system

Abstract

We provide the system. [Solution] An input method for parent users to enter their child's activity schedule, A schedule optimization means for optimizing the travel plan based on the aforementioned schedule, A means of arranging transportation based on the aforementioned travel plan, Tracking means for acquiring location information of the aforementioned means of transport and notifying the parent user, Warning mechanisms for rapid response to emergencies, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] There is a need to provide an environment that reduces the time and psychological burden associated with sending and receiving children to and from their hobbies and activities for working parents, and allows them to safely participate in their children's activities with peace of mind even in a busy daily life. Furthermore, a safe and efficient pick-up and drop-off management mechanism that can immediately respond to unexpected situations is required.

Means for Solving the Problems

[0005] This invention provides a system equipped with a schedule optimization means that uses artificial intelligence to determine the optimal travel order based on the child's activity schedule entered by the parent user. Furthermore, it includes a vehicle dispatch means that arranges transportation safely and efficiently based on the optimized travel plan. In addition, it includes a warning means that notifies the parent user of the real-time location information of the transportation and enables a rapid response in the event of an emergency, thereby significantly reducing the burden on the parent user and ensuring safety.

[0006] A "parent user" is someone who manages their child's activity schedule and uses this system to arrange transportation and ensure the child's safety.

[0007] "Children's activity schedules" refer to information including the date, time, location, and duration of extracurricular activities and other activities, and serve as basic data for the system to plan the most suitable mode of transportation.

[0008] "Input method" refers to the function or interface that allows parent users to provide the system with their child's activity schedule.

[0009] A "schedule optimization method" is a function that uses artificial intelligence to determine an efficient sequence of movements based on a child's activity schedule.

[0010] "Ride-hailing services" refer to the function of arranging appropriate means of transportation according to an optimized travel plan.

[0011] "Tracking" refers to a function that obtains real-time location information of the arranged transportation and notifies the parent user.

[0012] A "warning mechanism" is a function designed to prompt a quick response in the event of an emergency, and is intended to send emergency notifications to the parent user and other relevant parties.

[0013] "Transportation" refers to vehicles and other means of transport used to take children to and from extracurricular activities or other places of activity. [Brief explanation of the drawing]

[0014] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the 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.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0028] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention is a system that allows parents to manage their children's activity schedules and ensure safe and efficient transportation. The system is built upon the integration of terminals, servers, artificial intelligence algorithms, and transportation methods.

[0036] First, the user enters the child's activity schedule via their device. This input data, which includes information such as the type of activity, date and time, location, and duration, is sent to the server.

[0037] The server receives this schedule data and uses an artificial intelligence algorithm to create the optimal transportation plan. The algorithm considers travel time and order between activities and optimizes the plan to maximize overall efficiency. This optimization process minimizes wasted time and reduces the workload for the parent user.

[0038] The server then arranges transportation based on the optimized travel plan. This includes issuing dispatch instructions to partner transportation service providers. Once the dispatch is confirmed, the server notifies the terminal of the detailed schedule and dispatch information, allowing the user to review it.

[0039] While in transit, the server tracks the location of the mode of transport in real time and transmits this information to the device. This tracking allows users to check the current status on their device and manage their child's travel with peace of mind.

[0040] Furthermore, in emergencies, users can send emergency notifications through their devices. These notifications are quickly transmitted via the server to drivers and other relevant personnel, ensuring an immediate response is possible.

[0041] For example, if a user enters a schedule such as "piano lesson at 4 PM on Monday, soccer practice at 6 PM," the server calculates the optimal travel time based on this information and arranges transportation services. It provides real-time data at all times to ensure everything goes according to plan, helping users complete their daily tasks with peace of mind.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The user launches the application on their device and enters their child's activity schedule. The entered information, including date, time, location, and duration, is sent to the server.

[0045] Step 2:

[0046] The server receives schedule data sent by the user and stores it in the database. This information becomes the basic data necessary for subsequent processing.

[0047] Step 3:

[0048] The server activates an artificial intelligence algorithm and optimizes the travel plan using the received schedule data. The AI ​​considers travel distance, time of day, and the order of destinations to create the optimal transportation plan.

[0049] Step 4:

[0050] The server automatically requests vehicle dispatch from partner transportation service providers based on an optimized travel plan. This ensures that a vehicle is arranged for the required time and location.

[0051] Step 5:

[0052] The server notifies the terminal when the vehicle dispatch is complete and notifies the user of the scheduled pick-up / drop-off time and vehicle information. Based on this information, the user can confirm their child's pick-up / drop-off plan.

[0053] Step 6:

[0054] Once the mode of transport begins moving, the server acquires its location information in real time and transmits it to the device. The user can then constantly know the child's current location via the device.

[0055] Step 7:

[0056] When a user presses the emergency button on their device as needed, the server immediately sends an emergency notification to the driver and partner services to prompt a quick response.

[0057] Step 8:

[0058] Once all transfers are complete, the server will provide the user with a final transfer report and request feedback on the transfer service. This information will be used to improve future services.

[0059] (Example 1)

[0060] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0061] When managing their children's activity schedules, parents face the challenge of efficiently planning and safely and quickly transporting their children amidst busy daily lives. Individual appointments are often scheduled in distant locations or at different times, requiring optimized travel and rapid information sharing. However, traditional methods are time-consuming and laborious, and there are concerns about how to respond in emergencies.

[0062] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0063] In this invention, the server includes information input means, plan generation means, and vehicle procurement means. This enables the rapid and efficient optimization of travel plans, arrangement of transportation means, and immediate response in emergencies based on the child's activity schedule.

[0064] "Information input means" refers to an interface device that allows parent users to reliably input their child's activity schedule.

[0065] A "plan generation means" is a computing device or program that formulates an optimal travel plan based on the input schedule information.

[0066] "Vehicle procurement means" refers to the devices and procedures for securing and arranging appropriate means of transportation based on the results of the plan generation.

[0067] An "information notification device" is a communication device that acquires real-time location information of a means of transport and reports its status to the parent user.

[0068] A "warning system" is a system equipped with warning and communication functions to enable a rapid response in the event of an emergency.

[0069] "Machine learning" is an algorithm that analyzes large amounts of data to derive the optimal order of movement.

[0070] "Instant response" is a function that processes the parent user's input in real time and displays the result immediately.

[0071] The system of this invention is built to allow parent users to manage their children's activity schedules and ensure safe and efficient transportation. Specifically, it consists of an integrated system of terminals, servers, machine learning algorithms, and transportation services.

[0072] Users enter their child's activity schedule using their own device (smartphone or tablet). This device has dedicated application software installed and features an interface that allows for easy input of schedule information. For example, it's possible to enter schedules such as "Piano lesson at 4 PM on Monday, soccer practice at 6 PM."

[0073] Schedule information entered from the terminal is sent to a server at the center using a secure communication protocol (such as HTTPS). The server receives this information and uses a machine learning algorithm (for example, an algorithm provided by a cloud-based AI service provider) to generate the optimal travel plan. This algorithm has the ability to analyze large amounts of map data and past travel patterns to calculate the route that will get you to your destination in the shortest time.

[0074] Once the optimal route is determined, the server requests vehicle procurement from partner transportation service providers (e.g., ride-sharing companies). This process is managed automatically via an API, ensuring that arrangements are completed without any action from the user.

[0075] Furthermore, to ensure that parents are always aware of their child's whereabouts during transit, the server tracks the location of the mode of transport in real time and transmits this information to the device. This allows parents to check the current location from their device and ensure their child's safety.

[0076] The system described above also takes emergency response into consideration, allowing users to send emergency notifications from their devices. This feature enables the server to immediately send alerts to transportation services and emergency contacts, allowing for a swift response.

[0077] An example of a prompt message would be something like, "Based on this schedule, please suggest the most efficient route and mode of transportation."

[0078] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0079] Step 1:

[0080] The user enters their child's activity schedule using a terminal. This involves using a form to input the type of activity, location, date and time, and duration. The entered data is converted into a structured data format by the terminal. The converted data is then prepared for transmission to the server.

[0081] Step 2:

[0082] The terminal uses the HTTPS protocol to send the entered schedule data to the server. Here, the data is encrypted for security. The server parses the received data, converts it to the necessary format for storage in the database, and stores it there.

[0083] Step 3:

[0084] The server generates an optimal travel plan using a machine learning algorithm based on stored schedule data. The input consists of schedule data and external data regarding traffic conditions; the algorithm analyzes these to calculate the optimal route and timing. The output is an optimized travel schedule, which is used for subsequent arrangements.

[0085] Step 4:

[0086] Based on the generated optimal travel plan, the server requests vehicle arrangements from affiliated transportation service providers via API. Specifically, the server uses the required date, time, and location information to provide arrangement instructions to the transportation provider. Once the arrangement is complete, the server is notified of the transportation details.

[0087] Step 5:

[0088] The server sends completed vehicle arrangement information to the terminal for user confirmation. This includes confirmed vehicle assignments and estimated arrival times. The terminal displays the received information in a format that is easy for the user to understand intuitively.

[0089] Step 6:

[0090] While in transit, the server tracks the vehicle's location in real time and periodically transmits this information to the terminal. This allows the user to constantly monitor the transport status and adjust their actions as needed. This information is obtained by analyzing GPS data and converting it into location information.

[0091] Step 7:

[0092] Users can use their devices to send emergency notifications in emergencies. This action causes the server to immediately send alerts to transportation services and relevant parties. Notifications are marked as high importance and used to facilitate a rapid response. In this process, necessary actions are determined and information is sent based on the emergency information entered.

[0093] (Application Example 1)

[0094] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0095] In food delivery services, there is a need to achieve efficient and flexible delivery planning, especially during peak order times and when affected by traffic congestion. However, traditional manual scheduling makes it difficult to select the optimal delivery route, sometimes leading to delays and misdeliveries. Furthermore, because it does not take real-time traffic conditions into account, there is a problem in being unable to respond immediately to changes in the plan.

[0096] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0097] In this invention, the server includes an input means for the user to input a delivery schedule, a schedule optimization means for optimizing the delivery plan based on the schedule, and a dispatch means for arranging transportation based on the delivery plan. This enables the efficient formulation of delivery plans and flexible real-time response.

[0098] "Input means" refers to a device or software that allows users to register delivery schedules and other necessary information into the system.

[0099] "Schedule optimization methods" refer to algorithms and processing methods for constructing the optimal delivery plan based on the input schedule information.

[0100] "Vehicle dispatching" refers to the procedures and systems for arranging the necessary means of transportation based on an optimized delivery plan.

[0101] "Tracking technology" refers to technology that allows users to check the current location and progress of a means of transport in real time and provide that information to the user.

[0102] An "update mechanism" is a system for dynamically changing and optimizing delivery plans, taking into account real-time traffic conditions and other factors.

[0103] This invention provides a system for improving delivery efficiency in food delivery services. Specific embodiments are described below.

[0104] The server receives order data entered by users using smartphones or computers. This data includes information such as delivery time, delivery address, and order details. Based on the information received through the input methods, the server optimizes the delivery plan using schedule optimization methods. Here, AI algorithms (e.g., GOOGLE TENSOR® FLOW®) are used to calculate the delivery order and route, enabling efficient delivery.

[0105] Next, based on the optimized delivery plan, the server uses dispatching tools to arrange transportation. This arrangement involves sending necessary instructions to delivery partners available in real time. The delivery progress is monitored using tracking tools, and the location of the transportation is constantly communicated to the user.

[0106] Furthermore, the update mechanism allows the server to analyze real-time traffic conditions and dynamically adjust delivery routes as needed. This updated information is promptly fed back to both users and delivery partners.

[0107] For example, if a large number of orders come in during peak hours on a Sunday, the system can automatically calculate the most efficient delivery route and immediately communicate it to the delivery partner. This ensures that deliveries to customers are made on time.

[0108] An example of a prompt would be, "Calculate the optimal route for delivering to customer A at 2 PM on Sunday and to customer B at 2:30 PM." This prompt allows the AI ​​algorithm to automatically generate an efficient route plan.

[0109] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0110] Step 1:

[0111] The user enters their delivery schedule using their device. Specifically, they enter information such as their preferred delivery time, delivery address, and order details into an application on their device. This input data is then sent to the server.

[0112] Step 2:

[0113] The server analyzes the received input data and stores its contents in a database. The stored data is processed using an AI algorithm and used as information necessary for prioritizing deliveries and optimizing routes. The output at this stage is ready data for the algorithm to use for optimization.

[0114] Step 3:

[0115] The server uses AI algorithms (e.g., TensorFlow) to optimize the schedule. Based on the input delivery data, it calculates the optimal route and order to efficiently visit each delivery destination. This process also takes into account predicted traffic conditions and historical data. The optimized route output is then provided.

[0116] Step 4:

[0117] Based on the optimized route plan, the server sends instructions to available delivery partners using the dispatch system. Specifically, it sends push notifications containing delivery route information to the delivery partners' devices for confirmation.

