12:

[0403] The server transmits the latest delivery route information to the deliverer's terminal via the notification means.

[0404] Specific operation: The server sends route information to the delivery user's device via push notification or API.

[0405] Input: Optimal delivery route data.

[0406] Output: Notification to the sender terminal.

[0407] Step 13:

[0408] The deliverer's terminal receives the notification from the server and displays the new route information.

[0409] What happens: The delivery person's device receives a push notification and the new delivery route is displayed on a map within the app.

[0410] Input: Notification from the server (delivery route data).

[0411] Output: The new delivery route displayed on the terminal screen.

[0412] Through these steps, the system can generate efficient delivery routes based on changes in desired delivery times and real-time reflection of emotional information, reducing redelivery and delays. This improves the work efficiency of the delivery person and increases the convenience and satisfaction of the recipient.

[0413] (Application example 2)

[0414] 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."

[0415] In food delivery, users are required to be able to change their desired pick-up time, and delivery personnel are required to efficiently select delivery routes. However, current systems are unable to generate optimal suggestions or routes that take user emotions into account, limiting their ability to improve user satisfaction and improve delivery efficiency. Furthermore, because they do not take emotional data into account, they are unable to respond appropriately to users who are feeling stressed, posing challenges in improving the quality of their service.

[0416] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a user interface means for the recipient to input and change the desired delivery time, a communication means for transmitting the desired delivery time and emotion data input via the user interface means to the server, a data management means for receiving the desired delivery time and emotion data transmitted by the communication means and storing them in a database, a route generation means for generating an optimal delivery route based on the desired delivery time and emotion data stored in the data management means, a notification means for transmitting information about the delivery route generated by the route generation means to the deliverer's terminal, and an emotion engine for recognizing the emotions of the recipient. This enables efficient delivery route generation that takes user emotions into consideration and proposal of an optimal delivery time to the user.

[0417] Definitions of technical terms

[0418] The "user interface means" is a function that provides an interface for the recipient to input and change the desired delivery time.

[0419] The "communication means" is a function for transmitting the desired delivery time and emotion data input via the user interface means to the server.

[0420] The "data management means" is a function that receives the desired delivery time and emotion data sent by the communication means and stores them in a database.

[0421] The "route generation means" is a function that generates an optimal delivery route based on the desired delivery time and emotion data stored in the data management means.

[0422] The "notification means" is a function that transmits information about the delivery route generated by the route generation means to the deliverer's terminal.

[0423] The "emotion engine" is a function that recognizes the emotions of the recipient.

[0424] MODE FOR CARRYING OUT THE INVENTION

[0425] The present invention provides a system for generating an optimal delivery route for a food delivery service by utilizing a user's desired delivery time and emotion data. Specific embodiments are described below.

[0426] System Configuration

[0427] User Interface Means

[0428] Users can input and change their desired delivery time using a smartphone application that has an intuitive interface for inputting desired delivery times.

[0429] communication means

[0430] The desired delivery time and emotion data entered via the user interface are sent to the server via the Internet, and the data is sent in JSON format.

[0431] Data Management Measures

[0432] The server receives the desired delivery time and emotion data transmitted via the communication means and stores them in a database, which records the desired delivery time and emotion information for each user.

[0433] Route Generation Method

[0434] The server generates an optimal delivery route using a generative AI model based on the desired delivery time and emotion data stored in the data management means. This model takes into account the current location of the deliverer, traffic information, and the emotion information of the recipient.

[0435] Notification means

[0436] The optimum delivery route information generated by the route generation means is sent to the deliverer's terminal, and the deliverer receives the new route information in real time and delivers efficiently.

[0437] Emotion Engine

[0438] It recognizes the emotions of the recipient and generates emotional data for delivery suggestions and optimization. The emotion engine may detect user stress and suggest a faster delivery time.

[0439] Specific examples of programs

[0440] overview:

[0441] When a user changes their desired delivery time to "today between 3:00 PM and 5:00 PM," the emotion engine recognizes the user's emotions and acquires emotional data. The new desired delivery time and emotional data are sent to the server, which stores them in a database. The server then generates an optimal delivery route and notifies the delivery person's device of the new route information.

[0442] Hardware and software used:

[0443] Smartphone application ("Rakuhai Food")

[0444] Server-side database management system

[0445] Generative AI model (route generation engine)

[0446] Emotion Engine

[0447] Prompt Sentence Examples

[0448] Generate an optimal delivery route based on the revised delivery time and user emotion data. Factors taken into consideration include all current delivery items, the user's emotional state (e.g., stress), traffic information, and the delivery person's current location. Output the generated route information in JSON format.

[0449] In this way, a system for optimizing delivery routes taking into account the user's emotions is configured, which makes it possible to improve delivery efficiency while also increasing user satisfaction.

[0450] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0451] Program processing steps and detailed explanations

[0452] Step 1:

[0453] The user uses a smartphone application to input and change a new desired delivery time. The input data (e.g., desired delivery time "15:00-17:00") is received by the user interface, and the emotion engine obtains the user's emotional data (e.g., stress level). This information is temporarily saved.

[0454] Input and Output

[0455] Input: Desired delivery time entered into the user interface, emotion data

[0456] Output: Request data including desired delivery time and emotion data

[0457] Specific actions

[0458] The user enters the delivery time on the application screen.

[0459] The emotion engine detects the user's stress level and generates emotional data.

[0460] These data are temporarily saved as request data.

[0461] Step 2:

[0462] The user's smartphone sends the request data to the server. The data is sent in JSON format. The desired delivery time and emotion data are sent to the server via the communication method.

[0463] Input and Output

[0464] Input: Request data (desired delivery time, emotion data)

[0465] Output: JSON formatted data sent to the server

[0466] Specific actions

[0467] The smartphone terminal converts the request data into JSON format.

[0468] Send data to the server using the communication module.

[0469] Step 3:

[0470] The server stores the received request data in a database management system, which records the user ID, desired delivery time, emotion data, etc.

[0471] Input and Output

[0472] Input: JSON format data received by the server

[0473] Output: Updated database

[0474] Specific actions

[0475] The server analyzes the received data and extracts the user ID, desired delivery time, and emotion data.

[0476] The data management system stores the extracted data in a database.

[0477] Step 4:

[0478] Based on the database, the server generates the optimal delivery route using a generative AI model that takes into account the delivery person's current location, traffic information, and user emotion data.

[0479] Input and Output

[0480] Input: Desired delivery time from the database, emotion data, current location of the delivery person, traffic information

[0481] Output: Optimal delivery route information

[0482] Specific actions

[0483] Get the required data from the database.

[0484] Enter prompt text into the generative AI model to generate the optimal delivery route.

[0485] Example prompt: "Generate an optimal delivery route based on the revised delivery time and user sentiment data. Factors taken into account include all current delivery items, the user's emotional state (e.g., stress), traffic information, and the delivery person's current location. Output the generated route information in JSON format."

[0486] Step 5:

[0487] The optimum delivery route information generated by the route generation means is sent to the deliverer's terminal, and the deliverer receives the new route information in real time and delivers efficiently.

[0488] Input and Output

[0489] Input: Optimal delivery route information

[0490] Output: New route information displayed on the shipper's terminal

[0491] Specific actions

[0492] The server sends the generated delivery route information to the deliverer's terminal.

[0493] The delivery person's device receives the new route information and displays it on the application.

[0494] The above are the details of the specific processing steps and operations for carrying out the invention. In this way, it is possible to generate an efficient delivery route that takes into account the user's emotions and improve the satisfaction of the user and the delivery person.

[0495] 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.

[0496] 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.

[0497] 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.

[0498] [Second embodiment]

[0499] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0500] 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.

[0501] 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).

[0502] 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.

[0503] 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.

[0504] 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).

[0505] 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.

[0506] 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.

[0507] 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.

[0508] 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.

[0509] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0510] 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."

[0511] The present invention relates to a system that provides a user interface for the recipient to input and change a desired delivery time and includes a communication means for transmitting the input desired delivery time to a server. The system has a data management means for storing the desired delivery time received by the server in a database, and a route generation means for generating an optimal delivery route based on the stored information. It also has a notification means for transmitting information about the generated delivery route to the sender's terminal. This configuration allows changes made by the recipient to be reflected in real time, providing an efficient delivery route, thereby reducing redelivery and delivery delays.

[0512] (Example of specific program processing)

[0513] 1. The user changes the desired delivery time

[0514] Processing Description

[0515] Users can change the pickup time through the "Rakuhai" app. For example, a user can select "I want to change the delivery time to between 3:00 PM and 5:00 PM today."

[0516] Examples:

[0517] If User A wishes to change the current delivery time from "18:00-20:00" to "15:00-17:00", he or she uses the user interface means to select a new delivery time from the settings screen of the app and presses the "Confirm" button.

[0518] 2. The device sends the desired delivery time

[0519] Processing Description

[0520] After the user presses the confirm button, the terminal transmits the new desired delivery time to the server.

[0521] Examples:

[0522] User A's smartphone generates the information "Change to 15:00-17:00" in JSON format and sends it to the "Rakuhai" system server.

[0523] 3. The server updates the recipient's desired delivery time.

[0524] Processing Description

[0525] The server saves the received desired delivery time in the database, and updates the existing delivery information at the same time.

[0526] Examples:

[0527] The server updates User A's delivery schedule in the database from "18:00-20:00" to "15:00-17:00."

[0528] 4. The server generates an efficient delivery route

[0529] Processing Description

[0530] The server generates a new, optimized delivery route based on the latest desired delivery time using a generative AI model that also takes into account the deliverer's current location and traffic information.

[0531] Examples:

[0532] The server recalculates the optimal delivery route using the route generation AI, taking into account all other delivery information and User A's new time.

[0533] 5. The device retrieves the latest delivery route.

[0534] Processing Description

[0535] The deliverer's terminal receives the notification from the server and acquires the new route information, allowing the deliverer to deliver efficiently based on the latest delivery route.

[0536] Examples:

[0537] Delivery person B uses the "Rakuhai" app to check the latest delivery route notified by the server. This route reflects User A's new delivery time.

[0538] With the above configuration, the present invention provides a system that reflects changes in recipient preferences in real time and supports efficient delivery routing. This system reduces redelivery and delivery delays and improves the work efficiency of deliverers.

[0539] The processing flow will be explained below.

[0540] Specific explanation of program processing

[0541] (Step 1: User changes desired delivery time)

[0542] 1. The user launches the "Rakuhai" app.

[0543] 2. The user accesses their My Page or Order Details page and displays delivery details.

[0544] 3. The user selects the desired delivery time section and selects a new preferred time slot.

[0545] 4. The user confirms the changes and presses the "Confirm" button.

[0546] (Step 2: The device sends the desired delivery time)

[0547] 1. Obtain the data of the desired delivery time changed through the user interface means.

[0548] 2. The desired delivery time obtained by the device is converted into JSON format.

[0549] 3. The device sends a request to change the desired delivery time to the backend API endpoint.

[0550] 4. The device waits for a response from the server.

[0551] (Step 3: The server updates the recipient's desired delivery time)

[0552] 1. The server analyzes the request to change the desired delivery time received from the terminal.

[0553] 2. The server extracts the delivery ID and new desired delivery time from the request data.

[0554] 3. The server generates a database query based on the delivery ID to update the desired delivery time for the corresponding record to the new value.

[0555] 4. The server executes the generated database query.

[0556] 5. The server verifies that the database update completed successfully.

[0557] 6. The server sends a response to the terminal indicating that the desired delivery time has been successfully updated.

[0558] (Step 4: The server generates an efficient delivery route)

[0559] 1. The server re-fetches all delivery schedule information from the database.

[0560] 2. The server prepares to input all the delivery schedule information it has obtained into the generative AI model.

[0561] 3. The server also obtains the current location data of the deliverer and real-time traffic information.

[0562] 4. The server inputs all necessary data into the generated AI model and has it calculate the optimal delivery route.

[0563] 5. The server saves the generated optimal delivery route in the delivery route table in the database.

[0564] 6. The server sends a notification containing the new delivery route information to the deliverer's terminal.

[0565] (Step 5: The device retrieves the latest delivery route)

[0566] 1. The device receives a push notification from the server.

[0567] 2. The device analyzes the contents of the push notification and prepares a request to obtain a new delivery route.

[0568] 3. The device sends a request to the server's API endpoint to obtain the latest delivery route information.

[0569] 4. The terminal receives the response from the server and obtains the new delivery route data.

[0570] 5. The new delivery route data acquired by the device is displayed in the app's UI.

[0571] 6. The terminal notifies the user of the latest delivery route information and allows them to confirm it.

[0572] These are the program processing steps of the "Rakuhai" app. Through this specific processing, it is possible to reflect the recipient's desired delivery time in real time and generate and manage efficient delivery routes.

[0573] Example 1

[0574] 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."

[0575] In modern logistics systems, desired delivery times often change on the recipient's side, and there is a need to reflect these changes in real time and optimize delivery routes. Conventional systems have difficulty responding to sudden changes in desired delivery times or traffic information, which can lead to redelivery and delivery delays. Therefore, there is a need for a system that can quickly and efficiently reflect changes in desired delivery times on the recipient's side and generate optimal delivery routes.

[0576] 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.

[0577] In this invention, the server includes input means for the recipient to input or change the desired delivery time, transmission means for transmitting the desired delivery time input via the input means to the server, storage means for receiving the desired delivery time transmitted by the transmission means and storing it in a database, route generation means for generating an optimal delivery route based on the desired delivery time stored in the storage means, notification means for transmitting information on the delivery route generated by the route generation means to the deliverer's terminal, and supply and demand optimization means for optimizing the delivery route based on the deliverer's current situation and traffic information using a generative AI model. This allows changes in the recipient's request to be reflected in real time, reducing redelivery and delivery delays and enabling the generation of efficient delivery routes.

[0578] The "input means" is an interface device that allows the recipient to input or change the desired delivery time.

[0579] The "transmission means" is a device for transmitting the desired delivery time input via the input means to the server via the network.

[0580] The "storage means" is a device that receives the desired delivery time sent by the transmission means and stores it in a database.

[0581] The "route generation means" is a device for generating an optimal delivery route based on the desired delivery time stored in the storage means.

[0582] The "notification means" is a device for transmitting information about the delivery route generated by the route generation means to the terminal of the deliverer.

[0583] The "supply and demand optimization means" is a device that uses a generative AI model to calculate and generate the optimal delivery route based on the delivery person's current location and traffic information.

[0584] A "generative AI model" is an artificial intelligence model that uses machine learning algorithms to derive optimal delivery routes from input data.

[0585] A "prompt statement" is an instruction statement that causes a generative AI model to perform specific data processing or calculations.

[0586] The present invention is configured to provide an efficient delivery system, which allows recipients to input and change their desired delivery time, and this information is reflected in delivery management in real time.

[0587] First, the user operates the delivery app using a device such as a smartphone or PC. This delivery app has an input means and provides an interface that allows the user to select or change the desired delivery time. For example, the user can select "15:00-17:00" and press the "Confirm" button to enter the new desired delivery time.

[0588] Next, the terminal uses the transmission means to transmit this new desired delivery time to the server. The transmitted data can be in a general data format such as JSON format.

[0589] The server receives the desired delivery time data sent from the sending means and saves the information in the database using the saving means. Specifically, the server analyzes the received JSON data and stores the information in the database as an SQL query. At this time, the existing delivery information is also updated.

[0590] Based on the desired delivery time stored in the storage means, the server uses the route generation means to generate the optimal delivery route. A generative AI model is used here, which generates a route that takes into account the user's new desired delivery time, the delivery person's current location, traffic information, etc. The following prompt sentences are used in this process:

[0591] Prompt Sentence Examples

[0592] "Please generate the optimal delivery route taking into account the next delivery information, the current location of the delivery person, and traffic information. The new desired delivery time is 3:00 PM to 5:00 PM."

[0593] The generated optimal delivery route is sent to the deliverer's terminal using a notification means. This notification allows the deliverer to check the latest delivery route on their own terminal and deliver efficiently accordingly.

[0594] For example, if a delivery person has a dedicated delivery device, they will receive a real-time notification on that device saying, "A new delivery route has been set." This notification prompts the delivery person to open the "delivery app," check the new route information, and begin delivery.