[0118] Step 5:

[0119] During delivery, the location of the transport vehicle is monitored in real time using tracking devices. The server collects this information and notifies the user's device of the updated transport status as it occurs. Location data is continuously acquired and notified in real time.

[0120] Step 6:

[0121] If necessary, the server analyzes traffic conditions using update mechanisms and dynamically updates the delivery plan if route adjustments are required. The newly calculated route information is then sent back to the delivery partner for appropriate guidance. This update process utilizes real-time data, including traffic information APIs.

[0122] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0123] This invention provides a system that allows parents to manage their children's activity schedules and safely and efficiently arrange transportation, and further incorporates an emotion engine to realize optimal pick-up and drop-off services by taking into account the user's emotions. This system is built by integrating terminals, servers, artificial intelligence algorithms, and emotion recognition functions.

[0124] First, the user enters their child's activity schedule using an application on their device. This interface provides real-time feedback and is designed to allow parents to easily manage the schedule. The schedule information is sent to a server and stored in a database.

[0125] The server optimizes the travel plan using an artificial intelligence algorithm based on the received schedule data. This ensures efficient movement between activities and reduces the time burden on the parent user.

[0126] The emotion engine provides a means to analyze the user's emotions. Users can input their emotions via a terminal, or their emotions can be detected using voice or facial expression data. The server processes this emotion data and provides feedback to the schedule optimization system. This allows for schedule adjustments to be made with more leeway, for example, if the user is experiencing high stress levels.

[0127] The server arranges transportation based on an optimized travel plan. The location information of the arranged transportation is tracked in real time and notified to the user via the terminal. This information is important for the user to know the child's current location and to use the pick-up and drop-off service safely.

[0128] In an emergency, users can instantly send an emergency notification via their device. The server receives this notification and quickly sends a warning to the relevant parties to prompt appropriate action.

[0129] For example, if a user enters a schedule such as "Ballet lesson at 3 PM on Wednesday, English conversation class at 5 PM," and also enters that they are not feeling well, the emotion engine will prompt the schedule optimization system to make adjustments. As a result, the server will arrange for an earlier dispatch to allow for extra travel time, providing safe and comfortable transportation tailored to the user's situation.

[0130] The following describes the processing flow.

[0131] Step 1:

[0132] The user uses their device to enter their child's activity schedule into the app. The entered information includes the date, time, location, and duration of the activity, and the device sends this information to the server.

[0133] Step 2:

[0134] The server saves the received schedule data to the database. This saved data will be used for future schedule optimization.

[0135] Step 3:

[0136] Users input emotional data through their devices. This data can be entered manually or automatically acquired using voice or facial recognition functions.

[0137] Step 4:

[0138] The server analyzes the input emotion data and sends the information to the emotion engine. The emotion engine evaluates the user's emotional state and determines whether flexible schedule adjustments are necessary.

[0139] Step 5:

[0140] The server receives evaluation results from the emotion engine and uses an artificial intelligence algorithm to optimize the travel plan. Travel times and order are adjusted, and buffer time is added if necessary.

[0141] Step 6:

[0142] The server sends dispatch instructions to partner transportation services according to an optimized plan. The server ensures that travel time and vehicle arrangements are handled smoothly.

[0143] Step 7:

[0144] The terminal receives dispatch information from the server and notifies the user. The user can then review this information and understand the details regarding the child's transportation.

[0145] Step 8:

[0146] When the mode of transport begins to move, the server acquires its location information in real time and sends it to the device. This allows the user to always check the child's current location.

[0147] Step 9:

[0148] When a user presses the emergency button on their device, the server immediately sends an emergency notification to the relevant transportation or service provider. This is configured to allow for a rapid response.

[0149] Step 10:

[0150] Once the migration is complete, the server will provide the user with a final report and request feedback on the service. This feedback will be used to improve future services.

[0151] (Example 2)

[0152] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0153] There is a need for a system that allows parents to efficiently manage their children's activity schedules and ensure safe and smooth transportation. However, conventional systems have difficulty flexibly adjusting schedules while considering the user's emotions, and are inadequate in responding to sudden emotional changes or emergencies.

[0154] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0155] In this invention, the server includes an input means for the parent user to input the child's activity schedule, an emotion analysis means for adjusting the activity schedule based on the input emotion information, and a schedule optimization means for optimizing the travel plan based on the schedule and emotion information. This enables flexible schedule adjustments according to the user's emotions and circumstances, as well as safe and efficient transportation.

[0156] A "parent user" refers to a user who manages the child's activity schedule and is responsible for transportation.

[0157] "Activity schedule" refers to information indicating the date, time, and location of various activities in which children participate.

[0158] "Input means" refers to a device or program that provides an interface for a parent user to register their activity schedule in the system.

[0159] "Emotional analysis means" refers to a function that analyzes the emotional information of the parent user and adjusts the system's operation and schedule based on the results.

[0160] "Schedule optimization means" refers to a device or program that has the function of creating an efficient travel plan based on input activity schedules and emotional information.

[0161] "Tracking means" refers to the system's function for checking the current location of the arranged transportation and notifying the parent user.

[0162] An "emergency situation" refers to a sudden situation that requires a rapid response and where the system needs to issue a warning to ensure safety.

[0163] "Warning measures" refer to a part of a system that has the function of notifying relevant parties in the event of an emergency and prompting a swift response.

[0164] "Artificial intelligence" refers to a technology in which a system independently performs learning and analysis, and then executes optimization processes based on that learning.

[0165] "Real-time feedback" refers to the system's ability to immediately respond to information entered by the user.

[0166] This invention provides a system that allows parents to efficiently manage their children's activity schedules and ensure safe and smooth transportation. The system consists of a parent user's terminal, a central server, and artificial intelligence software.

[0167] Parent users utilize an application on their device to input activity schedules. This application features an intuitive interface designed for easy schedule entry and management. It also supports emotional input, allowing users to record emotions using text, audio, or video data.

[0168] The server receives the entered schedule and emotional information and stores it in a database. Furthermore, the server uses an artificial intelligence algorithm to perform schedule optimization. In this process, the entered emotional information is also taken into consideration to create an efficient travel plan that is sensitive to the user's feelings. It also has functions to arrange transportation and track the current location, allowing parents to check their child's travel status in real time.

[0169] For example, a parent user might input an activity schedule such as "Ballet lesson at 3 PM on Wednesday, English conversation class at 5 PM," and also input "Tired" as their current physical condition. Based on this information, the system would plan to finish travel earlier and create a schedule with some leeway. An example of a prompt to the generating AI model would be, "Please adjust the pick-up / drop-off schedule considering the parent user's feelings."

[0170] In the event of an emergency, the user can immediately issue an alert via their device. The server receives this alert and promptly notifies all relevant parties. As a result, a swift response and safety are ensured. In this way, the invention realizes a system that enables schedule management and safe travel while taking into account the user's emotions and state of mind.

[0171] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0172] Step 1:

[0173] The user enters their child's activity schedule using an application on their device. Specifically, they enter information into a form specifying the start time, end time, and location of each activity. The input in this step is the activity schedule, and the output is the schedule data sent to the server.

[0174] Step 2:

[0175] The terminal sends the schedule data entered by the user to the server. The server receives this data and saves it to its database. In this step, the entered schedule data is saved and ready for use in subsequent processing.

[0176] Step 3:

[0177] Users can input emotional data via their devices. This includes describing emotions through text input, as well as capturing facial expressions and voices in real time using a camera and microphone. The input in this step is emotional data, and the output is analyzable emotional information sent to the server.

[0178] Step 4:

[0179] The server processes the received emotional information and analyzes the user's emotions using emotion analysis tools. This process evaluates the input emotional data using an analysis algorithm to determine the emotional state (e.g., stress level, euphoria, etc.). The output of this step is data indicating the emotional state.

[0180] Step 5:

[0181] The server activates a schedule optimization mechanism, optimizing the travel plan based on the user's schedule data and analyzed sentiment data. This algorithm efficiently adjusts the order and timing to generate an optimal transportation plan that takes the user's emotions into consideration. The input for this step is schedule data and sentiment state data, and the output is the optimized transportation plan.

[0182] Step 6:

[0183] The server arranges transportation based on an optimized transportation plan. Furthermore, it obtains real-time location information of the arranged transportation and notifies the user via the terminal. In this step, transportation arrangement and location tracking are performed, and the output is a real-time location notification.

[0184] Step 7:

[0185] In the event of an emergency, the user uses their device to send an emergency notification. This notification is sent to a server, which quickly alerts relevant parties using warning mechanisms. The input in this step is the emergency notification, and the output is a prompt response via an alert notification.

[0186] (Application Example 2)

[0187] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0188] In modern society, it is crucial for parents to understand their children's diverse activity schedules and provide appropriate transportation. However, it is difficult for parents to efficiently plan travel while always ensuring their children's safety, and flexible responses that take into account the parents' emotions and the children's circumstances are particularly required. Conventional systems often fail to optimize plans while considering the parents' emotions and are limited to general reminder tracking notifications. Therefore, a comprehensive schedule management and travel support system that takes parents' emotions into account is needed.

[0189] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0190] In this invention, the server includes an input means for a parent user to input their child's activity schedule, a schedule optimization means for optimizing travel plans based on the schedule and performing emotional analysis, a means for arranging and tracking autonomous vehicles and providing notifications, and a warning issuing means for providing rapid notifications in emergencies. This enables more flexible and safer schedule management and transportation arrangements that take parental emotions into consideration.

[0191] A "parent user" is a person who is responsible for managing their child's activity schedule and ensuring safe and efficient transportation.

[0192] "Activity schedule" refers to a child's daily schedule of school, extracurricular activities, and other activities, and serves as basic information for parents to plan transportation arrangements based on this schedule.

[0193] "Input means" refers to a device or software that provides an interface for parent users to input their child's activity schedule via smartphone or computer.

[0194] A "schedule optimization method" is a process or system that uses artificial intelligence technology to create an efficient and safe travel plan based on the input activity schedule.

[0195] An "autonomous vehicle" is a vehicle that travels on the road without human intervention and safely transports children to their destinations based on a designated route and time.

[0196] "Tracking means" refers to technology or devices that collect location information of autonomous vehicles in real time, notify the parent user of that information, and perform safety checks.

[0197] A "warning system" is a system or method for instantly sending warnings or notifications to relevant parties in the event of an emergency.

[0198] "Emotional analysis means" refers to technology that analyzes the emotional state of parent users and children through audio and video data and reflects this in travel planning.

[0199] The server provides an interface for parents to enter their children's activity schedules via smartphone or computer. This allows parents to easily enter and manage schedules. The entered data is sent to the server and stored in a database.

[0200] The server generates an efficient travel plan using schedule optimization methods that leverage artificial intelligence technology. During this process, the emotional states of the parent user and child are analyzed using emotion analysis tools, and these are taken into account when optimizing the travel plan. Emotion analysis utilizes voice and facial expression data, and APIs such as Google Cloud Vision are used.

[0201] Furthermore, the server arranges for autonomous vehicles and tracks their location in real time. This allows parents to constantly check their child's current location from their smartphone, improving safety. In emergencies, the system immediately uses an alert system to quickly notify relevant parties.

[0202] For example, if a parent inputs a schedule for taking their child to piano lessons after school and records their emotional state as "tired" via voice input, the server will use emotion analysis to create a more relaxed travel schedule and arrange for an early autonomous vehicle. This reduces the burden on the parent. An example of a prompt to the generating AI model would be: "As a parent, I want to efficiently manage my child's transportation. My child has extracurricular activities after school, and I would like you to suggest the optimal transportation plan, taking my own emotional state into consideration."

[0203] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0204] Step 1:

[0205] Users use a smartphone or computer to enter their child's activity schedule into the application's interface. This input includes information such as the date, time, location, and duration of the activity. The entered data is pre-validated on the device to check for missing information or errors before being prepared to be sent to the server.

[0206] Step 2:

[0207] The server saves the received activity schedule data to the database. At this stage, it verifies that the saved data is correct and processes it into an appropriate format for use as input for schedule optimization.

[0208] Step 3:

[0209] The server collects user emotional data. Users register their emotional states (e.g., stress, fatigue) through the application using voice input or image recognition. The collected emotional data is analyzed by emotion recognition software such as Google Cloud Vision and converted into numerical data.

[0210] Step 4:

[0211] The server uses stored activity schedule data and analyzed sentiment data to perform schedule optimization. Here, a generative AI model is utilized to create an efficient travel plan. The output includes an optimized travel route, the type of transportation used, and a recommended travel start time.

[0212] Step 5:

[0213] The server arranges for autonomous vehicles. Based on an optimized travel plan, a vehicle is arranged to arrive at a specified location at a specified time. A vehicle operation service API is used to send a notification to the user when the arrangement is complete.

[0214] Step 6:

[0215] The server tracks the location of dispatched autonomous vehicles in real time and notifies the user. This tracking information is displayed in combination with map data and sent to the user through the application. The user can then check this information and understand the progress of the vehicle's movement.