[0595] A key feature of this invention is that if a user changes their desired delivery time, the change is reflected in real time. This reduces redelivery and delivery delays, resulting in more efficient delivery. Furthermore, by using a generative AI model, the system takes into account the current location of the deliverer and real-time traffic information, allowing for the generation of optimal delivery routes.

[0596] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0597] Divide the processing flow of this system's program into processing steps

[0598] Step 1: User enters or changes desired delivery time

[0599] Step 2: The device sends the desired delivery time to the server

[0600] Step 3: Store the requested delivery time received by the server in a database

[0601] Step 4: The server generates an efficient delivery route

[0602] Step 5: The delivery person's device receives the latest delivery route

[0603] Detailed description of each processing step

[0604] Step 1: User enters or changes desired delivery time

[0605] Input: A user launches a delivery app and selects a delivery time.

[0606] Output: A delivery time change request is generated.

[0607] Specific actions

[0608] The user opens the delivery app, selects the desired time slot from the displayed time slots, and presses the "Confirm" button. For example, if the user wants to change the time slot to "15:00-17:00," select that time slot and press the "Confirm" button.

[0609] Step 2: The device sends the desired delivery time to the server

[0610] Input: User selected delivery time information.

[0611] Output: Sends a request to change the desired delivery time to the server.

[0612] Specific actions

[0613] The user's device converts the selected desired delivery time into JSON format and sends it to the server as an HTTP POST request. For example, the user's device generates JSON data including the time information "15:00~17:00" and sends it to the server.

[0614] Step 3: Store the requested delivery time received by the server in a database

[0615] Input: JSON data of the desired delivery time sent to the server.

[0616] Output: The requested delivery time information updated in the database.

[0617] Specific actions

[0618] The server parses the received JSON data and saves the user's delivery information in the database. For example, if the server receives data for "15:00~17:00", it parses it, generates an SQL query, and updates the delivery information in the database.

[0619] Step 4: The server generates an efficient delivery route

[0620] Input: Latest desired delivery time information stored in the database, current location information of the delivery person, and traffic information.

[0621] Output: The generated optimal delivery route.

[0622] Specific actions

[0623] The server uses the generative AI model to generate the optimal delivery route based on the latest desired delivery time, the delivery person's current location, and traffic information. At this point, the server sends the following prompt to the generative AI model:

[0624] Example prompt: "Generate the optimal delivery route taking into account the following delivery information, the delivery person's current location, and traffic information. The new desired delivery time is between 3:00 PM and 5:00 PM."

[0625] The server receives the optimal delivery route generated by the generative AI model and stores that information.

[0626] Step 5: The delivery person's device receives the latest delivery route

[0627] Input: Optimal delivery route information sent from the server.

[0628] Output: The updated delivery route displayed on the delivery person's terminal.

[0629] Specific actions

[0630] The server notifies the delivery person's device of the new delivery route information, and the device receives this information. For example, the delivery person's device receives a notification that "a new delivery route has been set," and can check the latest delivery route within the app.

[0631] Through the above steps, even if the user changes the desired delivery time, the change is reflected in real time, an optimal delivery route is generated, and delivery is carried out efficiently.

[0632] (Application example 1)

[0633] 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."

[0634] In food delivery, when a user changes their desired delivery time, the delivery person's route becomes inefficient, resulting in redelivery and delays. When this happens, user satisfaction decreases and delivery efficiency drops significantly. To solve this, a system is needed that can reflect changes in the desired delivery time in real time and generate the optimal delivery route.

[0635] 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.

[0636] In this invention, the server includes a display device for the recipient to input and change the desired delivery time, a data transmission device for transmitting the desired delivery time input via the display device to the server, a data storage device for receiving the desired delivery time transmitted by the data transmission device and storing it in a database, a route generation device for generating an optimal delivery route based on the desired delivery time stored in the data storage device, a notification device for transmitting the delivery route generated by the route generation device to the carrier's terminal, and a processing device using artificial intelligence to optimize the delivery route generated by the route generation device. This allows the optimal delivery route to be generated in real time even when the user changes the delivery time, thereby improving delivery efficiency and reducing delays.

[0637] The "display device" is a device that provides an interactive operation screen for the recipient to input and change the desired delivery time.

[0638] The "data transmission means" is a means having a communication function for transmitting the desired delivery time input via the display means to the server.

[0639] The "data storage means" is a means for receiving the desired delivery time transmitted by the data transmission means and storing it in a database.

[0640] The "route generation means" is a means for generating an optimal delivery route based on the desired delivery time stored in the data storage means.

[0641] The "notification means" is a means for transmitting information about the delivery route generated by the route generation means to the carrier's terminal.

[0642] The "processing means" is a means that uses artificial intelligence to optimize the delivery route generated by the route generation means.

[0643] The "server" is a central processing unit that receives the desired delivery time, stores the data, generates routes, and sends notifications.

[0644] "Transporter's terminal" refers to an information processing device carried by the transporter to receive and display delivery route information notified from the server.

[0645] "Real-time" means that the moment a user changes their desired delivery time, the change is immediately reflected throughout the entire delivery system.

[0646] "Generative artificial intelligence" refers to machine learning algorithms and AI models that generate and optimize optimal delivery routes based on large amounts of data.

[0647] The present invention provides a system that allows recipients to change their desired delivery time in real time in order to significantly improve the efficiency of food delivery. Specific embodiments of this system are described below.

[0648] System Overview

[0649] This system consists of the following main elements:

[0650] 1. Display device means

[0651] 2. Data transmission method

[0652] 3. Data storage method

[0653] 4. Route Generation Method

[0654] 5. Means of notification

[0655] 6. Processing Means

[0656] Hardware and Software Use

[0657] Hardware: Smartphones, servers, carrier terminals

[0658] Software: Food delivery app (compatible with iOS / Android), database system (MySQL, PostgreSQL, etc.), route generation AI model (TensorFlow, PyTorch, etc.)

[0659] display means

[0660] The recipient can input and change the desired delivery time through the smartphone app. The display device means provides an interactive operation screen and is designed to allow the user to easily select the desired delivery time.

[0661] Examples:

[0662] If a user opens a food delivery app and wants to change their current desired delivery time from "18:00-20:00" to "15:00-17:00," they select a new time on the app screen and press the "Confirm" button.

[0663] Data transmission method

[0664] After a user changes their desired delivery time, their smartphone generates the new desired time as JSON data and sends it to the server via an HTTPS request, ensuring that the information reaches the server securely and quickly.

[0665] Data storage means

[0666] The server stores the received desired delivery time in a database. The stored data reflects the updated desired delivery time, and existing delivery information is updated appropriately.

[0667] Route Generation Method

[0668] Based on the latest desired delivery times stored in the database, the server generates the optimal delivery route using a generative AI model, taking into account the carrier's current location and traffic information.

[0669] Examples:

[0670] The server takes into account all delivery information and the user's new desired time and uses route generation AI to recalculate the optimal delivery route.

[0671] Notification means

[0672] The generated new delivery route is notified to the carrier's terminal, allowing the carrier to act efficiently based on the latest delivery route.

[0673] Examples:

[0674] The carrier uses the app to check the updated delivery route provided by the server, which now reflects the user's new delivery time.

[0675] Processing means

[0676] Processing methods using generative artificial intelligence generate and optimize optimal delivery routes based on large amounts of data, thereby improving delivery efficiency and minimizing delays.

[0677] Prompt Sentence Examples

[0678] If the desired delivery time changes, generate the optimal delivery route based on the new desired time. Take the following data into consideration:

[0679] Current location of the deliverer

[0680] Traffic information

[0681] Other delivery schedules

[0682] In this way, the system reflects changes in desired delivery times in real time and provides the optimal delivery route, thereby improving the efficiency of food delivery.

[0683] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0684] Step 1:

[0685] The user uses the display device to input and change the desired delivery time.

[0686] Input: Current desired delivery time and new desired delivery time

[0687] Output: Confirmation of new desired time

[0688] Specific action: The user selects a new desired delivery time on the settings screen of a food delivery app and presses the "Confirm" button.

[0689] Step 2:

[0690] The terminal generates a new desired delivery time as data in JSON format and transmits it to the server via the data transmission means.

[0691] Input: New desired delivery time selected and confirmed by the user

[0692] Output: HTTPS request to the server

[0693] What happens: The smartphone generates JSON data containing the new desired delivery time and sends it to the server via an HTTPS request.

[0694] Step 3:

[0695] The server receives the data and stores the new desired delivery time in a database using the data storage means.

[0696] Input: JSON data of the new desired delivery time sent from the device

[0697] Output: Desired delivery time updated in the database

[0698] What happens: The server analyzes the received data and updates the existing delivery information with the new desired delivery time.

[0699] Step 4:

[0700] The server uses the route generation means to generate an optimal delivery route based on the new desired delivery time.

[0701] Input: Updated desired delivery time, current delivery information, carrier's current location, traffic information

[0702] Output: Optimized delivery route

[0703] How it works: Using generative artificial intelligence, it recalculates the optimal delivery route based on all input data.

[0704] Step 5:

[0705] The server transmits the newly generated delivery route information to the carrier's terminal via the notification means.

[0706] Input: Optimized delivery route information

[0707] Output: Notification to carrier terminal and route information update

[0708] Specific operation: The server generates new delivery route data and sends it to the carrier's device via push notification.

[0709] Step 6:

[0710] The carrier's terminal displays the new delivery route information received from the server and delivers the goods according to it.

[0711] Input: New delivery route information sent from the server

[0712] Output: Efficient delivery by carriers

[0713] Specific operation: The carrier's terminal displays the latest delivery route information, and the carrier makes the delivery based on that information.

[0714] This process allows the system to generate the optimal delivery route in real time, even if the user changes the desired delivery time, preventing delays and redelivery.

[0715] 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.

[0716] The present invention relates to a system that provides a user interface for a recipient to input and change a desired delivery time and includes a communication means for transmitting the input desired delivery time to a server. The system has a data management means for storing the desired delivery time received by the server in a database, and a route generation means for generating an optimal delivery route based on the stored information. The system also has a notification means for transmitting information about the generated delivery route to the deliverer's terminal. The system also includes an emotion engine for recognizing the recipient's emotions, and is able to propose a desired delivery time and optimize the delivery route by taking into account the emotion information obtained from the emotion engine.

[0717] (Example of specific program processing)

[0718] 1. The user changes the desired delivery time

[0719] Processing Description

[0720] Users can change or input the pickup time through the "Rakuhai" app. For example, a user can select "I want to change the delivery time to between 3:00 PM and 5:00 PM today." At this time, the emotion engine recognizes the user's emotion and acquires emotion data.

[0721] Examples:

[0722] If User A wishes to change the current delivery time from "18:00-20:00" to "15:00-17:00," he or she selects a new delivery time from the app's settings screen using the user interface means and presses the "Confirm" button. At this time, the emotion engine detects that User A is feeling stressed and suggests an earlier time slot.

[0723] 2. The device sends the desired delivery time

[0724] Processing Description

[0725] When the user confirms the desired delivery time, the terminal transmits the new desired delivery time and emotion data to the server.

[0726] Examples:

[0727] User A's smartphone generates the information "change to 15:00-17:00" and emotion data in JSON format and sends it to the server.

[0728] 3. The server updates the recipient's desired delivery time.

[0729] Processing Description

[0730] The server stores the received desired delivery time and emotion data in a database, and updates the existing delivery information.

[0731] Examples:

[0732] The server updates User A's delivery schedule in the database from "18:00-20:00" to "15:00-17:00" and also saves the emotion data.

[0733] 4. The server generates an efficient delivery route

[0734] Processing Description

[0735] The server generates a new, optimized delivery route based on the latest desired delivery time and emotion data, using a generative AI model that also takes into account the deliverer's current location and traffic information.

[0736] Examples:

[0737] The server recalculates the optimal delivery route using the route generation AI, taking into account all other delivery information and User A's new time and emotion data.

[0738] 5. The device retrieves the latest delivery route.

[0739] Processing Description

[0740] The deliverer's terminal receives the notification from the server and acquires the new route information, allowing the deliverer to deliver efficiently based on the latest delivery route.

[0741] Examples:

[0742] Delivery person B uses the "Rakuhai" app to check the latest delivery route notified by the server. This route reflects User A's new delivery time and has been prioritized based on the emotion data.

[0743] With the above configuration, the present invention provides a system that supports more efficient delivery routing with higher user satisfaction by reflecting changes in recipient preferences and emotional information in real time. This system reduces redelivery and delivery delays, improves the work efficiency of deliverers, and increases convenience and satisfaction for recipients.

[0744] The processing flow will be explained below.

[0745] (Example of specific program processing)

[0746] 1. The user changes the desired delivery time

[0747] Step 1:

[0748] The user launches the "Rakuhai" app.

[0749] Step 2:

[0750] The user accesses their My Page or Order Details page and displays delivery details.

[0751] Step 3:

[0752] The user selects the desired delivery time section and selects a new desired time slot. At this time, the emotion engine recognizes the user's emotions from facial expressions, voice, etc. and captures them as data.

[0753] Step 4:

[0754] The user confirms the changes and presses the "Confirm" button.

[0755] 2. The device sends the desired delivery time and emotion data

[0756] Step 1:

[0757] The terminal collects the desired delivery time data and emotion data acquired through the user interface means.

[0758] Step 2:

[0759] The device converts this data into JSON format.

[0760] Step 3:

[0761] The device sends a request to the backend API endpoint to change the desired delivery time and emotion data.

[0762] Step 4:

[0763] The terminal waits for a response from the server.

[0764] 3. The server updates the recipient's desired delivery time and emotion data.

[0765] Step 1:

[0766] The server analyzes the request for change of desired delivery time and emotion data received from the terminal.

[0767] Step 2:

[0768] The server extracts the delivery ID, new desired delivery time, and emotion data from the request data.

[0769] Step 3:

[0770] Based on the delivery ID, the server generates a database query to update the desired delivery time and emotion data of the corresponding record to new values.

[0771] Step 4:

[0772] The server executes the generated database query.

[0773] Step 5:

[0774] The server verifies that the database update completed successfully.

[0775] Step 6:

[0776] The server sends a response to the terminal indicating that the desired delivery time and emotion data have been successfully updated.

[0777] 4. The server generates an efficient delivery route

[0778] Step 1:

[0779] The server retrieves all delivery schedule information and emotion data from the database.

[0780] Step 2:

[0781] The server prepares to input all the delivery schedule information it has obtained into the generative AI model.

[0782] Step 3:

[0783] The server also obtains the current location data of the deliverer and real-time traffic information.

[0784] Step 4:

[0785] The server inputs all necessary data into the generated AI model, which calculates the optimal delivery route, adjusting the urgency and priority based on emotional data.

[0786] Step 5:

[0787] The server stores the generated optimal delivery route in a delivery route table in the database.

[0788] Step 6:

[0789] The server sends a notification containing new delivery route information to the deliverer's terminal.

[0790] 5. The device retrieves the latest delivery route.

[0791] Step 1:

[0792] The device receives a push notification from the server.

[0793] Step 2:

[0794] The device analyzes the contents of the push notification and prepares a request to obtain a new delivery route.

[0795] Step 3:

[0796] The terminal sends a request to the server's API endpoint to obtain the latest delivery route information.

[0797] Step 4:

[0798] The terminal receives the response from the server and acquires new delivery route data.

[0799] Step 5:

[0800] The new delivery route data acquired by the device is displayed in the app's UI.

[0801] Step 6:

[0802] The terminal notifies the user of the latest delivery route information and allows the user to confirm it.

[0803] Example 2

[0804] 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."

[0805] In conventional delivery systems, changes to desired delivery times are not reflected in real time, and delivery routes are determined without taking into account the feelings of the recipient, resulting in frequent redelivery and reduced delivery efficiency and user satisfaction. Furthermore, efficient delivery is difficult because routes are generated without sufficient consideration of the deliverer's current location or traffic information.

[0806] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a user interface means for the recipient to input and change the desired delivery time, a communication means for transmitting the desired delivery time input via the user interface means to the server, a data management means for receiving the desired delivery time and emotion data transmitted by the communication means and storing them in a database, a route generation means for generating an optimal delivery route based on the desired delivery time and emotion data stored in the data management means, and a notification means for transmitting information about the delivery route generated by the route generation means to the deliverer's terminal. This allows changes to the desired delivery time to be reflected in real time, enabling the generation of an efficient delivery route that takes emotion information into account. It also enables the generation of an optimal route that takes the deliverer's current location and traffic information into account.