[0216] Step 7:

[0217] When a user reports an emergency through the application, the server immediately uses an alert system to notify vehicle operators and emergency contacts. This process generates and sends an emergency information log.

[0218] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0219] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0220] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0221] [Second Embodiment]

[0222] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0223] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0224] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0225] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0226] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0227] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0228] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0229] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0230] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0231] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0232] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0233] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0234] This invention is a system that allows parents to manage their children's activity schedules and ensure safe and efficient transportation. The system is built upon the integration of terminals, servers, artificial intelligence algorithms, and transportation methods.

[0235] First, the user enters the child's activity schedule via their device. This input data, which includes information such as the type of activity, date and time, location, and duration, is sent to the server.

[0236] The server receives this schedule data and uses an artificial intelligence algorithm to create the optimal transportation plan. The algorithm considers travel time and order between activities and optimizes the plan to maximize overall efficiency. This optimization process minimizes wasted time and reduces the workload for the parent user.

[0237] The server then arranges transportation based on the optimized travel plan. This includes issuing dispatch instructions to partner transportation service providers. Once the dispatch is confirmed, the server notifies the terminal of the detailed schedule and dispatch information, allowing the user to review it.

[0238] While in transit, the server tracks the location of the mode of transport in real time and transmits this information to the device. This tracking allows users to check the current status on their device and manage their child's travel with peace of mind.

[0239] Furthermore, in emergencies, users can send emergency notifications through their devices. These notifications are quickly transmitted via the server to drivers and other relevant personnel, ensuring an immediate response is possible.

[0240] For example, if a user enters a schedule such as "piano lesson at 4 PM on Monday, soccer practice at 6 PM," the server calculates the optimal travel time based on this information and arranges transportation services. It provides real-time data at all times to ensure everything goes according to plan, helping users complete their daily tasks with peace of mind.

[0241] The following describes the processing flow.

[0242] Step 1:

[0243] The user launches the application on their device and enters their child's activity schedule. The entered information, including date, time, location, and duration, is sent to the server.

[0244] Step 2:

[0245] The server receives schedule data sent by the user and stores it in the database. This information becomes the basic data necessary for subsequent processing.

[0246] Step 3:

[0247] The server activates an artificial intelligence algorithm and optimizes the travel plan using the received schedule data. The AI ​​considers travel distance, time of day, and the order of destinations to create the optimal transportation plan.

[0248] Step 4:

[0249] The server automatically requests vehicle dispatch from partner transportation service providers based on an optimized travel plan. This ensures that a vehicle is arranged for the required time and location.

[0250] Step 5:

[0251] The server notifies the terminal when the vehicle dispatch is complete and notifies the user of the scheduled pick-up / drop-off time and vehicle information. Based on this information, the user can confirm their child's pick-up / drop-off plan.

[0252] Step 6:

[0253] Once the mode of transport begins moving, the server acquires its location information in real time and transmits it to the device. The user can then constantly know the child's current location via the device.

[0254] Step 7:

[0255] When a user presses the emergency button on their device as needed, the server immediately sends an emergency notification to the driver and partner services to prompt a quick response.

[0256] Step 8:

[0257] Once all transfers are complete, the server will provide the user with a final transfer report and request feedback on the transfer service. This information will be used to improve future services.

[0258] (Example 1)

[0259] Next, we will describe Example 1. 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."

[0260] When managing their children's activity schedules, parents face the challenge of efficiently planning and safely and quickly transporting their children amidst busy daily lives. Individual appointments are often scheduled in distant locations or at different times, requiring optimized travel and rapid information sharing. However, traditional methods are time-consuming and laborious, and there are concerns about how to respond in emergencies.

[0261] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0262] In this invention, the server includes information input means, plan generation means, and vehicle procurement means. This enables the rapid and efficient optimization of travel plans, arrangement of transportation means, and immediate response in emergencies based on the child's activity schedule.

[0263] "Information input means" refers to an interface device that allows parent users to reliably input their child's activity schedule.

[0264] A "plan generation means" is a computing device or program that formulates an optimal travel plan based on the input schedule information.

[0265] "Vehicle procurement means" refers to the devices and procedures for securing and arranging appropriate means of transportation based on the results of the plan generation.

[0266] An "information notification device" is a communication device that acquires real-time location information of a means of transport and reports its status to the parent user.

[0267] A "warning system" is a system equipped with warning and communication functions to enable a rapid response in the event of an emergency.

[0268] "Machine learning" is an algorithm that analyzes large amounts of data to derive the optimal order of movement.

[0269] "Instant response" is a function that processes the parent user's input in real time and displays the result immediately.

[0270] The system of this invention is built to allow parent users to manage their children's activity schedules and ensure safe and efficient transportation. Specifically, it consists of an integrated system of terminals, servers, machine learning algorithms, and transportation services.

[0271] Users enter their child's activity schedule using their own device (smartphone or tablet). This device has dedicated application software installed and features an interface that allows for easy input of schedule information. For example, it's possible to enter schedules such as "Piano lesson at 4 PM on Monday, soccer practice at 6 PM."

[0272] Schedule information entered from the terminal is sent to a server at the center using a secure communication protocol (such as HTTPS). The server receives this information and uses a machine learning algorithm (for example, an algorithm provided by a cloud-based AI service provider) to generate the optimal travel plan. This algorithm has the ability to analyze large amounts of map data and past travel patterns to calculate the route that will get you to your destination in the shortest time.

[0273] Once the optimal route is determined, the server requests vehicle procurement from partner transportation service providers (e.g., ride-sharing companies). This process is managed automatically via an API, ensuring that arrangements are completed without any action from the user.

[0274] Furthermore, to ensure that parents are always aware of their child's whereabouts during transit, the server tracks the location of the mode of transport in real time and transmits this information to the device. This allows parents to check the current location from their device and ensure their child's safety.

[0275] The system described above also takes emergency response into consideration, allowing users to send emergency notifications from their devices. This feature enables the server to immediately send alerts to transportation services and emergency contacts, allowing for a swift response.

[0276] An example of a prompt message would be something like, "Based on this schedule, please suggest the most efficient route and mode of transportation."

[0277] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0278] Step 1:

[0279] The user enters their child's activity schedule using a terminal. This involves using a form to input the type of activity, location, date and time, and duration. The entered data is converted into a structured data format by the terminal. The converted data is then prepared for transmission to the server.

[0280] Step 2:

[0281] The terminal uses the HTTPS protocol to send the entered schedule data to the server. Here, the data is encrypted for security. The server parses the received data, converts it to the necessary format for storage in the database, and stores it there.

[0282] Step 3:

[0283] Based on the saved schedule data, the server uses a machine learning algorithm to generate an optimal travel plan. The inputs are the schedule data and external data regarding traffic conditions. The algorithm analyzes these to calculate the optimal route and timing. The output is an optimized travel schedule, which is used for the next arrangement procedure.

[0284] Step 4:

[0285] Based on the generated optimal travel plan, the server requests vehicle arrangements from the partnered transportation service providers via API. Specifically, the server uses the information on the required date, time, and location to give instructions for the arrangements to the transportation providers. When the arrangements are completed, the details of the transportation are notified to the server.

[0286] Step 5:

[0287] The server sends the completed vehicle arrangement information to the terminal so that the user can confirm it. This includes information such as the confirmed vehicle allocation information and the estimated arrival time. The terminal displays the received information in a form that is intuitive and easy for the user to understand.

[0288] Step 6:

[0289] During the journey, the server tracks the vehicle's position in real-time and periodically sends that information to the terminal. Thereby, the user can always monitor the transportation situation and adjust their actions as needed. This information is obtained by analyzing GPS data and converting it into position information.

[0290] Step 7:

[0291] Users can use their devices to send emergency notifications in emergencies. This action causes the server to immediately send alerts to transportation services and relevant parties. Notifications are marked as high importance and used to facilitate a rapid response. In this process, necessary actions are determined and information is sent based on the emergency information entered.

[0292] (Application Example 1)

[0293] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0294] In food delivery services, there is a need to achieve efficient and flexible delivery planning, especially during peak order times and when affected by traffic congestion. However, traditional manual scheduling makes it difficult to select the optimal delivery route, sometimes leading to delays and misdeliveries. Furthermore, because it does not take real-time traffic conditions into account, there is a problem in being unable to respond immediately to changes in the plan.

[0295] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0296] In this invention, the server includes an input means for the user to input a delivery schedule, a schedule optimization means for optimizing the delivery plan based on the schedule, and a dispatch means for arranging transportation based on the delivery plan. This enables the efficient formulation of delivery plans and flexible real-time response.

[0297] "Input means" refers to a device or software that allows users to register delivery schedules and other necessary information into the system.

[0298] "Schedule optimization methods" refer to algorithms and processing methods for constructing the optimal delivery plan based on the input schedule information.

[0299] "Vehicle dispatching" refers to the procedures and systems for arranging the necessary means of transportation based on an optimized delivery plan.

[0300] "Tracking technology" refers to technology that allows users to check the current location and progress of a means of transport in real time and provide that information to the user.

[0301] An "update mechanism" is a system for dynamically changing and optimizing delivery plans, taking into account real-time traffic conditions and other factors.

[0302] This invention provides a system for improving delivery efficiency in food delivery services. Specific embodiments are described below.

[0303] The server receives order data entered by users using smartphones or computers. This data includes information such as delivery time, delivery address, and order details. Based on the information received through the input methods, the server optimizes the delivery plan using scheduling optimization methods. Here, AI algorithms (e.g., Google TensorFlow) are used to calculate the delivery order and route, enabling efficient delivery.

[0304] Next, based on the optimized delivery plan, the server uses dispatching tools to arrange transportation. This arrangement involves sending necessary instructions to delivery partners available in real time. The delivery progress is monitored using tracking tools, and the location of the transportation is constantly communicated to the user.

[0305] Furthermore, the update mechanism allows the server to analyze real-time traffic conditions and dynamically adjust delivery routes as needed. This updated information is promptly fed back to both users and delivery partners.

[0306] For example, when a large number of orders are received during the peak hours on Sunday, the system can automatically calculate the most efficient delivery route and immediately inform the delivery partner. This ensures that deliveries are made to customers on time.

[0307] An example of a prompt sentence is "Please calculate the optimal route for delivering to Customer A at 2:00 PM on Sunday and to Customer B at 2:30 PM on Sunday." Based on this prompt, the AI algorithm automatically generates an efficient route plan.

[0308] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0309] Step 1:

[0310] The user uses the terminal to input the delivery schedule. Specifically, information such as the desired delivery time, delivery address, and order details is entered into the application on the terminal. This input data is sent to the server.

[0311] Step 2:

[0312] The server analyzes the received input data and stores its content in the database. The stored data is processed using an AI algorithm and used as information necessary for delivery prioritization and route optimization. The output at this stage is the data ready for the algorithm to use for optimization.

[0313] Step 3:

[0314] The server performs schedule optimization using an AI algorithm (e.g., TensorFlow). Based on the input delivery data, it calculates the optimal route and order to efficiently visit each delivery destination. In this process, predicted traffic conditions and past data are also considered. The output of the optimized route is provided.

[0315] [[ID=三十六]]ステップ4:

[0316] Based on the optimized route plan, the server sends instructions to available delivery partners using the dispatch system. Specifically, it sends push notifications containing delivery route information to the delivery partners' devices for confirmation.

[0317] Step 5:

[0318] During delivery, the location of the transport vehicle is monitored in real time using tracking devices. The server collects this information and notifies the user's device of the updated transport status as it occurs. Location data is continuously acquired and notified in real time.

[0319] Step 6:

[0320] If necessary, the server analyzes traffic conditions using update mechanisms and dynamically updates the delivery plan if route adjustments are required. The newly calculated route information is then sent back to the delivery partner for appropriate guidance. This update process utilizes real-time data, including traffic information APIs.

[0321] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0322] This invention provides a system that allows parents to manage their children's activity schedules and safely and efficiently arrange transportation, and further incorporates an emotion engine to realize optimal pick-up and drop-off services by taking into account the user's emotions. This system is built by integrating terminals, servers, artificial intelligence algorithms, and emotion recognition functions.

[0323] First, the user enters their child's activity schedule using an application on their device. This interface provides real-time feedback and is designed to allow parents to easily manage the schedule. The schedule information is sent to a server and stored in a database.

[0324] The server optimizes the travel plan using an artificial intelligence algorithm based on the received schedule data. This ensures efficient movement between activities and reduces the time burden on the parent user.

[0325] The emotion engine provides a means to analyze the user's emotions. Users can input their emotions via a terminal, or their emotions can be detected using voice or facial expression data. The server processes this emotion data and provides feedback to the schedule optimization system. This allows for schedule adjustments to be made with more leeway, for example, if the user is experiencing high stress levels.

[0326] The server arranges transportation based on an optimized travel plan. The location information of the arranged transportation is tracked in real time and notified to the user via the terminal. This information is important for the user to know the child's current location and to use the pick-up and drop-off service safely.

[0327] In an emergency, users can instantly send an emergency notification via their device. The server receives this notification and quickly sends a warning to the relevant parties to prompt appropriate action.

[0328] For example, if a user enters a schedule such as "Ballet lesson at 3 PM on Wednesday, English conversation class at 5 PM," and also enters that they are not feeling well, the emotion engine will prompt the schedule optimization system to make adjustments. As a result, the server will arrange for an earlier dispatch to allow for extra travel time, providing safe and comfortable transportation tailored to the user's situation.

[0329] The following describes the processing flow.

[0330] Step 1:

[0331] The user uses their device to enter their child's activity schedule into the app. The entered information includes the date, time, location, and duration of the activity, and the device sends this information to the server.

[0332] Step 2:

[0333] The server saves the received schedule data to the database. This saved data will be used for future schedule optimization.

[0334] Step 3:

[0335] Users input emotional data through their devices. This data can be entered manually or automatically acquired using voice or facial recognition functions.

[0336] Step 4:

[0337] The server analyzes the input emotion data and sends the information to the emotion engine. The emotion engine evaluates the user's emotional state and determines whether flexible schedule adjustments are necessary.

[0338] Step 5:

[0339] The server receives evaluation results from the emotion engine and uses an artificial intelligence algorithm to optimize the travel plan. Travel times and order are adjusted, and buffer time is added if necessary.

[0340] Step 6:

[0341] The server sends dispatch instructions to partner transportation services according to an optimized plan. The server ensures that travel time and vehicle arrangements are handled smoothly.

[0342] Step 7:

[0343] The terminal receives dispatch information from the server and notifies the user. The user can then review this information and understand the details regarding their child's transportation.

[0344] Step 8:

[0345] When the mode of transport begins to move, the server acquires its location information in real time and sends it to the device. This allows the user to always check the child's current location.

[0346] Step 9:

[0347] When a user presses the emergency button on their device, the server immediately sends an emergency notification to the relevant transportation or service provider. This is configured to allow for a rapid response.

[0348] Step 10:

[0349] Once the migration is complete, the server will provide the user with a final report and request feedback on the service. This feedback will be used to improve future services.

[0350] (Example 2)

[0351] Next, we will describe Example 2. 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".

[0352] There is a need for a system that allows parents to efficiently manage their children's activity schedules and ensure safe and smooth transportation. However, conventional systems have difficulty flexibly adjusting schedules while considering the user's emotions, and are inadequate in responding to sudden emotional changes or emergencies.

[0353] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0354] In this invention, the server includes an input means for the parent user to input the child's activity schedule, an emotion analysis means for adjusting the activity schedule based on the input emotion information, and a schedule optimization means for optimizing the travel plan based on the schedule and emotion information. This enables flexible schedule adjustments according to the user's emotions and circumstances, as well as safe and efficient transportation.

[0355] A "parent user" refers to a user who manages the child's activity schedule and is responsible for transportation.

[0356] "Activity schedule" refers to information indicating the date, time, and location of various activities in which children participate.

[0357] "Input means" refers to a device or program that provides an interface for a parent user to register their activity schedule in the system.

[0358] "Emotional analysis means" refers to a function that analyzes the emotional information of the parent user and adjusts the system's operation and schedule based on the results.

[0359] "Schedule optimization means" refers to a device or program that has the function of creating an efficient travel plan based on input activity schedules and emotional information.

[0360] "Tracking means" refers to the system's function for checking the current location of the arranged transportation and notifying the parent user.

[0361] An "emergency situation" refers to a sudden situation that requires a rapid response and where the system needs to issue a warning to ensure safety.

[0362] "Warning measures" refer to a part of a system that has the function of notifying relevant parties in the event of an emergency and prompting a swift response.

[0363] "Artificial intelligence" refers to a technology in which a system independently performs learning and analysis, and then executes optimization processes based on that learning.

[0364] "Real-time feedback" refers to the system's ability to immediately respond to information entered by the user.

[0365] This invention provides a system that allows parents to efficiently manage their children's activity schedules and ensure safe and smooth transportation. The system consists of a parent user's terminal, a central server, and artificial intelligence software.

[0366] Parent users utilize an application on their device to input activity schedules. This application features an intuitive interface designed for easy schedule entry and management. It also supports emotional input, allowing users to record emotions using text, audio, or video data.

[0367] The server receives the entered schedule and emotional information and stores it in a database. Furthermore, the server uses an artificial intelligence algorithm to perform schedule optimization. In this process, the entered emotional information is also taken into consideration to create an efficient travel plan that is sensitive to the user's feelings. It also has functions to arrange transportation and track the current location, allowing parents to check their child's travel status in real time.

[0368] For example, a parent user might input an activity schedule such as "Ballet lesson at 3 PM on Wednesday, English conversation class at 5 PM," and also input "Tired" as their current physical condition. Based on this information, the system would plan to finish travel earlier and create a schedule with some leeway. An example of a prompt to the generating AI model would be, "Please adjust the pick-up / drop-off schedule considering the parent user's feelings."

[0369] In the event of an emergency, the user can immediately issue an alert via their device. The server receives this alert and promptly notifies all relevant parties. As a result, a swift response and safety are ensured. In this way, the invention realizes a system that enables schedule management and safe travel while taking into account the user's emotions and state of mind.

[0370] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0371] Step 1:

[0372] The user enters their child's activity schedule using an application on their device. Specifically, they enter information into a form specifying the start time, end time, and location of each activity. The input in this step is the activity schedule, and the output is the schedule data sent to the server.

[0373] Step 2:

[0374] The terminal sends the schedule data entered by the user to the server. The server receives this data and saves it to its database. In this step, the entered schedule data is saved and ready for use in subsequent processing.

[0375] Step 3:

[0376] Users can input emotional data via their devices. This includes describing emotions through text input, as well as capturing facial expressions and voices in real time using a camera and microphone. The input in this step is emotional data, and the output is analyzable emotional information sent to the server.

[0377] Step 4:

[0378] The server processes the received emotional information and analyzes the user's emotions using emotion analysis tools. This process evaluates the input emotional data using an analysis algorithm to determine the emotional state (e.g., stress level, euphoria, etc.). The output of this step is data indicating the emotional state.

[0379] Step 5:

[0380] The server activates a schedule optimization mechanism, optimizing the travel plan based on the user's schedule data and analyzed sentiment data. This algorithm efficiently adjusts the order and timing to generate an optimal transportation plan that takes the user's emotions into consideration. The input for this step is schedule data and sentiment state data, and the output is the optimized transportation plan.

[0381] Step 6:

[0382] The server arranges transportation based on an optimized transportation plan. Furthermore, it obtains real-time location information of the arranged transportation and notifies the user via the terminal. In this step, transportation arrangement and location tracking are performed, and the output is a real-time location notification.

[0383] Step 7:

[0384] In the event of an emergency, the user uses their device to send an emergency notification. This notification is sent to a server, which quickly alerts relevant parties using warning mechanisms. The input in this step is the emergency notification, and the output is a prompt response via an alert notification.

[0385] (Application Example 2)

[0386] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0387] In modern society, it is crucial for parents to understand their children's diverse activity schedules and provide appropriate transportation. However, it is difficult for parents to efficiently plan travel while always ensuring their children's safety, and flexible responses that take into account the parents' emotions and the children's circumstances are particularly required. Conventional systems often fail to optimize plans while considering the parents' emotions and are limited to general reminder tracking notifications. Therefore, a comprehensive schedule management and travel support system that takes parents' emotions into account is needed.

[0388] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0389] In this invention, the server includes an input means for a parent user to input their child's activity schedule, a schedule optimization means for optimizing travel plans based on the schedule and performing emotional analysis, a means for arranging and tracking autonomous vehicles and providing notifications, and a warning issuing means for providing rapid notifications in emergencies. This enables more flexible and safer schedule management and transportation arrangements that take parental emotions into consideration.

[0390] A "parent user" is a person who is responsible for managing their child's activity schedule and ensuring safe and efficient transportation.

[0391] "Activity schedule" refers to a child's daily schedule of school, extracurricular activities, and other activities, and serves as basic information for parents to plan transportation arrangements based on this schedule.

[0392] "Input means" refers to a device or software that provides an interface for parent users to input their child's activity schedule via smartphone or computer.

[0393] A "schedule optimization method" is a process or system that uses artificial intelligence technology to create an efficient and safe travel plan based on the input activity schedule.

[0394] An "autonomous vehicle" is a vehicle that travels on the road without human intervention and safely transports children to their destinations based on a designated route and time.

[0395] "Tracking means" refers to technology or devices that collect location information of autonomous vehicles in real time, notify the parent user of that information, and perform safety checks.

[0396] A "warning system" is a system or method for instantly sending warnings or notifications to relevant parties in the event of an emergency.

[0397] "Emotional analysis means" refers to technology that analyzes the emotional state of parent users and children through audio and video data and reflects this in travel planning.

[0398] The server provides an interface for parents to enter their children's activity schedules via smartphone or computer. This allows parents to easily enter and manage schedules. The entered data is sent to the server and stored in a database.

[0399] The server generates an efficient travel plan using schedule optimization techniques that leverage artificial intelligence technology. During this process, the emotional states of both the parent user and the child are analyzed using emotion analysis techniques, and these are taken into account when optimizing the travel plan. Emotion analysis utilizes voice and facial expression data, and APIs such as Google Cloud Vision are used.

[0400] Furthermore, the server arranges for autonomous vehicles and tracks their location in real time. This allows parents to constantly check their child's current location from their smartphone, improving safety. In emergencies, the system immediately uses an alert system to quickly notify relevant parties.

[0401] For example, if a parent inputs a schedule for taking their child to piano lessons after school and records their emotional state as "tired" via voice input, the server will use emotion analysis to create a more relaxed travel schedule and arrange for an early autonomous vehicle. This reduces the burden on the parent. An example of a prompt to the generating AI model would be: "As a parent, I want to efficiently manage my child's transportation. My child has extracurricular activities after school, and I would like you to suggest the optimal transportation plan, taking my own emotional state into consideration."

[0402] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0403] Step 1:

[0404] Users use a smartphone or computer to enter their child's activity schedule into the application's interface. This input includes information such as the date, time, location, and duration of the activity. The entered data is pre-validated on the device to check for missing information or errors before being prepared to be sent to the server.

[0405] Step 2:

[0406] The server saves the received activity schedule data to the database. At this stage, it verifies that the saved data is correct and processes it into an appropriate format for use as input for schedule optimization.

[0407] Step 3:

[0408] The server collects user emotional data. Users register their emotional states (e.g., stress, fatigue) through the application using voice input or image recognition. The collected emotional data is analyzed by emotion recognition software such as Google Cloud Vision and converted into numerical data.

[0409] Step 4:

[0410] The server uses stored activity schedule data and analyzed sentiment data to perform schedule optimization. Here, a generative AI model is utilized to create an efficient travel plan. The output includes an optimized travel route, the type of transportation used, and a recommended travel start time.

[0411] Step 5:

[0412] The server arranges for autonomous vehicles. Based on an optimized travel plan, a vehicle is arranged to arrive at a specified location at a specified time. A vehicle operation service API is used to send a notification to the user when the arrangement is complete.

[0413] Step 6:

[0414] The server tracks the location of dispatched autonomous vehicles in real time and notifies the user. This tracking information is displayed in combination with map data and sent to the user through the application. The user can then check this information and understand the progress of the vehicle's movement.

[0415] Step 7:

[0416] When a user reports an emergency through the application, the server immediately uses an alert system to notify vehicle operators and emergency contacts. This process generates and sends an emergency information log.

[0417] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0418] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0419] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0420] [Third Embodiment]

[0421] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0422] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0423] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0424] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0425] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0426] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0427] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0428] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0429] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0430] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0431] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0432] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0433] This invention is a system that allows parents to manage their children's activity schedules and ensure safe and efficient transportation. The system is built upon the integration of terminals, servers, artificial intelligence algorithms, and transportation methods.

[0434] First, the user enters the child's activity schedule via their device. This input data, which includes information such as the type of activity, date and time, location, and duration, is sent to the server.

[0435] The server receives this schedule data and uses an artificial intelligence algorithm to create the optimal transportation plan. The algorithm considers travel time and order between activities and optimizes the plan to maximize overall efficiency. This optimization process minimizes wasted time and reduces the workload for the parent user.

[0436] The server then arranges transportation based on the optimized travel plan. This includes issuing dispatch instructions to partner transportation service providers. Once the dispatch is confirmed, the server notifies the terminal of the detailed schedule and dispatch information, allowing the user to review it.

[0437] While in transit, the server tracks the location of the mode of transport in real time and transmits this information to the device. This tracking allows users to check the current status on their device and manage their child's travel with peace of mind.

[0438] Furthermore, in emergencies, users can send emergency notifications through their devices. These notifications are quickly transmitted via the server to drivers and other relevant personnel, ensuring an immediate response is possible.