[0807] "User interface means" refers to an interface that allows the recipient to input and change the desired delivery time.

[0808] The "communication means" refers to a means for transmitting the desired delivery time input via the user interface means to the server.

[0809] "Data management means" refers to a means for receiving the desired delivery time and emotion data sent by the communication means and storing them in a database.

[0810] The "route generation means" refers to a means for generating an optimal delivery route based on the desired delivery time and emotion data stored in the data management means.

[0811] The "notification means" refers to a means for transmitting information about the delivery route generated by the route generation means to the terminal of the deliverer.

[0812] A "generative AI model" refers to an artificial intelligence model that generates optimal delivery routes using data such as desired delivery time, emotional data, the delivery person's current location, and traffic information.

[0813] "Emotional data" refers to data obtained by analyzing the user's emotions, and refers to information that can affect changes to the desired delivery time or route generation.

[0814] This invention describes a system that provides a user interface means for the recipient to input and change the desired delivery time, a communication means for transmitting the input desired delivery time to a server, and a system that uses this data to generate the optimal delivery route.

[0815] In this system, the user first launches the "Rakuhai" app on a device such as a smartphone or tablet. The user then selects the option to change the delivery time within the app and enters the new desired delivery time. At this time, the emotion engine analyzes the user's emotions and acquires emotional data. As a specific example, if a user wants to change the current delivery time from "18:00-20:00" to "15:00-17:00," they select a new delivery time from the app's settings screen and press the "Confirm" button. At this time, the emotion engine detects that the user is feeling stressed and suggests an earlier time slot.

[0816] When the user confirms the desired delivery time, the device generates the new desired delivery time and emotion data in JSON format and sends it to the server. For example, User A's smartphone generates the information "changed to 15:00-17:00" and emotion data and sends it to the server.

[0817] The server parses the received desired delivery time and emotion data and saves it in the database. At this time, the existing delivery information is also updated. Specifically, the server updates User A's delivery schedule in the database from "18:00-20:00" to "15:00-17:00" and saves the emotion data at the same time.

[0818] Next, the server retrieves the latest desired delivery time and emotion data from the database and uses the generative AI model to calculate the optimal delivery route. At this time, the server also takes into account the current location of the delivery person and traffic information. For example, the server recalculates the optimal delivery route using the route generation AI based on all other delivery information and User A's new time and emotion data. An example of a prompt sentence is, "Do you want to generate a new delivery route? The information taken into account includes emotion data."

[0819] Finally, the server notifies the delivery person's device of the latest delivery route information. The delivery person's device receives the notification from the server and displays the new route information. As a concrete example, the delivery person uses the "Rakuhai" app to check the latest delivery route notified by the server. This route reflects User A's new delivery time and has been given a higher priority based on emotion data.

[0820] With the above configuration, the present invention allows changes to desired delivery times to be reflected in real time, enabling the creation of efficient delivery routes that take emotional information into account. It also allows the creation of optimal routes that take into account the deliverer's current location and traffic information, reducing redelivery and delays, and improving the work efficiency of the deliverer and the convenience and satisfaction of the recipient.

[0821] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0822] Step 1:

[0823] The user launches the "Rakuhai" app.

[0824] Specific operation: The user taps the "Rakuhai" app from the smartphone's home screen to launch it.

[0825] Input: User action (app launch).

[0826] Output: Home screen displayed after launching the app.

[0827] Step 2:

[0828] The user selects the change delivery time option.

[0829] What happens: The user taps the menu icon in the app and selects the option to change delivery time.

[0830] Input: User action (option selection).

[0831] Output: Display of delivery time change screen.

[0832] Step 3:

[0833] The user inputs a new desired delivery time.

[0834] What happens: The user selects a new desired delivery time from the drop-down menu or calendar and fills out the form. For example, "15:00-17:00."

[0835] Input: User input data (new desired delivery time).

[0836] Output: The desired delivery time entered ("15:00~17:00").

[0837] Step 4:

[0838] The device activates an emotion engine and analyzes the user's emotions.

[0839] Specific operation: Uses the device's camera and microphone to analyze facial expressions and tone of voice to collect emotional data.

[0840] Input: User facial and voice data.

[0841] Output: Emotion data (e.g., "I feel stressed").

[0842] Step 5:

[0843] The user presses the "Confirm" button to confirm the time change.

[0844] Specific behavior: After the user enters a new desired delivery time in the input form, they tap the "Confirm" button.

[0845] Input: User action (tapping the confirm button).

[0846] Output: Confirmed desired delivery time data and emotion data.

[0847] Step 6:

[0848] The device generates new desired delivery time and emotion data in JSON format.

[0849] Specific operation: Convert the input desired delivery time and emotion data into JSON format.

[0850] Input: Desired delivery time data ("15:00~17:00") and emotion data.

[0851] Output: JSON format data (desired delivery time and emotion data).

[0852] Step 7:

[0853] The device sends the generated JSON format data to the server.

[0854] Specific operation: The device creates an HTTP request and sends the new desired delivery time and emotion data to the server.

[0855] Input: Desired delivery time data and emotion data in JSON format.

[0856] Output: Sending data to the server.

[0857] Step 8:

[0858] The server parses the desired delivery time and emotion data received.

[0859] Specific operation: The server parses the received JSON data and converts it into structured data.

[0860] Input: JSON data received from the terminal.

[0861] Output: Parsed desired delivery time data and sentiment data.

[0862] Step 9:

[0863] The server stores the parsed data in a database.

[0864] Specific operation: The server executes an SQL query to insert or update the desired delivery time and emotion data into the database.

[0865] Input: Parsed desired delivery time data and sentiment data.

[0866] Output: Records of data stored in a database.

[0867] Step 10:

[0868] The server retrieves the latest desired delivery time and emotion data from the database.

[0869] What happens: The server uses an SQL query to retrieve the required data from the database.

[0870] Input: None (Trigger in server).

[0871] Output: The latest desired delivery time data and sentiment data.

[0872] Step 11:

[0873] The server uses the generative AI model to calculate the optimal delivery route.

[0874] How it works: The server inputs data into the generative AI model to generate the optimal route, taking into account the delivery person's current location and traffic information.

[0875] Input: Desired delivery time data, emotion data, and delivery person's location and traffic information.

[0876] Output: Optimal delivery route data.

[0877] Step 12:

[0878] The server transmits the latest delivery route information to the deliverer's terminal via the notification means.

[0879] Specific operation: The server sends route information to the delivery user's device via push notification or API.

[0880] Input: Optimal delivery route data.

[0881] Output: Notification to the sender terminal.

[0882] Step 13:

[0883] The deliverer's terminal receives the notification from the server and displays the new route information.

[0884] What happens: The delivery person's device receives a push notification and the new delivery route is displayed on a map within the app.

[0885] Input: Notification from the server (delivery route data).

[0886] Output: The new delivery route displayed on the terminal screen.

[0887] Through these steps, the system can generate efficient delivery routes based on changes in desired delivery times and real-time reflection of emotional information, reducing redelivery and delays. This improves the work efficiency of the delivery person and increases the convenience and satisfaction of the recipient.

[0888] (Application example 2)

[0889] 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."

[0890] In food delivery, users are required to be able to change their desired pick-up time, and delivery personnel are required to efficiently select delivery routes. However, current systems are unable to generate optimal suggestions or routes that take user emotions into account, limiting their ability to improve user satisfaction and improve delivery efficiency. Furthermore, because they do not take emotional data into account, they are unable to respond appropriately to users who are feeling stressed, posing challenges in improving the quality of their service.

[0891] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a user interface means for the recipient to input and change the desired delivery time, a communication means for transmitting the desired delivery time and emotion data input via the user interface means to the server, a data management means for receiving the desired delivery time and emotion data transmitted by the communication means and storing them in a database, a route generation means for generating an optimal delivery route based on the desired delivery time and emotion data stored in the data management means, a notification means for transmitting information about the delivery route generated by the route generation means to the deliverer's terminal, and an emotion engine for recognizing the emotions of the recipient. This enables efficient delivery route generation that takes user emotions into consideration and proposal of an optimal delivery time to the user.

[0892] Definitions of technical terms

[0893] The "user interface means" is a function that provides an interface for the recipient to input and change the desired delivery time.

[0894] The "communication means" is a function for transmitting the desired delivery time and emotion data input via the user interface means to the server.

[0895] The "data management means" is a function that receives the desired delivery time and emotion data sent by the communication means and stores them in a database.

[0896] The "route generation means" is a function that generates an optimal delivery route based on the desired delivery time and emotion data stored in the data management means.

[0897] The "notification means" is a function that transmits information about the delivery route generated by the route generation means to the deliverer's terminal.

[0898] The "emotion engine" is a function that recognizes the emotions of the recipient.

[0899] MODE FOR CARRYING OUT THE INVENTION

[0900] The present invention provides a system for generating an optimal delivery route for a food delivery service by utilizing a user's desired delivery time and emotion data. Specific embodiments are described below.

[0901] System Configuration

[0902] User Interface Means

[0903] Users can input and change their desired delivery time using a smartphone application that has an intuitive interface for inputting desired delivery times.

[0904] communication means

[0905] The desired delivery time and emotion data entered via the user interface are sent to the server via the Internet, and the data is sent in JSON format.

[0906] Data Management Measures

[0907] The server receives the desired delivery time and emotion data transmitted via the communication means and stores them in a database, which records the desired delivery time and emotion information for each user.

[0908] Route Generation Method

[0909] The server generates an optimal delivery route using a generative AI model based on the desired delivery time and emotion data stored in the data management means. This model takes into account the current location of the deliverer, traffic information, and the emotion information of the recipient.

[0910] Notification means

[0911] The optimum delivery route information generated by the route generation means is sent to the deliverer's terminal, and the deliverer receives the new route information in real time and delivers efficiently.

[0912] Emotion Engine

[0913] It recognizes the emotions of the recipient and generates emotional data for delivery suggestions and optimization. The emotion engine may detect user stress and suggest a faster delivery time.

[0914] Specific examples of programs

[0915] overview:

[0916] When a user changes their desired delivery time to "today between 3:00 PM and 5:00 PM," the emotion engine recognizes the user's emotions and acquires emotional data. The new desired delivery time and emotional data are sent to the server, which stores them in a database. The server then generates an optimal delivery route and notifies the delivery person's device of the new route information.

[0917] Hardware and software used:

[0918] Smartphone application ("Rakuhai Food")

[0919] Server-side database management system

[0920] Generative AI model (route generation engine)

[0921] Emotion Engine

[0922] Prompt Sentence Examples

[0923] Generate an optimal delivery route based on the revised delivery time and user emotion data. Factors taken into consideration include all current delivery items, the user's emotional state (e.g., stress), traffic information, and the delivery person's current location. Output the generated route information in JSON format.

[0924] In this way, a system for optimizing delivery routes taking into account the user's emotions is configured, which makes it possible to improve delivery efficiency while also increasing user satisfaction.

[0925] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0926] Program processing steps and detailed explanations

[0927] Step 1:

[0928] The user uses a smartphone application to input and change a new desired delivery time. The input data (e.g., desired delivery time "15:00-17:00") is received by the user interface, and the emotion engine obtains the user's emotional data (e.g., stress level). This information is temporarily saved.

[0929] Input and Output

[0930] Input: Desired delivery time entered into the user interface, emotion data

[0931] Output: Request data including desired delivery time and emotion data

[0932] Specific actions

[0933] The user enters the delivery time on the application screen.

[0934] The emotion engine detects the user's stress level and generates emotional data.

[0935] These data are temporarily saved as request data.

[0936] Step 2:

[0937] The user's smartphone sends the request data to the server. The data is sent in JSON format. The desired delivery time and emotion data are sent to the server via the communication method.

[0938] Input and Output

[0939] Input: Request data (desired delivery time, emotion data)

[0940] Output: JSON formatted data sent to the server

[0941] Specific actions

[0942] The smartphone terminal converts the request data into JSON format.

[0943] Send data to the server using the communication module.

[0944] Step 3:

[0945] The server stores the received request data in a database management system, which records the user ID, desired delivery time, emotion data, etc.

[0946] Input and Output

[0947] Input: JSON format data received by the server

[0948] Output: Updated database

[0949] Specific actions

[0950] The server analyzes the received data and extracts the user ID, desired delivery time, and emotion data.

[0951] The data management system stores the extracted data in a database.

[0952] Step 4:

[0953] Based on the database, the server generates the optimal delivery route using a generative AI model that takes into account the delivery person's current location, traffic information, and user emotion data.

[0954] Input and Output

[0955] Input: Desired delivery time from the database, emotion data, current location of the delivery person, traffic information

[0956] Output: Optimal delivery route information

[0957] Specific actions

[0958] Get the required data from the database.

[0959] Enter prompt text into the generative AI model to generate the optimal delivery route.

[0960] Example prompt: "Generate an optimal delivery route based on the revised delivery time and user sentiment data. Factors taken into account include all current delivery items, the user's emotional state (e.g., stress), traffic information, and the delivery person's current location. Output the generated route information in JSON format."

[0961] Step 5:

[0962] The optimum delivery route information generated by the route generation means is sent to the deliverer's terminal, and the deliverer receives the new route information in real time and delivers efficiently.

[0963] Input and Output

[0964] Input: Optimal delivery route information

[0965] Output: New route information displayed on the shipper's terminal

[0966] Specific actions

[0967] The server sends the generated delivery route information to the deliverer's terminal.

[0968] The delivery person's device receives the new route information and displays it on the application.

[0969] The above are the details of the specific processing steps and operations for carrying out the invention. In this way, it is possible to generate an efficient delivery route that takes into account the user's emotions and improve the satisfaction of the user and the delivery person.

[0970] 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.

[0971] 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.

[0972] 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.

[0973] [Third embodiment]

[0974] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0975] 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.

[0976] 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).

[0977] 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.

[0978] 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.

[0979] 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).

[0980] 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.

[0981] 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.

[0982] 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.

[0983] 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.

[0984] 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.

[0985] 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."

[0986] The present invention relates to a system that provides a user interface for the recipient to input and change a desired delivery time and includes a communication means for transmitting the input desired delivery time to a server. The system has a data management means for storing the desired delivery time received by the server in a database, and a route generation means for generating an optimal delivery route based on the stored information. It also has a notification means for transmitting information about the generated delivery route to the sender's terminal. This configuration allows changes made by the recipient to be reflected in real time, providing an efficient delivery route, thereby reducing redelivery and delivery delays.

[0987] (Example of specific program processing)

[0988] 1. The user changes the desired delivery time

[0989] Processing Description

[0990] Users can change the pickup time through the "Rakuhai" app. For example, a user can select "I want to change the delivery time to between 3:00 PM and 5:00 PM today."

[0991] Examples:

[0992] If User A wishes to change the current delivery time from "18:00-20:00" to "15:00-17:00", he or she uses the user interface means to select a new delivery time from the settings screen of the app and presses the "Confirm" button.

[0993] 2. The device sends the desired delivery time

[0994] Processing Description

[0995] After the user presses the confirm button, the terminal transmits the new desired delivery time to the server.

[0996] Examples:

[0997] User A's smartphone generates the information "Change to 15:00-17:00" in JSON format and sends it to the "Rakuhai" system server.

[0998] 3. The server updates the recipient's desired delivery time.

[0999] Processing Description

[1000] The server saves the received desired delivery time in the database, and updates the existing delivery information at the same time.

[1001] Examples:

[1002] The server updates User A's delivery schedule in the database from "18:00-20:00" to "15:00-17:00."

[1003] 4. The server generates an efficient delivery route

[1004] Processing Description

[1005] The server generates a new, optimized delivery route based on the latest desired delivery time using a generative AI model that also takes into account the deliverer's current location and traffic information.

[1006] Examples:

[1007] The server recalculates the optimal delivery route using the route generation AI, taking into account all other delivery information and User A's new time.

[1008] 5. The device retrieves the latest delivery route.