[0439] For example, if a user enters a schedule such as "piano lesson at 4 PM on Monday, soccer practice at 6 PM," the server calculates the optimal travel time based on this information and arranges transportation services. It provides real-time data at all times to ensure everything goes according to plan, helping users complete their daily tasks with peace of mind.

[0440] The following describes the processing flow.

[0441] Step 1:

[0442] The user launches the application on their device and enters their child's activity schedule. The entered information, including date, time, location, and duration, is sent to the server.

[0443] Step 2:

[0444] The server receives schedule data sent by the user and stores it in the database. This information becomes the basic data necessary for subsequent processing.

[0445] Step 3:

[0446] The server activates an artificial intelligence algorithm and optimizes the travel plan using the received schedule data. The AI ​​considers travel distance, time of day, and the order of destinations to create the optimal transportation plan.

[0447] Step 4:

[0448] The server automatically requests vehicle dispatch from partner transportation service providers based on an optimized travel plan. This ensures that a vehicle is arranged for the required time and location.

[0449] Step 5:

[0450] The server notifies the terminal when the vehicle dispatch is complete and notifies the user of the scheduled pick-up / drop-off time and vehicle information. Based on this information, the user can confirm their child's pick-up / drop-off plan.

[0451] Step 6:

[0452] Once the mode of transport begins moving, the server acquires its location information in real time and transmits it to the device. The user can then constantly know the child's current location via the device.

[0453] Step 7:

[0454] When a user presses the emergency button on their device as needed, the server immediately sends an emergency notification to the driver and partner services to prompt a quick response.

[0455] Step 8:

[0456] Once all transfers are complete, the server will provide the user with a final transfer report and request feedback on the transfer service. This information will be used to improve future services.

[0457] (Example 1)

[0458] Next, we will describe Example 1. 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."

[0459] When managing their children's activity schedules, parents face the challenge of efficiently planning and safely and quickly transporting their children amidst busy daily lives. Individual appointments are often scheduled in distant locations or at different times, requiring optimized travel and rapid information sharing. However, traditional methods are time-consuming and laborious, and there are concerns about how to respond in emergencies.

[0460] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0461] In this invention, the server includes information input means, plan generation means, and vehicle procurement means. This enables the rapid and efficient optimization of travel plans, arrangement of transportation means, and immediate response in emergencies based on the child's activity schedule.

[0462] "Information input means" refers to an interface device that allows parent users to reliably input their child's activity schedule.

[0463] A "plan generation means" is a computing device or program that formulates an optimal travel plan based on the input schedule information.

[0464] "Vehicle procurement means" refers to the devices and procedures for securing and arranging appropriate means of transportation based on the results of the plan generation.

[0465] An "information notification device" is a communication device that acquires real-time location information of a means of transport and reports its status to the parent user.

[0466] A "warning system" is a system equipped with warning and communication functions to enable a rapid response in the event of an emergency.

[0467] "Machine learning" is an algorithm that analyzes large amounts of data to derive the optimal order of movement.

[0468] "Instant response" is a function that processes the parent user's input in real time and displays the result immediately.

[0469] The system of this invention is built to allow parent users to manage their children's activity schedules and ensure safe and efficient transportation. Specifically, it consists of an integrated system of terminals, servers, machine learning algorithms, and transportation services.

[0470] Users enter their child's activity schedule using their own device (smartphone or tablet). This device has dedicated application software installed and features an interface that allows for easy input of schedule information. For example, it's possible to enter schedules such as "Piano lesson at 4 PM on Monday, soccer practice at 6 PM."

[0471] Schedule information entered from the terminal is sent to a server at the center using a secure communication protocol (such as HTTPS). The server receives this information and uses a machine learning algorithm (for example, an algorithm provided by a cloud-based AI service provider) to generate the optimal travel plan. This algorithm has the ability to analyze large amounts of map data and past travel patterns to calculate the route that will get you to your destination in the shortest time.

[0472] Once the optimal route is determined, the server requests vehicle procurement from partner transportation service providers (e.g., ride-sharing companies). This process is managed automatically via an API, ensuring that arrangements are completed without any action from the user.

[0473] Furthermore, to ensure that parents are always aware of their child's whereabouts during transit, the server tracks the location of the mode of transport in real time and transmits this information to the device. This allows parents to check the current location from their device and ensure their child's safety.

[0474] The system described above also takes emergency response into consideration, allowing users to send emergency notifications from their devices. This feature enables the server to immediately send alerts to transportation services and emergency contacts, allowing for a swift response.

[0475] An example of a prompt message would be something like, "Based on this schedule, please suggest the most efficient route and mode of transportation."

[0476] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0477] Step 1:

[0478] The user enters their child's activity schedule using a terminal. This involves using a form to input the type of activity, location, date and time, and duration. The entered data is converted into a structured data format by the terminal. The converted data is then prepared for transmission to the server.

[0479] Step 2:

[0480] The terminal uses the HTTPS protocol to send the entered schedule data to the server. Here, the data is encrypted for security. The server parses the received data, converts it to the necessary format for storage in the database, and stores it there.

[0481] Step 3:

[0482] The server generates an optimal travel plan using a machine learning algorithm based on stored schedule data. The input consists of schedule data and external data regarding traffic conditions; the algorithm analyzes these to calculate the optimal route and timing. The output is an optimized travel schedule, which is used for subsequent arrangements.

[0483] Step 4:

[0484] Based on the generated optimal travel plan, the server requests vehicle arrangements from affiliated transportation service providers via API. Specifically, the server uses the required date, time, and location information to provide arrangement instructions to the transportation provider. Once the arrangement is complete, the server is notified of the transportation details.

[0485] Step 5:

[0486] The server sends completed vehicle arrangement information to the terminal for user confirmation. This includes confirmed vehicle assignments and estimated arrival times. The terminal displays the received information in a format that is easy for the user to understand intuitively.

[0487] Step 6:

[0488] While in transit, the server tracks the vehicle's location in real time and periodically transmits this information to the terminal. This allows the user to constantly monitor the transport status and adjust their actions as needed. This information is obtained by analyzing GPS data and converting it into location information.

[0489] Step 7:

[0490] Users can use their devices to send emergency notifications in emergencies. This action causes the server to immediately send alerts to transportation services and relevant parties. Notifications are marked as high importance and used to facilitate a rapid response. In this process, necessary actions are determined and information is sent based on the emergency information entered.

[0491] (Application Example 1)

[0492] Next, we will explain Application Example 1. In the following explanation, 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."

[0493] In food delivery services, there is a need to achieve efficient and flexible delivery planning, especially during peak order times and when affected by traffic congestion. However, traditional manual scheduling makes it difficult to select the optimal delivery route, sometimes leading to delays and misdeliveries. Furthermore, because it does not take real-time traffic conditions into account, there is a problem in being unable to respond immediately to changes in the plan.

[0494] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0495] In this invention, the server includes an input means for the user to input a delivery schedule, a schedule optimization means for optimizing the delivery plan based on the schedule, and a dispatch means for arranging transportation based on the delivery plan. This enables the efficient formulation of delivery plans and flexible real-time response.

[0496] "Input means" refers to a device or software that allows users to register delivery schedules and other necessary information into the system.

[0497] "Schedule optimization methods" refer to algorithms and processing methods for constructing the optimal delivery plan based on the input schedule information.

[0498] "Vehicle dispatching" refers to the procedures and systems for arranging the necessary means of transportation based on an optimized delivery plan.

[0499] "Tracking technology" refers to technology that allows users to check the current location and progress of a means of transport in real time and provide that information to the user.

[0500] An "update mechanism" is a system for dynamically changing and optimizing delivery plans, taking into account real-time traffic conditions and other factors.

[0501] This invention provides a system for improving delivery efficiency in food delivery services. Specific embodiments thereof are described below.

[0502] The server receives order data entered by users using smartphones or computers. This data includes information such as delivery time, delivery address, and order details. Based on the information received through the input methods, the server optimizes the delivery plan using schedule optimization methods. Here, AI algorithms (e.g., Google TensorFlow) are used to calculate the delivery order and route, enabling efficient delivery.

[0503] Next, based on the optimized delivery plan, the server uses dispatching tools to arrange transportation. This arrangement involves sending necessary instructions to delivery partners available in real time. The delivery progress is monitored using tracking tools, and the location of the transportation is constantly communicated to the user.

[0504] Furthermore, the update mechanism allows the server to analyze real-time traffic conditions and dynamically adjust delivery routes as needed. This updated information is promptly fed back to both users and delivery partners.

[0505] For example, if a large number of orders come in during peak hours on a Sunday, the system can automatically calculate the most efficient delivery route and immediately communicate it to the delivery partner. This ensures that deliveries to customers are made on time.

[0506] An example of a prompt would be, "Calculate the optimal route for delivering to customer A at 2 PM on Sunday and to customer B at 2:30 PM." This prompt allows the AI ​​algorithm to automatically generate an efficient route plan.

[0507] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0508] Step 1:

[0509] The user enters their delivery schedule using their device. Specifically, they enter information such as their preferred delivery time, delivery address, and order details into an application on their device. This input data is then sent to the server.

[0510] Step 2:

[0511] The server analyzes the received input data and stores its contents in a database. The stored data is processed using an AI algorithm and used as information necessary for prioritizing deliveries and optimizing routes. The output at this stage is ready data for the algorithm to use for optimization.

[0512] Step 3:

[0513] The server uses AI algorithms (e.g., TensorFlow) to optimize the schedule. Based on the input delivery data, it calculates the optimal route and order to efficiently visit each delivery destination. This process also takes into account predicted traffic conditions and historical data. The optimized route output is then provided.

[0514] Step 4:

[0515] Based on the optimized route plan, the server sends instructions to available delivery partners using the dispatch system. Specifically, it sends push notifications containing delivery route information to the delivery partners' devices for confirmation.

[0516] Step 5:

[0517] During delivery, the location of the transport vehicle is monitored in real time using tracking devices. The server collects this information and notifies the user's device of the updated transport status as it occurs. Location data is continuously acquired and notified in real time.

[0518] Step 6:

[0519] If necessary, the server analyzes traffic conditions using update mechanisms and dynamically updates the delivery plan if route adjustments are required. The newly calculated route information is then sent back to the delivery partner for appropriate guidance. This update process utilizes real-time data, including traffic information APIs.

[0520] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0521] This invention provides a system that allows parents to manage their children's activity schedules and safely and efficiently arrange transportation, and further incorporates an emotion engine to realize optimal pick-up and drop-off services by taking into account the user's emotions. This system is built by integrating terminals, servers, artificial intelligence algorithms, and emotion recognition functions.

[0522] First, the user enters their child's activity schedule using an application on their device. This interface provides real-time feedback and is designed to allow parents to easily manage the schedule. The schedule information is sent to a server and stored in a database.

[0523] The server optimizes the travel plan using an artificial intelligence algorithm based on the received schedule data. This ensures efficient movement between activities and reduces the time burden on the parent user.

[0524] The emotion engine provides a means to analyze the user's emotions. Users can input their emotions via a terminal, or their emotions can be detected using voice or facial expression data. The server processes this emotion data and provides feedback to the schedule optimization system. This allows for schedule adjustments to be made with more leeway, for example, if the user is experiencing high stress levels.

[0525] The server arranges transportation based on an optimized travel plan. The location information of the arranged transportation is tracked in real time and notified to the user via the terminal. This information is important for the user to know the child's current location and to use the pick-up and drop-off service safely.

[0526] In an emergency, users can instantly send an emergency notification via their device. The server receives this notification and quickly sends a warning to the relevant parties to prompt appropriate action.

[0527] For example, if a user enters a schedule such as "Ballet lesson at 3 PM on Wednesday, English conversation class at 5 PM," and also enters that they are not feeling well, the emotion engine will prompt the schedule optimization system to make adjustments. As a result, the server will arrange for an earlier dispatch to allow for extra travel time, providing safe and comfortable transportation tailored to the user's situation.

[0528] The following describes the processing flow.

[0529] Step 1:

[0530] The user uses their device to enter their child's activity schedule into the app. The entered information includes the date, time, location, and duration of the activity, and the device sends this information to the server.

[0531] Step 2:

[0532] The server saves the received schedule data to the database. This saved data will be used for future schedule optimization.

[0533] Step 3:

[0534] Users input emotional data through their devices. This data can be entered manually or automatically acquired using voice or facial recognition functions.

[0535] Step 4:

[0536] The server analyzes the input emotion data and sends the information to the emotion engine. The emotion engine evaluates the user's emotional state and determines whether flexible schedule adjustments are necessary.

[0537] Step 5:

[0538] The server receives evaluation results from the emotion engine and uses an artificial intelligence algorithm to optimize the travel plan. Travel times and order are adjusted, and buffer time is added if necessary.

[0539] Step 6:

[0540] The server sends dispatch instructions to partner transportation services according to an optimized plan. The server ensures that travel time and vehicle arrangements are handled smoothly.

[0541] Step 7:

[0542] The terminal receives dispatch information from the server and notifies the user. The user can then review this information and understand the details regarding their child's transportation.

[0543] Step 8:

[0544] When the mode of transport begins to move, the server acquires its location information in real time and sends it to the device. This allows the user to always check the child's current location.

[0545] Step 9:

[0546] When a user presses the emergency button on their device, the server immediately sends an emergency notification to the relevant transportation or service provider. This is configured to allow for a rapid response.

[0547] Step 10:

[0548] Once the migration is complete, the server will provide the user with a final report and request feedback on the service. This feedback will be used to improve future services.

[0549] (Example 2)

[0550] Next, we will describe Example 2. 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."

[0551] There is a need for a system that allows parents to efficiently manage their children's activity schedules and ensure safe and smooth transportation. However, conventional systems have difficulty flexibly adjusting schedules while considering the user's emotions, and are inadequate in responding to sudden emotional changes or emergencies.

[0552] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0553] In this invention, the server includes an input means for the parent user to input the child's activity schedule, an emotion analysis means for adjusting the activity schedule based on the input emotion information, and a schedule optimization means for optimizing the travel plan based on the schedule and emotion information. This enables flexible schedule adjustments according to the user's emotions and circumstances, as well as safe and efficient transportation.

[0554] A "parent user" refers to a user who manages the child's activity schedule and is responsible for transportation.

[0555] "Activity schedule" refers to information indicating the date, time, and location of various activities in which children participate.

[0556] "Input means" refers to a device or program that provides an interface for a parent user to register their activity schedule in the system.

[0557] "Emotional analysis means" refers to a function that analyzes the emotional information of the parent user and adjusts the system's operation and schedule based on the results.

[0558] "Schedule optimization means" refers to a device or program that has the function of creating an efficient travel plan based on input activity schedules and emotional information.

[0559] "Tracking means" refers to the system's function for checking the current location of the arranged transportation and notifying the parent user.

[0560] An "emergency situation" refers to a sudden situation that requires a rapid response and where the system needs to issue a warning to ensure safety.

[0561] "Warning measures" refer to a part of a system that has the function of notifying relevant parties in the event of an emergency and prompting a swift response.

[0562] "Artificial intelligence" refers to a technology in which a system independently performs learning and analysis, and then executes optimization processes based on that learning.

[0563] "Real-time feedback" refers to the system's ability to immediately respond to information entered by the user.

[0564] This invention provides a system that allows parents to efficiently manage their children's activity schedules and ensure safe and smooth transportation. The system consists of a parent user's terminal, a central server, and artificial intelligence software.

[0565] Parent users utilize an application on their device to input activity schedules. This application features an intuitive interface designed for easy schedule entry and management. It also supports emotional input, allowing users to record emotions using text, audio, or video data.

[0566] The server receives the entered schedule and emotional information and stores it in a database. Furthermore, the server uses an artificial intelligence algorithm to perform schedule optimization. In this process, the entered emotional information is also taken into consideration to create an efficient travel plan that is sensitive to the user's feelings. It also has functions to arrange transportation and track the current location, allowing parents to check their child's travel status in real time.

[0567] For example, a parent user might input an activity schedule such as "Ballet lesson at 3 PM on Wednesday, English conversation class at 5 PM," and also input "Tired" as their current physical condition. Based on this information, the system would plan to finish travel earlier and create a schedule with some leeway. An example of a prompt to the generating AI model would be, "Please adjust the pick-up / drop-off schedule considering the parent user's feelings."

[0568] In the event of an emergency, the user can immediately issue an alert via their device. The server receives this alert and promptly notifies all relevant parties. As a result, a swift response and safety are ensured. In this way, the invention realizes a system that enables schedule management and safe travel while taking into account the user's emotions and state of mind.

[0569] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0570] Step 1:

[0571] The user enters their child's activity schedule using an application on their device. Specifically, they enter information into a form specifying the start time, end time, and location of each activity. The input in this step is the activity schedule, and the output is the schedule data sent to the server.

[0572] Step 2:

[0573] The terminal sends the schedule data entered by the user to the server. The server receives this data and saves it to its database. In this step, the entered schedule data is saved and ready for use in subsequent processing.

[0574] Step 3:

[0575] Users can input emotional data via their devices. This includes describing emotions through text input, as well as capturing facial expressions and voices in real time using a camera and microphone. The input in this step is emotional data, and the output is analyzable emotional information sent to the server.

[0576] Step 4:

[0577] The server processes the received emotional information and analyzes the user's emotions using emotion analysis tools. This process evaluates the input emotional data using an analysis algorithm to determine the emotional state (e.g., stress level, euphoria, etc.). The output of this step is data indicating the emotional state.

[0578] Step 5:

[0579] The server activates a schedule optimization mechanism, optimizing the travel plan based on the user's schedule data and analyzed sentiment data. This algorithm efficiently adjusts the order and timing to generate an optimal transportation plan that takes the user's emotions into consideration. The input for this step is schedule data and sentiment state data, and the output is the optimized transportation plan.

[0580] Step 6:

[0581] The server arranges transportation based on an optimized transportation plan. Furthermore, it obtains real-time location information of the arranged transportation and notifies the user via the terminal. In this step, transportation arrangement and location tracking are performed, and the output is a real-time location notification.

[0582] Step 7:

[0583] In the event of an emergency, the user uses their device to send an emergency notification. This notification is sent to a server, which quickly alerts relevant parties using warning mechanisms. The input in this step is the emergency notification, and the output is a prompt response via an alert notification.

[0584] (Application Example 2)

[0585] Next, we will explain application example 2. In the following explanation, 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."

[0586] In modern society, it is crucial for parents to understand their children's diverse activity schedules and provide appropriate transportation. However, it is difficult for parents to efficiently plan travel while always ensuring their children's safety, and flexible responses that take into account the parents' emotions and the children's circumstances are particularly required. Conventional systems often fail to optimize plans while considering the parents' emotions and are limited to general reminder tracking notifications. Therefore, a comprehensive schedule management and travel support system that takes parents' emotions into account is needed.

[0587] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0588] In this invention, the server includes an input means for a parent user to input their child's activity schedule, a schedule optimization means for optimizing travel plans based on the schedule and performing emotional analysis, a means for arranging and tracking autonomous vehicles and providing notifications, and a warning issuing means for providing rapid notifications in emergencies. This enables more flexible and safer schedule management and transportation arrangements that take parental emotions into consideration.

[0589] A "parent user" is a person who is responsible for managing their child's activity schedule and ensuring safe and efficient transportation.

[0590] "Activity schedule" refers to a child's daily schedule of school, extracurricular activities, and other activities, and serves as basic information for parents to plan transportation arrangements based on this schedule.

[0591] "Input means" refers to a device or software that provides an interface for parent users to input their child's activity schedule via smartphone or computer.

[0592] A "schedule optimization method" is a process or system that uses artificial intelligence technology to create an efficient and safe travel plan based on the input activity schedule.

[0593] An "autonomous vehicle" is a vehicle that travels on the road without human intervention and safely transports children to their destinations based on a designated route and time.

[0594] "Tracking means" refers to technology or devices that collect location information of autonomous vehicles in real time, notify the parent user of that information, and perform safety checks.

[0595] A "warning system" is a system or method for instantly sending warnings or notifications to relevant parties in the event of an emergency.

[0596] "Emotional analysis means" refers to technology that analyzes the emotional state of parent users and children through audio and video data and reflects this in travel planning.

[0597] The server provides an interface for parents to enter their children's activity schedules via smartphone or computer. This allows parents to easily enter and manage schedules. The entered data is sent to the server and stored in a database.

[0598] The server generates an efficient travel plan using schedule optimization techniques that leverage artificial intelligence technology. During this process, the emotional states of both the parent user and the child are analyzed using emotion analysis techniques, and these are taken into account when optimizing the travel plan. Emotion analysis utilizes voice and facial expression data, and APIs such as Google Cloud Vision are used.

[0599] Furthermore, the server arranges for autonomous vehicles and tracks their location in real time. This allows parents to constantly check their child's current location from their smartphone, improving safety. In emergencies, the system immediately uses an alert system to quickly notify relevant parties.

[0600] For example, if a parent inputs a schedule for taking their child to piano lessons after school and records their emotional state as "tired" via voice input, the server will use emotion analysis to create a more relaxed travel schedule and arrange for an early autonomous vehicle. This reduces the burden on the parent. An example of a prompt to the generating AI model would be: "As a parent, I want to efficiently manage my child's transportation. My child has extracurricular activities after school, and I would like you to suggest the optimal transportation plan, taking my own emotional state into consideration."

[0601] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0602] Step 1:

[0603] Users use a smartphone or computer to enter their child's activity schedule into the application's interface. This input includes information such as the date, time, location, and duration of the activity. The entered data is pre-validated on the device to check for missing information or errors before being prepared to be sent to the server.

[0604] Step 2:

[0605] The server saves the received activity schedule data to the database. At this stage, it verifies that the saved data is correct and processes it into an appropriate format for use as input for schedule optimization.

[0606] Step 3:

[0607] The server collects user emotional data. Users register their emotional states (e.g., stress, fatigue) through the application using voice input or image recognition. The collected emotional data is analyzed by emotion recognition software such as Google Cloud Vision and converted into numerical data.

[0608] Step 4:

[0609] The server uses stored activity schedule data and analyzed sentiment data to perform schedule optimization. Here, a generative AI model is utilized to create an efficient travel plan. The output includes an optimized travel route, the type of transportation used, and a recommended travel start time.

[0610] Step 5:

[0611] The server arranges for autonomous vehicles. Based on an optimized travel plan, a vehicle is arranged to arrive at a specified location at a specified time. A vehicle operation service API is used to send a notification to the user when the arrangement is complete.

[0612] Step 6:

[0613] The server tracks the location of dispatched autonomous vehicles in real time and notifies the user. This tracking information is displayed in combination with map data and sent to the user through the application. The user can then check this information and understand the progress of the vehicle's movement.

[0614] Step 7:

[0615] When a user reports an emergency through the application, the server immediately uses an alert system to notify vehicle operators and emergency contacts. This process generates and sends an emergency information log.

[0616] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0617] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0618] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0619] [Fourth Embodiment]

[0620] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0621] As shown in Figure 7, the 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.

[0622] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0623] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0624] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0625] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0626] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0627] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0628] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0629] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0630] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0631] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0632] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0633] This invention is a system that allows parents to manage their children's activity schedules and ensure safe and efficient transportation. The system is built upon the integration of terminals, servers, artificial intelligence algorithms, and transportation methods.

[0634] First, the user enters the child's activity schedule via their device. This input data, which includes information such as the type of activity, date and time, location, and duration, is sent to the server.

[0635] The server receives this schedule data and uses an artificial intelligence algorithm to create the optimal transportation plan. The algorithm considers travel time and order between activities and optimizes the plan to maximize overall efficiency. This optimization process minimizes wasted time and reduces the workload for the parent user.

[0636] The server then arranges transportation based on the optimized travel plan. This includes issuing dispatch instructions to partner transportation service providers. Once the dispatch is confirmed, the server notifies the terminal of the detailed schedule and dispatch information, allowing the user to review it.

[0637] While in transit, the server tracks the location of the mode of transport in real time and transmits this information to the device. This tracking allows users to check the current status on their device and manage their child's travel with peace of mind.

[0638] Furthermore, in emergencies, users can send emergency notifications through their devices. These notifications are quickly transmitted via the server to drivers and other relevant personnel, ensuring an immediate response is possible.

[0639] For example, if a user enters a schedule such as "piano lesson at 4 PM on Monday, soccer practice at 6 PM," the server calculates the optimal travel time based on this information and arranges transportation services. It provides real-time data at all times to ensure everything goes according to plan, helping users complete their daily tasks with peace of mind.

[0640] The following describes the processing flow.

[0641] Step 1:

[0642] The user launches the application on their device and enters their child's activity schedule. The entered information, including date, time, location, and duration, is sent to the server.

[0643] Step 2:

[0644] The server receives schedule data sent by the user and stores it in the database. This information becomes the basic data necessary for subsequent processing.

[0645] Step 3:

[0646] The server activates an artificial intelligence algorithm and optimizes the travel plan using the received schedule data. The AI ​​considers travel distance, time of day, and the order of destinations to create the optimal transportation plan.

[0647] Step 4:

[0648] The server automatically requests vehicle dispatch from partner transportation service providers based on an optimized travel plan. This ensures that a vehicle is arranged for the required time and location.

[0649] Step 5:

[0650] The server notifies the terminal when the vehicle dispatch is complete and notifies the user of the scheduled pick-up / drop-off time and vehicle information. Based on this information, the user can confirm their child's pick-up / drop-off plan.

[0651] Step 6:

[0652] Once the mode of transport begins moving, the server acquires its location information in real time and transmits it to the device. The user can then constantly know the child's current location via the device.

[0653] Step 7:

[0654] When a user presses the emergency button on their device as needed, the server immediately sends an emergency notification to the driver and partner services to prompt a quick response.