[1009] Processing Description

[1010] The deliverer's terminal receives the notification from the server and acquires the new route information, allowing the deliverer to deliver efficiently based on the latest delivery route.

[1011] Examples:

[1012] Delivery person B uses the "Rakuhai" app to check the latest delivery route notified by the server. This route reflects User A's new delivery time.

[1013] With the above configuration, the present invention provides a system that reflects changes in recipient preferences in real time and supports efficient delivery routing. This system reduces redelivery and delivery delays and improves the work efficiency of deliverers.

[1014] The processing flow will be explained below.

[1015] Specific explanation of program processing

[1016] (Step 1: User changes desired delivery time)

[1017] 1. The user launches the "Rakuhai" app.

[1018] 2. The user accesses their My Page or Order Details page and displays delivery details.

[1019] 3. The user selects the desired delivery time section and selects a new preferred time slot.

[1020] 4. The user confirms the changes and presses the "Confirm" button.

[1021] (Step 2: The device sends the desired delivery time)

[1022] 1. Obtain the data of the desired delivery time changed through the user interface means.

[1023] 2. The desired delivery time obtained by the device is converted into JSON format.

[1024] 3. The device sends a request to change the desired delivery time to the backend API endpoint.

[1025] 4. The device waits for a response from the server.

[1026] (Step 3: The server updates the recipient's desired delivery time)

[1027] 1. The server analyzes the request to change the desired delivery time received from the terminal.

[1028] 2. The server extracts the delivery ID and new desired delivery time from the request data.

[1029] 3. The server generates a database query based on the delivery ID to update the desired delivery time for the corresponding record to the new value.

[1030] 4. The server executes the generated database query.

[1031] 5. The server verifies that the database update completed successfully.

[1032] 6. The server sends a response to the terminal indicating that the desired delivery time has been successfully updated.

[1033] (Step 4: The server generates an efficient delivery route)

[1034] 1. The server re-fetches all delivery schedule information from the database.

[1035] 2. The server prepares to input all the delivery schedule information it has obtained into the generative AI model.

[1036] 3. The server also obtains the current location data of the deliverer and real-time traffic information.

[1037] 4. The server inputs all necessary data into the generated AI model and has it calculate the optimal delivery route.

[1038] 5. The server saves the generated optimal delivery route in the delivery route table in the database.

[1039] 6. The server sends a notification containing the new delivery route information to the deliverer's terminal.

[1040] (Step 5: The device retrieves the latest delivery route)

[1041] 1. The device receives a push notification from the server.

[1042] 2. The device analyzes the contents of the push notification and prepares a request to obtain a new delivery route.

[1043] 3. The device sends a request to the server's API endpoint to obtain the latest delivery route information.

[1044] 4. The terminal receives the response from the server and obtains the new delivery route data.

[1045] 5. The new delivery route data acquired by the device is displayed in the app's UI.

[1046] 6. The terminal notifies the user of the latest delivery route information and allows them to confirm it.

[1047] These are the program processing steps of the "Rakuhai" app. Through this specific processing, it is possible to reflect the recipient's desired delivery time in real time and generate and manage efficient delivery routes.

[1048] Example 1

[1049] 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."

[1050] In modern logistics systems, desired delivery times often change on the recipient's side, and there is a need to reflect these changes in real time and optimize delivery routes. Conventional systems have difficulty responding to sudden changes in desired delivery times or traffic information, which can lead to redelivery and delivery delays. Therefore, there is a need for a system that can quickly and efficiently reflect changes in desired delivery times on the recipient's side and generate optimal delivery routes.

[1051] 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.

[1052] In this invention, the server includes input means for the recipient to input or change the desired delivery time, transmission means for transmitting the desired delivery time input via the input means to the server, storage means for receiving the desired delivery time transmitted by the transmission means and storing it in a database, route generation means for generating an optimal delivery route based on the desired delivery time stored in the storage means, notification means for transmitting information on the delivery route generated by the route generation means to the deliverer's terminal, and supply and demand optimization means for optimizing the delivery route based on the deliverer's current situation and traffic information using a generative AI model. This allows changes in the recipient's request to be reflected in real time, reducing redelivery and delivery delays and enabling the generation of efficient delivery routes.

[1053] The "input means" is an interface device that allows the recipient to input or change the desired delivery time.

[1054] The "transmission means" is a device for transmitting the desired delivery time input via the input means to the server via the network.

[1055] The "storage means" is a device that receives the desired delivery time sent by the transmission means and stores it in a database.

[1056] The "route generation means" is a device for generating an optimal delivery route based on the desired delivery time stored in the storage means.

[1057] The "notification means" is a device for transmitting information about the delivery route generated by the route generation means to the terminal of the deliverer.

[1058] The "supply and demand optimization means" is a device that uses a generative AI model to calculate and generate the optimal delivery route based on the delivery person's current location and traffic information.

[1059] A "generative AI model" is an artificial intelligence model that uses machine learning algorithms to derive optimal delivery routes from input data.

[1060] A "prompt statement" is an instruction statement that causes a generative AI model to perform specific data processing or calculations.

[1061] The present invention is configured to provide an efficient delivery system, which allows recipients to input and change their desired delivery time, and this information is reflected in delivery management in real time.

[1062] First, the user operates the delivery app using a device such as a smartphone or PC. This delivery app has an input means and provides an interface that allows the user to select or change the desired delivery time. For example, the user can select "15:00-17:00" and press the "Confirm" button to enter the new desired delivery time.

[1063] Next, the terminal uses the transmission means to transmit this new desired delivery time to the server. The transmitted data can be in a general data format such as JSON format.

[1064] The server receives the desired delivery time data sent from the sending means and saves the information in the database using the saving means. Specifically, the server analyzes the received JSON data and stores the information in the database as an SQL query. At this time, the existing delivery information is also updated.

[1065] Based on the desired delivery time stored in the storage means, the server uses the route generation means to generate the optimal delivery route. A generative AI model is used here, which generates a route that takes into account the user's new desired delivery time, the delivery person's current location, traffic information, etc. The following prompt sentences are used in this process:

[1066] Prompt Sentence Examples

[1067] "Please generate the optimal delivery route taking into account the next delivery information, the current location of the delivery person, and traffic information. The new desired delivery time is 3:00 PM to 5:00 PM."

[1068] The generated optimal delivery route is sent to the deliverer's terminal using a notification means. This notification allows the deliverer to check the latest delivery route on their own terminal and deliver efficiently accordingly.

[1069] For example, if a delivery person has a dedicated delivery device, they will receive a real-time notification on that device saying, "A new delivery route has been set." This notification prompts the delivery person to open the "delivery app," check the new route information, and begin delivery.

[1070] A key feature of this invention is that if a user changes their desired delivery time, the change is reflected in real time. This reduces redelivery and delivery delays, resulting in more efficient delivery. Furthermore, by using a generative AI model, the system takes into account the current location of the deliverer and real-time traffic information, allowing for the generation of optimal delivery routes.

[1071] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1072] Divide the processing flow of this system's program into processing steps

[1073] Step 1: User enters or changes desired delivery time

[1074] Step 2: The device sends the desired delivery time to the server

[1075] Step 3: Store the requested delivery time received by the server in a database

[1076] Step 4: The server generates an efficient delivery route

[1077] Step 5: The delivery person's device receives the latest delivery route

[1078] Detailed description of each processing step

[1079] Step 1: User enters or changes desired delivery time

[1080] Input: A user launches a delivery app and selects a delivery time.

[1081] Output: A delivery time change request is generated.

[1082] Specific actions

[1083] The user opens the delivery app, selects the desired time slot from the displayed time slots, and presses the "Confirm" button. For example, if the user wants to change the time slot to "15:00-17:00," select that time slot and press the "Confirm" button.

[1084] Step 2: The device sends the desired delivery time to the server

[1085] Input: User selected delivery time information.

[1086] Output: Sends a request to change the desired delivery time to the server.

[1087] Specific actions

[1088] The user's device converts the selected desired delivery time into JSON format and sends it to the server as an HTTP POST request. For example, the user's device generates JSON data including the time information "15:00~17:00" and sends it to the server.

[1089] Step 3: Store the requested delivery time received by the server in a database

[1090] Input: JSON data of the desired delivery time sent to the server.

[1091] Output: The requested delivery time information updated in the database.

[1092] Specific actions

[1093] The server parses the received JSON data and saves the user's delivery information in the database. For example, if the server receives data for "15:00~17:00", it parses it, generates an SQL query, and updates the delivery information in the database.

[1094] Step 4: The server generates an efficient delivery route

[1095] Input: Latest desired delivery time information stored in the database, current location information of the delivery person, and traffic information.

[1096] Output: The generated optimal delivery route.

[1097] Specific actions

[1098] The server uses the generative AI model to generate the optimal delivery route based on the latest desired delivery time, the delivery person's current location, and traffic information. At this point, the server sends the following prompt to the generative AI model:

[1099] Example prompt: "Generate the optimal delivery route taking into account the following delivery information, the delivery person's current location, and traffic information. The new desired delivery time is between 3:00 PM and 5:00 PM."

[1100] The server receives the optimal delivery route generated by the generative AI model and stores that information.

[1101] Step 5: The delivery person's device receives the latest delivery route

[1102] Input: Optimal delivery route information sent from the server.

[1103] Output: The updated delivery route displayed on the delivery person's terminal.

[1104] Specific actions

[1105] The server notifies the delivery person's device of the new delivery route information, and the device receives this information. For example, the delivery person's device receives a notification that "a new delivery route has been set," and can check the latest delivery route within the app.

[1106] Through the above steps, even if the user changes the desired delivery time, the change is reflected in real time, an optimal delivery route is generated, and delivery is carried out efficiently.

[1107] (Application example 1)

[1108] 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."

[1109] In food delivery, when a user changes their desired delivery time, the delivery person's route becomes inefficient, resulting in redelivery and delays. When this happens, user satisfaction decreases and delivery efficiency drops significantly. To solve this, a system is needed that can reflect changes in the desired delivery time in real time and generate the optimal delivery route.

[1110] 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.

[1111] In this invention, the server includes a display device for the recipient to input and change the desired delivery time, a data transmission device for transmitting the desired delivery time input via the display device to the server, a data storage device for receiving the desired delivery time transmitted by the data transmission device and storing it in a database, a route generation device for generating an optimal delivery route based on the desired delivery time stored in the data storage device, a notification device for transmitting the delivery route generated by the route generation device to the carrier's terminal, and a processing device using artificial intelligence to optimize the delivery route generated by the route generation device. This allows the optimal delivery route to be generated in real time even when the user changes the delivery time, thereby improving delivery efficiency and reducing delays.

[1112] The "display device" is a device that provides an interactive operation screen for the recipient to input and change the desired delivery time.

[1113] The "data transmission means" is a means having a communication function for transmitting the desired delivery time input via the display means to the server.

[1114] The "data storage means" is a means for receiving the desired delivery time transmitted by the data transmission means and storing it in a database.

[1115] The "route generation means" is a means for generating an optimal delivery route based on the desired delivery time stored in the data storage means.

[1116] The "notification means" is a means for transmitting information about the delivery route generated by the route generation means to the carrier's terminal.

[1117] The "processing means" is a means that uses artificial intelligence to optimize the delivery route generated by the route generation means.

[1118] The "server" is a central processing unit that receives the desired delivery time, stores the data, generates routes, and sends notifications.

[1119] "Transporter's terminal" refers to an information processing device carried by the transporter to receive and display delivery route information notified from the server.

[1120] "Real-time" means that the moment a user changes their desired delivery time, the change is immediately reflected throughout the entire delivery system.

[1121] "Generative artificial intelligence" refers to machine learning algorithms and AI models that generate and optimize optimal delivery routes based on large amounts of data.

[1122] The present invention provides a system that allows recipients to change their desired delivery time in real time in order to significantly improve the efficiency of food delivery. Specific embodiments of this system are described below.

[1123] System Overview

[1124] This system consists of the following main elements:

[1125] 1. Display device means

[1126] 2. Data transmission method

[1127] 3. Data storage method

[1128] 4. Route Generation Method

[1129] 5. Means of notification

[1130] 6. Processing Means

[1131] Hardware and Software Use

[1132] Hardware: Smartphones, servers, carrier terminals

[1133] Software: Food delivery app (compatible with iOS / Android), database system (MySQL, PostgreSQL, etc.), route generation AI model (TensorFlow, PyTorch, etc.)

[1134] display means

[1135] The recipient can input and change the desired delivery time through the smartphone app. The display device means provides an interactive operation screen and is designed to allow the user to easily select the desired delivery time.

[1136] Examples:

[1137] If a user opens a food delivery app and wants to change their current desired delivery time from "18:00-20:00" to "15:00-17:00," they select a new time on the app screen and press the "Confirm" button.

[1138] Data transmission method

[1139] After a user changes their desired delivery time, their smartphone generates the new desired time as JSON data and sends it to the server via an HTTPS request, ensuring that the information reaches the server securely and quickly.

[1140] Data storage means

[1141] The server stores the received desired delivery time in a database. The stored data reflects the updated desired delivery time, and existing delivery information is updated appropriately.

[1142] Route Generation Method

[1143] Based on the latest desired delivery times stored in the database, the server generates the optimal delivery route using a generative AI model, taking into account the carrier's current location and traffic information.

[1144] Examples:

[1145] The server takes into account all delivery information and the user's new desired time and uses route generation AI to recalculate the optimal delivery route.

[1146] Notification means

[1147] The generated new delivery route is notified to the carrier's terminal, allowing the carrier to act efficiently based on the latest delivery route.

[1148] Examples:

[1149] The carrier uses the app to check the updated delivery route provided by the server, which now reflects the user's new delivery time.

[1150] Processing means

[1151] Processing methods using generative artificial intelligence generate and optimize optimal delivery routes based on large amounts of data, thereby improving delivery efficiency and minimizing delays.

[1152] Prompt Sentence Examples

[1153] If the desired delivery time changes, generate the optimal delivery route based on the new desired time. Take the following data into consideration:

[1154] Current location of the deliverer

[1155] Traffic information

[1156] Other delivery schedules

[1157] In this way, the system reflects changes in desired delivery times in real time and provides the optimal delivery route, thereby improving the efficiency of food delivery.

[1158] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1159] Step 1:

[1160] The user uses the display device to input and change the desired delivery time.

[1161] Input: Current desired delivery time and new desired delivery time

[1162] Output: Confirmation of new desired time

[1163] Specific action: The user selects a new desired delivery time on the settings screen of a food delivery app and presses the "Confirm" button.

[1164] Step 2:

[1165] The terminal generates a new desired delivery time as data in JSON format and transmits it to the server via the data transmission means.

[1166] Input: New desired delivery time selected and confirmed by the user

[1167] Output: HTTPS request to the server

[1168] What happens: The smartphone generates JSON data containing the new desired delivery time and sends it to the server via an HTTPS request.

[1169] Step 3:

[1170] The server receives the data and stores the new desired delivery time in a database using the data storage means.

[1171] Input: JSON data of the new desired delivery time sent from the device

[1172] Output: Desired delivery time updated in the database

[1173] What happens: The server analyzes the received data and updates the existing delivery information with the new desired delivery time.

[1174] Step 4:

[1175] The server uses the route generation means to generate an optimal delivery route based on the new desired delivery time.

[1176] Input: Updated desired delivery time, current delivery information, carrier's current location, traffic information

[1177] Output: Optimized delivery route

[1178] How it works: Using generative artificial intelligence, it recalculates the optimal delivery route based on all input data.

[1179] Step 5:

[1180] The server transmits the newly generated delivery route information to the carrier's terminal via the notification means.

[1181] Input: Optimized delivery route information

[1182] Output: Notification to carrier terminal and route information update

[1183] Specific operation: The server generates new delivery route data and sends it to the carrier's device via push notification.

[1184] Step 6:

[1185] The carrier's terminal displays the new delivery route information received from the server and delivers the goods according to it.

[1186] Input: New delivery route information sent from the server

[1187] Output: Efficient delivery by carriers

[1188] Specific operation: The carrier's terminal displays the latest delivery route information, and the carrier makes the delivery based on that information.

[1189] This process allows the system to generate the optimal delivery route in real time, even if the user changes the desired delivery time, preventing delays and redelivery.

[1190] 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.