[0655] Step 8:

[0656] Once all transfers are complete, the server will provide the user with a final transfer report and request feedback on the transfer service. This information will be used to improve future services.

[0657] (Example 1)

[0658] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0659] When managing their children's activity schedules, parents face the challenge of efficiently planning and safely and quickly transporting their children amidst busy daily lives. Individual appointments are often scheduled in distant locations or at different times, requiring optimized travel and rapid information sharing. However, traditional methods are time-consuming and laborious, and there are concerns about how to respond in emergencies.

[0660] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0661] In this invention, the server includes information input means, plan generation means, and vehicle procurement means. This enables the rapid and efficient optimization of travel plans, arrangement of transportation means, and immediate response in emergencies based on the child's activity schedule.

[0662] "Information input means" refers to an interface device that allows parent users to reliably input their child's activity schedule.

[0663] A "plan generation means" is a computing device or program that formulates an optimal travel plan based on the input schedule information.

[0664] "Vehicle procurement means" refers to the devices and procedures for securing and arranging appropriate means of transportation based on the results of the plan generation.

[0665] An "information notification device" is a communication device that acquires real-time location information of a means of transport and reports its status to the parent user.

[0666] A "warning system" is a system equipped with warning and communication functions to enable a rapid response in the event of an emergency.

[0667] "Machine learning" is an algorithm that analyzes large amounts of data to derive the optimal order of movement.

[0668] "Instant response" is a function that processes the parent user's input in real time and displays the result immediately.

[0669] The system of this invention is built to allow parent users to manage their children's activity schedules and ensure safe and efficient transportation. Specifically, it consists of an integrated system of terminals, servers, machine learning algorithms, and transportation services.

[0670] Users enter their child's activity schedule using their own device (smartphone or tablet). This device has dedicated application software installed and features an interface that allows for easy input of schedule information. For example, it's possible to enter schedules such as "Piano lesson at 4 PM on Monday, soccer practice at 6 PM."

[0671] Schedule information entered from the terminal is sent to a server at the center using a secure communication protocol (such as HTTPS). The server receives this information and uses a machine learning algorithm (for example, an algorithm provided by a cloud-based AI service provider) to generate the optimal travel plan. This algorithm has the ability to analyze large amounts of map data and past travel patterns to calculate the route that will get you to your destination in the shortest time.

[0672] Once the optimal route is determined, the server requests vehicle procurement from partner transportation service providers (e.g., ride-sharing companies). This process is managed automatically via an API, ensuring that arrangements are completed without any action from the user.

[0673] Furthermore, to ensure that parents are always aware of their child's whereabouts during transit, the server tracks the location of the mode of transport in real time and transmits this information to the device. This allows parents to check the current location from their device and ensure their child's safety.

[0674] The system described above also takes emergency response into consideration, allowing users to send emergency notifications from their devices. This feature enables the server to immediately send alerts to transportation services and emergency contacts, allowing for a swift response.

[0675] An example of a prompt message would be something like, "Based on this schedule, please suggest the most efficient route and mode of transportation."

[0676] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0677] Step 1:

[0678] The user enters their child's activity schedule using a terminal. This involves using a form to input the type of activity, location, date and time, and duration. The entered data is converted into a structured data format by the terminal. The converted data is then prepared for transmission to the server.

[0679] Step 2:

[0680] The terminal uses the HTTPS protocol to send the entered schedule data to the server. Here, the data is encrypted for security. The server parses the received data, converts it to the necessary format for storage in the database, and stores it there.

[0681] Step 3:

[0682] The server generates an optimal travel plan using a machine learning algorithm based on stored schedule data. The input consists of schedule data and external data regarding traffic conditions; the algorithm analyzes these to calculate the optimal route and timing. The output is an optimized travel schedule, which is used for subsequent arrangements.

[0683] Step 4:

[0684] Based on the generated optimal travel plan, the server requests vehicle arrangements from affiliated transportation service providers via API. Specifically, the server uses the required date, time, and location information to provide arrangement instructions to the transportation provider. Once the arrangement is complete, the server is notified of the transportation details.

[0685] Step 5:

[0686] The server sends completed vehicle arrangement information to the terminal for user confirmation. This includes confirmed vehicle assignments and estimated arrival times. The terminal displays the received information in a format that is easy for the user to understand intuitively.

[0687] Step 6:

[0688] While in transit, the server tracks the vehicle's location in real time and periodically transmits this information to the terminal. This allows the user to constantly monitor the transport status and adjust their actions as needed. This information is obtained by analyzing GPS data and converting it into location information.

[0689] Step 7:

[0690] Users can use their devices to send emergency notifications in emergencies. This action causes the server to immediately send alerts to transportation services and relevant parties. Notifications are marked as high importance and used to facilitate a rapid response. In this process, necessary actions are determined and information is sent based on the emergency information entered.

[0691] (Application Example 1)

[0692] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0693] In food delivery services, there is a need to achieve efficient and flexible delivery planning, especially during peak order times and when affected by traffic congestion. However, traditional manual scheduling makes it difficult to select the optimal delivery route, sometimes leading to delays and misdeliveries. Furthermore, because it does not take real-time traffic conditions into account, there is a problem in being unable to respond immediately to changes in the plan.

[0694] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0695] In this invention, the server includes an input means for the user to input a delivery schedule, a schedule optimization means for optimizing the delivery plan based on the schedule, and a dispatch means for arranging transportation based on the delivery plan. This enables the efficient formulation of delivery plans and flexible real-time response.

[0696] "Input means" refers to a device or software that allows users to register delivery schedules and other necessary information into the system.

[0697] "Schedule optimization methods" refer to algorithms and processing methods for constructing the optimal delivery plan based on the input schedule information.

[0698] "Vehicle dispatching" refers to the procedures and systems for arranging the necessary means of transportation based on an optimized delivery plan.

[0699] "Tracking technology" refers to technology that allows users to check the current location and progress of a means of transport in real time and provide that information to the user.

[0700] An "update mechanism" is a system for dynamically changing and optimizing delivery plans, taking into account real-time traffic conditions and other factors.

[0701] This invention provides a system for improving delivery efficiency in food delivery services. Specific embodiments are described below.

[0702] The server receives order data entered by users using smartphones or computers. This data includes information such as delivery time, delivery address, and order details. Based on the information received through the input methods, the server optimizes the delivery plan using scheduling optimization methods. Here, AI algorithms (e.g., Google TensorFlow) are used to calculate the delivery order and route, enabling efficient delivery.

[0703] Next, based on the optimized delivery plan, the server uses dispatching tools to arrange transportation. This arrangement involves sending necessary instructions to delivery partners available in real time. The delivery progress is monitored using tracking tools, and the location of the transportation is constantly communicated to the user.

[0704] Furthermore, the update mechanism allows the server to analyze real-time traffic conditions and dynamically adjust delivery routes as needed. This updated information is promptly fed back to both users and delivery partners.

[0705] For example, if a large number of orders come in during peak hours on a Sunday, the system can automatically calculate the most efficient delivery route and immediately communicate it to the delivery partner. This ensures that deliveries to customers are made on time.

[0706] An example of a prompt would be, "Calculate the optimal route for delivering to customer A at 2 PM on Sunday and to customer B at 2:30 PM." This prompt allows the AI ​​algorithm to automatically generate an efficient route plan.

[0707] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0708] Step 1:

[0709] The user enters their delivery schedule using their device. Specifically, they enter information such as their preferred delivery time, delivery address, and order details into an application on their device. This input data is then sent to the server.

[0710] Step 2:

[0711] The server analyzes the received input data and stores its contents in a database. The stored data is processed using an AI algorithm and used as information necessary for prioritizing deliveries and optimizing routes. The output at this stage is ready data for the algorithm to use for optimization.

[0712] Step 3:

[0713] The server uses AI algorithms (e.g., TensorFlow) to optimize the schedule. Based on the input delivery data, it calculates the optimal route and order to efficiently visit each delivery destination. This process also takes into account predicted traffic conditions and historical data. The optimized route output is then provided.

[0714] Step 4:

[0715] Based on the optimized route plan, the server sends instructions to available delivery partners using the dispatch system. Specifically, it sends push notifications containing delivery route information to the delivery partners' devices for confirmation.

[0716] Step 5:

[0717] During delivery, the location of the transport vehicle is monitored in real time using tracking devices. The server collects this information and notifies the user's device of the updated transport status as it occurs. Location data is continuously acquired and notified in real time.

[0718] Step 6:

[0719] If necessary, the server analyzes traffic conditions using update mechanisms and dynamically updates the delivery plan if route adjustments are required. The newly calculated route information is then sent back to the delivery partner for appropriate guidance. This update process utilizes real-time data, including traffic information APIs.

[0720] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0721] This invention provides a system that allows parents to manage their children's activity schedules and safely and efficiently arrange transportation, and further incorporates an emotion engine to realize optimal pick-up and drop-off services by taking into account the user's emotions. This system is built by integrating terminals, servers, artificial intelligence algorithms, and emotion recognition functions.

[0722] First, the user enters their child's activity schedule using an application on their device. This interface provides real-time feedback and is designed to allow parents to easily manage the schedule. The schedule information is sent to a server and stored in a database.

[0723] The server optimizes the travel plan using an artificial intelligence algorithm based on the received schedule data. This ensures efficient movement between activities and reduces the time burden on the parent user.

[0724] The emotion engine provides a means to analyze the user's emotions. Users can input their emotions via a terminal, or their emotions can be detected using voice or facial expression data. The server processes this emotion data and provides feedback to the schedule optimization system. This allows for schedule adjustments to be made with more leeway, for example, if the user is experiencing high stress levels.

[0725] The server arranges transportation based on an optimized travel plan. The location information of the arranged transportation is tracked in real time and notified to the user via the terminal. This information is important for the user to know the child's current location and to use the pick-up and drop-off service safely.

[0726] In an emergency, users can instantly send an emergency notification via their device. The server receives this notification and quickly sends a warning to the relevant parties to prompt appropriate action.

[0727] For example, if a user enters a schedule such as "Ballet lesson at 3 PM on Wednesday, English conversation class at 5 PM," and also enters that they are not feeling well, the emotion engine will prompt the schedule optimization system to make adjustments. As a result, the server will arrange for an earlier dispatch to allow for extra travel time, providing safe and comfortable transportation tailored to the user's situation.

[0728] The following describes the processing flow.

[0729] Step 1:

[0730] The user uses their device to enter their child's activity schedule into the app. The entered information includes the date, time, location, and duration of the activity, and the device sends this information to the server.

[0731] Step 2:

[0732] The server saves the received schedule data to the database. This saved data will be used for future schedule optimization.

[0733] Step 3:

[0734] Users input emotional data through their devices. This data can be entered manually or automatically acquired using voice or facial recognition functions.

[0735] Step 4:

[0736] The server analyzes the input emotion data and sends the information to the emotion engine. The emotion engine evaluates the user's emotional state and determines whether flexible schedule adjustments are necessary.

[0737] Step 5:

[0738] The server receives evaluation results from the emotion engine and uses an artificial intelligence algorithm to optimize the travel plan. Travel times and order are adjusted, and buffer time is added if necessary.

[0739] Step 6:

[0740] The server sends dispatch instructions to partner transportation services according to an optimized plan. The server ensures that travel time and vehicle arrangements are handled smoothly.

[0741] Step 7:

[0742] The terminal receives dispatch information from the server and notifies the user. The user can then review this information and understand the details regarding their child's transportation.

[0743] Step 8:

[0744] When the mode of transport begins to move, the server acquires its location information in real time and sends it to the device. This allows the user to always check the child's current location.

[0745] Step 9:

[0746] When a user presses the emergency button on their device, the server immediately sends an emergency notification to the relevant transportation or service provider. This is configured to allow for a rapid response.

[0747] Step 10:

[0748] Once the migration is complete, the server will provide the user with a final report and request feedback on the service. This feedback will be used to improve future services.

[0749] (Example 2)

[0750] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0751] There is a need for a system that allows parents to efficiently manage their children's activity schedules and ensure safe and smooth transportation. However, conventional systems have difficulty flexibly adjusting schedules while considering the user's emotions, and are inadequate in responding to sudden emotional changes or emergencies.

[0752] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0753] In this invention, the server includes an input means for the parent user to input the child's activity schedule, an emotion analysis means for adjusting the activity schedule based on the input emotion information, and a schedule optimization means for optimizing the travel plan based on the schedule and emotion information. This enables flexible schedule adjustments according to the user's emotions and circumstances, as well as safe and efficient transportation.

[0754] A "parent user" refers to a user who manages the child's activity schedule and is responsible for transportation.

[0755] "Activity schedule" refers to information indicating the date, time, and location of various activities in which children participate.

[0756] "Input means" refers to a device or program that provides an interface for a parent user to register their activity schedule in the system.

[0757] "Emotional analysis means" refers to a function that analyzes the emotional information of the parent user and adjusts the system's operation and schedule based on the results.