[1191] The present invention relates to a system that provides a user interface for a recipient to input and change a desired delivery time and includes a communication means for transmitting the input desired delivery time to a server. The system has a data management means for storing the desired delivery time received by the server in a database, and a route generation means for generating an optimal delivery route based on the stored information. The system also has a notification means for transmitting information about the generated delivery route to the deliverer's terminal. The system also includes an emotion engine for recognizing the recipient's emotions, and is able to propose a desired delivery time and optimize the delivery route by taking into account the emotion information obtained from the emotion engine.

[1192] (Example of specific program processing)

[1193] 1. The user changes the desired delivery time

[1194] Processing Description

[1195] Users can change or input the pickup time through the "Rakuhai" app. For example, a user can select "I want to change the delivery time to between 3:00 PM and 5:00 PM today." At this time, the emotion engine recognizes the user's emotion and acquires emotion data.

[1196] Examples:

[1197] If User A wishes to change the current delivery time from "18:00-20:00" to "15:00-17:00," he or she selects a new delivery time from the app's settings screen using the user interface means and presses the "Confirm" button. At this time, the emotion engine detects that User A is feeling stressed and suggests an earlier time slot.

[1198] 2. The device sends the desired delivery time

[1199] Processing Description

[1200] When the user confirms the desired delivery time, the terminal transmits the new desired delivery time and emotion data to the server.

[1201] Examples:

[1202] User A's smartphone generates the information "change to 15:00-17:00" and emotion data in JSON format and sends it to the server.

[1203] 3. The server updates the recipient's desired delivery time.

[1204] Processing Description

[1205] The server stores the received desired delivery time and emotion data in a database, and updates the existing delivery information.

[1206] Examples:

[1207] The server updates User A's delivery schedule in the database from "18:00-20:00" to "15:00-17:00" and also saves the emotion data.

[1208] 4. The server generates an efficient delivery route

[1209] Processing Description

[1210] The server generates a new, optimized delivery route based on the latest desired delivery time and emotion data, using a generative AI model that also takes into account the deliverer's current location and traffic information.

[1211] Examples:

[1212] The server recalculates the optimal delivery route using the route generation AI, taking into account all other delivery information and User A's new time and emotion data.

[1213] 5. The device retrieves the latest delivery route.

[1214] Processing Description

[1215] The deliverer's terminal receives the notification from the server and acquires the new route information, allowing the deliverer to deliver efficiently based on the latest delivery route.

[1216] Examples:

[1217] Delivery person B uses the "Rakuhai" app to check the latest delivery route notified by the server. This route reflects User A's new delivery time and has been prioritized based on the emotion data.

[1218] With the above configuration, the present invention provides a system that supports more efficient delivery routing with higher user satisfaction by reflecting changes in recipient preferences and emotional information in real time. This system reduces redelivery and delivery delays, improves the work efficiency of deliverers, and increases convenience and satisfaction for recipients.

[1219] The processing flow will be explained below.

[1220] (Example of specific program processing)

[1221] 1. The user changes the desired delivery time

[1222] Step 1:

[1223] The user launches the "Rakuhai" app.

[1224] Step 2:

[1225] The user accesses their My Page or Order Details page and displays delivery details.

[1226] Step 3:

[1227] The user selects the desired delivery time section and selects a new desired time slot. At this time, the emotion engine recognizes the user's emotions from facial expressions, voice, etc. and captures them as data.

[1228] Step 4:

[1229] The user confirms the changes and presses the "Confirm" button.

[1230] 2. The device sends the desired delivery time and emotion data

[1231] Step 1:

[1232] The terminal collects the desired delivery time data and emotion data acquired through the user interface means.

[1233] Step 2:

[1234] The device converts this data into JSON format.

[1235] Step 3:

[1236] The device sends a request to the backend API endpoint to change the desired delivery time and emotion data.

[1237] Step 4:

[1238] The terminal waits for a response from the server.

[1239] 3. The server updates the recipient's desired delivery time and emotion data.

[1240] Step 1:

[1241] The server analyzes the request for change of desired delivery time and emotion data received from the terminal.

[1242] Step 2:

[1243] The server extracts the delivery ID, new desired delivery time, and emotion data from the request data.

[1244] Step 3:

[1245] Based on the delivery ID, the server generates a database query to update the desired delivery time and emotion data of the corresponding record to new values.

[1246] Step 4:

[1247] The server executes the generated database query.

[1248] Step 5:

[1249] The server verifies that the database update completed successfully.

[1250] Step 6:

[1251] The server sends a response to the terminal indicating that the desired delivery time and emotion data have been successfully updated.

[1252] 4. The server generates an efficient delivery route

[1253] Step 1:

[1254] The server retrieves all delivery schedule information and emotion data from the database.

[1255] Step 2:

[1256] The server prepares to input all the delivery schedule information it has obtained into the generative AI model.

[1257] Step 3:

[1258] The server also obtains the current location data of the deliverer and real-time traffic information.

[1259] Step 4:

[1260] The server inputs all necessary data into the generated AI model, which calculates the optimal delivery route, adjusting the urgency and priority based on emotional data.

[1261] Step 5:

[1262] The server stores the generated optimal delivery route in a delivery route table in the database.

[1263] Step 6:

[1264] The server sends a notification containing new delivery route information to the deliverer's terminal.

[1265] 5. The device retrieves the latest delivery route.

[1266] Step 1:

[1267] The device receives a push notification from the server.

[1268] Step 2:

[1269] The device analyzes the contents of the push notification and prepares a request to obtain a new delivery route.

[1270] Step 3:

[1271] The terminal sends a request to the server's API endpoint to obtain the latest delivery route information.

[1272] Step 4:

[1273] The terminal receives the response from the server and acquires new delivery route data.

[1274] Step 5:

[1275] The new delivery route data acquired by the device is displayed in the app's UI.

[1276] Step 6:

[1277] The terminal notifies the user of the latest delivery route information and allows the user to confirm it.

[1278] Example 2

[1279] 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."

[1280] In conventional delivery systems, changes to desired delivery times are not reflected in real time, and delivery routes are determined without taking into account the feelings of the recipient, resulting in frequent redelivery and reduced delivery efficiency and user satisfaction. Furthermore, efficient delivery is difficult because routes are generated without sufficient consideration of the deliverer's current location or traffic information.

[1281] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a user interface means for the recipient to input and change the desired delivery time, a communication means for transmitting the desired delivery time input via the user interface means to the server, a data management means for receiving the desired delivery time and emotion data transmitted by the communication means and storing them in a database, a route generation means for generating an optimal delivery route based on the desired delivery time and emotion data stored in the data management means, and a notification means for transmitting information about the delivery route generated by the route generation means to the deliverer's terminal. This allows changes to the desired delivery time to be reflected in real time, enabling the generation of an efficient delivery route that takes emotion information into account. It also enables the generation of an optimal route that takes the deliverer's current location and traffic information into account.

[1282] "User interface means" refers to an interface that allows the recipient to input and change the desired delivery time.

[1283] The "communication means" refers to a means for transmitting the desired delivery time input via the user interface means to the server.

[1284] "Data management means" refers to a means for receiving the desired delivery time and emotion data sent by the communication means and storing them in a database.

[1285] The "route generation means" refers to a means for generating an optimal delivery route based on the desired delivery time and emotion data stored in the data management means.

[1286] The "notification means" refers to a means for transmitting information about the delivery route generated by the route generation means to the terminal of the deliverer.

[1287] A "generative AI model" refers to an artificial intelligence model that generates optimal delivery routes using data such as desired delivery time, emotional data, the delivery person's current location, and traffic information.

[1288] "Emotional data" refers to data obtained by analyzing the user's emotions, and refers to information that can affect changes to the desired delivery time or route generation.

[1289] This invention describes a system that provides a user interface means for the recipient to input and change the desired delivery time, a communication means for transmitting the input desired delivery time to a server, and a system that uses this data to generate the optimal delivery route.

[1290] In this system, the user first launches the "Rakuhai" app on a device such as a smartphone or tablet. The user then selects the option to change the delivery time within the app and enters the new desired delivery time. At this time, the emotion engine analyzes the user's emotions and acquires emotional data. As a specific example, if a user wants to change the current delivery time from "18:00-20:00" to "15:00-17:00," they select a new delivery time from the app's settings screen and press the "Confirm" button. At this time, the emotion engine detects that the user is feeling stressed and suggests an earlier time slot.

[1291] When the user confirms the desired delivery time, the device generates the new desired delivery time and emotion data in JSON format and sends it to the server. For example, User A's smartphone generates the information "changed to 15:00-17:00" and emotion data and sends it to the server.

[1292] The server parses the received desired delivery time and emotion data and saves it in the database. At this time, the existing delivery information is also updated. Specifically, the server updates User A's delivery schedule in the database from "18:00-20:00" to "15:00-17:00" and saves the emotion data at the same time.

[1293] Next, the server retrieves the latest desired delivery time and emotion data from the database and uses the generative AI model to calculate the optimal delivery route. At this time, the server also takes into account the current location of the delivery person and traffic information. For example, the server recalculates the optimal delivery route using the route generation AI based on all other delivery information and User A's new time and emotion data. An example of a prompt sentence is, "Do you want to generate a new delivery route? The information taken into account includes emotion data."

[1294] Finally, the server notifies the delivery person's device of the latest delivery route information. The delivery person's device receives the notification from the server and displays the new route information. As a concrete example, the delivery person uses the "Rakuhai" app to check the latest delivery route notified by the server. This route reflects User A's new delivery time and has been given a higher priority based on emotion data.

[1295] With the above configuration, the present invention allows changes to desired delivery times to be reflected in real time, enabling the creation of efficient delivery routes that take emotional information into account. It also allows the creation of optimal routes that take into account the deliverer's current location and traffic information, reducing redelivery and delays, and improving the work efficiency of the deliverer and the convenience and satisfaction of the recipient.

[1296] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1297] Step 1:

[1298] The user launches the "Rakuhai" app.

[1299] Specific operation: The user taps the "Rakuhai" app from the smartphone's home screen to launch it.

[1300] Input: User action (app launch).

[1301] Output: Home screen displayed after launching the app.

[1302] Step 2:

[1303] The user selects the change delivery time option.

[1304] What happens: The user taps the menu icon in the app and selects the option to change delivery time.

[1305] Input: User action (option selection).

[1306] Output: Display of delivery time change screen.

[1307] Step 3:

[1308] The user inputs a new desired delivery time.

[1309] What happens: The user selects a new desired delivery time from the drop-down menu or calendar and fills out the form. For example, "15:00-17:00."

[1310] Input: User input data (new desired delivery time).

[1311] Output: The desired delivery time entered ("15:00~17:00").

[1312] Step 4:

[1313] The device activates an emotion engine and analyzes the user's emotions.

[1314] Specific operation: Uses the device's camera and microphone to analyze facial expressions and tone of voice to collect emotional data.

[1315] Input: User facial and voice data.

[1316] Output: Emotion data (e.g., "I feel stressed").

[1317] Step 5:

[1318] The user presses the "Confirm" button to confirm the time change.

[1319] Specific behavior: After the user enters a new desired delivery time in the input form, they tap the "Confirm" button.

[1320] Input: User action (tapping the confirm button).

[1321] Output: Confirmed desired delivery time data and emotion data.

[1322] Step 6:

[1323] The device generates new desired delivery time and emotion data in JSON format.

[1324] Specific operation: Convert the input desired delivery time and emotion data into JSON format.

[1325] Input: Desired delivery time data ("15:00~17:00") and emotion data.

[1326] Output: JSON format data (desired delivery time and emotion data).

[1327] Step 7:

[1328] The device sends the generated JSON format data to the server.

[1329] Specific operation: The device creates an HTTP request and sends the new desired delivery time and emotion data to the server.

[1330] Input: Desired delivery time data and emotion data in JSON format.

[1331] Output: Sending data to the server.

[1332] Step 8:

[1333] The server parses the desired delivery time and emotion data received.

[1334] Specific operation: The server parses the received JSON data and converts it into structured data.

[1335] Input: JSON data received from the terminal.

[1336] Output: Parsed desired delivery time data and sentiment data.

[1337] Step 9:

[1338] The server stores the parsed data in a database.

[1339] Specific operation: The server executes an SQL query to insert or update the desired delivery time and emotion data into the database.

[1340] Input: Parsed desired delivery time data and sentiment data.

[1341] Output: Records of data stored in a database.

[1342] Step 10:

[1343] The server retrieves the latest desired delivery time and emotion data from the database.

[1344] What happens: The server uses an SQL query to retrieve the required data from the database.

[1345] Input: None (Trigger in server).

[1346] Output: The latest desired delivery time data and sentiment data.

[1347] Step 11:

[1348] The server uses the generative AI model to calculate the optimal delivery route.

[1349] How it works: The server inputs data into the generative AI model to generate the optimal route, taking into account the delivery person's current location and traffic information.

[1350] Input: Desired delivery time data, emotion data, and delivery person's location and traffic information.

[1351] Output: Optimal delivery route data.

[1352] Step 12:

[1353] The server transmits the latest delivery route information to the deliverer's terminal via the notification means.

[1354] Specific operation: The server sends route information to the delivery user's device via push notification or API.

[1355] Input: Optimal delivery route data.

[1356] Output: Notification to the sender terminal.

[1357] Step 13:

[1358] The deliverer's terminal receives the notification from the server and displays the new route information.

[1359] What happens: The delivery person's device receives a push notification and the new delivery route is displayed on a map within the app.

[1360] Input: Notification from the server (delivery route data).

[1361] Output: The new delivery route displayed on the terminal screen.

[1362] Through these steps, the system can generate efficient delivery routes based on changes in desired delivery times and real-time reflection of emotional information, reducing redelivery and delays. This improves the work efficiency of the delivery person and increases the convenience and satisfaction of the recipient.

[1363] (Application example 2)

[1364] 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."

[1365] In food delivery, users are required to be able to change their desired pick-up time, and delivery personnel are required to efficiently select delivery routes. However, current systems are unable to generate optimal suggestions or routes that take user emotions into account, limiting their ability to improve user satisfaction and improve delivery efficiency. Furthermore, because they do not take emotional data into account, they are unable to respond appropriately to users who are feeling stressed, posing challenges in improving the quality of their service.

[1366] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a user interface means for the recipient to input and change the desired delivery time, a communication means for transmitting the desired delivery time and emotion data input via the user interface means to the server, a data management means for receiving the desired delivery time and emotion data transmitted by the communication means and storing them in a database, a route generation means for generating an optimal delivery route based on the desired delivery time and emotion data stored in the data management means, a notification means for transmitting information about the delivery route generated by the route generation means to the deliverer's terminal, and an emotion engine for recognizing the emotions of the recipient. This enables efficient delivery route generation that takes user emotions into consideration and proposal of an optimal delivery time to the user.

[1367] Definitions of technical terms

[1368] The "user interface means" is a function that provides an interface for the recipient to input and change the desired delivery time.

[1369] The "communication means" is a function for transmitting the desired delivery time and emotion data input via the user interface means to the server.

[1370] The "data management means" is a function that receives the desired delivery time and emotion data sent by the communication means and stores them in a database.

[1371] The "route generation means" is a function that generates an optimal delivery route based on the desired delivery time and emotion data stored in the data management means.

[1372] The "notification means" is a function that transmits information about the delivery route generated by the route generation means to the deliverer's terminal.

[1373] The "emotion engine" is a function that recognizes the emotions of the recipient.

[1374] MODE FOR CARRYING OUT THE INVENTION

[1375] The present invention provides a system for generating an optimal delivery route for a food delivery service by utilizing a user's desired delivery time and emotion data. Specific embodiments are described below.

[1376] System Configuration

[1377] User Interface Means

[1378] Users can input and change their desired delivery time using a smartphone application that has an intuitive interface for inputting desired delivery times.

[1379] communication means

[1380] The desired delivery time and emotion data entered via the user interface are sent to the server via the Internet, and the data is sent in JSON format.

[1381] Data Management Measures

[1382] The server receives the desired delivery time and emotion data transmitted via the communication means and stores them in a database, which records the desired delivery time and emotion information for each user.

[1383] Route Generation Method

[1384] The server generates an optimal delivery route using a generative AI model based on the desired delivery time and emotion data stored in the data management means. This model takes into account the current location of the deliverer, traffic information, and the emotion information of the recipient.

[1385] Notification means

[1386] The optimum delivery route information generated by the route generation means is sent to the deliverer's terminal, and the deliverer receives the new route information in real time and delivers efficiently.

[1387] Emotion Engine

[1388] It recognizes the emotions of the recipient and generates emotional data for delivery suggestions and optimization. The emotion engine may detect user stress and suggest a faster delivery time.

[1389] Specific examples of programs

[1390] overview:

[1391] When a user changes their desired delivery time to "today between 3:00 PM and 5:00 PM," the emotion engine recognizes the user's emotions and acquires emotional data. The new desired delivery time and emotional data are sent to the server, which stores them in a database. The server then generates an optimal delivery route and notifies the delivery person's device of the new route information.

[1392] Hardware and software used:

[1393] Smartphone application ("Rakuhai Food")

[1394] Server-side database management system

[1395] Generative AI model (route generation engine)

[1396] Emotion Engine

[1397] Prompt Sentence Examples

[1398] Generate an optimal delivery route based on the revised delivery time and user emotion data. Factors taken into consideration include all current delivery items, the user's emotional state (e.g., stress), traffic information, and the delivery person's current location. Output the generated route information in JSON format.

[1399] In this way, a system for optimizing delivery routes taking into account the user's emotions is configured, which makes it possible to improve delivery efficiency while also increasing user satisfaction.

[1400] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1401] Program processing steps and detailed explanations

[1402] Step 1:

[1403] The user uses a smartphone application to input and change a new desired delivery time. The input data (e.g., desired delivery time "15:00-17:00") is received by the user interface, and the emotion engine obtains the user's emotional data (e.g., stress level). This information is temporarily saved.

[1404] Input and Output

[1405] Input: Desired delivery time entered into the user interface, emotion data

[1406] Output: Request data including desired delivery time and emotion data

[1407] Specific actions

[1408] The user enters the delivery time on the application screen.

[1409] The emotion engine detects the user's stress level and generates emotional data.

[1410] These data are temporarily saved as request data.

[1411] Step 2:

[1412] The user's smartphone sends the request data to the server. The data is sent in JSON format. The desired delivery time and emotion data are sent to the server via the communication method.

[1413] Input and Output

[1414] Input: Request data (desired delivery time, emotion data)

[1415] Output: JSON formatted data sent to the server

[1416] Specific actions

[1417] The smartphone terminal converts the request data into JSON format.

[1418] Send data to the server using the communication module.

[1419] Step 3:

[1420] The server stores the received request data in a database management system, which records the user ID, desired delivery time, emotion data, etc.

[1421] Input and Output

[1422] Input: JSON format data received by the server

[1423] Output: Updated database

[1424] Specific actions

[1425] The server analyzes the received data and extracts the user ID, desired delivery time, and emotion data.

[1426] The data management system stores the extracted data in a database.

[1427] Step 4:

[1428] Based on the database, the server generates the optimal delivery route using a generative AI model that takes into account the delivery person's current location, traffic information, and user emotion data.

[1429] Input and Output

[1430] Input: Desired delivery time from the database, emotion data, current location of the delivery person, traffic information

[1431] Output: Optimal delivery route information

[1432] Specific actions

[1433] Get the required data from the database.

[1434] Enter prompt text into the generative AI model to generate the optimal delivery route.

[1435] Example prompt: "Generate an optimal delivery route based on the revised delivery time and user sentiment data. Factors taken into account include all current delivery items, the user's emotional state (e.g., stress), traffic information, and the delivery person's current location. Output the generated route information in JSON format."

[1436] Step 5:

[1437] The optimum delivery route information generated by the route generation means is sent to the deliverer's terminal, and the deliverer receives the new route information in real time and delivers efficiently.

[1438] Input and Output

[1439] Input: Optimal delivery route information

[1440] Output: New route information displayed on the shipper's terminal

[1441] Specific actions

[1442] The server sends the generated delivery route information to the deliverer's terminal.

[1443] The delivery person's device receives the new route information and displays it on the application.

[1444] The above are the details of the specific processing steps and operations for carrying out the invention. In this way, it is possible to generate an efficient delivery route that takes into account the user's emotions and improve the satisfaction of the user and the delivery person.

[1445] 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.

[1446] 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.

[1447] 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.

[1448] [Fourth embodiment]

[1449] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1450] 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.

[1451] 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).

[1452] 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.

[1453] 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.

[1454] 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).

[1455] 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.

[1456] 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.

[1457] 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.

[1458] 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.

[1459] 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.

[1460] 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.

[1461] 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."

[1462] The present invention relates to a system that provides a user interface for the recipient to input and change a desired delivery time and includes a communication means for transmitting the input desired delivery time to a server. The system has a data management means for storing the desired delivery time received by the server in a database, and a route generation means for generating an optimal delivery route based on the stored information. It also has a notification means for transmitting information about the generated delivery route to the sender's terminal. This configuration allows changes made by the recipient to be reflected in real time, providing an efficient delivery route, thereby reducing redelivery and delivery delays.

[1463] (Example of specific program processing)

[1464] 1. The user changes the desired delivery time

[1465] Processing Description

[1466] Users can change the pickup time through the "Rakuhai" app. For example, a user can select "I want to change the delivery time to between 3:00 PM and 5:00 PM today."

[1467] Examples:

[1468] If User A wishes to change the current delivery time from "18:00-20:00" to "15:00-17:00", he or she uses the user interface means to select a new delivery time from the settings screen of the app and presses the "Confirm" button.

[1469] 2. The device sends the desired delivery time

[1470] Processing Description

[1471] After the user presses the confirm button, the terminal transmits the new desired delivery time to the server.

[1472] Examples:

[1473] User A's smartphone generates the information "Change to 15:00-17:00" in JSON format and sends it to the "Rakuhai" system server.

[1474] 3. The server updates the recipient's desired delivery time.

[1475] Processing Description

[1476] The server saves the received desired delivery time in the database, and updates the existing delivery information at the same time.

[1477] Examples:

[1478] The server updates User A's delivery schedule in the database from "18:00-20:00" to "15:00-17:00."

[1479] 4. The server generates an efficient delivery route

[1480] Processing Description

[1481] The server generates a new, optimized delivery route based on the latest desired delivery time using a generative AI model that also takes into account the deliverer's current location and traffic information.

[1482] Examples:

[1483] The server recalculates the optimal delivery route using the route generation AI, taking into account all other delivery information and User A's new time.

[1484] 5. The device retrieves the latest delivery route.

[1485] Processing Description

[1486] The deliverer's terminal receives the notification from the server and acquires the new route information, allowing the deliverer to deliver efficiently based on the latest delivery route.

[1487] Examples:

[1488] Delivery person B uses the "Rakuhai" app to check the latest delivery route notified by the server. This route reflects User A's new delivery time.

[1489] With the above configuration, the present invention provides a system that reflects changes in recipient preferences in real time and supports efficient delivery routing. This system reduces redelivery and delivery delays and improves the work efficiency of deliverers.

[1490] The processing flow will be explained below.

[1491] Specific explanation of program processing

[1492] (Step 1: User changes desired delivery time)

[1493] 1. The user launches the "Rakuhai" app.

[1494] 2. The user accesses their My Page or Order Details page and displays delivery details.

[1495] 3. The user selects the desired delivery time section and selects a new preferred time slot.

[1496] 4. The user confirms the changes and presses the "Confirm" button.

[1497] (Step 2: The device sends the desired delivery time)

[1498] 1. Obtain the data of the desired delivery time changed through the user interface means.

[1499] 2. The desired delivery time obtained by the device is converted into JSON format.

[1500] 3. The device sends a request to change the desired delivery time to the backend API endpoint.

[1501] 4. The device waits for a response from the server.

[1502] (Step 3: The server updates the recipient's desired delivery time)

[1503] 1. The server analyzes the request to change the desired delivery time received from the terminal.

[1504] 2. The server extracts the delivery ID and new desired delivery time from the request data.

[1505] 3. The server generates a database query based on the delivery ID to update the desired delivery time for the corresponding record to the new value.

[1506] 4. The server executes the generated database query.

[1507] 5. The server verifies that the database update completed successfully.

[1508] 6. The server sends a response to the terminal indicating that the desired delivery time has been successfully updated.

[1509] (Step 4: The server generates an efficient delivery route)

[1510] 1. The server re-fetches all delivery schedule information from the database.

[1511] 2. The server prepares to input all the delivery schedule information it has obtained into the generative AI model.

[1512] 3. The server also obtains the current location data of the deliverer and real-time traffic information.

[1513] 4. The server inputs all necessary data into the generated AI model and has it calculate the optimal delivery route.

[1514] 5. The server saves the generated optimal delivery route in the delivery route table in the database.

[1515] 6. The server sends a notification containing the new delivery route information to the deliverer's terminal.

[1516] (Step 5: The device retrieves the latest delivery route)

[1517] 1. The device receives a push notification from the server.

[1518] 2. The device analyzes the contents of the push notification and prepares a request to obtain a new delivery route.

[1519] 3. The device sends a request to the server's API endpoint to obtain the latest delivery route information.

[1520] 4. The terminal receives the response from the server and obtains the new delivery route data.

[1521] 5. The new delivery route data acquired by the device is displayed in the app's UI.

[1522] 6. The terminal notifies the user of the latest delivery route information and allows them to confirm it.

[1523] These are the program processing steps of the "Rakuhai" app. Through this specific processing, it is possible to reflect the recipient's desired delivery time in real time and generate and manage efficient delivery routes.

[1524] Example 1

[1525] 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."

[1526] In modern logistics systems, desired delivery times often change on the recipient's side, and there is a need to reflect these changes in real time and optimize delivery routes. Conventional systems have difficulty responding to sudden changes in desired delivery times or traffic information, which can lead to redelivery and delivery delays. Therefore, there is a need for a system that can quickly and efficiently reflect changes in desired delivery times on the recipient's side and generate optimal delivery routes.

[1527] 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.

[1528] In this invention, the server includes input means for the recipient to input or change the desired delivery time, transmission means for transmitting the desired delivery time input via the input means to the server, storage means for receiving the desired delivery time transmitted by the transmission means and storing it in a database, route generation means for generating an optimal delivery route based on the desired delivery time stored in the storage means, notification means for transmitting information on the delivery route generated by the route generation means to the deliverer's terminal, and supply and demand optimization means for optimizing the delivery route based on the deliverer's current situation and traffic information using a generative AI model. This allows changes in the recipient's request to be reflected in real time, reducing redelivery and delivery delays and enabling the generation of efficient delivery routes.

[1529] The "input means" is an interface device that allows the recipient to input or change the desired delivery time.

[1530] The "transmission means" is a device for transmitting the desired delivery time input via the input means to the server via the network.

[1531] The "storage means" is a device that receives the desired delivery time sent by the transmission means and stores it in a database.

[1532] The "route generation means" is a device for generating an optimal delivery route based on the desired delivery time stored in the storage means.

[1533] The "notification means" is a device for transmitting information about the delivery route generated by the route generation means to the terminal of the deliverer.

[1534] The "supply and demand optimization means" is a device that uses a generative AI model to calculate and generate the optimal delivery route based on the delivery person's current location and traffic information.

[1535] A "generative AI model" is an artificial intelligence model that uses machine learning algorithms to derive optimal delivery routes from input data.

[1536] A "prompt statement" is an instruction statement that causes a generative AI model to perform specific data processing or calculations.

[1537] The present invention is configured to provide an efficient delivery system, which allows recipients to input and change their desired delivery time, and this information is reflected in delivery management in real time.

[1538] First, the user operates the delivery app using a device such as a smartphone or PC. This delivery app has an input means and provides an interface that allows the user to select or change the desired delivery time. For example, the user can select "15:00-17:00" and press the "Confirm" button to enter the new desired delivery time.

[1539] Next, the terminal uses the transmission means to transmit this new desired delivery time to the server. The transmitted data can be in a general data format such as JSON format.

[1540] The server receives the desired delivery time data sent from the sending means and saves the information in the database using the saving means. Specifically, the server analyzes the received JSON data and stores the information in the database as an SQL query. At this time, the existing delivery information is also updated.

[1541] Based on the desired delivery time stored in the storage means, the server uses the route generation means to generate the optimal delivery route. A generative AI model is used here, which generates a route that takes into account the user's new desired delivery time, the delivery person's current location, traffic information, etc. The following prompt sentences are used in this process:

[1542] Prompt Sentence Examples

[1543] "Please generate the optimal delivery route taking into account the next delivery information, the current location of the delivery person, and traffic information. The new desired delivery time is 3:00 PM to 5:00 PM."

[1544] The generated optimal delivery route is sent to the deliverer's terminal using a notification means. This notification allows the deliverer to check the latest delivery route on their own terminal and deliver efficiently accordingly.

[1545] For example, if a delivery person has a dedicated delivery device, they will receive a real-time notification on that device saying, "A new delivery route has been set." This notification prompts the delivery person to open the "delivery app," check the new route information, and begin delivery.

[1546] A key feature of this invention is that if a user changes their desired delivery time, the change is reflected in real time. This reduces redelivery and delivery delays, resulting in more efficient delivery. Furthermore, by using a generative AI model, the system takes into account the current location of the deliverer and real-time traffic information, allowing for the generation of optimal delivery routes.

[1547] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1548] Divide the processing flow of this system's program into processing steps

[1549] Step 1: User enters or changes desired delivery time

[1550] Step 2: The device sends the desired delivery time to the server

[1551] Step 3: Store the requested delivery time received by the server in a database

[1552] Step 4: The server generates an efficient delivery route

[1553] Step 5: The delivery person's device receives the latest delivery route

[1554] Detailed description of each processing step

[1555] Step 1: User enters or changes desired delivery time

[1556] Input: A user launches a delivery app and selects a delivery time.

[1557] Output: A delivery time change request is generated.

[1558] Specific actions

[1559] The user opens the delivery app, selects the desired time slot from the displayed time slots, and presses the "Confirm" button. For example, if the user wants to change the time slot to "15:00-17:00," select that time slot and press the "Confirm" button.

[1560] Step 2: The device sends the desired delivery time to the server

[1561] Input: User selected delivery time information.

[1562] Output: Sends a request to change the desired delivery time to the server.

[1563] Specific actions

[1564] The user's device converts the selected desired delivery time into JSON format and sends it to the server as an HTTP POST request. For example, the user's device generates JSON data including the time information "15:00~17:00" and sends it to the server.

[1565] Step 3: Store the requested delivery time received by the server in a database

[1566] Input: JSON data of the desired delivery time sent to the server.

[1567] Output: The requested delivery time information updated in the database.

[1568] Specific actions

[1569] The server parses the received JSON data and saves the user's delivery information in the database. For example, if the server receives data for "15:00~17:00", it parses it, generates an SQL query, and updates the delivery information in the database.

[1570] Step 4: The server generates an efficient delivery route

[1571] Input: Latest desired delivery time information stored in the database, current location information of the delivery person, and traffic information.

[1572] Output: The generated optimal delivery route.

[1573] Specific actions

[1574] The server uses the generative AI model to generate the optimal delivery route based on the latest desired delivery time, the delivery person's current location, and traffic information. At this point, the server sends the following prompt to the generative AI model:

[1575] Example prompt: "Generate the optimal delivery route taking into account the following delivery information, the delivery person's current location, and traffic information. The new desired delivery time is between 3:00 PM and 5:00 PM."

[1576] The server receives the optimal delivery route generated by the generative AI model and stores that information.

[1577] Step 5: The delivery person's device receives the latest delivery route

[1578] Input: Optimal delivery route information sent from the server.

[1579] Output: The updated delivery route displayed on the delivery person's terminal.

[1580] Specific actions

[1581] The server notifies the delivery person's device of the new delivery route information, and the device receives this information. For example, the delivery person's device receives a notification that "a new delivery route has been set," and can check the latest delivery route within the app.

[1582] Through the above steps, even if the user changes the desired delivery time, the change is reflected in real time, an optimal delivery route is generated, and delivery is carried out efficiently.

[1583] (Application example 1)

[1584] 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."