[0758] "Schedule optimization means" refers to a device or program that has the function of creating an efficient travel plan based on input activity schedules and emotional information.

[0759] "Tracking means" refers to the system's function for checking the current location of the arranged transportation and notifying the parent user.

[0760] An "emergency situation" refers to a sudden situation that requires a rapid response and where the system needs to issue a warning to ensure safety.

[0761] "Warning measures" refer to a part of a system that has the function of notifying relevant parties in the event of an emergency and prompting a swift response.

[0762] "Artificial intelligence" refers to a technology in which a system independently performs learning and analysis, and then executes optimization processes based on that learning.

[0763] "Real-time feedback" refers to the system's ability to immediately respond to information entered by the user.

[0764] This invention provides a system that allows parents to efficiently manage their children's activity schedules and ensure safe and smooth transportation. The system consists of a parent user's terminal, a central server, and artificial intelligence software.

[0765] Parent users utilize an application on their device to input activity schedules. This application features an intuitive interface designed for easy schedule entry and management. It also supports emotional input, allowing users to record emotions using text, audio, or video data.

[0766] The server receives the entered schedule and emotional information and stores it in a database. Furthermore, the server uses an artificial intelligence algorithm to perform schedule optimization. In this process, the entered emotional information is also taken into consideration to create an efficient travel plan that is sensitive to the user's feelings. It also has functions to arrange transportation and track the current location, allowing parents to check their child's travel status in real time.

[0767] For example, a parent user might input an activity schedule such as "Ballet lesson at 3 PM on Wednesday, English conversation class at 5 PM," and also input "Tired" as their current physical condition. Based on this information, the system would plan to finish travel earlier and create a schedule with some leeway. An example of a prompt to the generating AI model would be, "Please adjust the pick-up / drop-off schedule considering the parent user's feelings."

[0768] In the event of an emergency, the user can immediately issue an alert via their device. The server receives this alert and promptly notifies all relevant parties. As a result, a swift response and safety are ensured. In this way, the invention realizes a system that enables schedule management and safe travel while taking into account the user's emotions and state of mind.

[0769] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0770] Step 1:

[0771] The user enters their child's activity schedule using an application on their device. Specifically, they enter information into a form specifying the start time, end time, and location of each activity. The input in this step is the activity schedule, and the output is the schedule data sent to the server.

[0772] Step 2:

[0773] The terminal sends the schedule data entered by the user to the server. The server receives this data and saves it to its database. In this step, the entered schedule data is saved and ready for use in subsequent processing.

[0774] Step 3:

[0775] Users can input emotional data via their devices. This includes describing emotions through text input, as well as capturing facial expressions and voices in real time using a camera and microphone. The input in this step is emotional data, and the output is analyzable emotional information sent to the server.

[0776] Step 4:

[0777] The server processes the received emotional information and analyzes the user's emotions using emotion analysis tools. This process evaluates the input emotional data using an analysis algorithm to determine the emotional state (e.g., stress level, euphoria, etc.). The output of this step is data indicating the emotional state.

[0778] Step 5:

[0779] The server activates a schedule optimization mechanism, optimizing the travel plan based on the user's schedule data and analyzed sentiment data. This algorithm efficiently adjusts the order and timing to generate an optimal transportation plan that takes the user's emotions into consideration. The input for this step is schedule data and sentiment state data, and the output is the optimized transportation plan.

[0780] Step 6:

[0781] The server arranges transportation based on an optimized transportation plan. Furthermore, it obtains real-time location information of the arranged transportation and notifies the user via the terminal. In this step, transportation arrangement and location tracking are performed, and the output is a real-time location notification.

[0782] Step 7:

[0783] In the event of an emergency, the user uses their device to send an emergency notification. This notification is sent to a server, which quickly alerts relevant parties using warning mechanisms. The input in this step is the emergency notification, and the output is a prompt response via an alert notification.

[0784] (Application Example 2)

[0785] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0786] In modern society, it is crucial for parents to understand their children's diverse activity schedules and provide appropriate transportation. However, it is difficult for parents to efficiently plan travel while always ensuring their children's safety, and flexible responses that take into account the parents' emotions and the children's circumstances are particularly required. Conventional systems often fail to optimize plans while considering the parents' emotions and are limited to general reminder tracking notifications. Therefore, a comprehensive schedule management and travel support system that takes parents' emotions into account is needed.

[0787] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0788] In this invention, the server includes an input means for a parent user to input their child's activity schedule, a schedule optimization means for optimizing travel plans based on the schedule and performing emotional analysis, a means for arranging and tracking autonomous vehicles and providing notifications, and a warning issuing means for providing rapid notifications in emergencies. This enables more flexible and safer schedule management and transportation arrangements that take parental emotions into consideration.

[0789] A "parent user" is a person who is responsible for managing their child's activity schedule and ensuring safe and efficient transportation.

[0790] "Activity schedule" refers to a child's daily schedule of school, extracurricular activities, and other activities, and serves as basic information for parents to plan transportation arrangements based on this schedule.

[0791] "Input means" refers to a device or software that provides an interface for parent users to input their child's activity schedule via smartphone or computer.

[0792] A "schedule optimization method" is a process or system that uses artificial intelligence technology to create an efficient and safe travel plan based on the input activity schedule.

[0793] An "autonomous vehicle" is a vehicle that travels on the road without human intervention and safely transports children to their destinations based on a designated route and time.

[0794] "Tracking means" refers to technology or devices that collect location information of autonomous vehicles in real time, notify the parent user of that information, and perform safety checks.

[0795] A "warning system" is a system or method for instantly sending warnings or notifications to relevant parties in the event of an emergency.

[0796] "Emotional analysis means" refers to technology that analyzes the emotional state of parent users and children through audio and video data and reflects this in travel planning.

[0797] The server provides an interface for parents to enter their children's activity schedules via smartphone or computer. This allows parents to easily enter and manage schedules. The entered data is sent to the server and stored in a database.

[0798] The server generates an efficient travel plan using schedule optimization techniques that leverage artificial intelligence technology. During this process, the emotional states of both the parent user and the child are analyzed using emotion analysis techniques, and these are taken into account when optimizing the travel plan. Emotion analysis utilizes voice and facial expression data, and APIs such as Google Cloud Vision are used.

[0799] Furthermore, the server arranges for autonomous vehicles and tracks their location in real time. This allows parents to constantly check their child's current location from their smartphone, improving safety. In emergencies, the system immediately uses an alert system to quickly notify relevant parties.

[0800] For example, if a parent inputs a schedule for taking their child to piano lessons after school and records their emotional state as "tired" via voice input, the server will use emotion analysis to create a more relaxed travel schedule and arrange for an early autonomous vehicle. This reduces the burden on the parent. An example of a prompt to the generating AI model would be: "As a parent, I want to efficiently manage my child's transportation. My child has extracurricular activities after school, and I would like you to suggest the optimal transportation plan, taking my own emotional state into consideration."

[0801] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0802] Step 1:

[0803] Users use a smartphone or computer to enter their child's activity schedule into the application's interface. This input includes information such as the date, time, location, and duration of the activity. The entered data is pre-validated on the device to check for missing information or errors before being prepared to be sent to the server.

[0804] Step 2:

[0805] The server saves the received activity schedule data to the database. At this stage, it verifies that the saved data is correct and processes it into an appropriate format for use as input for schedule optimization.

[0806] Step 3:

[0807] The server collects user emotional data. Users register their emotional states (e.g., stress, fatigue) through the application using voice input or image recognition. The collected emotional data is analyzed by emotion recognition software such as Google Cloud Vision and converted into numerical data.

[0808] Step 4:

[0809] The server uses stored activity schedule data and analyzed sentiment data to perform schedule optimization. Here, a generative AI model is utilized to create an efficient travel plan. The output includes an optimized travel route, the type of transportation used, and a recommended travel start time.

[0810] Step 5:

[0811] The server arranges for autonomous vehicles. Based on an optimized travel plan, a vehicle is arranged to arrive at a specified location at a specified time. A vehicle operation service API is used to send a notification to the user when the arrangement is complete.

[0812] Step 6:

[0813] The server tracks the location of dispatched autonomous vehicles in real time and notifies the user. This tracking information is displayed in combination with map data and sent to the user through the application. The user can then check this information and understand the progress of the vehicle's movement.

[0814] Step 7:

[0815] When a user reports an emergency through the application, the server immediately uses an alert system to notify vehicle operators and emergency contacts. This process generates and sends an emergency information log.

[0816] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0817] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0818] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0819] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0820] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0821] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0822] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0823] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0824] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0825] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0826] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0827] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0828] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0829] 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.

[0830] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0831] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0832] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0833] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0834] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0835] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0836] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0837] The following is further disclosed regarding the embodiments described above.

[0838] (Claim 1)

[0839] An input method for parent users to enter their child's activity schedule,

[0840] A schedule optimization means for optimizing the travel plan based on the aforementioned schedule,

[0841] A means of arranging transportation based on the aforementioned travel plan,

[0842] Tracking means for acquiring location information of the aforementioned means of transport and notifying the parent user,

[0843] Warning mechanisms for rapid response to emergencies,

[0844] A system that includes this.

[0845] (Claim 2)

[0846] The system according to claim 1, wherein the schedule optimization means determines the optimal movement order using artificial intelligence.

[0847] (Claim 3)

[0848] The system according to claim 1, wherein the input means includes an interface for providing real-time feedback to the parent user.

[0849] "Example 1"

[0850] (Claim 1)

[0851] A means for parent users to input information about their child's activity schedule,

[0852] A plan generation means for optimizing the travel plan based on the aforementioned schedule,

[0853] A means of procuring vehicles for arranging transportation based on the aforementioned travel plan,

[0854] An information notification means for acquiring location information of the transportation means and providing the information to the parent user,

[0855] Warning measures to respond quickly to emergencies,

[0856] A system that includes this.

[0857] (Claim 2)

[0858] The system according to claim 1, wherein the plan generation means determines the optimal movement order using machine learning.

[0859] (Claim 3)

[0860] The system according to claim 1, wherein the information input means includes a dialogue means that provides an immediate response to the parent user.

[0861] "Application Example 1"

[0862] (Claim 1)

[0863] An input method for the user to enter the delivery schedule,

[0864] A schedule optimization means for optimizing the delivery plan based on the aforementioned schedule,

[0865] A dispatching means for arranging means of transport based on the aforementioned delivery plan,

[0866] Tracking means for acquiring location information of the aforementioned transportation means and notifying the user,

[0867] A means of updating transportation plans in real time, taking traffic conditions into consideration,

[0868] A system that includes this.

[0869] (Claim 2)

[0870] The system according to claim 1, wherein the schedule optimization means determines the optimal delivery order using artificial intelligence.

[0871] (Claim 3)

[0872] The system according to claim 1, wherein the input means includes an interface for providing real-time feedback to the user.

[0873] "Example 2 of combining an emotion engine"

[0874] (Claim 1)

[0875] An input method for parent users to enter their child's activity schedule,

[0876] An emotion analysis means that adjusts the activity schedule based on the input emotion information,

[0877] A schedule optimization means that optimizes the travel plan based on the aforementioned schedule and emotional information,

[0878] A tracking means that arranges transportation based on the aforementioned travel plan and acquires location information,

[0879] Warning mechanisms for rapid response to emergencies,

[0880] A system that includes this.

[0881] (Claim 2)

[0882] The system according to claim 1, wherein the schedule optimization means determines the optimal travel order using artificial intelligence.

[0883] (Claim 3)

[0884] The system according to claim 1, wherein the input means includes an interface for providing real-time feedback to the parent user.

[0885] "Application example 2 when combining with an emotional engine"

[0886] (Claim 1)

[0887] An input method for parent users to enter their child's activity schedule,

[0888] A schedule optimization means that optimizes the travel plan based on the aforementioned schedule,

[0889] A means for arranging an autonomous vehicle based on the aforementioned travel plan,

[0890] Tracking means for acquiring location information of the autonomous vehicle and notifying the parent user,

[0891] A means of issuing warnings to respond quickly to emergencies,

[0892] An emotion analysis tool that analyzes emotions and reflects them in travel plans,

[0893] A system that includes this.

[0894] (Claim 2)

[0895] The system according to claim 1, wherein the schedule optimization means determines the optimal movement order together with the emotion analysis results using artificial intelligence.

[0896] (Claim 3)

[0897] The system according to claim 1, wherein the input means includes an interface that provides real-time responses to the parent user and adjusts notifications based on emotion data. [Explanation of Symbols]

[0898] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An input method for parent users to enter their child's activity schedule, A schedule optimization means for optimizing the travel plan based on the aforementioned schedule, A means of arranging transportation based on the aforementioned travel plan, Tracking means for acquiring location information of the aforementioned means of transport and notifying the parent user, Warning mechanisms for rapid response to emergencies, A system that includes this.

2. The system according to claim 1, wherein the schedule optimization means determines the optimal movement order using artificial intelligence.

3. The system according to claim 1, wherein the input means includes an interface for providing real-time feedback to the parent user.

Images