[1585] In food delivery, when a user changes their desired delivery time, the delivery person's route becomes inefficient, resulting in redelivery and delays. When this happens, user satisfaction decreases and delivery efficiency drops significantly. To solve this, a system is needed that can reflect changes in the desired delivery time in real time and generate the optimal delivery route.

[1586] 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.

[1587] In this invention, the server includes a display device for the recipient to input and change the desired delivery time, a data transmission device for transmitting the desired delivery time input via the display device to the server, a data storage device for receiving the desired delivery time transmitted by the data transmission device and storing it in a database, a route generation device for generating an optimal delivery route based on the desired delivery time stored in the data storage device, a notification device for transmitting the delivery route generated by the route generation device to the carrier's terminal, and a processing device using artificial intelligence to optimize the delivery route generated by the route generation device. This allows the optimal delivery route to be generated in real time even when the user changes the delivery time, thereby improving delivery efficiency and reducing delays.

[1588] The "display device" is a device that provides an interactive operation screen for the recipient to input and change the desired delivery time.

[1589] The "data transmission means" is a means having a communication function for transmitting the desired delivery time input via the display means to the server.

[1590] The "data storage means" is a means for receiving the desired delivery time transmitted by the data transmission means and storing it in a database.

[1591] The "route generation means" is a means for generating an optimal delivery route based on the desired delivery time stored in the data storage means.

[1592] The "notification means" is a means for transmitting information about the delivery route generated by the route generation means to the carrier's terminal.

[1593] The "processing means" is a means that uses artificial intelligence to optimize the delivery route generated by the route generation means.

[1594] The "server" is a central processing unit that receives the desired delivery time, stores the data, generates routes, and sends notifications.

[1595] "Transporter's terminal" refers to an information processing device carried by the transporter to receive and display delivery route information notified from the server.

[1596] "Real-time" means that the moment a user changes their desired delivery time, the change is immediately reflected throughout the entire delivery system.

[1597] "Generative artificial intelligence" refers to machine learning algorithms and AI models that generate and optimize optimal delivery routes based on large amounts of data.

[1598] The present invention provides a system that allows recipients to change their desired delivery time in real time in order to significantly improve the efficiency of food delivery. Specific embodiments of this system are described below.

[1599] System Overview

[1600] This system consists of the following main elements:

[1601] 1. Display device means

[1602] 2. Data transmission method

[1603] 3. Data storage method

[1604] 4. Route Generation Method

[1605] 5. Means of notification

[1606] 6. Processing Means

[1607] Hardware and Software Use

[1608] Hardware: Smartphones, servers, carrier terminals

[1609] Software: Food delivery app (compatible with iOS / Android), database system (MySQL, PostgreSQL, etc.), route generation AI model (TensorFlow, PyTorch, etc.)

[1610] display means

[1611] The recipient can input and change the desired delivery time through the smartphone app. The display device means provides an interactive operation screen and is designed to allow the user to easily select the desired delivery time.

[1612] Examples:

[1613] If a user opens a food delivery app and wants to change their current desired delivery time from "18:00-20:00" to "15:00-17:00," they select a new time on the app screen and press the "Confirm" button.

[1614] Data transmission method

[1615] After a user changes their desired delivery time, their smartphone generates the new desired time as JSON data and sends it to the server via an HTTPS request, ensuring that the information reaches the server securely and quickly.

[1616] Data storage means

[1617] The server stores the received desired delivery time in a database. The stored data reflects the updated desired delivery time, and existing delivery information is updated appropriately.

[1618] Route Generation Method

[1619] Based on the latest desired delivery times stored in the database, the server generates the optimal delivery route using a generative AI model, taking into account the carrier's current location and traffic information.

[1620] Examples:

[1621] The server takes into account all delivery information and the user's new desired time and uses route generation AI to recalculate the optimal delivery route.

[1622] Notification means

[1623] The generated new delivery route is notified to the carrier's terminal, allowing the carrier to act efficiently based on the latest delivery route.

[1624] Examples:

[1625] The carrier uses the app to check the updated delivery route provided by the server, which now reflects the user's new delivery time.

[1626] Processing means

[1627] Processing methods using generative artificial intelligence generate and optimize optimal delivery routes based on large amounts of data, thereby improving delivery efficiency and minimizing delays.

[1628] Prompt Sentence Examples

[1629] If the desired delivery time changes, generate the optimal delivery route based on the new desired time. Take the following data into consideration:

[1630] Current location of the deliverer

[1631] Traffic information

[1632] Other delivery schedules

[1633] In this way, the system reflects changes in desired delivery times in real time and provides the optimal delivery route, thereby improving the efficiency of food delivery.

[1634] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1635] Step 1:

[1636] The user uses the display device to input and change the desired delivery time.

[1637] Input: Current desired delivery time and new desired delivery time

[1638] Output: Confirmation of new desired time

[1639] Specific action: The user selects a new desired delivery time on the settings screen of a food delivery app and presses the "Confirm" button.

[1640] Step 2:

[1641] The terminal generates a new desired delivery time as data in JSON format and transmits it to the server via the data transmission means.

[1642] Input: New desired delivery time selected and confirmed by the user

[1643] Output: HTTPS request to the server

[1644] What happens: The smartphone generates JSON data containing the new desired delivery time and sends it to the server via an HTTPS request.

[1645] Step 3:

[1646] The server receives the data and stores the new desired delivery time in a database using the data storage means.

[1647] Input: JSON data of the new desired delivery time sent from the device

[1648] Output: Desired delivery time updated in the database

[1649] What happens: The server analyzes the received data and updates the existing delivery information with the new desired delivery time.

[1650] Step 4:

[1651] The server uses the route generation means to generate an optimal delivery route based on the new desired delivery time.

[1652] Input: Updated desired delivery time, current delivery information, carrier's current location, traffic information

[1653] Output: Optimized delivery route

[1654] How it works: Using generative artificial intelligence, it recalculates the optimal delivery route based on all input data.

[1655] Step 5:

[1656] The server transmits the newly generated delivery route information to the carrier's terminal via the notification means.

[1657] Input: Optimized delivery route information

[1658] Output: Notification to carrier terminal and route information update

[1659] Specific operation: The server generates new delivery route data and sends it to the carrier's device via push notification.

[1660] Step 6:

[1661] The carrier's terminal displays the new delivery route information received from the server and delivers the goods according to it.

[1662] Input: New delivery route information sent from the server

[1663] Output: Efficient delivery by carriers

[1664] Specific operation: The carrier's terminal displays the latest delivery route information, and the carrier makes the delivery based on that information.

[1665] This process allows the system to generate the optimal delivery route in real time, even if the user changes the desired delivery time, preventing delays and redelivery.

[1666] 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.

[1667] The present invention relates to a system that provides a user interface for a recipient to input and change a desired delivery time and includes a communication means for transmitting the input desired delivery time to a server. The system has a data management means for storing the desired delivery time received by the server in a database, and a route generation means for generating an optimal delivery route based on the stored information. The system also has a notification means for transmitting information about the generated delivery route to the deliverer's terminal. The system also includes an emotion engine for recognizing the recipient's emotions, and is able to propose a desired delivery time and optimize the delivery route by taking into account the emotion information obtained from the emotion engine.

[1668] (Example of specific program processing)

[1669] 1. The user changes the desired delivery time

[1670] Processing Description

[1671] Users can change or input the pickup time through the "Rakuhai" app. For example, a user can select "I want to change the delivery time to between 3:00 PM and 5:00 PM today." At this time, the emotion engine recognizes the user's emotion and acquires emotion data.

[1672] Examples:

[1673] If User A wishes to change the current delivery time from "18:00-20:00" to "15:00-17:00," he or she selects a new delivery time from the app's settings screen using the user interface means and presses the "Confirm" button. At this time, the emotion engine detects that User A is feeling stressed and suggests an earlier time slot.

[1674] 2. The device sends the desired delivery time

[1675] Processing Description

[1676] When the user confirms the desired delivery time, the terminal transmits the new desired delivery time and emotion data to the server.

[1677] Examples:

[1678] User A's smartphone generates the information "change to 15:00-17:00" and emotion data in JSON format and sends it to the server.

[1679] 3. The server updates the recipient's desired delivery time.

[1680] Processing Description

[1681] The server stores the received desired delivery time and emotion data in a database, and updates the existing delivery information.

[1682] Examples:

[1683] The server updates User A's delivery schedule in the database from "18:00-20:00" to "15:00-17:00" and also saves the emotion data.

[1684] 4. The server generates an efficient delivery route

[1685] Processing Description

[1686] The server generates a new, optimized delivery route based on the latest desired delivery time and emotion data, using a generative AI model that also takes into account the deliverer's current location and traffic information.

[1687] Examples:

[1688] The server recalculates the optimal delivery route using the route generation AI, taking into account all other delivery information and User A's new time and emotion data.

[1689] 5. The device retrieves the latest delivery route.

[1690] Processing Description

[1691] The deliverer's terminal receives the notification from the server and acquires the new route information, allowing the deliverer to deliver efficiently based on the latest delivery route.

[1692] Examples:

[1693] Delivery person B uses the "Rakuhai" app to check the latest delivery route notified by the server. This route reflects User A's new delivery time and has been prioritized based on the emotion data.

[1694] With the above configuration, the present invention provides a system that supports more efficient delivery routing with higher user satisfaction by reflecting changes in recipient preferences and emotional information in real time. This system reduces redelivery and delivery delays, improves the work efficiency of deliverers, and increases convenience and satisfaction for recipients.

[1695] The processing flow will be explained below.

[1696] (Example of specific program processing)

[1697] 1. The user changes the desired delivery time

[1698] Step 1:

[1699] The user launches the "Rakuhai" app.

[1700] Step 2:

[1701] The user accesses their My Page or Order Details page and displays delivery details.

[1702] Step 3:

[1703] The user selects the desired delivery time section and selects a new desired time slot. At this time, the emotion engine recognizes the user's emotions from facial expressions, voice, etc. and captures them as data.

[1704] Step 4:

[1705] The user confirms the changes and presses the "Confirm" button.

[1706] 2. The device sends the desired delivery time and emotion data

[1707] Step 1:

[1708] The terminal collects the desired delivery time data and emotion data acquired through the user interface means.

[1709] Step 2:

[1710] The device converts this data into JSON format.

[1711] Step 3:

[1712] The device sends a request to the backend API endpoint to change the desired delivery time and emotion data.

[1713] Step 4:

[1714] The terminal waits for a response from the server.

[1715] 3. The server updates the recipient's desired delivery time and emotion data.

[1716] Step 1:

[1717] The server analyzes the request for change of desired delivery time and emotion data received from the terminal.

[1718] Step 2:

[1719] The server extracts the delivery ID, new desired delivery time, and emotion data from the request data.

[1720] Step 3:

[1721] Based on the delivery ID, the server generates a database query to update the desired delivery time and emotion data of the corresponding record to new values.

[1722] Step 4:

[1723] The server executes the generated database query.

[1724] Step 5:

[1725] The server verifies that the database update completed successfully.

[1726] Step 6:

[1727] The server sends a response to the terminal indicating that the desired delivery time and emotion data have been successfully updated.

[1728] 4. The server generates an efficient delivery route

[1729] Step 1:

[1730] The server retrieves all delivery schedule information and emotion data from the database.

[1731] Step 2:

[1732] The server prepares to input all the delivery schedule information it has obtained into the generative AI model.

[1733] Step 3:

[1734] The server also obtains the current location data of the deliverer and real-time traffic information.

[1735] Step 4:

[1736] The server inputs all necessary data into the generated AI model, which calculates the optimal delivery route, adjusting the urgency and priority based on emotional data.

[1737] Step 5:

[1738] The server stores the generated optimal delivery route in a delivery route table in the database.

[1739] Step 6:

[1740] The server sends a notification containing new delivery route information to the deliverer's terminal.

[1741] 5. The device retrieves the latest delivery route.

[1742] Step 1:

[1743] The device receives a push notification from the server.

[1744] Step 2:

[1745] The device analyzes the contents of the push notification and prepares a request to obtain a new delivery route.

[1746] Step 3:

[1747] The terminal sends a request to the server's API endpoint to obtain the latest delivery route information.

[1748] Step 4:

[1749] The terminal receives the response from the server and acquires new delivery route data.

[1750] Step 5:

[1751] The new delivery route data acquired by the device is displayed in the app's UI.

[1752] Step 6:

[1753] The terminal notifies the user of the latest delivery route information and allows the user to confirm it.

[1754] Example 2

[1755] 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."

[1756] In conventional delivery systems, changes to desired delivery times are not reflected in real time, and delivery routes are determined without taking into account the feelings of the recipient, resulting in frequent redelivery and reduced delivery efficiency and user satisfaction. Furthermore, efficient delivery is difficult because routes are generated without sufficient consideration of the deliverer's current location or traffic information.

[1757] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a user interface means for the recipient to input and change the desired delivery time, a communication means for transmitting the desired delivery time input via the user interface means to the server, a data management means for receiving the desired delivery time and emotion data transmitted by the communication means and storing them in a database, a route generation means for generating an optimal delivery route based on the desired delivery time and emotion data stored in the data management means, and a notification means for transmitting information about the delivery route generated by the route generation means to the deliverer's terminal. This allows changes to the desired delivery time to be reflected in real time, enabling the generation of an efficient delivery route that takes emotion information into account. It also enables the generation of an optimal route that takes the deliverer's current location and traffic information into account.

[1758] "User interface means" refers to an interface that allows the recipient to input and change the desired delivery time.

[1759] The "communication means" refers to a means for transmitting the desired delivery time input via the user interface means to the server.

[1760] "Data management means" refers to a means for receiving the desired delivery time and emotion data sent by the communication means and storing them in a database.

[1761] The "route generation means" refers to a means for generating an optimal delivery route based on the desired delivery time and emotion data stored in the data management means.

[1762] The "notification means" refers to a means for transmitting information about the delivery route generated by the route generation means to the terminal of the deliverer.

[1763] A "generative AI model" refers to an artificial intelligence model that generates optimal delivery routes using data such as desired delivery time, emotional data, the delivery person's current location, and traffic information.

[1764] "Emotional data" refers to data obtained by analyzing the user's emotions, and refers to information that can affect changes to the desired delivery time or route generation.

[1765] This invention describes a system that provides a user interface means for the recipient to input and change the desired delivery time, a communication means for transmitting the input desired delivery time to a server, and a system that uses this data to generate the optimal delivery route.

[1766] In this system, the user first launches the "Rakuhai" app on a device such as a smartphone or tablet. The user then selects the option to change the delivery time within the app and enters the new desired delivery time. At this time, the emotion engine analyzes the user's emotions and acquires emotional data. As a specific example, if a user wants to change the current delivery time from "18:00-20:00" to "15:00-17:00," they select a new delivery time from the app's settings screen and press the "Confirm" button. At this time, the emotion engine detects that the user is feeling stressed and suggests an earlier time slot.

[1767] When the user confirms the desired delivery time, the device generates the new desired delivery time and emotion data in JSON format and sends it to the server. For example, User A's smartphone generates the information "changed to 15:00-17:00" and emotion data and sends it to the server.

[1768] The server parses the received desired delivery time and emotion data and saves it in the database. At this time, the existing delivery information is also updated. Specifically, the server updates User A's delivery schedule in the database from "18:00-20:00" to "15:00-17:00" and saves the emotion data at the same time.

[1769] Next, the server retrieves the latest desired delivery time and emotion data from the database and uses the generative AI model to calculate the optimal delivery route. At this time, the server also takes into account the current location of the delivery person and traffic information. For example, the server recalculates the optimal delivery route using the route generation AI based on all other delivery information and User A's new time and emotion data. An example of a prompt sentence is, "Do you want to generate a new delivery route? The information taken into account includes emotion data."

[1770] Finally, the server notifies the delivery person's device of the latest delivery route information. The delivery person's device receives the notification from the server and displays the new route information. As a concrete example, the delivery person uses the "Rakuhai" app to check the latest delivery route notified by the server. This route reflects User A's new delivery time and has been given a higher priority based on emotion data.

[1771] With the above configuration, the present invention allows changes to desired delivery times to be reflected in real time, enabling the creation of efficient delivery routes that take emotional information into account. It also allows the creation of optimal routes that take into account the deliverer's current location and traffic information, reducing redelivery and delays, and improving the work efficiency of the deliverer and the convenience and satisfaction of the recipient.

[1772] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1773] Step 1:

[1774] The user launches the "Rakuhai" app.

[1775] Specific operation: The user taps the "Rakuhai" app from the smartphone's home screen to launch it.

[1776] Input: User action (app launch).

[1777] Output: Home screen displayed after launching the app.

[1778] Step 2:

[1779] The user selects the change delivery time option.

[1780] What happens: The user taps the menu icon in the app and selects the option to change delivery time.

[1781] Input: User action (option selection).

[1782] Output: Display of delivery time change screen.

[1783] Step 3:

[1784] The user inputs a new desired delivery time.

[1785] What happens: The user selects a new desired delivery time from the drop-down menu or calendar and fills out the form. For example, "15:00-17:00."

[1786] Input: User input data (new desired delivery time).

[1787] Output: The desired delivery time entered ("15:00~17:00").

[1788] Step 4:

[1789] The device activates an emotion engine and analyzes the user's emotions.

[1790] Specific operation: Uses the device's camera and microphone to analyze facial expressions and tone of voice to collect emotional data.

[1791] Input: User facial and voice data.

[1792] Output: Emotion data (e.g., "I feel stressed").

[1793] Step 5:

[1794] The user presses the "Confirm" button to confirm the time change.

[1795] Specific behavior: After the user enters a new desired delivery time in the input form, they tap the "Confirm" button.

[1796] Input: User action (tapping the confirm button).

[1797] Output: Confirmed desired delivery time data and emotion data.

[1798] Step 6:

[1799] The device generates new desired delivery time and emotion data in JSON format.

[1800] Specific operation: Convert the input desired delivery time and emotion data into JSON format.

[1801] Input: Desired delivery time data ("15:00~17:00") and emotion data.

[1802] Output: JSON format data (desired delivery time and emotion data).

[1803] Step 7:

[1804] The device sends the generated JSON format data to the server.

[1805] Specific operation: The device creates an HTTP request and sends the new desired delivery time and emotion data to the server.

[1806] Input: Desired delivery time data and emotion data in JSON format.

[1807] Output: Sending data to the server.

[1808] Step 8:

[1809] The server parses the desired delivery time and emotion data received.

[1810] Specific operation: The server parses the received JSON data and converts it into structured data.

[1811] Input: JSON data received from the terminal.

[1812] Output: Parsed desired delivery time data and sentiment data.

[1813] Step 9:

[1814] The server stores the parsed data in a database.

[1815] Specific operation: The server executes an SQL query to insert or update the desired delivery time and emotion data into the database.

[1816] Input: Parsed desired delivery time data and sentiment data.

[1817] Output: Records of data stored in a database.

[1818] Step 10:

[1819] The server retrieves the latest desired delivery time and emotion data from the database.

[1820] What happens: The server uses an SQL query to retrieve the required data from the database.

[1821] Input: None (Trigger in server).

[1822] Output: The latest desired delivery time data and sentiment data.

[1823] Step 11:

[1824] The server uses the generative AI model to calculate the optimal delivery route.

[1825] How it works: The server inputs data into the generative AI model to generate the optimal route, taking into account the delivery person's current location and traffic information.

[1826] Input: Desired delivery time data, emotion data, and delivery person's location and traffic information.

[1827] Output: Optimal delivery route data.

[1828] Step 12:

[1829] The server transmits the latest delivery route information to the deliverer's terminal via the notification means.

[1830] Specific operation: The server sends route information to the delivery user's device via push notification or API.

[1831] Input: Optimal delivery route data.

[1832] Output: Notification to the sender terminal.

[1833] Step 13:

[1834] The deliverer's terminal receives the notification from the server and displays the new route information.

[1835] What happens: The delivery person's device receives a push notification and the new delivery route is displayed on a map within the app.

[1836] Input: Notification from the server (delivery route data).

[1837] Output: The new delivery route displayed on the terminal screen.

[1838] Through these steps, the system can generate efficient delivery routes based on changes in desired delivery times and real-time reflection of emotional information, reducing redelivery and delays. This improves the work efficiency of the delivery person and increases the convenience and satisfaction of the recipient.

[1839] (Application example 2)

[1840] 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."

[1841] In food delivery, users are required to be able to change their desired pick-up time, and delivery personnel are required to efficiently select delivery routes. However, current systems are unable to generate optimal suggestions or routes that take user emotions into account, limiting their ability to improve user satisfaction and improve delivery efficiency. Furthermore, because they do not take emotional data into account, they are unable to respond appropriately to users who are feeling stressed, posing challenges in improving the quality of their service.

[1842] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a user interface means for the recipient to input and change the desired delivery time, a communication means for transmitting the desired delivery time and emotion data input via the user interface means to the server, a data management means for receiving the desired delivery time and emotion data transmitted by the communication means and storing them in a database, a route generation means for generating an optimal delivery route based on the desired delivery time and emotion data stored in the data management means, a notification means for transmitting information about the delivery route generated by the route generation means to the deliverer's terminal, and an emotion engine for recognizing the emotions of the recipient. This enables efficient delivery route generation that takes user emotions into consideration and proposal of an optimal delivery time to the user.

[1843] Definitions of technical terms

[1844] The "user interface means" is a function that provides an interface for the recipient to input and change the desired delivery time.

[1845] The "communication means" is a function for transmitting the desired delivery time and emotion data input via the user interface means to the server.

[1846] The "data management means" is a function that receives the desired delivery time and emotion data sent by the communication means and stores them in a database.

[1847] The "route generation means" is a function that generates an optimal delivery route based on the desired delivery time and emotion data stored in the data management means.

[1848] The "notification means" is a function that transmits information about the delivery route generated by the route generation means to the deliverer's terminal.

[1849] The "emotion engine" is a function that recognizes the emotions of the recipient.

[1850] MODE FOR CARRYING OUT THE INVENTION

[1851] The present invention provides a system for generating an optimal delivery route for a food delivery service by utilizing a user's desired delivery time and emotion data. Specific embodiments are described below.

[1852] System Configuration

[1853] User Interface Means

[1854] Users can input and change their desired delivery time using a smartphone application that has an intuitive interface for inputting desired delivery times.

[1855] communication means

[1856] The desired delivery time and emotion data entered via the user interface are sent to the server via the Internet, and the data is sent in JSON format.

[1857] Data Management Measures

[1858] The server receives the desired delivery time and emotion data transmitted via the communication means and stores them in a database, which records the desired delivery time and emotion information for each user.

[1859] Route Generation Method

[1860] The server generates an optimal delivery route using a generative AI model based on the desired delivery time and emotion data stored in the data management means. This model takes into account the current location of the deliverer, traffic information, and the emotion information of the recipient.

[1861] Notification means

[1862] The optimum delivery route information generated by the route generation means is sent to the deliverer's terminal, and the deliverer receives the new route information in real time and delivers efficiently.

[1863] Emotion Engine

[1864] It recognizes the emotions of the recipient and generates emotional data for delivery suggestions and optimization. The emotion engine may detect user stress and suggest a faster delivery time.

[1865] Specific examples of programs

[1866] overview:

[1867] When a user changes their desired delivery time to "today between 3:00 PM and 5:00 PM," the emotion engine recognizes the user's emotions and acquires emotional data. The new desired delivery time and emotional data are sent to the server, which stores them in a database. The server then generates an optimal delivery route and notifies the delivery person's device of the new route information.

[1868] Hardware and software used:

[1869] Smartphone application ("Rakuhai Food")

[1870] Server-side database management system

[1871] Generative AI model (route generation engine)

[1872] Emotion Engine

[1873] Prompt Sentence Examples

[1874] Generate an optimal delivery route based on the revised delivery time and user emotion data. Factors taken into consideration include all current delivery items, the user's emotional state (e.g., stress), traffic information, and the delivery person's current location. Output the generated route information in JSON format.

[1875] In this way, a system for optimizing delivery routes taking into account the user's emotions is configured, which makes it possible to improve delivery efficiency while also increasing user satisfaction.

[1876] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1877] Program processing steps and detailed explanations

[1878] Step 1:

[1879] The user uses a smartphone application to input and change a new desired delivery time. The input data (e.g., desired delivery time "15:00-17:00") is received by the user interface, and the emotion engine obtains the user's emotional data (e.g., stress level). This information is temporarily saved.

[1880] Input and Output

[1881] Input: Desired delivery time entered into the user interface, emotion data

[1882] Output: Request data including desired delivery time and emotion data

[1883] Specific actions

[1884] The user enters the delivery time on the application screen.

[1885] The emotion engine detects the user's stress level and generates emotional data.

[1886] These data are temporarily saved as request data.

[1887] Step 2:

[1888] The user's smartphone sends the request data to the server. The data is sent in JSON format. The desired delivery time and emotion data are sent to the server via the communication method.

[1889] Input and Output

[1890] Input: Request data (desired delivery time, emotion data)

[1891] Output: JSON formatted data sent to the server

[1892] Specific actions

[1893] The smartphone terminal converts the request data into JSON format.

[1894] Send data to the server using the communication module.

[1895] Step 3:

[1896] The server stores the received request data in a database management system, which records the user ID, desired delivery time, emotion data, etc.

[1897] Input and Output

[1898] Input: JSON format data received by the server

[1899] Output: Updated database

[1900] Specific actions

[1901] The server analyzes the received data and extracts the user ID, desired delivery time, and emotion data.

[1902] The data management system stores the extracted data in a database.

[1903] Step 4:

[1904] Based on the database, the server generates the optimal delivery route using a generative AI model that takes into account the delivery person's current location, traffic information, and user emotion data.

[1905] Input and Output

[1906] Input: Desired delivery time from the database, emotion data, current location of the delivery person, traffic information

[1907] Output: Optimal delivery route information

[1908] Specific actions

[1909] Get the required data from the database.

[1910] Enter prompt text into the generative AI model to generate the optimal delivery route.

[1911] Example prompt: "Generate an optimal delivery route based on the revised delivery time and user sentiment data. Factors taken into account include all current delivery items, the user's emotional state (e.g., stress), traffic information, and the delivery person's current location. Output the generated route information in JSON format."

[1912] Step 5:

[1913] The optimum delivery route information generated by the route generation means is sent to the deliverer's terminal, and the deliverer receives the new route information in real time and delivers efficiently.

[1914] Input and Output

[1915] Input: Optimal delivery route information

[1916] Output: New route information displayed on the shipper's terminal

[1917] Specific actions

[1918] The server sends the generated delivery route information to the deliverer's terminal.

[1919] The delivery person's device receives the new route information and displays it on the application.

[1920] The above are the details of the specific processing steps and operations for carrying out the invention. In this way, it is possible to generate an efficient delivery route that takes into account the user's emotions and improve the satisfaction of the user and the delivery person.

[1921] 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.

[1922] 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.

[1923] 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.

[1924] 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.

[1925] 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.

[1926] 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.

[1927] 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).

[1928] 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.

[1929] 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."

[1930] 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.

[1931] 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).

[1932] 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.

[1933] 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.

[1934] 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.

[1935] 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.

[1936] 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.

[1937] 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.

[1938] 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.

[1939] 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.

[1940] 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.

[1941] 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.

[1942] The following is further disclosed regarding the above embodiment.

[1943] (Claim 1)

[1944] A user interface means for the recipient to input and change a desired delivery time;

[1945] a communication means for transmitting the desired delivery time input via the user interface means to a server;

[1946] a data management means for receiving the desired delivery time transmitted by the communication means and storing the received time in a database;

[1947] a route generation means for generating an optimal delivery route based on the desired delivery time stored in the data management means;

[1948] A system including a notification means for transmitting information about the delivery route generated by the route generation means to a terminal of a deliverer.

[1949] (Claim 2)

[1950] 2. The system according to claim 1, wherein said user interface means allows the recipient to change the desired delivery time in real time.

[1951] (Claim 3)

[1952] 2. The system according to claim 1, wherein the route generation means optimizes the delivery route taking into account the current location of the deliverer and traffic information.

[1953] "Example 1"

[1954] (Claim 1)

[1955] An input means for the recipient to input and change the desired delivery time;

[1956] a transmission means for transmitting the desired delivery time input via the input means to a server;

[1957] a storage means for receiving the desired delivery time transmitted by the transmission means and storing the received time in a database;

[1958] a route generation means for generating an optimal delivery route based on the desired delivery time stored in the storage means;

[1959] notification means for transmitting information about the delivery route generated by the route generation means to a terminal of the deliverer;

[1960] A supply and demand optimization method that uses a generative AI model to optimize delivery routes based on the current status of the delivery person and traffic information,

[1961] A system including:

[1962] (Claim 2)

[1963] 2. The system according to claim 1, wherein said input means allows the recipient to change the desired delivery time in real time.

[1964] (Claim 3)

[1965] The system according to claim 1, wherein the supply and demand optimization means optimizes the delivery route taking into account the current location of the delivery person and traffic information.

[1966] "Application Example 1"

[1967] (Claim 1)

[1968] a display device for the recipient to input and change the desired delivery time;

[1969] data transmission means for transmitting the desired delivery time input via the display means to a server;

[1970] data storage means for receiving the desired delivery time transmitted by the data transmission means and storing the received time in a database;

[1971] a route generation means for generating an optimal delivery route based on the desired delivery time stored in the data storage means;

[1972] a notification means for transmitting information about the delivery route generated by the route generation means to a carrier's terminal;

[1973] A system including a processing means that uses generative artificial intelligence to optimize the delivery route generated by the route generation means.

[1974] (Claim 2)

[1975] 2. The system according to claim 1, wherein said display device allows the recipient to change the desired delivery time in real time.

[1976] (Claim 3)

[1977] 2. The system according to claim 1, wherein the route generation means optimizes the delivery route taking into account the current location of the carrier and traffic information.

[1978] "Example 2: Combining Emotion Engines"

[1979] (Claim 1)

[1980] A user interface means for the recipient to input and change a desired delivery time;

[1981] a communication means for transmitting the desired delivery time input via the user interface means to a server;

[1982] a data management means for receiving the desired delivery time and emotion data transmitted by the communication means and storing them in a database;

[1983] a route generation means for generating an optimal delivery route based on the desired delivery time and emotion data stored in the data management means;

[1984] A system including a notification means for transmitting information about the delivery route generated by the route generation means to a terminal of a deliverer.

[1985] (Claim 2)

[1986] 2. The system according to claim 1, wherein said user interface means allows the recipient to change the desired delivery time and emotion information in real time.

[1987] (Claim 3)

[1988] The system of claim 1, wherein the route generation means uses a generative AI model that optimizes delivery routes by taking into account the current location of the deliverer and traffic information.

[1989] "Application example 2 when combining emotion engines"

[1990] (Claim 1)

[1991] A user interface means for the recipient to input and change a desired delivery time;

[1992] a communication means for transmitting the desired delivery time and emotion data input via the user interface means to a server;

[1993] a data management means for receiving the desired delivery time and emotion data transmitted by the communication means and storing them in a database;

[1994] a route generation means for generating an optimal delivery route based on the desired delivery time and emotion data stored in the data management means;

[1995] notification means for transmitting information about the delivery route generated by the route generation means to a terminal of the deliverer;

[1996] The system includes an emotion engine for recognizing the recipient's emotions.

[1997] (Claim 2)

[1998] 2. The system according to claim 1, wherein said user interface means allows the recipient to change the desired delivery time in real time and makes suggestions based on the recipient's feelings.

[1999] (Claim 3)

[2000] 2. The system according to claim 1, wherein the route generation means optimizes the delivery route by taking into consideration the current location of the deliverer, traffic information, and emotional data of the recipient. [Explanation of symbols]

[2001] 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. a user interface means for the recipient to input and change a desired delivery time; a communication means for transmitting the desired delivery time input via the user interface means to a server; a data management means for receiving the desired delivery time transmitted by the communication means and storing the received time in a database; a route generation means for generating an optimal delivery route based on the desired delivery time stored in the data management means; A system including a notification means for transmitting information about the delivery route generated by the route generation means to a terminal of a deliverer.

2. 2. The system according to claim 1, wherein said user interface means allows the recipient to change the desired delivery time in real time.

3. 2. The system according to claim 1, wherein the route generation means optimizes the delivery route by taking into account the current location of the deliverer and traffic information.

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